Journal of Economic
and Social Studies
Volume 3
Number 2
JECOSS
Print ISSN: 1986 - 8499
Online ISSN: 1986 - 8502
Fall 2013
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STATEMENT OF PURPOSE
Journal of Economic and Social Studies (JECOSS) aims to develop scientific
knowledge in the areas that include, and are related to Economics, Business
Administration, Public Administration, Political Studies, International Relations,
Labor Economics and Industrial Relations, Econometry, Sociology and Psychology.
As an international social sciences journal with interdisciplinary feature, it will set a
ground to bring social science communities across disciplines identified above with
a view for sharing information and debate. The journal publishes refereed articles
and technical research notes that build on theory and contemporary scientific
knowledge. Articles submitted to JECOSS will be peer-reviewed and expected
to report previously unpublished scientific work. Submitted manuscripts should
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EDITORIAL BOARD
AKIN, Zafer
BAYRAKTAROGLU, Serkan
CIVAN, Abdulkadir
TOBB University of Economics and Technology, TURKEY
Suleyman Sah University, TURKEY
Gediz University, TURKEY
COSKUN, Ali
Fatih University, TURKEY
DEMIROZ, Fatih
Florida International University, USA
DHAOUI, Abderrazak
University of Sousse, TUNISIA
DREHER, Sabine
York University, CANADA
DUMENCI, Levent
Virginia Commonwealth University, USA
LEE, Chew Ging
The University of Nottingham, Malaysia Campus, MALAYSIA
GULER, Bulent
Indiana University at Bloomington, USA
HAFALIR, Isa
Carnegie Mellon University, USA
HARCAR, Talha
Pennsylvania State University, USA
IKRAMOV, Nuriddin
Sacramento State University, USA
IZZI DIEN, Mawil
Trinity Saint Davis University, UK
KANIBIR, Huseyin
Bursa Orhangazi University, TURKEY
KAPUCU, Naim
University of Central Florida, USA
KARAMUJIC, Muharem
The University of Melbourne, AUSTRALIA
KURTOVIC, Emir
Sarajevo University, BOSNIA AND HERZEGOVINA
LONCAR, Dragan
University of Belgrade, SERBIA
MARTINOVIC, Maja
Zagreb School of Economics and Management, CROATIA
OMERBEGOVIC ARAPOVIC, Adisa
Sarajevo Graduate School of Business, BOSNIA AND HERZEGOVINA
OZDEVECIOGLU, Mahmut
Meliksah University, TURKEY
OZTURK, Ahmet Bulent
University of Central Florida, USA
PASIC, Mugdim
Sarajevo University, BOSNIA AND HERZEGOVINA
PINNINGTON, Ashly H.
The British University in Dubai, UAE
RAJIC, Vesna
University of Belgrade, SERBIA
RAMIC, Sukrija
Zenica University, BOSNIA AND HERZEGOVINA
ROSE Andrew K.
University of California, Berkeley, USA
SARI, Ramazan
Middle East Technical University, TURKEY
SAVEVSKA, Maja
University of Warwick, UK
STOCKER, John
University of Delaware, USA
SUVANKULOV, Farrukh
Zirve University, TURKEY
TOURK, Khairy A.
Illionis Institute of Technology, USA
UC, Mustafa
Epoka University, ALBANIA
ULUBASOGLU, Mehmet Ali
Deakin University, AUSTRALIA
WITKOWSKI, Jaroslaw
University of Economics, POLAND
YILDIRIM, Yildiray
Syracuse University, USA
JECOSS
Journal of Economic
and Social Studies
Volume 3
Number 2
Fall 2013
CONTENTS
Refereed Articles
5
Do Private Savings Offset Public Savings in Turkey?
Hasan Göcen, Hüseyin Kalyoncu And Muhittin Kaplan,
15
Store Personality: Perceptions Towards Consumer Electronics Chain Stores in
Turkey:A Case of University Students
Keti Ventura, Ipek Kazancoglu, Elif Ustundagli and Rezan Tatlidil
39
The Role of Twin Deficit Problem in Sustainable Growth: An Econometric
Analysis for Turkey
Halil UCAL and Mehmet BOLUKBAS
53
Cox Regression Models with Time-Varying Covariates Applied to Survival
Success of Young Firms
Aygül Anavatan and Murat Karaöz
69
Unit Root Properties of Energy Consumption and Production in Turkey
Özgür Polat, Enes E. Uslu, Hüseyin Kalyoncu,
87
Measuring and Reporting Cost of Quality in a Turkish Manufacturing
Company: A Case Study in Electric Industry
Hilmi Kirlioglu and Zülküf Çevik,
101
Social Anxiety and Usage of Online Technological Communication Tools
among Adolescents
Bilal Sisman, Sinan Yoruk and Ali Eleren
115
State as the Source of Wealth: In Ottoman Economic Thought: A different
approach to reflections in the aftermath of the global crisis
Birol Çetin
131
Impact of Military Expenditure and Economic Growth on External Debt:
New Evidence from a Panel of SAARC Countries
Khalid Zaman, Iqtidar Ali Shah, Muhammad Mushtaq Khan and Mehboob Ahmad,
149
Government Expenditure on Nomadic Education in Nigeria:
Implications for Achieving the Millennium Development Goals
Akighir David Terfa, Okpe. I
166
List of Reviewers for This Issue
Journal of Economic and Social Studies
Do Private Savings Offset
Public Savings in Turkey?
Hasan GÖCEN
Department of Economics,
Faculty of Economics and Administrative Sciences
Meliksah University, 38280 Kayseri, Turkey
hgocen@meliksah.edu.tr
Hüseyin KALYONCU
Department of International Trade and Business,
Faculty of Economics and Administrative Sciences
Meliksah University, 38280 Kayseri, Turkey
hkalyoncu@meliksah.edu.tr
Muhittin KAPLAN
Department of Economics,
Faculty of Economics and Administrative Sciences
Meliksah University, 38280 Kayseri, Turkey
mkaplan@meliksah.edu.tr
AbstrAct
The issue of whether public savings offset private savings, and visa vice,
has important implications for the effectiveness of fiscal policy. This study
examines long-run relationship between public and private savings rates using
annual Turkish data for the period 1975-2005. The result of Engle-Granger
cointegration test has shown that there is no long-run relationship between
private and public savings ratios. However, once endogenously determined
structural break is allowed, the test results confirm the existence of the
cointegration relationship between private and public savings. Econometric
estimation of the offset coefficients using both FMOLS and DOLS yields values
of between -0.11 and -0.82. The results also indicate that the potency of fiscal
policy significantly reduced with the liberalization of financial markets.
KEYWOrDs
Savings, Offset
Coefficient, Ricardian
Equivalence, DOLS,
FMOLS.
ArtIcLE HIstOrY
Submitted: 29 Jun 2012
Resubmitted: 13
December 2012
Accepted: 25
December2012
JEL codes: E6, H6, E21.
Volume 3
Number 2
Fall 2013
5
Hasan GÖCEN / Hüseyin KALYONCU / Muhittin KAPLAN
Introduction
The relationship between private and public savings has been central issue in both
the theoretical and the empirical literature. The importance of the subject stems from
the fact that the effectiveness of fiscal policy is closely related to the responsiveness
of private saving to changes in fiscal stance. The relationship between lower public
deficits and national savings, however, remains controversial both theoretically and
empirically. Theoretically, while Keynes (1936) assumes no relationship between
private and public savings, Friedman (1957) and Modigliani (1946) develop models
showing full substitution between private and public savings. Barro (1974) also
introduced the notion of perfect substitutability between private and public savings,
which is called Ricardian Equivalence Proposition (REP).
Although there area number of opposing views in the theoretical literature,
ultimately, it is an empirical issue to determine the extent to which private savings
offset public savings. In the empirical literature, the relationship between private
and public savings is investigated for different countries using different econometric
methodologies. However, there is no consensus over the size offset coefficient (for
a survey see Seater, 1993, Holmes 2006 and Ricciuti 2007). Studies on advanced
economies have shown that about half of the change in public savings is offset by an
opposite change in private saving (Masson et. al. (1998); Hemming et. al. (2002);
Holmes (2006); Mandal and Payne (2007); Seater and Mariano (1985); Leiderman
and Razin (1988); Makin and Narayan (2009); De Castro andFernandez (2009)).
Although empirical studies are limited in number, offset coefficients were found
to be higher for developing countries than for developed countries (Loayza et. al.
(2000); Lopez et. al. (2000); De Mello et. al.(2004); Edwards (1996); Masson et. al.
1998; Bulir and Swiston (2009)).
This study provides evidence on the validity of the REP by applying powerful
econometric techniques of DOLS and FMOLS to time series data of a developing
country, Turkey. This paper is organized as follows. Following section sets out the
econometric methodology and the data employed in this study. Then, we presented
the findings of the study in the empirical section. Last section concludes.
6
Journal of Economic and Social Studies
Do Private Savings Offset
Public Savings in Turkey?
Methodology and Data
Empirical studies on testing the REP estimate the following model:
(1)
where refers to private sector savings as a proportion of GDP, is public sector savings
as a ratio to GDP; is the long-run public-private offset (substitution) coefficient is
the intercept term and represents usual error term. takes value between 0 (no offset)
and -1 (full offset). If , then a decrease in public sector savings is fully offset by an
increase in private sector savings.
The data employed in our empirical analysis is an annual private and public sector as
a percentage of GDP obtained from State Planning Organization (SPO) publications
for the years 1975 and 2005. Before estimating the long-run offset function given
in equation (1), we first need to investigate the time series properties of the private
and public sector saving ratios. Results obtained from unit root tests which are
performed to determine whether savings variables have a unit root are presented in
Table 1a and Table 1b. While Table 1a presents the results obtained from the ADF,
DF-GSL, PP, KPSS and ERS unit root tests, Table 1b shows the Ng-Perron unit
root test results. Examination of the Tables show that the null hypothesis of unit
root could not be rejected for both private and public sector savings ratios.
Table 1.a. Unit Root Test Results
Constant
-1.432876
-1.367547
-1.454917
0.538798
8.002194
ADF
DF-GLS
PP
KPSS
ERS
PSR
Constant and Trend
-1.133958
-1.595668
-1.253357
0.110454
13.83224
Constant
-1.473065
-1.384922
-1.479741
9.029962
8.084297
GSR
Constant and Trend
-2.322051
-1.798766
-1.480789
0.380299
12.96383
Note: ADF, DF-GSL, PP, KPSS and ERS stand for Augmented Dickey-Fuller (1979), Phillips Perron (1988),
Elliot, Rothenberg, and Stock (1996), Kwiatkowski, Phillips, Schmidt and Shin (1992), Elliot, Rothenberg,
and Stock point optimal (ERS, 1996) unit root tests.
Volume 3
Number 2
Fall 2013
7
Hasan GÖCEN / Hüseyin KALYONCU / Muhittin KAPLAN
Table 1.b. Ng-Perron Unit Root test Results
PSR
GSR
Asymptotic critical values*:
1%
5%
10%
MZa
-3.24375
-3.23349
MZt
-1.25975
-1.27022
MSB
0.38836
0.39283
MPT
7.53622
7.57531
-13.8000
-8.10000
-5.70000
-2.58000
-1.98000
-1.62000
0.17400
0.23300
0.27500
1.78000
3.17000
4.45000
Note:The number of lags used in Ng-Perron (2001) unit root test is determined by Schwarz Information
Criteria(SIC) and turned out to be zero for all specifications.
Having established that private and public savings ratios are I(1) variables, we need to
test for cointegration between private and public savings to avoid spurious regression.
To determine whether there is long-run relationship among these variables, the
Engle-Granger (1987) methodology is employed. Testing for cointegration within
this methodology involves extracting the residuals from equation (1) and testing
for unit root in residuals. The Engle-Granger bivariate cointegration equation
and the ADF tests applied to residuals are reported in Table 2. The optimal lag
determined by using Schwarz and Akaike information criteria turned out to be zero.
The cointegration test statistic is -2.086 with a probability value of 0.251 implying
non-rejection of the null of unit root in residuals. Hence, there appears to there is no
long-run relationship between private and public sectors savings ratios.
Table2. Engle- Granger Cointegration Test
Dependent Variable
PSR
Constant
20.157
(0.531)*
ADF test statistics (probability):
-2.086 (0.251)
Test Critical values:
1% level
5% level
10% level
GSR
-1.009
(0.101)*
-3.671
-2.964
-2.621
Note: The values in parenthesis are standard errors. * indicate significant at 1% level.
Furthermore, we employed Johansen multivariate cointegration tests to explore if
there is a long run relationship between private and public savings. The number of
8
Journal of Economic and Social Studies
Do Private Savings Offset
Public Savings in Turkey?
lags used in the underlying the vector auto regression (VAR) model were determined
as one for the model according to both the Schwarz Bayesian Criterion (SBC) and
Akaike’s Information Criterion (AIC). The corresponding values of SBC and AIC
criterion are 9.160 and 8.867 respectively.
The cointegration test results obtained from the Johansen and Juselius (1990)
method for the model (1) is presented in Table 3. The examination of the table
indicates that the null hypothesis of no cointegration cannot be rejected by both the
maximum eigenvalue and the trace statistic for the model implying that there is no
long-run relationship between private and public savings.
Table 3. Johansen-Juselius Maximum Likelihood Co integration Tests
Trace Test
Null
Alternative
r=0
r≥1
r≤1
r≥2
Statistic
11.946
1.881
Critical Values
15.494
3.841
Maximum Eigenvalue Test
Null
Alternative Statistic
r=0
r=1
10.065
r≤1
r=2
1.8810
Critical Values
14.264
3.8415
Notes: Asterisks (*) denotes statistical significance at 5%. R stands for the number of cointegrating vectors.
However, the cointegration tests have a low power in the presence of a structural
break (Gregory and Hansen, 1996). For this reason, we applied Gregory-Hansen
cointegration procedure to test whether there is long-run relationship among private
and public savings. Specifically, Gregory and Hansen (1996) provide the following
three structural break alternatives given by equations (2a-2c):
(2a)
(2b)
(2c)
where D represents a dummy variable equal to 0 if is less than or equal to unknown
timing of change , otherwise it is equal to one; is time trend; other variables are
defined as before. The first co integration regression (2a) is allowed to have a level
break, the second model includes level shift and time trend and third model includes
regime shift variable.
Volume 3
Number 2
Fall 2013
9
Hasan GÖCEN / Hüseyin KALYONCU / Muhittin KAPLAN
Given that the structural break point is unknown, Gregory-Hansen procedure
involves computing the cointegration test statistics for each possible break and
taking the minimum test statistics (ADF test) across all possible break points. That
is, the break point is unknown and determined by finding the minimum value for
the ADF statistic. The Akaike Information criterion (AIC) is used to determine
the number of lags of the change in the residual used in computing the ADF
statistic and turned out to be zero for all three models. The results of the GregoryHansen Cointegration procedure for all specifications indicate that the null of no
cointegration is rejected with an endogenous break year of 1989. The ADF statistics
for equations (2a-2c) are -5.082, -5.34836 and -5.15361 respectively and they are
statistically significant at 5 percent level.
Empirical Results
Having found evidence of co integration and having established that private and
public saving are I(1), the equations (2a-2c) are estimated using the Dynamic
OLS (DOLS) proposed by Stock and Watson (1993) and the FMOLS proposed
by Phillips and Hansen (1990).In the estimation of equations (2a-2c) with the
Dynamic OLS (DOLS), we used two lead and lag terms. The number of lead and
lag-terms are determined by using AIC and SBC criterion. The results obtained
from FMOLS and DOLS estimators are presented in Tables 4a-4c. Examination
of the Tables indicates that while the FMOLS coefficients of offset (betas) ranges
between -0.82 and -0.46, the DOLS coefficients of betas ranges from -0.74 to -0.11
yielding a partial offset. For models (2a) and (2b), coefficient on government savings
is statistically significant at 1% level. However, the offset coefficient is insignificant
in the model (2c). The long-run offset coefficient estimated by FMOLS (DOLS)
is -0.458 (-0.11) but they are both statistically insignificant. However, there was
statistically significant (at 5% level) change in the slope coefficient, , after 1989 for
DOLS estimates. Thus allowing for the slope change in the regime shift specification
in the DOLS case, the long-run coefficient is -0.72 (. The structural break dummy,
D, is significant across alternative estimates implying the presence of structural
break in the data. Taken together, the results show that a structural break did occur
in the long-run relationship between private and public saving in 1989.
10
Journal of Economic and Social Studies
Do Private Savings Offset
Public Savings in Turkey?
Table 4.a. FMOLS and DOLS Estimates for Level Shift Model, 1975-2005
FMOLS
16.129
(1.002)*
-0.709
(0.129)*
5.112
(1.268)*
Constant
GSR
D
DOLS
15.734
(0.682)*
-0.741
(0.0967)*
5.377
(0.891)*
Note: *, **, *** indicate significance at 1%, 5% and 10% level of significance respectively. The values in parenthesis are standard errors.
Table 4.b. FMOLS and DOLS Estimates for Level Shift with trend Model, 1975-2005
FMOLS
18.263
(1.310)*
-0.819
(0.124)*
7.320
(1.503)*
-0.193
(0.084)**
Constant
GSR
D
TREND
DOLS
13.892
(1.393)*
-0.577
(0.148)*
4.693
(1.049)*
0.137
(0.088)
Note:Seethenote in Table3.a.
Table 4.c. FMOLS and DOLS Estimated for Regime Shift Model, 1975-2005
FMOLS
14.571
(2.977)*
-0.458
(0.462)
6.627
(3.032)**
-0.268
(0.483)
Constant
GSR
D
DGSR
DOLS
11.685
(2.263)*
-0.109
(0.349)
9.355
(2.318)*
-0.613
(0.322)**
Note:Seethenote in Table3a.
Volume 3
Number 2
Fall 2013
11
Hasan GÖCEN / Hüseyin KALYONCU / Muhittin KAPLAN
Concluding Comments
This study examines the long-run relationship between private and public sector
saving ratios using FMOLS and DOLS methodologies. Empirical findings of this
study can be summarized as follows: First, there is no long-run relationship between
private and public savings unless endogenous structural break in the cointegration
relationship is allowed in Turkish case. Secondly, the extent of offset coefficients
ranges from -0.82 to -0.11 supporting weak form of Ricardian equivalence.
Statistically significant change in the slope coefficient in DOLS case also shows
that the substitution (offset) between private and public savings are stronger after
1989. This point is particularly worth mentioning because financial repression in
Turkish economy was fully removed at this date. Thirdly, the results of the paper
suggest that the effectiveness of fiscal policy implementations by the government
has decreased significantly after achieving financial liberalization in 1989.The
statistically significant and relatively large coefficient () on regime shift variable can
be taken as an evidence for this argument.
References
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Do Private Savings Offset
Public Savings in Turkey?
Engle, R. F. & Granger,C. W. J. (1987), Co-integration and error correction: representation, estimating
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Volume 3
Number 2
Fall 2013
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Hasan GÖCEN / Hüseyin KALYONCU / Muhittin KAPLAN
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14
Journal of Economic and Social Studies
Journal of Economic and Social Studies
Store Personality: Perceptions Towards
Consumer Electronics Chain Stores in
Turkey A Case of University Students
Keti VENTURA
Ege University, Faculty of Economics and Administrative Sciences,
Business Administration
Ege University Campus, 35100 Bornova İzmir
keti.ventura@ege.edu.tr
Ipek KAZANCOGLU
Ege University
Elif USTUNDAGLI
Ege University
Rezan TATLIDIL
Ege University
AbstrAct
The purpose of this study is to identify, develop and compare the determinants of store personality of the most preferred consumer electronics
chain stores, as perceived by young consumers in Turkey. A questionnaire survey including a 22-item store personality scale was conducted
among 855 students using a convenience sampling method. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA)
was performed. Findings suggest that greater accuracy of information is
needed in the purchasing decision related to high involvement products
such as consumer electronics. Also it was found that younger consumers
prefer reliable stores that give accurate information, value for money,
and provides price-quality fit. This study addresses the neglected area
of store personality development and validation for consumer electronics relates through an understanding of young consumers perceptions
towards store personality determinants.
KEYWOrDs
Store personality, Consumer
Electronic Chain Stores,
Confirmatory Factor Analysis,
Turkey
ArtIcLE HIstOrY
Submitted: 31 July 2012
Resubmitted: 05 November 2012
Resubmitted: 18 December 2012
Accepted: 21 December 2012
JEL codes: M31, M39
Volume 3
Number 2
Fall 2013
15
Ahlem-Selma MESSAI / Fathi JOUINI
Introduction
In recent years, the growing importance of technology in our daily life has increased
enthusiasm for consumer electronics consumption. In particular, young consumers,
who are leading the adoption of new technologies, have become more ambitious in their
purchases (Accenture, 2012, p. 6). In Turkey, consumer electronics is one of the fastest
growing markets, with sales of 3,648 million TL in 2011 (GfK, 2011), with several
new entrants establishing themselves the market. However, many of the products and
brands sold in consumer electronics retail stores are perceived as being very similar
(Yozgat and Deniz, 2008, p. 121). Pursuing sustainable competitive advantage in the
current market environment necessitates some degree of differentiation in the products
offered by consumer electronics retailers. Therefore, as individual customers tend to
attribute humanized characteristics to brands or products, building a particular store
personality with appropriate characteristics (Blankson and Crawford, 2012, pp. 311315) can be an effective way to differentiate a particular store from competitors, and
position itself through these characteristics, which include product availability, service
quality, value for money, and store atmosphere.
The concept of “brand as a person”, or in other words “brand personality”, as the set
of human characteristics associated with a brand (Aaker, 1997, p. 347) is an important
concern for consumers, and in turn, for marketers and academicians (Grohmann,
2003, p. 224; Aaker and Fournier, 1995, p. 392; Wang and Yang, 2008, p. 460;
Ambroise, et al., 2005, p. 32). Customers interaction with brands is often similar
to their interaction with other people, especially when the brands are attached to
such meaningful objects as clothes or cars (Aaker, 1996, p. 142). As individuals tend
to associate the brand with their life situations and roles (Ligas and Cotte, 1999, p.
611), interaction with brands as if they were people necessitates defining personality
traits that affect the relationship between attributes of people and their behavior in
various situations (Hurley, 1998, p. 116), such as purchasing. Furthermore, in order
to be useful in a social context, a brand’s meaning should be formed based on three
components: its physical make up, functional characteristics, and characterizationi.e., personality (Ligas and Cotte, 1999, p. 612). As human or brand personalities are
related in the context of retail stores (Brengman and Willems, 2008, p. 27), consumers
are able to identify a particular personality related to a store based on both its tangible
(design, environment, etc.) and intangible (attitude of sales personnel, service quality,
etc.) components. Despite approximate similarity in price, service, merchandising and
marketing activities, some stores are overwhelmingly preferred to others (Martineau,
1958, p. 47). Thus, it could be concluded that there should be other factors that
16
Journal of Economic and Social Studies
Predicting Banking Distress in European Countries
directly or indirectly affect consumers, and in turn, their preferences. Store personality
is considered to be one factor responsible for differentiating and positioning a store,
because when a store is humanized, it relates to self-meaning that has congruent
personalities to oneself (Chan, et al., 2003, p. 302), this being consistent with the
“self-congruity” theory (Sirgy and Samli, 1985; Sirgy, et al., 2000).
As Turkish consumer electronics chain stores are all highly competitive and
implement similar marketing strategies, some degree of differentiation is necessary
within their positioning strategies, especially in regard to younger consumers. In
this respect, the purpose of this study is to identify and compare the determinants
of store personality of the most preferred consumer electronics chain stores, as
perceived by young consumers in Turkey. Additionally, it aims to explore specific
store personality determinants, and also to develop a scale in a consumer electronics
chain store context. Accordingly, exploratory factor analysis (EFA) and confirmatory
factor analysis (CFA) were applied to the most preferred consumer electronics chain
stores, in order to validate the scale. The conceptual framework for the empirical
research was based on store personality in retailing services. In the first section of
the study, the concept of store personality is discussed. Following this, the research
design and the results of the study are presented. The study is concluded by outlining
the implications and recommendations for the practitioners, the limitations of the
study, and opportunities for further research.
Store personality has been investigated by relatively few researchers including
Martineau (1958), d’Astous and Levesque (2003), Brengman and Willems (2008).
As the scales developed in these studies are too general, and based on a specific
context, they cannot be appropriately applied to consumer electronics chain stores.
Accordingly, the studies of these authors are utilized to develop a new scale to increase
understanding of the perceptions of university students’ towards consumer electronics
chain stores. The findings of the present study have the potential to contribute to store
personality literature by developing and validating a store personality scale for the use
of consumer electronics retailers to position themselves in young consumer markets.
Literature Review
The concept of store personality was introduced by Martineau (1958, p. 47), who
defined it as “the way in which the store is defined in the shopper’s mind, partly
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Ahlem-Selma MESSAI / Fathi JOUINI
by its functional qualities and partly by an aura of psychological attributes”. Store
personality is commonly related to store image, but there are important differences
in meaning. Although store image is associated with all the dimensions related to the
store, store personality is restricted to those dimensions that correspond to human
traits (d’Astous and Levesque, 2003, pp. 455-456). As the concept of human and
brand personality are both directly transferable within the context of retail stores
(Brengman and Willems, 2008, p. 27; Khan, 2010, pp. 9-10) these traits are relevant
to the concept of “brand personality”.
Aaker (1997) proposed the commonly accepted brand personality dimensions
(sincerity, excitement, competence, sophistication, and ruggedness), and defined the
concept, mainly by focusing on its positive attributes. The brand personality concept
can help brand strategists enrich their understanding of people’s perceptions and
attitudes toward the brand. It contributes to a differentiated brand identity, guiding
the communication effort and creating brand equity (Aaker, 1996, p. 150). Customers
often interact with brands in the same way they interact with other people (Aaker,
1996, p. 142). When consumers view it as having human characteristics, the brand
is said to have a personality. Examples of brands found to have strong personalities
include Harley Davidson (ruggedness) and Nike (excitement). Madrigal and Boush
(2008) stated that trait inferences can also be made about store personality from the
combination of marketing mix elements in which the retailers engage. For the stores
themselves, other attributes, such as ambience, design and social components are
also of concern (d’Astous and Levesque, 2003, p. 457) as these could directly affect
the perception of store personality. Other aspects that affect store personality are
store name, store environment, service quality, store personnel, merchandise quality,
and carried brand names (Brengman and Willems, 2009, p. 347).
A number of studies on store personality were conducted by Martineau (1958), who
proposed the main influencing factors could be classified into three main areas: layout
and architecture, symbols and colors, and advertising and sales personnel. However,
d’Astous and Levesque (2003) stressed that the dimensions used by Martineau (1958)
were related with image rather than personality, and they developed a 5 dimensional
scale, consisting of “sophistication”, “enthusiasm”, “genuineness”, “solidity” and
“pleasantness”, which included a total of 34 sub items. In the same study, they also
prepared a reduced scale with the highest factor loadings: “enthusiasm” (welcomeness,
enthusiasm, liveliness and dynamism); “sophistication” (chicness, being high class,
elegance and style); “genuineness” (honesty, sincerity, reliability and honesty/truth);
“solidity” (hardiness, solidity, reputation and prosperity) and “unpleasantness”
18
Journal of Economic and Social Studies
Predicting Banking Distress in European Countries
(annoyance, irritation, loudness and superficiality). These dimensions were those
which had been most commonly accepted and used in previous studies (Brengman
and Willems, 2009). In Brengman and Willems’ (2008) study, in which a fashion store
was evaluated in the terms of store personality, 5 major classifications were proposed.
These were “store atmosphere” related with design, ambience and social factors;
“merchandise” related with price, quality, style and assortment; “retailer’s reputation”
related with “word-of-mouth”, advertising, communication and social responsibility;
“service” related with direct interactivity along with “format and location”.
In a store environment, factors as such as attachment, experience and structure
are also important. These formations are evaluated through defining mechanisms,
triggering memories linked to affect, which is either positive (Orth, Limon and Rose,
2010, p. 1207) or negative. Thus consumers develop a perception about a particular
store that will affect shopping decisions. For this reasons, the design and structure of
the store, and the qualities of the sales personnel represent important indicators of
perceived store personality. Where the environment is formal, expressive, symbolic
and has a professionally planned setting that interacts with the product, (Fiore
and Ogle, 2000, p. 34) it influences the customer’s perception of store personality
(Harrell and Hurt, 1976). As consumers repeatedly see, touch, hear and smell the
commodities, as well as experience the environment, they derive value from formal,
expressive and symbolic qualities, and this process influences their beliefs about the
store (Fiore and Ogle, 2000, p. 34; Darden and Babin, 1994, p. 101). Subsequently,
they associate the brand with their lifestyles and roles, thus there is a strong
connection with their view of “self ” (Ligas and Cotte, 1999, p. 613). Thus, they use
brand personality to define their sense of “self ” and tend to seek brands or stores
with congruent personalities (Chan, et al., 2003, p. 304), consistent with the “selfcongruity” theory (Sirgy and Samli, 1985; Sirgy, et al., 2000). However, the way a
store is perceived depends on the personality of each customer (Wesley, et al., 2006,
pp. 167–168). The impressions in consumers’ minds will result in particular store
preferences (Martineau, 1958:55; Brengman and Willems, 2009, p. 352). A good
impression can be achieved by building a store personality and finding a suitable
“location” in the minds of a group of consumers or a market segment (Keller, 2003,
p. 119), a strategy known as “positioning”.
Most importantly, brands’ objective personality traits do not exist independent of
consumer perception (Zentes, Morschett and Schramm-Klein, 2008, p. 169). The
process by which consumers use a product category and attribute information from
memory has implications for selecting the appropriate positioning strategy to achieve
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Ahlem-Selma MESSAI / Fathi JOUINI
brand association (Punja and Moon, 2002, p. 276). The brand, with its symbolic
and human attributes, customizes its marketing mix according to store personality.
However the personality that managers aim to implement may be different to that
perceived by consumers. If there is a major gap between managers’ implementations
and consumers’ perceptions of these, then it will be impossible for managers to
communicate with consumers in a satisfactory manner.
As store personality is directly related with “the perceptions of consumers”, it
becomes important to evaluate store personality in the context of store positioning.
Perceptions are mostly formed according to the factors representing the store’s
“intangible assets”, which, according to Hooley, et al. (2001), are most difficult
for competitors to imitate. Therefore, if a firm can succeed in positioning itself
through personality characteristics, it will make an important contribution to its
performance in terms of competition and long-term survival.
While, the literature contains a number of studies on the determinants of brand
personality, there is a need for further studies on store personality and its determinants,
as these have received less attention. In this field, Martineau (1958) mostly focused on
store image attributes to define store personality, d’Astous and Levesque (2003) utilized
Aaker’s (1997) brand personality dimensions to develop a general store personality
scale; however, this does not fit all retail stores. One example of the development of
a new scale is Brengman and Willems’ (2008), which used qualitative methods to
develop a scale for fashion stores based on d’Astous and Levesque (2003). In this study,
we draw on this previous research (Martineau, 1958; d’Astous and Levesque, 2003;
Brengman and Willems’, 2008) to understand the perceptions of young consumers
towards the determinants of store personality. Using survey methodology, a new store
personality scale is developed for consumer electronics chain stores.
Field Study
According to the GfK Retail and Technology 2011 Report, consumer electronics
is one of the fastest growing sub-sectors in Turkey, with sales of 3,648 million TL.
The consumer electronics sub-sector includes of color televisions, audio appliances,
video players, cash registers, audio-video cassettes, television satellite receivers and
antennas, electronic scales and electronic calculators. There are various domestic and
foreign actors in the Turkish market, notably Teknosa, Vatan Computer, Bimeks,
20
Journal of Economic and Social Studies
Predicting Banking Distress in European Countries
Darty, MediaMarket, BestBuy, Electroworld and Gold. These highly competitive
market players need to be differentiated through their positioning strategies. A
consumer electronics product is not only a tool with which the user performs a
task, but also a decorative item for the home, or means to express one’s personality
and lifestyle (Han, et al., 2001, p. 145). For this reason, the purchase of electronics
products entails high involvement, in which consumers seek specific qualities in
the products themselves. This very personalized approach makes the consumer
electronics sector particularly suitable for store personality research.
In this competitive environment, building store personality can be a significant factor
in positioning a store. Within this context, the aim of this study is to explore and
compare the determinants of store personality, as perceived by young consumers,
of the most preferred consumer electronics chain stores in the Turkish market. In
March 2011 a questionnaire survey was conducted among 855 students from the
Faculty of Economics and Administrative Sciences, Ege University in Izmir, using
a convenience sampling method. The questionnaires, which took 10-15 minutes to
complete, were distributed in the classes and campus area by three research assistants,
who had been informed of the content. This sample was chosen due to the fact that
young consumers are more familiar with consumer electronics and often influence
family purchasing decisions (Hafstrom, et al., 1992). In addition, the enthusiasm of
young people for consumer electronics makes them a potentially highly profitable
segment of the market (Accenture, 2012, p. 15).
The questionnaire consisted of three sections. The respondents were asked to state their
preferred consumer electronics store in the first section. The second section gave 22
statements relating to the determinants of store personality for the consumer electronics
context. These statements, generated by the author, were based on the following:
Martineau’s (1958) store personality determinants (architecture, colour schemes,
advertising, salespeople and others), d’Astous and Levesque’s (2003) determinants for
store personality dimensions; and Brengman and Willems, (2008, 2009)’s five major
fashion store personality determinants (store atmosphere, merchandise, reputation,
service and format). Brengman and Willems, (2009) determined four categories
containing different items as follows : (i) “store atmosphere”: interior design, music,
layout, window display (Berman and Evans, 2010, pp. 508-509); (ii) “merchandise”:
price, quality, product range (Berry, 1969); (iii) “service”: sales people’s attitudes
(O’Cass, A. and Grace, D., 2008); (iv) “format”: premium branded products, highincome level target (Brengman and Willems, 2009). A 5-point ‘Likert’ scale ranging
from “strongly disagree (1)” to “strongly agree (5)” was utilized. Finally, in the last
section, there were some demographic questions related to the respondent’s gender,
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Ahlem-Selma MESSAI / Fathi JOUINI
age, income level. The questionnaire was originally prepared in Turkish, and the
statements were translated into English for the tables.
The findings of the study are presented in two parts. In the first part, EFA was
conducted to the determinants (Martineau, 1958; d’Astous and Levesque, 2003;
Brengman and Willems, 2008) of store personality in order to identify specific
factors of store personality and obtain important insights about the data structure.
In the second part of the study, ANOVA is performed to compare the perceptions
of respondents to the specific determinants of store personality. Following this, first
and second-order CFA was performed for each most preferred store in order to test
the validity of scale, that is to assess its fit to the proposed theoretical basis.
Findings
The sample comprised 53.1 % female and 46.9 % male students. TeknoSa (52.4
%), MediaMarkt (27.9 %) and Vatan Computer (21.1 %) were chosen as the most
preferred consumer electronics chain stores, comprising 87.9 % of the sample. The
profile of the sample appears in Table 1.
Table 1. Profile of the sample
Variables
Sex
Female
Male
Missing
N
Valid Percent
379
335
38
53.1
46.9
--
Total
752
100
Variables
Monthly Income
650-1379 TL
1380-2109 TL
2210-2839 TL
2840-3569 TL
3570-4299 TL
4300-5029 TL
5030-5759 TL
5760-6489 TL
6490 TL +
Missing
Total
N
Valid Percent
236
174
113
49
44
18
12
9
28
69
752
34.6
25.5
16.5
7.2
6.4
2.6
1.8
1.3
4.1
100
Mostly Preferred Electronic Store
Age
TeknoSA
Mediamarkt
Vatan
Total
18-24
25-31
607
145
80.7
19.3
Total
752
100
22
384
210
158
752
51.0
27.9
21.1
100
Journal of Economic and Social Studies
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In order to establish the evaluations related to the statements determining store
personality, one sample t-test was conducted. As shown Table 2, the findings of one
sample t-test about the respondents’ perceptions of store personality determinants
revealed that young respondents (a) can easily find the products they are looking for in
these stores (t=31.622 df:739 p=0.000), (b) visit these stores for its premium branded
products (t=23.362 df:736 p=0.000), (c) get accurate information (t=28.401 df:747
p=0.000) and (d) receive value for their money (t=20.535 df:743 p=0.000).
Table 2. One Sample T-Test of the Respondents’ Evaluations
Statements
Mean
I visit this store for the premium branded products.
3.88
I think stores like this sell high-priced products.
3.09
I appreciate the interior design of this store.
3.60
I think this store serves high-income customers.
2.81
I appreciate the window display of this store.
3.32
The music played in this store enables me to take pleasure from
3.31
shopping
I appreciate the young and dynamic sales staff of this store
3.15
I find more suitable consumer electronics products for young
3.54
people in this store compared to other stores
Only the latest technology products are sold in this store
3.65
The low turnover of salespeople in this store gives me confidence. 3.21
The salespeople in this store are very knowledgeable.
3.56
I can easily find what I am looking for in this store.
3.96
This store determines a price which is appropriate for the quality
3.71
of the product.
Information given related to the products is correct in this store. 3.86
I think the advertisements of this store give accurate information. 3.66
I think this store always gives me value for money.
3.70
I do not think that this store makes false claims to increase sales.* 2.36
I do not like the aggressive attitude of the salespeople towards
3.52
customers.*
Whenever I want to buy a product from this store, they tell me
3.69
that the product is out of stock *
The confusing layout of this store makes it difficult to find what I
3.74
am looking for.*
This store’s interior colour irritates me. *
3.77
The constant crowding in this store irritates me. *
3.35
Std.
dev.
0.991
1.129
0.982
1.124
1.029
t
df
Sig.
25.822
2.389
17.865
-4.976
8.852
854
854
854
854
854
0.000
0.017
0.000
0.000
0.000
1.072
4.007
854
0.000
1.029
15.279 854
0.000
0.945
19.963 854
0.000
1.080
1.069
0.961
0.820
5.674
5.628
16.980
34.351
854
854
854
854
0.000
0.000
0.000
0.000
0.899
22.905 854
0.000
0.815 30.762
0.900 21.403
0.895 23.006
0.982 -18.943
854
854
854
841
0.000
0.000
0.000
0.000
1.130
13.310 836
0.000
1.030
19.489 842
0.000
1.009
21.286 838
0.000
0.996
1.108
22.269 835
9.307
846
0.000
0.000
Test value is 3 (neither agrees nor disagrees) *recoded
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Ahlem-Selma MESSAI / Fathi JOUINI
Common
Factors
Factor Interpretation
Factor
(CumulaLoadtive % of
ing
variance
explained)
Statements
The confusing layout of this store makes it difficult to
find what I am looking for.*
This store’s interior colour irritates me. *
Pleasantness Whenever I want to buy a product from this store, they
tell me that the product is out of stock.*
The constant crowding in this store irritates me.*
I do not like the aggressive attitude of the salespeople
towards customers.*
Information given related to the products is accurate in
this store.
I think this store always gives me value for money.
I think the advertisements of this store give accurate
Reliability
information.
The salespeople in this store are very knowledgeable.
This store determines a price which is appropriate for
the quality of the product.
I appreciate the interior design of this store.
I appreciate the window display of this store.
Welcomeness
The music played in this store enables me to take pleasure from shopping.
KMO
Bartlett Test
Cronbach
Alpha
0.799
0.791
0.762
21.775
0.80
41.989
0.77
56.032
0.67
0.694
0.640
0.751
0.735
0.727
0.670
0.626
0.812
0.752
0.704
0.834
2940.500; (df: 78; p<0.05)
An exploratory factor analyses was perfomed on the total sample in order to identify
the specific determinants of the store personality with Varimax rotation. The KaiserMeyer-Olkin (KMO) test and Bartlett’s test of sphericity were computed to assess
the appropriateness of factor analyses to the data. The Kaiser-Meyer-Olkin Measure
(KMO) of Sampling Adequacy (0.834) also showed that sample adequacy was
satisfactory and the Bartlett’s test of sphericity was significant (p<0.000). The factor
analysis of the 22 item scale yielded a ‘three principal components’ solution. Each of
these three factors had an eigen value greater than one. The statements with factor
loadings lower than 0.50 were removed from the study. During the factor analysis,
eight variables that were unrelated to any factor were excluded, and a total of three
factors were extracted from the remaining 13 items. The analysis produced three
store personality factors, and explained 56.3% of the variance. Also, Cronbach’s
24
Journal of Economic and Social Studies
Predicting Banking Distress in European Countries
alpha coefficients were calculated in order to check the internal consistency and
reliability of each factor. Factor loadings ranged from 0.63 to 0.81 and alpha
coefficients ranged from 0.67 to 0.80, indicating a high internal consistency and
reliability for the factors. The factors were declared as “Pleasantness”, “Reliability”
and “Welcomeness” in accordance with their respective factor loadings (Table 3).
Table 3. Results of Exploratory Factor Analysis
Common
Factors
Factor
Loading
Statements
The confusing layout of this store makes it difficult
to find what I am looking for.*
This store’s interior colour irritates me. *
Pleasantness Whenever I want to buy a product from this store,
they tell me that the product is out of stock.*
The constant crowding in this store irritates me.*
I do not like the aggressive attitude of the salespeople towards customers.*
Information given related to the products is accurate in this store.
I think this store always gives me value for money.
I think the advertisements of this store give accuReliability
rate information.
The salespeople in this store are very knowledgeable.
This store determines a price which is appropriate
for the quality of the product.
I appreciate the interior design of this store.
I appreciate the window display of this store.
Welcomeness
The music played in this store enables me to take
pleasure from shopping.
KMO
Bartlett Test
Factor Interpretation
Cronbach
(Cumulative Alpha
% of variance
explained)
0.799
0.791
0.762
21.775
0.80
41.989
0.77
56.032
0.67
0.694
0.640
0.751
0.735
0.727
0.670
0.626
0.812
0.752
0.704
0.834
2940.500; (df: 78; p<0.05)
In order to compare the respondents’ evaluations of “Pleasantness”, “Reliability”
and “Welcomness” factors, and explore the differences between the most preferred
stores, both a sample t-test and ANOVA were conducted. H1 is generated as follows:
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H1a/b/c/d/e/f/g/h/i/k/l/m/n: All three stores are statistically different according to
(a) layout, (b) interior colour, (c) product availability, (d) crowdedness, (e)
attitude of salespeople, (f )accuracy of product information, (g) value for
money, (h) accuracy of information in ads, (i) knowledge of salespeople, (k)
price-quality fit, (l) interior design, (m) window display and (n) in store
music.
Findings of the sample t-tests (Table 4) revealed that the majority of the mean values
for each item were very close among the three stores. Considering the findings, it
can be proposed that, although these three are the most preferred ones, they were
able to differentiate themselves to a limited extent in relation to store personality
determinants. It can be said that, although young people perceive these stores as being
similar in all services, Vatan Computer and Teknosa were considered to give better
value for money (F=7.847 df: 2/749 p=0.000) compared with MediaMarkt. Vatan
Computer sets more reasonable prices according to the quality of their products
(F=7.335 df: 2/749 p=0.001) than the other two. Sales personnel in MediaMarkt
are perceived to have more knowledge (F=4.662 df: 2/749 p=0.010) than those in
Teknosa. Also, the respondents who preferred MediaMarkt and Teknosa reported
that the music in these stores gave a more pleasurable shopping experience (F=6.601
df:2/749 p=0.001) than was stated by those who preferred Vatan Computer.
Considering these findings, H1g; H1k; H1i and H1n are supported (p<0.05).
26
Journal of Economic and Social Studies
Volume 3
Table 4. Comparison of One Sample T-Test of Three Stores
MediaMarkt
Teknosa
Common Factors
Number 2
Pleasantness
Fall 2013
Mean
t**
df
Mean
t**
13.812 386
3.71
9.873
206
3.78
10.093 142
3.74
14.750 385
3.74
10.548 200
3.77
9.972
145
Whenever I want to buy a product from this store, they tell
3.69
me that the product is out of stock.*
14.161 388
3.61
7.932
205
3.69
8.004
144
The constant crowding in this store irritates me.*
5.590
390
3.25
3.038
206
3.49
5.283
145
7.368
987
3.62
8.107
204
3.56
5.600
144
22.667 393
3.81
13.311 209
3.93
12.473 147
Statements
Mean
The confusing layout of this store makes it difficult to find
3.70
what I am looking for.*
This store’s interior color irritates me. *
3.30
I do not like the aggressive attitude of the salespeople to3.41
wards customers.*
Information given related to the products is accurate in this
3.83
store.
Reliability
Welcomeness
df
df
3.56
12.901 393
3.80
12.442 209
3.84
11.135 147
I think the advertisements of this store give accurate infor3.67
mation.
16.056 393
3.65
9.364
209
3.62
7.941
147
The salespeople in this store are very knowledgeable.
9.607
147
393
3.68
11.022 209
3.63
7.233
This store determines a price which is appropriate for the
3.56
quality of the product.
12.811 393
3.77
11.947 209
3.86
10.594 147
I appreciate the interior design of this store.
3.63
13.560 393
3.54
7.619
209
3.54
6.314
147
I appreciate the window display of this store.
3.35
7.489
393
3.37
5.150
209
3.14
4.369
147
The music played in this store enables me to take pleasure
3.12
from shopping.
2.280
393
3.29
3.909
209
2.87
3.422
147
Test value is 3 (neither agrees nor disagrees)
*recoded
**p<0.05
3.45
27
Predicting Banking Distress in European Countries
I think this store always gives me value for money.
t**
Vatan
Ahlem-Selma MESSAI / Fathi JOUINI
EFA is essential in determining the underlying constructs for a set of measured
variables. In order to test how well the measured variables represent the number
of constructs (Brown, 2006), CFA was conducted with Maximum Likelihood
Estimation in LISREL 8.80 (Jöreskog and Sörbom, 1997). CFA verifies the factor
structure of a set of observed variables and statistically tests the validity and reliability
of a hypothesized factor model (Suhr, 2006, p. 1). The hypotheses tested are as
follows:
H2: The correlated (first-order) store personality factors explain an
important proportion of the variance in the data.
H3: The set of store personality determinants comprises the latent variable,
overall store personality.
First-order CFA was performed to examine the construct more closely and establish
construct validity for each of the most preferred consumer electronics chain
stores. The estimation of the first-order CFA model revealed that the data defined
three factors with regression coefficients varying among the three stores. All the
coefficients were significant at the 5 % level (Table 5). Therefore, the hypothesis
H2 was supported. Vatan Computer store had the highest correlations between
“pleasantness and reliability” (r=0.68), “reliability and welcomeness” (r=0.74),
“pleasantness and welcomeness” (r=0.52) respectively. In order to obtain as much
understanding of the data as possible, second-order factor analysis was performed
(McClain, 1996, p. 131; Correia, et al., 2008, p. 167). In comparison to first-order
models with correlated factors, second-order factor models can provide a more
interpretable model (Chen, et. al., 2005, p. 472).
Second-order CFA was conducted on the three-dimensional model of perceived
store personality and compared each store independently, with the same items.
Figure 1 presents the hierarchical construct of perceived store personality, consisting
of several correlated first-order factors and a single second-order factor. In this
model, the latent variables were “perceived store personality”, “pleasantness”,
“reliability”, “welcomeness”, and the observed variables are store personality
determinants. “Pleasantness” and “reliability” were represented by five items each,
and “welcomeness” by three items.
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Journal of Economic and Social Studies
Predicting Banking Distress in European Countries
Figure 1. Second-Order Confirmatory Factor Analysis of Perceived Store Personality
LAYOUT
INTERIOR COLOR
PLEASANTNESS
PRODUCT
AVALIABILITY
CROWDED AFFECT
ATTITUDE OF
SALESPEOPLE
ACCURATE PRODUCT
INFORMATION
VALUE FOR MONEY
PERCEIVED STORE
PERSONALITYY
RELIABILITY
ACCURATE
INFORMATION IN ADS
KNOWLEDGEABLE
SALESPEOPLE
PRICE-QUALITY FIT
INTERIOR DESIGN
WELCOMING
WINDOW DISPLAY
IN STORE MUSIC
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Ahlem-Selma MESSAI / Fathi JOUINI
The standardized regression coefficients of the models and associated t-values for the
13 items are shown in Table 5. The output revealed that every standardized regression
coefficient and the associated t-values are significant (p ≤ 0.05). The resulting fit
indices (GFI, CFI, AGFI, RMSEA, χ2 /df ) for all three store personality models
displays satisfactory measure fit, which supported the construct validity of the
measures. In order to assess the convergent validity of “pleasantness”, “reliability” and
“welcomeness” constructs, construct reliability was computed. Construct reliability
values ranged from 0.617 to 0.893, which shows an acceptable convergent validity.
Discriminant validity is computed by latent variable correlation matrix (Table 6).
As seen from the Table 6, although some of the AVE (Average Variance Exracted)
values are at moderate level (AVE<0.5) (Paswan, 2009), the square root values of
AVE for all three stores are larger than the correlations, which demonstrates an
acceptable discriminant validity.
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Journal of Economic and Social Studies
Volume 3
Table 5. Results of the CFA of Store Personality Scale Among the Most Preferred Consumer Electronics Chain Stores
TEKNOSA (N=384)
Predictive Parameter Estimates
Number 2
Fall 2013
Overall Model Fit:
*Significant at p ≤ 0.05
VATAN (N=158)
31
Predicting Banking Distress in European Countries
PERCEIVED STORE PERSONALITY → PLEASANTNESS
PERCEIVED STORE PERSONALITY → RELIABILITY
PERCEIVED STORE PERSONALITY → WELCOMENESS
PLEASANTNESS →LAYOUT
PLEASANTNESS →INTERIOR COLOR
PLEASANTNESS →PRODUCT AVAILABALITY
PLEASANTNESS →CROWDEDNESS
PLEASANTNESS →ATTITUDE OF SALESPEOPLE
RELIABILITY →ACCURACY OF PRODUCT INFORMATION
RELIABILITY → VALUE FOR MONEY
RELIABILITY → ACCURACY OF INFORMATION IN ADS
RELIABILITY → KNOWLEDGABLE SALESPEOPLE
RELIABILITY → PRICE-QUALITY FIT
WELCOMENESS →INTERIOR DESIGN
WELCOMENESS → WINDOW DISPLAY
WELCOMENESS → IN STORE MUSIC
MEDIAMARKT (N=210)
Standardized
Standardized
Standardized
t-value Regression
R2
t-value Regression R2
t-value Regression
R2
Coefficients
Coefficients
Coefficients
2.77* 0.37
0.13
5.19*
0.66
0.44 5.53* 0.69
0.48
3.22* 0.83
0.68
4.44*
0.86
0.74 10.04* 0.98
0.97
2.64* 0.50
0.25
4.88*
0.50
0.25 8.22* 0.82
0.56
7.60* 0.76
0.58
7.73*
0.77
0.60 6.33* 0.82
0.67
7.49* 0.74
0.55
7.58 * 0.74
0.55 6.35* 0.83
0.69
7.34* 0.74
0.51
6.59*
0.60
0.36 5.52* 0.58
0.34
6.09* 0.54
0.30
5.57*
0.48
0.23 4.77* 0.45
0.20
0.50
0.36
0.61
0.37 0.46
0.21
6.25* 0.54
0.41
5.08*
0.69
0.48 10.68* 0.76
0.58
6.65* 0.72
0.52
5.07*
0.69
0.48 11.88* 0.85
0.72
6.66* 0.73
0.53
5.14*
0.73
0.53 10.99* 0.78
0.61
0.55
0.30
0.42
0.17 0.73
0.53
5.55* 0.53
0.28
4.30*
0.47
0.22 11.61* 0.83
0.68
0.55
0.30
0.82
0.67 0.74
0.55
3.43* 0.67
0.45
7.30*
0.72
0.52 10.44* 0.83
0.69
2.86* 0.30
0.088 6.34*
0.54
0.30 9.20* 0.70
0.49
GFI=0.93, AGFI=0.90,CFI= 0.94,GFI=0.95, AGFI=0.90,CFI=0.98,GFI=0.90, AGFI=0.87,CFI= 0.90,
RMSEA=0.033, χ262=96.34,χ2 /RMSEA=0.031, χ262=73.67, χ2/RMSEA=0.074, χ262=259.78, χ2/
df=1.55
df=1.18
df=4.19
Ahlem-Selma MESSAI / Fathi JOUINI
Table 6. The Latent Variable Correlation Matrix: Discriminant Validity
Reliability
Teknosa (n=384)
Pleasantness
Welcomeness
Reliability
MediaMarkt (n=210)
Pleasantness
Welcomeness
Reliability
Vatan Computer (n=158) Pleasantness
Welcomeness
Reliability
0.62
0.30
0.41
0.61
0.57
0.43
0.79
0.68
0.74
Pleasantness
Welcoming
0.67
0.18
0.53
0.65
0.33
0.70
0.75
0.52
0.76
Note: Square root of AVE is on the diagonal.
The values of some other goodness-of-fit indices are the following: GFITEKNOSA
= 0.93, AGFITEKNOSA = 0.90, CFITEKNOSA = 0.94, RMSEATEKNOSA = 0.033, χ2/
dfTEKNOSA=1.55; GFIMEDIAMARKT=0.95, AGFIMEDIAMARKT=0.90, CFIMEDIAMARKT=0.98,
RMSEAMEDIAMARKT=0.031, χ2/dfMEDIAMARKT=1.18; GFIVATAN=0.90, AGFIVATAN =0.87,
CFIVATAN= 0.90, RMSEAVATAN=0.074, χ2/dfVATAN=4.19. Therefore, the three store
personality factors determined perceived store personality, thus H3 is supported.
The factor “reliability” had the highest standardized regression coefficients among
the three stores. This means that when “reliability” increases by one, the perceived
store personality increases by 0.83; 0.86 and 0.98. In all three stores, the most
important determinants for the “pleasantness” factor are “layout” (βTeknosa=0.76;
βMediaMarkt=0.77; βVatan=0.82) and “interior color” (βTeknosa=0.74; βMediaMarkt=0.74;
βVatan=0.83). The reliability factor derives mainly from the “accurate information
in ads” (βTeknosa=0.73; βMediaMarkt=0.73) and “value for money” (βTeknosa=0.72;
βMediaMarkt=0.69) in Teknosa and MediaMarkt; “value for money” (βVatan=0.85) and
“price-quality fit” (βVatan=0.83) in Vatan Computer. The highest coefficients for the
“Welcomeness” factor were “window display” (βTeknosa=0.67; βVatan=0.83) in Teknosa
and Vatan Computer; “interior design” (βMediaMarkt=0.82) in MediaMarkt.
Conclusion and Implications
The consumer electronics market is one of the fastest growing in Turkey. In recent
years, the entry of global chain stores into the Turkish market and the extension
policies of local chain stores have increased competition in this sector. As 34.6 % of
32
Journal of Economic and Social Studies
Predicting Banking Distress in European Countries
the population in Turkey comprises young people (TSI, 2011, p. 13), the interest
in consumer electronics is growing rapidly, thus forcing consumer electronics
retailers to be more innovative in the diversification of their marketing and
positioning strategies. However, it can be seen that there is insufficient diversity in
the retailing mix policies and strategies among the retailers with regard to factors
such as goods and services offered, store location, operating procedures, pricing
tactics, store atmosphere, customer services and promotional methods. Within this
context, the purpose of this study is to identify and compare the determinants of
the most preferred consumer electronics chain stores’ personalities, as perceived by
a representative sample of Turkish university students. It aims to explore the factors
that make up the specific store personality determinants in a consumer electronics
chain store context. The reason for this is the critical need for the most popular
electronics product chain stores to differentiate and gain competitive advantage,
especially for young consumers such as university students, who represent an
important section of this market (Accenture, 2012, p. 15).
In the literature, there are few studies relating to store personality. This concept
was firstly introduced by Martineau (1958), who mainly focused on store image
attributes in defining store personality, while d’Astous and Levesque (2003)
developed a “general” store personality scale based on Aaker’s (1997) brand personality
dimensions. Additionally, Brengman and Willems (2008) developed a scale using
retailing mix, aimed specifically at “fashion stores”. As the scales developed in these
studies are generalized and context based, they are not appropriate for consumer
electronics chain stores. Accordingly, these studies have been utilized as the basis
for a new scale specifically designed to gain an understanding of university student
perceptions of chain stores in the electronics sector.
The findings of the present study contributes to the literature by developing and
validating a store personality scale specifically for consumer electronics retailers
based on university students’ perceptions of store personality determinants. In the
Turkish market, Teknosa, MediaMarkt and Vatan Computer were selected as the
most preferred chain stores. In the study, in order to identify specific factors of
store personality, EFA was conducted and three factors were identified: “reliability”,
“pleasantness” and “welcomeness”. Following this, CFA was performed on these
factors and a confirmatory factor analytic model was generated. First-order models
with correlated factors were performed to examine the construct more closely,
while second-order factor analysis was used to define the most important factors
and determine the relative importance of each factor to the overall, for each
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Ahlem-Selma MESSAI / Fathi JOUINI
chain store (Correia, et al., 2008, p. 173). The results indicate that “reliability” is
perceived to be the most important factor in all three stores. In contrast, factors
that are perceived to be least important by university students were “pleasantness”
for Vatan Computer and Teknosa, “welcomeness” for MediaMarkt. One of the
most important items perceived was “Value for money”, which explains “reliability”
factor in all three store. This is due to the fact that purchasing electronic products
requires high involvement which means that consumers put a greater emphasis on
finding information about brands and products when making purchases. Moreover,
in Teknosa and MediaMarkt, “accurate information in the advertisements” of the
stores and in Vatan Computer “price-quality fit” best explains the “reliability” factor.
The second store personality factor, “pleasantness” is found to be best explained by
“layout” and “interior design” in all three stores. “Window display” is very much
related with the “welcomeness’ factor in Teknosa and Vatan, while “interior design”
is the most important item in explaining this factor in MediaMarkt.
These findings emphasize the need for accurate information in the purchasing
decision making process for high-involvement products, such as consumer
electronics (Ahmed, et al., 2004). Young consumers prefer a reliable store that gives
accurate information, value for money and has price-quality fit. In addition, the
store atmosphere and merchandise are perceived as the most important determinants
of store personality by university students. This may be due to the need for young
consumers e.g. university students, to be able to touch, hear and even smell products,
as well as see them, which contributes to a pleasant shopping experience and a
feeling of being welcome in the store.
Considering these findings, in order to increase the reliability of such stores it may
be appropriate to recommend that managers ensure that sales personnel are provided
with information relative to the products, as well as the price. This is considered
to promote sales. In addition, stores should avoid misleading advertising and sales
promotions as this can cause store avoidance. In order to prevent this problem and
assist in monitoring students’ buying habits, loyalty cards can be given to contracted
universities. Also, detailed explanations regarding the usage of products can be given
on their web sites in the form of videos. Another vital measure is to improve after-sales
service, such as maintenance, installation, and repair and even offer replacement with
another product where necessary. Considering of the importance of the university
market, it would be very useful for chain stores to promote their most popular
products at university festivals, organize a variety of events and give special incentives
to students, in order to capture these potential long term customers of the future.
34
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Predicting Banking Distress in European Countries
As argued by Brengman and Willems (2009), it may be appropriate to propose
that the managers of store chains should reduce the perception of overcrowding
by rearranging the layout to facilitate shopping and in store traffic flow, to create a
more pleasant store atmosphere. Managers may be encouraged to develop strategies
for relieving congestion in crowded areas such as entrance, halls, cash register
locations, customer services and shopping areas. This study shows the potential for
a store-personality scale developed for consumer electronics chain stores in helping
retailers understand the perception of young customers. This understanding can
enable stores to reposition themselves in a competitive market by implementing an
integrated communication strategy.
The main academic contribution of this study is that it can be seen as a preliminary
effort to identify the most distinctive personality factors and determinants of
consumer electronics chain stores perceived by university students in Turkey. As
consumer electronics stores and their personality characteristics have received
a limited amount of research attention in the marketing literature, this study is
expected to be useful for potential domestic and foreign consumer electronics
retailers investing in this sector.
Limitations and Future Research
This study has a number of limitations. In sampling design in particular, due to
budget limitations, the use of convenience sampling method in only one metropolitan
city, Izmir, and one university may not represent the general perceptions of Turkish
university students. However, despite its limitations, this study can be seen as a
preliminary effort in analyzing the perceptions of Turkish university students, a
highly profitable segment of the market (Accenture, 2012, p. 15).
In his study, Martineau (1958) mostly focused on store image attributes to define
store personality, while d’Astous and Levesque (2003) utilized Aaker’s (1997) brand
personality dimensions to develop a “general” store personality scale. Additionally,
Brengman and Willems’ (2008) developed a scale only for “fashion stores”, which
is therefore unsuited to consumer electronics. The scale developed in this study can
only be applied to consumer electronics chain stores, because it includes specific
determinants. Additionally, this scale can be used to measure the effect of store
personality determinants on store loyalty, store image and alternative methodologies,
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Ahlem-Selma MESSAI / Fathi JOUINI
including the usage of both qualitative and quantitative techniques. This process would
be able to provide a deeper understanding of consumer perceptions and attitudes.
Further studies can be made into different types of retailers, as well as customer
segments from other countries in order to explore the effects of cultural differences. In
addition, further research conducted on a wider sample size involving other universities
in Izmir and other metropolitan cities would allow a stronger representative view.
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38
Journal of Economic and Social Studies
Journal of Economic and Social Studies
The Role of Twin Deficit Problem in
Sustainable Growth: An Econometric
Analysis for Turkey
Halil UCAL
Adnan Menderes University
Faculty of Economics and Administrative Sciences
Nazilli, Aydin, Turkey
hucal@adu.edu.tr
Mehmet BOLUKBAS
Adnan Menderes University
Faculty of Economics and Administrative Sciences
Nazilli, Aydin, Turkey
mbolukbas@adu.edu.tr
AbstrAct
In economics literature the relationship between budget deficit and
current account deficit is known as twin deficit hypothesis. The Keynesian
Approach accepts a relationship between two deficits. In contrast to
this, Ricardian Equivalence Hypothesis defends there is no relationship
between these two deficits. Twin deficit has become the subject of several
studies to test which of these hypotheses are reliable but no consensus has
been achieved. Some studies found a relationship from budget deficit
to current account deficit but some of them had the opposite result.
Especially after 1980 it is known that many developed and developing
countries encountered with this twin deficit problem. Turkey also has
the problem of twin deficit. Therefore, it is important to find whether
there is causality between them and the direction of this causality. In
this study the relationship between budget deficit and current account
deficit is examined by using Johansen Cointegration Analysis. This
study is based on period 1996:Q1-2011:Q4. According to results of cointegration; variable coefficients are statistically significant and consistent
with what we expected in hypotheses. Current account deficit (CAD) has
a significant negative effect on budget deficit (BD). When there is a 1%
increase in CAD, BD decreases 0,12%. This finding is consistent with
economic theory because according to Keynesian Approach two deficits
have relationship with each other. However, in contrast to this approach,
the direction is from CAD to BD and also coefficient is negative.
KEYWOrDs
Budget Deficit, Current Account
Deficit, Sustainable Growth,
Econometric Modeling, Turkey
ArtIcLE HIstOrY
Submitted: 5 October 2012
Resubmitted: 18 October 201
Accepted: 09 January 2013
JEL codes: H62, F32, O4
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Halil UCAL / Mehmet BOLUKBAS
Introduction
The Twin Deficit is referred to a situation where an economy is running both
Current Account Deficit (CAD) and Budget Deficit (BD). According to Ricardian
Equivalence CAD and BD are not correlated. Budget deficit is a result of tax cut
which reduces public revenues and public saving (Alkswani, 2000). Decrease in
public savings will be compensated by an increase in private saving. Therefore
national saving will not be affected and the budget deficit will have no effect on the
current trade deficit (Alkswani, 2000). On the other hand, according to Keynesian
proposition the two deficits are linked and the direction is from BD to CAD. If
there is a budget deficit, government has to borrow more and as a result the interest
rates will rise. The rise of interest rates leads inflow of money from abroad and then
the local currency appreciates. The appreciation of currency results with increase in
import and decrease in export. As a result, trade deficit increase and current account
balance distorted.
The twin deficit has started to become a problem with the beginning of the 1980’s
in USA. Increase in military expenditures and decrease in income tax raised budget
deficit. The increase in budget deficit caused increase in debt of US to the rest of
the world and therefore caused distortion in balance of payments. After the global
crisis in 2008, it is seen that not only in USA also in other developed and developing
countries have the same macroeconomic problems. Especially in developed countries
such as European countries faced with serious problems in their economies. Growth
in developing economies such as China and India has become a danger for developed
countries. Foreign trade worsened and caused decrease in balance of payments in
western countries. Also high borrowing of governments deepened crisis in European
countries.
In recent years, CAD has become the most discussed issue for Turkey’s Economy.
According to Peker (2009) macroeconomic policies such as inflation targeting
generally cause appreciation of local currency and thus stimulate import. Turkey has
lack of savings like other developing countries. Because of this, growth in economy
depends on import oriented production and consumption. Although Turkish
Economy performs high level of growth, the trade balance is worsening. In the last
decade Turkish foreign trade has showed a large increase. However, increase in trade
volume has become more than increase in export. Also increase of gas and oil prices
in the world has increased Turkey’s energy expenditure. Therefore trade balance and
also current account balance worsened.
40
Journal of Economic and Social Studies
The Role of Twin Deficit Problem in Sustainable Growth: An Econometric Analysis for Turkey
After the 1999 earthquake and 2001 crisis, fiscal policies tightened and to increase
the revenues new tax policies have been implied. Especially new taxes such as Private
Consumption Tax (PCT) on import oriented goods have been implied to help
improving budget balance. Especially PCT revenues on petroleum products, almost
totally import oriented, helped to finance the budget deficit. Tax burden is 20% in
2011 which was 13% in 1998. Also share of value-added taxes (VAT) from import
in total value-added tax revenues raised to 17% which was 11% in 1999. The gap
between domestic VAT and VAT from import is closed as of 2011.
The growth in economy and tightened fiscal policies reduced the vulnerability to
crisis of Turkish economy. However, good performance of budget balance had no
positive effect on balance of payments. Export-import ratio was under 70% except
2001 and 2009. After 2001 Trade deficit increased continuously and in period 19972004 CAD/GDP ratio was 1,1% but in period 2005-2010 the ratio raised to 5,1%.
Graph 1 shows the relation of BD and CAD in the last 15 years.
Figure 1. Budget Deficit and Current Account Deficit in Turkey,
1996-2011(millions of $)
Source: Electronic Data Delivery System (EDDS), CBRT, 2012.
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As seen in the figure, especially after the 2001, Current Account Balance continuously
worsens. However, in this period Turkish economy experienced high growth rates.
With the global financial crises in 2009 CAD decreases sharply. After that it increases
sharply too. In this period BD moves in the opposite direction. According to graph,
BD did not rise over 30 billion dollars except 2009. Shrink in economy and decrease
in foreign trade decreased budget revenues in 2009. However in the last decade BD/
GDP ratio decreased continuously and become -1.4% as of 2011. This ratio is less
than 3% which is the reference value in Maastricht Criteria. As of 2011 most of the
EU member countries do not meet this criterion.
In this paper it is discussed whether CAD and BD has a correlation with each other
and if there is, in which direction is this relationship. According to hypothesis of this
paper there is a correlation between these two deficits and it is negatively correlated.
Because the increase in trade deficit increases the budget tax revenues and this help
to decrease budget deficit.
Literature Review
In economic literature, there are many empirical researches that focused on twin
deficit problem. In 1980’s United States faced with increase in federal trade deficit
(TD) and federal budget deficit together. After that the relationship between trade
deficit and budget deficit has become an important subject for researchers.
Darrat (1988) tried to find the linkage between TD and BD by using data period
1960:I to 1984:IV for United States. He found the evidence of causality from
budget deficit to trade deficit and stronger causality from trade to budget deficit by
using multivariate Granger Causality Test.
In the other study for the U.S., Enders and Lee (1990) searched the relationship
between BD and CAD in period 1947 to 1987 by using VAR analysis. They found
that government spending innovation generates a persistent current account deficit.
Also, Abelln (1990) examined the relationship between federal budget deficits
and merchandise trade deficit for U.S. He used multivariate time series within
autoregressive model for period 1979:02 through 1985:02. He found that indirectly
budget deficits affect trade deficits.
42
Journal of Economic and Social Studies
The Role of Twin Deficit Problem in Sustainable Growth: An Econometric Analysis for Turkey
Another work on US budget deficit and current account deficit linkage is study
of Bahmani-Oskooee (1989). He examined the linkage in period 1973-1985 and
concluded that the budget deficit contribute to current account deficit.
Not only U.S. but also other countries are faced with this twin deficit issue.
Therefore, there are studies about other countries too. Islam (1998) examined
the casual relationship between budget deficits and trade deficits of Brazil from
1973:1Q through 1991:Q4. The results suggested that there is a bilateral causality
between them.
Vamvoukas (1999) used annual data in period between 1948 and 1994 for Greece.
He used error correction model for the analysis and found that budget deficit has
short and long run positive and significant causal effects on trade deficit.
Alkswani (2000) studied on twin deficit problem in petroleum economy by using
Saudi Arabia annual data from 1970 to 1999. In his empirical analysis he used
ECM, Johansen cointegration and Granger bivariate causality tests and as a result
found that trade deficit causes budget deficit.
Puah et al. (2006) analyzed the twin deficits debate in Malaysia and Johansen-Juselius
co-integration test results show that budget deficit and current account deficit do not
contain common stohastic trend in long run. In addition unidirectional causality
running from current account to budgetary variable where the deterioration in
current account deficit could worsen the budgetary position in the case of Malaysia.
Merza et al. (2012) examined twin deficits hypothesis for Kuwait for the quarterly
period (1993:4-2010:4). To analyze the relationship between variables they applied
the VAR model and tested for existence and the direction of causality and the results
show that the direction of causality current account to budget balance that is an
increase in current account causes a decrease in the government budget surplus or
an increase in budget deficit.
Also in Turkey, there are many studies focusing on Turkey’s twin deficit problem.
Some of these studies are Ay, et al.(2004), Aksu and Başar (2005), Utkulu (2003),
Yücel and Ata (2003), Kutlar and Şimşek (2001), Zengin (2000), Sever and Demir
(2007), Akbostancı and Tunç (2002). Some of them used current account deficit
variable and some used trade deficit variable in their empirical studies. Most of them
used quarterly data for Turkey.
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Halil UCAL / Mehmet BOLUKBAS
Akbostancı and Tunç (2002) used quarterly variables between 1987:Q1 and
2001:Q3. They used Budget balance and trade balance as a percentage of GDP. By
using ECM and Cointegration analysis the empirical results show that there is a
long run relationship between two and in the short run worsening of budget balance
worsens trade balance.
Sever and Demir (2007) used quarterly data between the years 1987 and 2006 to
examine the relationship of budget deficit with current account deficit. By using
stationarity test, granger causality test and VAR analysis they found that budget
deficit influence current account deficit indirectly.
Kutlar and Şimşek (2001) used budget deficit and trade balance seasonally adjusted
data in log form in period 1984(4) through 2000(2). In the analysis stationarity test,
granger causality test, misspecification test, cointegration test and ECM used and
found that there is a positive relationship between two variables and trade deficit
increase budget deficit.
Zengin (2000) used seasonally adjusted quarterly data for period 1987:I through
1998:I. The main variables are trade deficit and consolidated budget deficit as
ratios to GNP. In the analysis VAR, Variance decompositions and impulse response
function used. The result of the empirical analysis is that budget deficit influence
trade balance.
Yücel and Ata (2003) used yearly data from 1975 to 2002. The variables are current
account deficit and budget deficit both in log form. The result of the empirical
analysis is that there is a cointegration between CA and BD and there is a long run
positive relationship. Granger causality test results say that causality is from BD to
CA in lag(1) and causality is from CA to BD in lag (3,4 and 7).
Utkulu (2003) used budget deficit and trade deficit variables as yearly data in period
between 1950 and 2000. By using cointegration analysis and ECM, he found that
there is a two sided long run causality between budget and trade deficits.
Ay et al.(2004) used monthly data between 1992 and 2003 for the empirical analysis
to find the linkage between BD and CAD. The variables used in the empirical
analysis were in percentage of GDP. They used Granger Causality test and regression
analysis. According to the empirical analysis there is reciprocal relationship between
two variables. According to two regression analysis the coefficients are positive.
44
Journal of Economic and Social Studies
The Role of Twin Deficit Problem in Sustainable Growth: An Econometric Analysis for Turkey
Model, Method and Data Set
In this section, a multivariate model has established to investigate twin deficit
problem in Turkey.
(1)
where BD and CAD are budget deficit and current account deficit respectively.
Budget deficit (BD) is generally defined as an amount by which some measure
of government expenditure and some measure of government revenue. BD is
dependent variable, whereas, current account is independent variable in this model.
And current account deficit (CAD) Current account deficit includes foreign trade in
goods, services and transfers. Current account occurs when a country’s total import
of goods, services and transfers is greater than total export of goods services and
transfers. Many studies in the literature use BD as an independent variable. But in
this study BD is used as dependent variable unlike other studies.
This paper adopted the method of co-integration first found by Engle-Granger
(1987), developed by Johansen (1988) and applied by Johansen and Juselius
(1990). This method depends on direct investigation of co-integration in the vector
autoregressive (VAR) representation and produces maximum likelihood estimators
of the unconstrained co-integration vector, but it allows one to explicitly test for
number of co-integration vectors. Johansen’s methodology takes its starting points
in the vector auto regression (VAR) of order p given by;
(2)
Where yt is a k vector of non-stationary variables I(1), xt is a d vector of deterministic
variable; and Ɛt indicates an innovation vector. This VAR can be written as;
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Halil UCAL / Mehmet BOLUKBAS
(3)
where
(4)
Where cointegration hypothesis defined as a reduced rank of the matrix π is stated in
the form of π = αβ. α and β represent the two matrix which have (kxr)-dimensional
and r rank. r is the number of co-integration (rank), β is a co-integration vector
showing long-term effects of variables in the equilibrium relations and α indicates
speed of adjustment in error correction model. Accordingly an matrix π is estimated
from an unrestricted VAR in Johansen method and tested that specified conditions
with reduced rank of π rejected or not. And determined by the help of Johansen
method’s test statistics (λtrace and λmak) how many rank of the matrix π has.In this
context, the data set of the variables used to determine the twin deficit problem in
Turkey belong to1996:Q1-2011:Q4 period. All data were taken from Electronic
Data Delivery System (EDDS) published by the Central Bank of the Republic of
Turkey (CBRT). And Econometric Views (Eviews 5.1) software program was used
for all tests and estimates.
Empirical Results and Discussion
Before constructing the Johansen method, it is important to make some process
and pre-tests. Firstly the independent variables were transformed into logarithmic
form and variables are understood to have seasonal effect deseasonalized by using
moving average method. Then univariate time series of variables are checked by
using Augmented Dickey Fuller (ADF) (1979) unit root test. ADF unit root test
results can be seen in Table 1. Variables were initially tested with first-level values and
then tested with the levels of receipt of the first differences. Accordingly determined
that all variables are integrated in the same order I(1). Therefore the necessary precondition for co-integration is provided.
46
Journal of Economic and Social Studies
The Role of Twin Deficit Problem in Sustainable Growth: An Econometric Analysis for Turkey
Table 1. ADF Unit Root Test
Variables
BD
CAD
ΔBD
ΔCAD
Critical Values
ADF Test
-2.318258 [3]
-3.353061 [1]
-9.694507 [2]
-4.617754 [6]
1%
-4.1118
-4.1104
-3.5440
-3.5526
Note: Trend and intercept term is used as test type for BD and CAD variables,
but only intercept term is used for the first differences of variables (Δ). The
values in square brackets indicates appropriate length of delay according to AIC.
It is necessary to determine an appropriate number of delay to apply Johansen
method. There are many measurements in the literature to determine the length
of delay; Akaike Info Criterion, Schwarz Info Criterion, Hannan-Quin Criterion
and Recent Forecast Error Criterion are the most commonly used (Johansen, 1995;
Enders, 1995). But these criterions are not enough on their own. Also there should
not be econometric problems in the length of delay selected with info criterions.
According to this, in this model the length of delay is determined as two. In this
context the model presented in Table 2 shows forecasting of diagnostic test is
successful.
Table 2. Diagnostic Test Results
White Heteroskedasticity
Chi-sq
14.897
Normality Test
Jarque-Bera
0.203535
0.633672
Df
18
Prop
0.669
Df
2
2
Prop
0.9032
0.7285
After checking univariate of all time series variables the relation between BD and
CAD variables can be tested by co-integration test. The purpose of the co-integration
test is to determine whether a group of non-stationary series is co-integrated or not.
According to Table 1, all variables are I(1), that means co-integration relation
between BD and CAD can be investigated by using Johansen Co-integration
Method.The results of λtrace and λmak statistics are presented in Table 3. λtrace
and λmak statistics helps to find existence of co-integration and number of vectors.
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According to the statistics; the null hypothesis (there is no co-integration relation
between variables), is rejected against to alternative hypothesis (there is at least one
co-integration relationship between the variables). In this case, there has to be at
least one co-integration relationship at 5 % critical value.
Table 3. Co-integration Test
Null Hypothesis (H0)
Alternative
(H1)
Hypothesisis
Trace and Mak Sta5% Critical Value
tistics
Eigenvalue
λTrace
λTrace statistic
r=0
r>0
0.309956
23.57399
15.49471
r≤1
r>1
0.009183
0.571998
3.841466
λMak
λMak statistic
r=0
r=1
0.309956
23.00199
14.26460
r=1
r=2
0.009183
0.571998
3.841466
The co-integration equation is presented in Table 4. According to results of cointegration; variable coefficients are statistically significant and consistent with what
we expected in hypotheses. CAD has a significant negative effect on BD. When
there is a 1% increase in CAD, BD decreases 0,12%. This finding is consistent
with economic theory because according to Keynesian Approach two deficits have
relationship with each other. However, in contrast to this approach, the direction is
from CAD to BD and also coefficient is negative.
Table 4. Co-integration Equation
BD
CAD
Normalized
Co-integration coefficient (β′)
1.000
0.122535
(0.08580)
Adaptation rates coefficient (α)
-0.000427
(7.68E-05)
-5.23E-05
(0.00019)
Co-integration Equation
BD= 5001.857 - 0.122535CAD
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The Role of Twin Deficit Problem in Sustainable Growth: An Econometric Analysis for Turkey
If there is a co-integration relationship among non-stationary variables, there has to
be an error correction representation (Engle and Granger, 1987) which illustrates
the dynamic convergence of the system to the long-run equilibrium. A precondition
for the existence of co-integration is that all the variables are integrated of the same
order. If this is fulfilled, then the residuals from the long-run estimates can be used
as the error correction term (ECT) to explain the short run dynamic.The error
correction term in short run indicates that when the deviations in the short run will
be adjusted in the next period (Cholifihani, 2008).
Error correction model (vector error correction: VEC) was established in order
to investigate the short-run dynamics of variables acting together in the long-run
and the results are presented in Table 5. As seen in Table 5; coefficient of error
correction term (ECt-1) is statistically significant and negative. If the error correction
term is negative, that means deviations in the short-run will be eliminated and
series converges to the long-run equilibrium value again among the series moving
together in the long-run. Namely error correction term is good working. According
to the result approximately 87 % of deviations from the long-run equilibrium value
eliminate in each period.
Table 5. Error Correction Model Estimation Results
DBAt= β0 + β1DCAt-1 + αECt-1+ ut
Variables
DBAt-1
DCAt-1
ECt-1
Invariable term
Coefficient
-0.049275
-0.247044
-0.874470
-138.1142
R 2 = 0.44
R2 = 0.46
t-statistic
-0.33937
-1.45152
-4.69637
-0.31490
F = 17.12
Conclusion
In this paper we tested whether there is a relationship between BD and CAD in Turkey
with the framework of growth. In the last decade, Turkey’s economy performed
well. After the 2001 crisis new economic policies strengthened the economy against
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crises. With the help of tight fiscal policies, government did not compromise on the
budget. However increase in consumption, appreciated currency, lack of savings and
rise in price of energy products caused an increase in trade deficit. As a result current
account deficit rose. According to empirical resultsthere is a significant negative
correlation between BD - CAD and the direction is from CAD to BD. When there
is a 1% increase in CAD, BD decreases 0,12%. Many studies on Turkey do not
cover last decade’s data. But in this study we reflect the effects of structural changes
in Turkish Economy after the period 2001 in terms of BD and CAD. In this regard,
empirical results of this study are differentiated from others. Because many studies
in literature show that incease in CAD results from incease in BD. Unlike studies
in literature, the results of this paper indicate that increase in CAD decrease in BD.
It is possible to say that Turkey’s fiscal, tax and growth policies in the last periods
provide this conclusion. That is to say, an increase in CAD helps to fix the budget
balance. 2/3 of tax revenues come from indirect taxes which means most of tax
revenues in Turkey come from consumption tax.
It seems that economic growth in Turkey bases on consumption and this case result
with CAD.This is not a sustainable situation. Because, a period of slowdown in
the economy causes not only a decrease in CAD but also a deterioration of budget
balance. This situation reduces the credibility of the government and the economy.
Therefore Turkish economy has to cope with CAD not with tax policies but with
increasing production facilities. If not, the economy may face with both deficits at
the same time.
References
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Journal of Macroeconomics, 12, 81-96.
Akbostancı, E. and G.İ. Tunç (2002) Turkish Twin Deficit: An Error Correction
Model of Trade Balance, Middle East Technical Universty, ERC working papers,
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Aksu, H and S. Başar (2005) İkiz Açıklar Hipotezi’nin Türkiye Açısından
Araştırılması, İktisat, İşletme ve Finansa Dergisi, (20), 109–114.
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The Role of Twin Deficit Problem in Sustainable Growth: An Econometric Analysis for Turkey
Alkswani, A.M. (2000) Twin Deficit Phenomenon in Petroleum Economy: Evidence
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Arasındaki İlişki: Türkiye Örneği (1992-2003), Selçuk Üniversitesi, Sosyal Bilimler
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Islam, M.F. (1998) Brazil’s Twin Deficits: An Empirical Examination, Atlantic
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Johansen, S. (1995) Likelihood Basic Inference in Cointegration Vector Autoregressive
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Etkileri, Ekonometrik Bir Yaklaşım: 1984–2000, Dokuz Eylül Üniversitesi, İİBF
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Journal of Economic and Social Studies
Cox Regression Models with Time-Varying
Covariates Applied to Survival Success of
Young Firms 1(*)
Aygül Anavatan,
Akdeniz University, Faculty of Economics and Administrative Sciences,
Department of Econometrics, 07058, Antalya, Turkey
aygulanavatan@akdeniz.edu.tr,
Murat Karaöz
Akdeniz University, Faculty of Economics and Administrative Sciences,
Department of Econometrics, 07058, Antalya, Turkey,
mkaraoz@akdeniz.edu.tr
AbstrAct
The most widely used model in multivariate analysis of survival
data is proportional hazards model proposed by Cox. While it is easy
to get and interpret the results of the model, the basic assumption of
proportional hazards model is that independent variables assumed
to remain constant throughout the observation period. Model can
give biased results in cases which this assumption is violated. One
of the methods used modelling the hazard ratio in the cases that the
proportional hazard assumption is not met is to add a time-dependent
variable showing the interaction between the predictor variable and
a parametric function of time. In this study, we investigate the factors
that affect the survival time of the firms and the time dependence of
these factors using Cox regression considering time-varying variables.
The firm data comes from Business Development Centers (İŞGEM)
which is a prominent business incubation center operating in Turkey.
KEYWOrDs
Survival Analysis, Cox Regression
Model, Proportional Hazard
Assumption, New Firms
ArtIcLE HIstOrY
Submitted:22 Jun 2012
Resubmitted:03 January 2013
Accepted:25 March 2013
Jel code: C41, C24, M13
1
This research paper has been an extension to the findings of the scientific research project
“The Factors Affecting Survival and Growth Performance of Newly Established Enterprises
in Business Incubators: A Survey on the KOSGEB Business Development Centers (İŞGEM)”,
109K139, which has been funded with grant from TÜBİTAK (The Scientific and Technological
Research Council of Turkey). We also acknowledge the administrative support to the project
from Turkish Small and Medium Entreprises Development Organisation (KOSGEB).
(*)
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Stavros RODOKANAKIS / Vasileios A. VLACHOS
Introduction
Survival analysis deals with the probability of occurrence of a given event at a set of
particular points in a time interval (Cox and Oakes, 1984; Sertkaya, Ata and Sözer,
2005). In the small business and entrepreneurship literature, survival analysis has
been used to track the start-ups over the years. The typical survival anaylsis may
include the reports of hazard rates, ratios and survival curves while relating a likely
set of independent variables to a specific event. A survival curve of a cohort of newly
established firms reports what percentage of the cohort continue to survive since its
inception over time, indicating whether some of the firms are failed over the years
(Karaöz and Albeni, 2011). In many survival studies, it has been examined whether
some variables or risk factors are effective on survival or not. Cox proportional hazards
(PH) model is the most preferred model in order to investigate the effect of variables
on survival time. The key assumption of Cox model is that hazard rate related to
different levels of the factors is constant throughout the follow-up period (Başar,
2006). Violation of the PH assumption requires additional measures for unbiased
results of Cox survival regression. In this paper, Cox regression has been applied to
investigate the survival of newly established firms under incubation. Violation of PH
assumption has been tested and further Cox regressions are performed considering
time-varying effects of independent variables to survival.
Survival Analysis
Survival analysis is a collection of statistical procedures for data analysis for which
the outcome variable of interest is time until an event occurs (Harrell, 2001). This
event may be failure, and for this reason, the analysis of such data is often referred to
as survival analysis (Bellera et al., 2010). The main objectives of the survival analysis
are i) to estimate and interpret survival characteristics: Kaplan-Meier plots, median
estimation and confidence intervals (CI), ii) to compare survival in different groups:
Log-rank test, iii) to assess the relationship of explanatory variables to survival time:
Cox regression model (Yay, Çoker and Uysal, 2007).
In a survival analysis, it is usually referred to the time variable as survival time,
because it gives the time that an individual has “survived” over some followup period
(Geiss et al., 2009). It is also typically referred to the event as a failure, because the
54
Journal of Economic and Social Studies
Evaluating the employment probability: Men and women in comparative perspective
in Attica and Central Macedonia
event of interest usually is death, disease incidence, or some other negative individual
experience (Kleinbaum and Klein, 2005).
When survival time (�) is defined as a random variable with cumulative
distribution function �(�) = ��(�� � ��) and probability density function
�(�) = � �(�)⁄� (�), survival function �(�) is explained by Equation (2.1) (Yay,
Çoker and Uysal, 2007);
�(�) = �(� � �) = 1 � �(�)
(2.1)
Survival function �(�) gives the probability that the random variable � exceeds
the specified time � (Kleinbaum and Klein, 2005). All survival functions have the
characteristics that i) they are nonincreasing; that is, they head downward as �
increases, ii) at time � = 0, �(�) = �(0) = 1; that is, at the start of the study,
since no one has gotten the event yet, the probability of surviving past time 0 is
one, iii) at time � = ∞, �(�) = �(∞) = 0; that is, theoretically, if the study
period increased without limit, eventually nobody would survive, so the survival
curve must eventually fall to zero (Kleinbaum and Klein, 2005).
The hazard function �(�), with its complement of survival function �(�), is given
by Equation (2.2), where �� denotes a small interval of time (Kleinbaum and
Klein, 2005);
�(�) = �im����
�(��������|���)
(2.2)
��
The hazard function �(�) gives the instantaneous potential per unit time for the
event to occur, given that the individual has survived up to time � (Tabatabai et
al., 2007). In contrast to the survival function, which focuses on not failing, the
hazard function focuses on failing, that is, on the event occurring. Thus, in some
sense, the hazard function can be considered as giving the opposite side of the
information given by the survival function (Kleinbaum and Klein, 2005).
The Cox Proportional Hazards Model
The Cox PH model is usually written in terms of the hazard model formula�
shown at Equation (2.3). This model gives an expression for the hazard at time t
2
Volume 3
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Stavros RODOKANAKIS / Vasileios A. VLACHOS
for an individual with a given specification of a set of explanatory variables
denoted by �. That is, � represents a collection of predictor variables that is being
modeled to predict an individual’s hazard (Kleinbaum and Klein, 2005);
�
�(�� �) = �� (�)� ∑��� �� ��
(2.3)
The Cox model formula says that the hazard at time � is the product of two
quantities. The first of these, �� (�), is called the baseline hazard function. The
second quantity is the exponential expression � to the linear sum of �� �� , where
the sum is over the � explanatory � variables (Kleinbaum and Klein, 2005).
In general, a hazard ratio (��) is defined as the hazard for one individual divided
by the hazard for a different individual. The two individuals being compared can
be distinguished by their values for the set of predictors, that is, the X’s. Hazard
ratio is shown by the following formula, where �∗ denotes the set of predictors for
one individual, and � denotes the set of predictors for the other individual
(Kleinbaum and Klein, 2005);
�
*
�
� *
� = h�t�X � = h0 (t) exp�∑ βi Xi � = exp�∑p β�i �X i* -Xi ��
HR
i=1
�
� (t�X)
� (t)
h
h0
exp�∑ βi X i �
(2.4)
�∗ = ���∗ � ��∗ � � � ��∗ ��and�� = ��� � �� � � � �� � denote the set of �’s for two
individuals.
Once the model is fitted and the values for �∗ and � are specified, the value of the
exponential expression for the estimated hazard ratio is a constant, which does not
depend on time. If we denote this constant by ��̂, then hazard ratio can be written
as shown below (Kleinbaum and Klein, 2005);
�
�� = exp�∑��� ��� (��∗ � �� )�
(2.5)
If hazard ratio is greater than 1, the group which has the distinction of 1 category
of the variable will higher significantly likely to be exposed to interest event by
comparison 0 category of that variable. If the hazard ratio is equal to 1, chance of
closing the two groups are equal; if it is between 0 and 1, the group receiving 0
category value has a lower closing probability by comparison 1 category.
3
56
Journal of Economic and Social Studies
Evaluating the employment probability: Men and women in comparative perspective
in Attica and Central Macedonia
The basic assumptions of the Cox regression model can be explained as follows
(Yay, Çoker and Uysal, 2007); i) the effects of independent variables on the hazard
function are loglinear. ii) The relationship between loglineer function of
independent variables and the hazard function is multiplicative. iii) In addition to
these two assumption, observations should independent of each other and hazard
ratio should remains unchanged with respect to time, ie., is constant. This
assumption related to hazard ratio is known as proportional hazard assumption.
A key reason for the popularity of the Cox model is that, even though the baseline
hazard is not specified, reasonably good estimates of regression coefficients, hazard
ratios of interest, and adjusted survival curves can be obtained for a wide variety of
data situations. Another way of saying this is that the Cox PH model is a “robust”
model, so that the results from using the Cox model will closely approximate the
results for the correct parametric model (Kleinbaum and Klein, 2005).
In addition to the general “robustness” of the Cox model, the specific form of the
model is attractive for several reasons (Kleinbaum and Klein, 2005). First, the
�
exponential part � ∑��� �� �� of hazard model ensures that the fitted model will
always give estimated hazards that are non-negative. Another tempting property of
the Cox model is that, even though the baseline hazard part of the model is
unspecified, it is still possible to estimate the �’s in the exponential part of the
model. Lastly, it is preferred over the logistic model when survival time
information is available and there is censoring. That is, the Cox model uses more
information (the survival times) than the logistic model, which considers a (0�1)
outcome and ignores survival times and censoring.
Evaluating the Proportional Hazards Assumption
For variables not satisfying the non-proportionality assumption, the power of the
corresponding tests is reduced, that is, it is less likely to conclude for a significant
effect when there is actually one. If the hazard ratio is increasing over time, the
estimated coefficient assuming PH is overestimating at first and underestimating
later on. For those variables of the model with a constant hazard ratio, the power of
tests is also reduced as a consequence of an inferior fit of the model (Bellera et al.,
2010).
4
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Stavros RODOKANAKIS / Vasileios A. VLACHOS
There are three general approaches to assess the PH assumption: 1) Graphical
Approaches; Kaplan-Meier and log-log plots, observed versus expected plots, 2)
Goodness of fit (GOF) test, 3) Statistical Methods; schoenfeld residuals, the logrank test and time-dependent covariates.
Extension of the Cox Proportional Hazards Model
An important feature of this formula, which concerns the PH assumption, is that
the baseline hazard is a function of �, but does not involve the �’s. The �’s in the
formula are called time-independent �’s (Kleinbaum and Klein, 2005). It is
possible, nevertheless, to consider �’s which do involve �. Such �’s are called
time-dependent variables. If time-dependent variables are considered, the Cox
model form may still be used, but such a model no longer satisfies the PH
assumption, and is called the extended Cox model (Kleinbaum and Klein, 2005).
In the case of being time-dependent explanatory variables, Cox regression model
expands to a model which contains time-independent variables and some
functions of the time the product with these variables. Independent variables are,
where �� � �� � � � ��� time-independent variables and �� (�)� �� (�)� � � ��� (�)
time-dependent variables (Sertkaya, Ata and Sözer, 2005);
�(�) = ��� � �� � � � ��� � �� (�)� �� (�)� � � ��� (�)�
as shown. Accordingly, Cox regression model is, � and � which denote vector of
coefficients of explanatory variables (Sertkaya, Ata and Sözer, 2005);
�
�
�
�
���� �(�)� = �� (�) exp �∑���
�� �� �(�)�
�� �� + ∑���
(2.6)
as written. Where �(�) is defined as a function of time. Selection of �(�) varies
according to the state of the variables used and according to the information level
of the researchers. This function usually is defined in the form of �, ���( �), ��(�)
or step functions (Sertkaya, Ata and Sözer, 2005).
The general hazard ratio formula for extended Cox model is shown below
(Kleinbaum and Klein, 2005);
58
5
Journal of Economic and Social Studies
Evaluating the employment probability: Men and women in comparative perspective
in Attica and Central Macedonia
�
� (�) = �����
��
�
∗ (�)�
� ����(�)�
(2.7)
�� �
��
= exp �∑���
�� ���∗ (�) � �� (�)��
�� ���∗ � �� � + ∑���
An Application Into New Firm Survival Under Incubation
Although the survival analysis extensively has been used in medical research on
individuals, recently it becomes widely popular in business success and survival
research. Thus, rather than on individuals, in this paper, we apply Cox regression
to investigate the survival of newly established firms under incubation. There are
studies applying survival violation of PH assumption has been tested and further
Cox regressions are performed considering time-varying effects of independent
variables to survival. Our 414 observations on firm characteristics acquired from
12 different incubators, İŞGEMs, located across Turkey, in Zonguldak, Tarsus,
Ereğli, Eskişehir, Adana, Mersin, Van, Avanos, Samsun, Elazığ, Yozgat and
Diyarbakır provinces. The data includes almost all firms that currently existing
İŞGEMs or the firms that resided in the past yet left İŞGEMs by graduation or
failure. The survey data consists of the total.
A business incubator can be identified as an organization which mentors the
development of newly founded firms by specialized services such as providing
office space, specialized staff, machinery, equipment, facilities and business
assistance (Aernoudt, 2004). Thus a business incubator is a framework
organization which contains a collection of newly established firms. İŞGEMs are
one of the significant business incubation concept operating in Turkey.
Variables Used in the Analysis
For our analysis, factors affecting the initial success of young enterprises can be
summarized as i) Human capital characteristics of new enterprise's owner such as
education level and sector experience, ii) Firm characteristics such as scale, age and
human capital, iii) Industry characteristics such as market growth rate and entry
barriers, iv) Incubation features, v) Other external factors such as macroeconomic
fluctuations, regional factors and public policies (Hackett and Dilts, 2004;
Aernoudt, 2004). All of the data and variables used in our analysis are taken from
Karaöz and Albeni (2011) and descriptive statistics and definitions are presented at
6
Volume 3
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Fall 2013
59
Stavros RODOKANAKIS / Vasileios A. VLACHOS
An Application Into New Firm Survival Under Incubation
Although the survival analysis extensively has been used in medical research on
individuals, recently it becomes widely popular in business success and survival
research. Thus, rather than on individuals, in this paper, we apply Cox regression
to investigate the survival of newly established firms under incubation. There are
studies applying survival violation of PH assumption has been tested and further
Cox regressions are performed considering time-varying effects of independent
variables to survival. Our 414 observations on firm characteristics acquired from 12
different incubators, İŞGEMs, located across Turkey, in Zonguldak, Tarsus, Ereğli,
Eskişehir, Adana, Mersin, Van, Avanos, Samsun, Elazığ, Yozgat and Diyarbakır
provinces. The data includes almost all firms that currently existing İŞGEMs or the
firms that resided in the past yet left İŞGEMs by graduation or failure. The survey
data consists of the total.
A business incubator can be identified as an organization which mentors the
development of newly founded firms by specialized services such as providing office
space, specialized staff, machinery, equipment, facilities and business assistance
(Aernoudt, 2004). Thus a business incubator is a framework organization which
contains a collection of newly established firms. İŞGEMs are one of the significant
business incubation concept operating in Turkey.
Variables Used in the Analysis
For our analysis, factors affecting the initial success of young enterprises can be
summarized as i) Human capital characteristics of new enterprise’s owner such as
education level and sector experience, ii) Firm characteristics such as scale, age and
human capital, iii) Industry characteristics such as market growth rate and entry
barriers, iv) Incubation features, v) Other external factors such as macroeconomic
fluctuations, regional factors and public policies (Hackett and Dilts, 2004;
Aernoudt, 2004). All of the data and variables used in our analysis are taken from
Karaöz and Albeni (2011) and descriptive statistics and definitions are presented at
Table 3.1. The entrepreneur’s age, gender, education, professional career history and
experience and family environment factors are the main factors in the literature in
terms of the survival of firms (Karaöz and Albeni, 2011).
60
Journal of Economic and Social Studies
Evaluating the employment probability: Men and women in comparative perspective
in Attica and Central Macedonia
Table 1. The variables used in analysis and descriptive statistics
VARIABLE
DEFINITION
Number of
Mean Minimum Maximum
Observation
EVENT OF INTEREST
If the firm is closed (failed) during or after
414
the incubation 1, otherwise 0
exit
-
0
1
41,52
2
158
414
-
0
1
414
-
0
1
367
3,64
3
4,25
414
-
0
1
414
5,83
0
40
414
-
0
1
414
1,24
1
4
DEPENDENT VARIABLE
The elapsed time from the firm’s entry
404
into incubation until it’s closed (month)
incubage
INDEPENDENT VARIABLES
If entrepreneur’s income only comes from
the incubated firm 1, otherwise 0
If entrepreneur is female 1, male 0 (If
gender
there are both male and female partner 0)
Entrepreneur’s age (If there is a partnerlnentage ship, it is taken as the oldest entrepreneur’s age-logarithmic scale)
If entrepreneur is a college graduate 1,
enteduuni otherwise 0 (if there is a partnership and
one of the partners is college graduate 1)
Entrepreneur’s prior experience before arentexp
riving İŞGEM (year)
If there is a role model for entrepreneurfamily
ship in entrepreneur’s family or surrounding 1, otherwise 0
The number of partners within the estabpartner
lished firm
CHARACTERISTICS OF THE ENTREPRENEUR
income
export
If the firm export 1, otherwise 0
414
-
0
1
lnempini
initial firm size (logarithmic scale)
392
1,31
0
5,70
414
-
0
1
414
-
0
1
414
-
0
1
414
-
0
1
If the firm is a brand owner 1, otherwise 0 414
-
0
1
If firm’s founding capital is completely
loan 1, otherwise 0
If entrepreneur is in cooperation with
networkstakeholders within and outside the incuing
bator 1, otherwise 0
If entrepreneur has made innovation 1,
innova
otherwise 0
If the firm has had an advertising 1, othadvert
erwise 0
FEATURES OF THE FIRM
onlyloan
brand
Volume 3
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EXTERNAL FEA- INDUSTRIAL INCUBATION SERVICES
TURES
PROPERTIES AND PROPERTIES
Stavros RODOKANAKIS / Vasileios A. VLACHOS
comserv
whenest
incubsize
sector
compete
prorank
cycle
If entrepreneur has used at least one of
the common services offered by incuba- 414
tion 1, otherwise 0
If the incubated firm entered the incubation center within first 3 years (36 months) 414
of incubation center 1, otherwise 0
The number of incubation’s workshop
If the firm is in the manufacturing industry
1, in the service sector 0
Intensity of competition in the sector (1-5
Likert scale)
(%) Share of the GDP per capita of the
province in the Country GDP where the
incubation center is located
If the firm has experienced an economic
crisis 1, otherwise 0
-
0
1
-
0
1
414
43,14
14
84
411
-
0
1
410
-
1
5
414
1,51
0,59
2,07
414
-
0
1
Source: Karaöz M. and Albeni M.,” The Factors Affecting Survival and Growth Performance of Newly
Established Enterprises in Business Incubators: A Survey on the KOSGEB Business Development Centers
(İŞGEM)”, TÜBİTAK Project No: 109K139, Isparta, March 2011.
(exit) variable is used as dependent variable. It takes the value of 1 if the firm is closed
within the period in incubation or after the firm has graduated from incubation, the
value of 0 in other cases. In addition to (exit), exit time (incubage) is the other
main variable in our survival analysis. As seen at Table 3.1, for our dataset, the firms’
average life expectancy is 41.52 months. The maximum survival time observed as
158 months. Some of the firms failed either during or some time after leaving the
incubator. Yet some of the firms still continue their activity either at incubator or
outside the incubator. Survival curve of firms has been presented at Figure 3.1.
According to the figure, surivors after 158 months diminish to about 20%.
62
Journal of Economic and Social Studies
Evaluating the employment probability: Men and women in comparative perspective
in Attica and Central Macedonia
Figure 1. The survival curve of firms which is present or graduate from incubation (month)
0.00
0.25
0.50
0.75
1.00
Kaplan-Meier survival estimate
0
50
100
150
analysis time
Results
All Cox Regression results with and without considering time effects are presented in
Table 3.2. (gender), (lnentage), (family), (export), (lnempini), (advert), (brand),
(comserv), (sector), (compete) and (cycle) variables are insignificant in Model 1,
which the time-dependent effects have not taken into account. According to Model
1 estimates, entrepreneur’s gender, age, whether s/he is affected family environment;
initial firm size, whether the firm exports and does advertising, whether the firm
is brand owner; whether the firm takes advantage of common services offered by
incubators; the sector in which the firm, intensity of competition in the sector and
whether the firm experienced any macroeconomic crisis are not significant on the
firms’ survival times. Our tests indicate that further estimations are necessary using
time-dependent variables. Thus we produce further new estimates and present most
relevant two model results at Table 3.2.
Model 2 includes the variables which in Model 1 and all of the interaction terms
created by each of these variables multiplying , which is a function of time, in
order to handle variable-time interaction. The Model 3 are obtained by removing
the interaction terms of (lnempini), (innova), (enteduuni), (whenest), (export),
(brand), (gender), (sector), (advert), (networking), (entexp), (income),
(onlyloan), (partner), (family), (lnentage), (comserv), (compete) and (cycle)
variables from the model. Model 3 is the best model that takes into account timedependent effects. The variables of (incubsize) and (prorank) are found to be the
time-dependent variables.
Volume 3
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Stavros RODOKANAKIS / Vasileios A. VLACHOS
Table 2. The estimates of the basic model and Cox model with time-dependent variables
Variable Coefficient
Variable
income
gender
lnentage
enteduuni
entexp
family
partner
export
lnempini
1.18
-0.056
0.265
0.659
-0.084
-0.307
-1.71
0.827
0.214
0.010*** 0.892
0.732
0.044**
0.042** 0.402
0.015**
0.308
0.278
5.16
1.14
6.45
0.289
-0.307
-4.63
1.07
6.47
0.274
0.253
0.745
0.422
0.924
0.342
0.205
0.844
0.576
0.847
1.75
-0.093
0.721
0.762
-0.101
-0.249
-2.39
0.951
0.196
0.000*** 0.826
0.364
0.024**
0.013** 0.518
0.001*** 0.303
0.298
income
gender
lnentage
enteduuni
entexp
family
partner
export
lnempini
-0.959
-0.352
-1.48
0.139
0.055
1.23
-1.08
-1.25
-0.023
0.427
0.699
0.474
0.861
0.505
0.212
0.457
0.678
0.954
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
Model 1
Model 2
Model 3
Model 2
(cont.)
Model 3
(cont.)
*, **, and *** indicate significance at the 1, 5, and 10% levels, respectively.
Log-likelihood and prob values of Model 1, 2 and 3, respectively, are -190.632 [0.000***],
-165.552 [0.000***] and -173.255 [0.000***].
64
Journal of Economic and Social Studies
Evaluating the employment probability: Men and women in comparative perspective
in Attica and Central Macedonia
onlyloan networking innova
advert
brand
comserv whenest incubsize sector compete prorank cycle
-1.03
-1.47
-1.67
0.636
0.865
0.264
-1.18
0.063*
0.004***
0.006*** 0.17
0.275
0.592
0.013** 0.002*** 0.738 0.416
0.013** 0.21
-6.97
4.45
-2.24
-2.74
-4.22
-6.63
-0.985
-0.261
19.4
0.215
0.333
0.74
0.522
0.685
0.217
0.813
0.015** 0.291 0.23
0.003*** 0.085*
-1.88
-1.54
-2.46
0.615
1.61
0.638
-2.25
-0.253
16.9
0.002*** 0.004***
0.001*** 0.198
0.074* 0.234
-0.02
-0.156 -0.157
-4.39
2.92
-0.425 -0.341
0.000*** 0.009*** 0.362 0.099*
-1.16
0.46
10.5
0.791
0.002*** 0.040**
onlyloan networking innova
advert
brand
comserv whenest incubsize sector compete prorank cycle
1.3
-1.7
-0.147
0.924
1.48
1.99
-0.415
0.059
0.378
0.177
0.937
0.418
0.582
0.161
0.718
0.030** 0.344 0.17
0.001*** 0.108
-
-
-
-
-
-
-
0.058
-
-
-5
-
-
-
-
-
-
-
0.017** -
-
0.001*** -
Volume 3
Number 2
Fall 2013
1.03
-0.903
-5.74
-2.5
-
65
Stavros RODOKANAKIS / Vasileios A. VLACHOS
Also considering the Model 2 and 3, we obtain various results regarding the variables.
The possibility of failure of the firms, whose owners only dependent on earnings
coming from its new-born firm, is about 6 times higher than other firms. In this
case it has been seen that the entrepreneurs having income from other sources are
more likely to be successful in start-up business. It is interesting to see the result that
the firms whose owners are university graduates have about two times higher risk of
failure than other firms. Yet there is a plausible explanation. Most of the incubator
residents are specialized in low-technology industries, which have higher likelihood
of failure. University graduates, who later realized that the new business has not
much prospect, close the firm immediately and return looking for a job related to his
carreer. University graduates have higher chance of finding a better paying job than
non-university graduates. By the same token, non-university graduates seem to strive
more to keep the new business alive. An increase in the number of partners in the
firm decreases the possibility of failure of firms to 20%. It is interesting to see that
failure risk of firms, whose founding capital is formed entirely by loans, is only about
%15 of the other firms, whose initial capital is partially or fully self-financed. If an
entrepreneur is in collaboration with stakeholders within and outside the incubation,
survival probability of the firm becomes approximately 5-times higher. Moreover, it
has been seen from the estimates that innovation activity of new firms increases chance
of survival approximately 12-times. Brand ownership also increases the chance of the
firm’s survival. Establishing a firm within an incubation center that is within its first
3-years (36 months) increases survival probability. Finally, firms those experiences a
macroeconomic crisis have nearly two times more likelihood of failure than others.
Conclusions
Cox proportional hazard model, besides others, rest on proportional hazards
assumption that independent variables do not vary with time. When PH assumption
is violated, Cox regression estimates become biased. Then, Cox survival estimates
can be corrected by including the time-varying effects to the analysis. Identification
and calculation of time-dependent effects give the opportunity to obtain some
otherwise unseen valuable special time pattern information.
In our analysis, initially, the Cox regression was performed by considering that all
explanatory variables are constant over time. Then, extended Cox regression models
66
Journal of Economic and Social Studies
Evaluating the employment probability: Men and women in comparative perspective
in Attica and Central Macedonia
were estimated by including the time-dependent explanatory variables in the model.
Our extended model results have shown that it become useful to estimate the Cox
Proportional Hazards regression by also including the time-varying explanatory
variables to the analysis. Both the time-independent and time-dependent variables
create significant effects on the probability of survival of the İŞGEM firms.
Overall, our estimates suggest that entrepreneurial experience acquired before
starting business at İŞGEM, higher number of partners in the firm, formation
of the firm’s capital completely by loan, being in collaboration with stakeholders
within and outside the incubator, innovative activities in the firm, starting the new
business within first 36 months of an incubator (in a young incubator), higher
number of office spaces, establishing the firm in an economically larger province,
and the density of competition in the sector have positive impact on the probability
of survival of the new-born firms within the incubator. Entrepreneurs whose only
source of income comes from the young firm, who has college diploma, who has
brand ownership at the firm, who experience a macroeconomic crisis are more likely
to fail.
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(2010). Variables with time-varying effects and the Cox model: Some statistical concepts illustrated
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Cox, D.R., & Oakes, D. (1984). Anaylsis of Survival Data. London: Chapman and Hall.
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Göller Bölgesi Üzerine Bir Araştırma. Ph.D. Thesis. Department of Economics, Süleyman Demirel
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Geiss, K., Meyer, M., Radespiel-Tröger, M., & Gefeller, O. (2009). SURVSOFT—Software for
nonparametric survival analysis. Computer Methods and Programs in Biomedicine, Elsevier Ireland
LTD., 96, 63–71.
Hackett, M., & Dilts, D.M. (2004). A Systematic Review of Business Incubation Research. Journal of
Technology Transfer, 29, 55-82.
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Karaöz, M., & Albeni, M., (2011), İş Kuluçkalarında Yeni Kurulan Girişimlerin Hayatta Kalma
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Üzerine bir Araştırma. The Scientific and Technological Research Council of Turkey (TÜBİTAK).
(Issue Brief No. 109K139).
Kleinbaum, D.G., & Klein, M. (2005). Survival Analysis: A Self-Learning Text (2nd Ed.). New York:
Springer.
Scheike, T. H. (2004). Time-Varying Effects in Survival Analysis. In: N. Balakrishnan & C.R. Rao.
(Ed.), Advances in Survival Analysis, 61-85. Amsterdam: Elsevier North-Holland.
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İncelenmesi, Cerrahpaşa Tıp Dergisi, 38, 139-45.
Journal of Economic and Social Studies
Unit Root Properties of Energy
Consumption and Production in Turkey
Özgür Polat
Department of Economics
Dicle University, Diyarbakır, Turkey
opolat@dicle.edu.tr
Enes E. Uslu
Department of Econometrics
Ataturk University, Erzurum, Turkey
ertad10@hotmail.com
Hüseyin Kalyoncu
Department of International Trade
Meliksah University, Kayseri, Turkey
hkalyoncu@meliksah.edu.tr
AbstrAct
This study analyzes unit root properties of total and sectorial energy
production and consumption series of Turkey. This study is the first
to analyze unit root properties of Turkish energy production and
consumption in detail. The unit root analysis of energy production
and consumption are tested by using unit root tests based on LM
considering without structural break and with one and two structural
breaks. According to unit root test without structural break, the unit
root hypothesis is rejected only for consumption of natural gas. The unit
root hypothesis is rejected for 15 out of the 33 series by the LS test with
one structural break. When unit root test with two structural breaks are
conducted, 25 out of the 33 series are found to be stationary around a
deterministic trend. The production of hydraulic and the consumption
of lignite, electricity, petroleum, coal and electricity, total energy and
petroleum consumption in Transportation sector are found to be nonstationary, which indicates that the impacts of innovations on these
variables will be permanent. The policy implication of the results suggests
that the impacts of shocks on energy consumption and production will be
temporary and not have a long memory for most of variables.
KEYWOrDs
Energy Consumption, Energy
Production, Unit Root Analysis,
Turkey
ArtIcLE HIstOrY
Submitted: 04 October 2012
Resubmitted: 24 December 2012
Accepted: 25 March 2013
JEL code: Q43, Q48
Volume 3
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Özgür Polat / Enes E. Uslu / Hüseyin Kalyoncu
Introduction
The impact of unit root properties of energy variables for the formulation and consequences of economic policies are crucial in several aspects, especially on structural
transitions from shocks in energy markets towards key macroeconomic variables
(Mishra, Sharma, & Smyth, 2009; Narayan & Smyth, 2007). Impact of shocks on
energy variable can be permanent or transitory according to its unit root properties. If the energy variable is stationary, impact of shocks will be transitory and long
short term. On the other hand, if the energy variable is not stationary, the impacts
of shocks will be permanent and have a long memory. Hendry and Juselius (2000)
indicate that economic variables can inherit unit root properties from related economic variables and can in turn transmit this property to other related variables.
They argued that relationship between economic variables can spread unit root
properties throughout the economy. In this context, knowledge of unit root properties of an energy variable is of importance, since this property can be inherited by
related macroeconomic variables. The impact of energy demand on economic activity can be serious. The literature has shown that energy price shocks, via their substantial impact on energy consumption, have significant impacts on output (Chang
& Wong, 2003; Du, Yanan, & Wei, 2010; Hamilton, 1996, 2007; Huang, Hwang,
& Peng, 2005; Jayaraman & Choong, 2009; Jiménez-Rodríguez, 2008; Lardic &
Mignon, 2008; B. R. Lee, Lee, & Ratti, 2001; Lorde, Jackman, & Thomas, 2009;
Zhang, 2011), inflation (Chang & Wong, 2003; Cologni & Manera, 2008; Cuñado & Pérez de Gracia, 2003; Ewing & Thompson, 2007), unemployment (Carruth,
Hooker, & Oswald, 1998; Chang & Wong, 2003; Rafiq, Salim, & Bloch, 2009),
employment (Papapetrou, 2001), stock market (Arouri, Lahiani, & Nguyen, 2011;
Basher, Haug, & Sadorsky, 2012; Evangelia, 2001; Filis, Degiannakis, & Floros,
2011; Park & Ratti, 2008; Sadorsky, 1999), investment (Rafiq et al., 2009), the
budget deficit (Rafiq et al., 2009), exchange rate (Ayadi, 2005; Basher et al., 2012;
S. S. Chen & Chen, 2007; Narayan, Narayan, & Prasad, 2008; Özturk, Feridun,
& Kalyoncu, 2008), interest rate (Lowinger, Wihlborg, & Willman, 1985; Park &
Ratti, 2008), exports (Chiou Wei & Zhu, 2002; Faria, Mollick, Albuquerque, &
León-Ledesma, 2009; Zhang, 2011), fluctuations in business cycle (Kim & Loungani, 1992) and money supply (Zhang, 2011).
Besides shocks on energy demand, Hamilton (2007) showed that disruptions on
energy supply can also have significant impact on economic activity by presenting a
model based on Cobb-Douglas production function as below:
70
Journal of Economic and Social Studies
Unit Root Properties of Energy Consumption and Production in Turkey
Analysis for Selected OECD Countries
Y = F ( L, K , E )
(1)
where output (Y) is production, (L) is labour, (K) is capital and (E) is energy use of
a firm. The profits (π) of a firm can be estimated as:
(2)
where P is the price of output per unit, W is the nominal wage paid for labour, Q
is the nominal cost of energy used in the production process and r is the nominal
rate of rented capital. The equilibrium energy price for rational firm will be at a level
where marginal product of energy is equal to unit price of energy:
FE ( L, K , E ) = Q / P
(3)
where FE(L,K,E) is the partial derivative of F(.) regarding E. The following equation will be obtained in case both sides of the equation (3) are multiplied by E and
divided by Y:
(4)
Eq (4) indicates that the elasticity of output regarding change in energy consumption used in the production process can be derived from the cost of the energy used
to produce the total output. Disruptions in energy production will affect energy
prices and a change in energy prices used in production process will also have a
significant impact on output of an economy as shown in Eq (4). Therefore, shocks
on non-stationary energy production series will be permanent and affect economic
activity perpetually , while shocks on stationary energy production series will be
transitory and affect economic activity temporarily, via transmission mechanism
(Narayan, Narayan, & Smyth, 2008).
The unit root properties of energy variables are of importance for forecasting these
variables. Accurate forecasts are crucial for energy planning and policy formulation.
Future values of a stationary energy variable can be forecasted based on its past
behavior (P. F. Chen & Lee, 2007), while past data about a nonstationary energy
variable are useless in forecasting (Mishra et al., 2009).
Stationarity of energy consumption can be due to a multitude of factors. Hsu, Lee,
and Lee (2008) suggested that abundance of energy resources, less energy consumption, new environmental regulations and laws introduced by governments and middle income level may lead to stationarity of energy consumption.
Volume 3
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Özgür Polat / Enes E. Uslu / Hüseyin Kalyoncu
The goal of this study is to analyze the unit root properties of energy consumption
and production in Turkey by employing a Lagrange Multiplier based unit root test
without structural break proposed by Schmidt and Phillips (1992) (SP) and a unit
root test considering one structural break proposed by J. Lee and Strazicich (2004)
(LS) and two structural breaks developed by J. Lee and Strazicich (2003) (LS). If
the time series of the variable to be tested for the unit root properties has structural
breaks, the unit root hypothesis cannot be rejected by conventional unit root tests
(Perron, 1989). Monte Carlo simulations point that statistical performance of LS is
better than other alternatives (Narayan, Narayan, & Popp, 2010). This study is the
first to investigate unit root properties of Turkish energy production and consumption in detail. The next section briefly summarizes the literature on studies analyzing
the unit root properties of energy consumption and production. Section 3 describes
data used in the analysis. Section 4 summarizes the unit root tests used in this study.
Section 5 presents results of the unit root test. Section 6 discusses main findings and
implications of the results for policy formulation and implementation.
Brief Overview of the Literature
Although there have been numerous studies analyzing the unit root properties of
energy consumption series, only a handful of studies have investigated energy production. Barros, Gil-Alana, and Payne (2011) examine the time series behavior of
oil production for 13 OPEC member countries for the period of January 1973 and
October 2008. They found that oil production series have mean reverting persistence with breaks identified in 10 out of the 13 countries. The results of the study
indicate that the impact of shocks on oil production in these countries will be persistent in the long run for all countries.
Narayan, Narayan, and Smyth (2008) analyze the unit root properties of crude
oil production for 60 countries by conducting panel data unit root tests with and
without structural breaks between 1971 and 2003. The results of tests without a
structural break are inconclusive, while the results of test with a structural break are
conclusive and indicate the stationary structure of production series of crude oil and
natural gas liquids.
Maslyuk and Smyth (2009) test for non-linarities and unit roots in crude oil production. They used monthly crude oil production for 17 OPEC and non-OPEC
72
Journal of Economic and Social Studies
Unit Root Properties of Energy Consumption and Production in Turkey
Analysis for Selected OECD Countries
countries between January 1973 and December 2007. The results of their study
show the presence of threshold effects on the crude oil production and unit root for
11 of the countries in both regimes and a partial unit root for the others.
In contrast to the dearth of studies investigating unit root properties of energy production series, there are numerous studies on unit root properties of energy consumption. Narayan and Smyth (2007) analyze the stationarity properties of per
capita energy consumption of 182 countries for the period of 1979 to 2000 by
using annual data. The results of univariate unit root test indicate that the series
of 56 countries are nonstationary at the 10% level or better. The panel data unit
root test indicate that there is overwhelming evidence about stationary of energy
consumption.
P. F. Chen and Lee (2007) investigate energy consumption per capita series of 7
regional panel sets for the period of 1971 to 2002 by employing panel unit root
testing procedure, and find stationary structure in all series. A substantial literature
review about the unit root properties of energy consumption can be found in P. F.
Chen and Lee (2007), Hsu et al. (2008) and Aslan and Kum (2011).
Data
The unit root properties of primary total production, total and sectorial consumption of various energy variables of Turkey covering different periods are explored in
this study as shown in Table 1. Energy production data are obtained from TURKSTAT (Turkish Statistical Institution) and energy consumption data are obtained
from Ministry of Energy and Natural Resources (MENR) of Turkey. The periods
of analysis are determined by data availability. All data used in this study are transformed to natural logarithmic form prior to unit root tests. Descriptive statistics of
the variables subject to analysis are presented in Table 1.
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Özgür Polat / Enes E. Uslu / Hüseyin Kalyoncu
Table 1. Descriptive Statistics
Series Code
PCL
PLT
PPM
PNG
PHC
PGL
PWD
PEY
CCL
CLT
CPM
CNG
CHC
CGL
CWD
CEY
IND
IND_PET
IND_ECT
IND_NGS
TPT
TPT_PET
TPT_ECT
RES
RES_PET
RES_ECT
ACL
ACL_PET
ACL_ECT
OSC
OSC_PET
OSC_ECT
NEY
Series Name
Period
Production
Coal
1950 - 2008
Lignite
1950 - 2008
Petroleum
1950 - 2008
Natural Gas
1976 - 2008
Hydraulic
1950 - 2008
Geothermal
1963 - 2008
Wood
1950 - 2008
Electricity
1923 - 2009
Consumption
Coal
1970 - 2009
Lignite
1970 - 2009
Petroleum
1970 - 2009
Natural Gas
1976 - 2009
Hydraulic
1970 - 2009
Geothermal
1970 - 2009
Wood
1970 - 2009
Electricity
1923 - 2009
Sectorial Consumption
Industrial
1970 - 2009
Industrial (Petroleum)
1970 - 2009
Industrial (Electricity)
1970 - 2009
Industrial (Natural gas)
1976 - 2009
Transportation
1970 - 2009
Transportation (Petroleum)
1970 - 2009
Transportation (Electricity)
1970 - 2009
Residential
1970 - 2009
Residential (Petroleum)
1970 - 2009
Residential (Electricity)
1970 - 2009
Agricultural
1970 - 2009
Agricultural (Petroleum)
1970 - 2009
Agricultural (Electricity)
1970 - 2009
Other sectors
1970 - 2009
Other sectors (Petroleum)
1970 - 2009
Other sectors (Electricity)
1970 - 2009
Non-energy
1970 - 2009
Unit
Mean
Std. Dev.
TEP
TEP
TEP
TEP
TEP
TEP
TEP
106 kWh
2097
5498
2325
293
1322
318
4405
34695
623
4569
1325
284
1329
309
764
53778
TEP
TEP
TEP
TEP
TEP
TEP
TEP
106 kWh
6411
8084
23066
9089
1971
354
4776
28122
3942
4061
7786
10980
1215
296
615
43089
TEP
TEP
TEP
TEP
TEP
TEP
TEP
TEP
TEP
TEP
TEP
TEP
TEP
TEP
TEP
TEP
TEP
15218
4699
2630
2508
8869
8637
36
16368
3346
2252
2083
1927
129
18450
4700
2381
1471
8461
1810
1773
2680
3826
3976
22
4926
2428
2079
1208
1058
149
6117
1670
2227
1152
Note: TEP indicates Ton Equivalent Petroleum
Time series plot for the production of energy variables of Turkey are shown in Figure
1. Decrease in petroleum, coal and wood production series are remarkable in com-
74
Journal of Economic and Social Studies
Unit Root Properties of Energy Consumption and Production in Turkey
Analysis for Selected OECD Countries
parison to other series in recent years. The decrease in wood production for energy
usage indicates substitution for this resource with other energy resources such as
natural gas. Trends for other series increase with some fluctuations over the periods analyzed and display steep increase thereafter. However, electricity and geothermal production series have no serious fluctuation indicating successful production
policies on these energy variables and these production process variables’ structural
strength towards disruptive shocks.
Figure 1. Energy Production (Source: TURKSTAT)
Natural Gas
0
0
200
Production - Electricity
50000
100000
150000
Production - Natural Gas
400
600
800
1000
200000
Electricity
1923
1933
1943
1953
1963
1973
Years
1983
1993
2003
1976
2013
1986
1996
2006
Years
Hydraulic
0
0
1000
Production - Hydraulic
1000
2000
3000
Production - Petroleum
2000
3000
4000
4000
5000
Petroleum
1950
1960
1970
1980
Years
1990
2000
2010
1950
1960
1970
1990
2000
2010
Lignite
0
1000
1500
Production - Lignite
5000
10000
Production - Coal
2000
2500
3000
15000
Coal
1980
Years
1950
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1970
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Years
1990
2000
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1950
1960
1970
1980
Years
1990
2000
2010
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Özgür Polat / Enes E. Uslu / Hüseyin Kalyoncu
Geothermal
0
3000
200
3500
Production - Wood
4000
4500
Production - Geothermal
400
600
800
5000
5500
1000
Wood
1950
1960
1970
1980
Years
1990
2000
2010
1963
1973
1983
Years
1993
2003
Time series plot for consumption of energy variables of Turkey are shown in Figure
2. Only consumption of geothermal and wood series for energy usage significantly
decrease among all energy variables. The decrease in wood consumption is consistent with its decrease in production, owing to alternative energy resources such as
natural gas production. The increase in consumption of electricity, natural gas and
petroleum are remarkable compared to other variables, and indicate the importance
of these energy resources for economy in Turkey. Although the price of natural gas
in Turkey is the highest in the world (Altunsoy, 2008), the remarkable increase in
its consumption indicates it is still cheaper than other energy resources in Turkey.
Figure 2. Energy Consumption (Source: MENR)
Natural Gas
0
0
Consumption - Electricity
50000
100000
Consumption - Natural Gas
10000
20000
30000
150000
40000
Electricity
1923
76
1933
1943
1953
1963
1973
Years
1983
1993
2003
2013
1975
1985
1995
Years
2005
Journal of Economic and Social Studies
Unit Root Properties of Energy Consumption and Production in Turkey
Analysis for Selected OECD Countries
Hydraulic
0
10000
Consumption - Hydraulic
1000
2000
3000
Consumption - Petroleum
15000 20000 25000 30000
4000
35000
Petroleum
1970
1980
1990
Years
2000
1970
2010
1980
2000
2010
2000
2010
2000
2010
Coal
0
0
Consumption - Coal
5000
10000
Consumption - Lignite
5000
10000
15000
15000
Lignite
1990
Years
1970
1980
1990
Years
2000
2010
1970
1980
Geothermal
1990
Years
0
3500
200
Consumption - Geothermal
400
600
800
Consumption - Wood
4000
4500
5000
1000
5500
Wood
1970
1980
1990
Years
2000
2010
1970
1980
1990
Years
Time series plot for sectorial consumption of energy variables of Turkey are shown
in Figure 3. The increase in energy consumption in industry indicates how the importance of industry has increased in the economy. At the end of 1990s, use of
petroleum decrease significantly in industry. When compared to other energy resources, the significant increase in natural gas consumption in industry indicates a
substitution between energy resources because of increasing oil prices and energy
Volume 3
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Özgür Polat / Enes E. Uslu / Hüseyin Kalyoncu
policies promoting natural gas consumption. Total energy consumption in every
sector increased with a positive trend indicating the rapid growth in the Turkish
economy in the last decade. Structural breaks are clear in 1994, 1999, 2001 and
2008 when economic crises occurred.
Figure 3. Sectorial Energy Consumption (Source: MENR)
Industrial Petroleum
0
2000
Consumption - Industrial
10000
20000
Consumption - Industrial (Petroleum)
4000
6000
8000
30000
10000
Total Industrial
1970
1980
1990
Years
2000
2010
1970
2000
2010
Industrial Natural Gas
0
Consumption - Industrial (Natural gas)
2000
4000
6000
Consumption - Industrial (Electricity)
2000
4000
6000
0
1970
1980
1990
Years
2000
1975
2010
1985
1995
Years
2005
0
0
Consumption - Transportation
5000
10000
15000
Consumption - Transportation (Petroleum)
5000
10000
15000
20000
Transportation Petroleum
20000
Total Transportation
1970
78
1990
Years
8000
Industrial Electricity
1980
1980
1990
Years
2000
2010
1970
1980
1990
Years
2000
2010
Journal of Economic and Social Studies
Unit Root Properties of Energy Consumption and Production in Turkey
Analysis for Selected OECD Countries
Total Residental
0
10000
Consumption - Residential
15000
20000
25000
Consumption - Transportation (Electricity)
20
40
60
80
30000
Transportation Electricity
1970
1980
1990
Years
2000
1970
2010
1990
Years
2000
2010
Residental Electricity
0
Consumption - Residential (Electricity)
2000
4000
6000
Consumption - Residential (Petroleum)
2000
4000
6000
8000
8000
10000
Residental Petroleum
1980
1970
1980
1990
Years
2000
1970
2010
1990
Years
2000
2010
Agriculture Petroleum
0
0
Consumption - Agricultural
1000
2000
3000
4000
Consumption - Agricultural (Petroleum)
1000
2000
3000
4000
5000
5000
Total Agriculture
1980
1970
1980
1990
Years
2000
2010
1970
1990
Years
2000
2010
2000
2010
Total Other Sectors
0
10000
Consumption - Other sectors
15000 20000 25000 30000
Consumption - Agricultural (Electricity)
100
200
300
400
500
35000
Agriculture Electricity
1980
1970
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1990
Years
2000
Fall 2013
2010
1970
1980
1990
Years
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Özgür Polat / Enes E. Uslu / Hüseyin Kalyoncu
Other Sectors Petroleum
0
2000
Consumption - Other sectors (Electricity)
2000
4000
6000
8000
Consumption - Other sectors (Petroleum)
4000
6000
8000
10000
Other Sectors Electricity
1970
1980
1990
Years
2000
2010
1970
1980
1990
Years
2000
2010
Econometric Methodology
The LS unit root test is based on Lagrangian Multiplier (LM) for trending data. J.
Lee and Strazicich (2003, 2004) extended Schmidt and Phillips (1992) methodology by considering structural breaks. The form of the test allows endogenous determination of two structural breaks under both the null and alternative hypotheses for
a change in both the level and trend.
DYt =δ ′DZt + ϕ St −1 + ε t ,
(5)
where Z t = [1, t , D1t , D2t , DT1t , DT2t ] is a vector of exogenous variables,
δ = [ µ , γ , d1 , d 2 , d3 , d 4 ] is a parameter vector of Zt and the subsequent dummies,
which allow two time changes in the level and trend, are as follows:
D jt
(6)
1 t ≥ TBj + 1
and DT jt
=
0 t < TBj + 1
t − TBj t ≥ TBj + 1
, j 1, 2.
=
t < TBj + 1
0
ψ x= Y1 − Z1δ and St =Yt −ψ x − Ztδ where δ are coefficients in the regression
of DYt on DZ t . The null and alternative hypotheses are:
H 0 : β − 1 = ϕ = 0 vs H1 : β − 1 = ϕ < 0
80
(7)
Journal of Economic and Social Studies
Unit Root Properties of Energy Consumption and Production in Turkey
Analysis for Selected OECD Countries
λ (=
λ1 TB1 / T , λ=
TB 2 / T ) ) LS
To determine the location of the breaks (=
2
procedure utilizes a grid search as follows:
LMτ = inf τλ ( λ )
(8)
Break points are where the corresponding test statistic is minimal.
Results
The results of the unit root tests with one and two structural breaks and without
structural break are presented in Table 2. Three distinct unit root tests are used in
this study to distinguish the impacts of structural break(s) on the energy series. We
considered breaks at level and trend of the series. The number of lags is determined
according to the general to specific method up to specific number of maximum lag1
running by t-statistics significance at the 10% significance level.
The unit root hypothesis is rejected only for consumption of natural gas by conventional unit root tests without structural break. The LS unit root test with one structural break rejected the unit root hypothesis for 15 out of the 33 series. When two
structural breaks are taken into account, 25 out of the 33 series are found stationary.
This series is stationary around deterministic trend with breaks. The production
of hydraulic and the consumption of lignite, electricity, petroleum, and coal, total
energy consumption in the transportation sector and consumption of petroleum in
the transportation sector are found to be non-stationary. According to the results,
structural breaks in energy variables of Turkey should be taken into consideration
when the unit root properties are examined. If the time series of the variable with
structural breaks are tested by conventional unit root tests, the unit root hypothesis may be not cannot rejected (Perron, 1989). Our results verify the theory that
the number of rejection of unit root null hypothesis declines when the number of
structural breaks is increased.
1
The number of maximum lag depends on number of observation of the series.
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Özgür Polat / Enes E. Uslu / Hüseyin Kalyoncu
Table 2. Results of unit root tests
Series
PHC
PGL
PLT
PWD
PPM
PCL
PNG
PEY
CHC
CGL
CLT
CWD
CPM
CCL
CNG
CEY
IND
IND_PET
IND_ECT
IND_NGS
TPT
TPT_PET
TPT_ECT
OSC
OSC_PET
OSC_ECT
RES
RES_PET
RES_ECT
ACL
ACL_PET
ACL_ECT
NEY
SP
k
0
0
2
8
8
0
8
9
0
3
9
2
6
9
8
11
0
5
6
0
0
0
5
0
0
0
0
0
0
0
7
8
1
t statistics
-1.52
-2.12
-1.45
-0.73
1.83
-1.99
-2.16
-0.45
0.14
-1.94
-1.93
-0.53
-0.93
-1.80
-3.13c
-0.08
-2.22
-1.72
1.45
-1.53
-1.68
-2.56
-2.07
-1.40
-1.15
-0.98
-1.46
-1.07
-1.11
-1.64
-2.73
-1.94
-3.74a
LS - one break
k
t statistics
6
-3.87
3
-3.58
2
-3.44
9
-4.20c
7
-3.37
9
-4.73b
8
-6.65a
9
-3.68
0
-2.33
2
-5.74a
9
-3.87
5
-4.26c
10 -4.30c
10 -2.94
5
-5.76a
11 -4.68b
5
-5.03b
9
-4.14
0
-3.98
4
-3.19
0
-4.11
3
-4.25c
9
-3.95
0
-2.53
1
-4.78b
9
-3.94
0
-2.42
9
-4.97b
9
-3.95
4
-3.61
7
-4.48c
8
-4.95b
2
-5.01b
TB
1999
2006
1991
1990
1988
1994
1994
1987
1966
1989
1998
1989
1991
1989
1987
1981
2000
2003
1985
1993
1997
1997
2002
2001
2000
1985
2001
1993
1985
1995
1994
1992
2003
LS - two breaks
k
t statistics
6
-5.04
9
-8.71a
3
-6.35a
6
-5.79b
7
-5.40c
8
-6.46a
2
-16.39a
9
-4.51
7
-5.39b
2
-6.88a
9
-4.62
10 -6.18b
6
-4.65
5
-5.06
2
-9.17a
11 -4.87
5
-5.69b
9
-6.41a
5
-5.97b
6
-8.61a
8
-4.68
8
-5.15
6
-6.99a
6
-8.54a
2
-7.47a
9
-6.40a
6
-8.44a
9
-11.48a
9
-7.02a
7
-6.82a
7
-5.39c
9
-5.64b
3
-6.60a
TB1
1983
1987
1987
1984
1988
1988
1988
1944
1968
1975
1979
1972
1965
1975
1988
1981
1991
1989
1984
1994
1987
1987
1986
1982
1996
1982
1982
1987
1982
1993
1993
1994
1997
TB2
1993
2006
2001
1996
1994
1994
2003
1973
1993
1987
1999
1990
2002
1993
1990
1989
2000
1994
2000
1999
1991
1991
2002
1999
2000
1995
1999
1993
1995
2006
1999
2006
2003
Notes: k indicates the number of lags. a, b and c denote significance at the 1% 5% and 10% level, respectively.
TB denotes time breaks.
82
Journal of Economic and Social Studies
Unit Root Properties of Energy Consumption and Production in Turkey
Analysis for Selected OECD Countries
Conclusion
Specification of unit root properties of energy consumption and production is crucial for energy policy formulations and implementations. The impact of shocks on
energy variables with a stationary process will be temporary and long short term,
while impact of shocks on energy variables with a nonstationary process will be
permanent and have a long memory.
In this study, the unit root properties of total and sectorial energy production and
consumption series of Turkey are investigated. This study is the first to investigate
unit root properties of Turkish energy production and consumption in detail. The
unit root structure for energy variables are tested by using the unit root tests based
on LM without structural break and with one and two structural breaks. The results of unit root test without structural break show that the unit root hypothesis is
rejected only for consumption of natural gas. In the case of one structural break,
the unit root hypothesis is rejected for 15 out of the 33 series by LS test. When
two structural breaks are taken into account, 25 out of the 33 series are found to
be stationary around a deterministic trend with breaks. The production of hydraulic, the consumption of lignite, electricity, petroleum, coal, electricity, total energy
consumption and petroleum consumption in the transportation sector are found to
be non-stationary, which indicates that the impact of innovations on these variables
will be permanent.
The policy implication of these results suggests that the impacts of shocks on energy
consumption and production will be temporary and not have a long memory for
most of the variables. Therefore, the economic impact of energy stabilization and
conservation policies will be temporary in Turkey. The results of this study, which
found that most of the variables are stationary, are consistent the consensus about
stationarity of energy variables found in numerous other studies (Narayan et al.,
2010). In addition, the historical data on these stationary variables can be taken into
account to forecast the future values of these variables.
Volume 3
Number 2
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83
Özgür Polat / Enes E. Uslu / Hüseyin Kalyoncu
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86
Journal of Economic and Social Studies
Journal of Economic and Social Studies
Measuring and Reporting Cost of
Quality in a Turkish Manufacturing
Company: A Case Study in Electric
Industry
Hilmi KIRLIOĞLU,
Sakarya University,
Faculty of Business Administration,
Department of Accounting and Finance, / 54187 Esentepe/Sakarya, Turkey.
hilmik@sakarya.edu.tr
Zülküf ÇEVİK,
Sakarya University,
Faculty of Business Administration,
Department of Accounting and Finance, / 54187 Esentepe/Sakarya, Turkey.
zcevik@sakarya.edu.tr
AbstrAct
Contemporarily, the competition in the markets has thoroughly heated
up. Many companies try to decrease their costs in order to survive in
this cruel market. In this respects, the quality costs gain importance in
all over the world and in Turkey, too.In this study, the implementation
of quality costs measuring and reporting system has been performed in
a company. Accordingly, the data has been collected from a Turkish
manufacturing company. The data gathered from this company’s
accounting department has been used for studying on quality costs
measuring and reporting system.Consequently, it is found out that the
company cannot measure its quality costs adequately, for this reason
quality reporting system in the company is not efficient. The company
needs to give more significance to the quality costs measuring and
reporting.
JEL codes: L15, M41, M49,
Volume 3
Number 2
Fall 2013
KEYWOrDs
Total Quality Management,
Quality Costs, Managerial
Accounting.
ArtIcLE HIstOrY
Submitted:23 September 2012
Resubmitted:16 November 2012
Accepted:25 December 2012
87
Hilmi KIRLIOĞLU / Zülküf ÇEVİK
Introduction
In recent years, competitive environment of companies has been getting harder and
harder. In order to have sustainable competitive advantage, companies should produce their products to entirely supply customers’ needs, wants and demands. Subsequently, companies need to have more quality products to remain competitive with
other companies.
To gain a competitive advantage over rival companies, a company should produce
high quality products. While producing high quality product, the company should
also take into account its quality costs. Shortly, companies need to produce high
quality products in a low quality costs. As a result, quality and quality costs gain vital
importance for a company to survive in a highly competitive market.
The significance of this study is to comprehend the necessity of the quality system
for a company which operates in the global and local markets. Another gist of the
study is to provide recognition of quality costs system benefit to the profit and brand
name. The quality costs system causes decreasing in the production cost and increasing in the brand name which will be perceived as producing qualified products.
The aims of this study are to show the importance of the quality costs for a company
which competes in a highly competitive market, and also demonstrate the necessity
of quality costs system so as to have high qualified product with a low quality costs.
As it is well known, the quality cost is not the responsibility of a department or an
individual, on the contrary, every person in an organization should be responsible
for quality. Highly qualified products can be reached by the collaboration of all
departments in an organization. In this sense, the main aim of this study is to demonstrate the function of accounting department in quality costing activities. Those
activities can be summarized as; the measurement of quality costs, the classification
of this costs and the reporting techniques of the quality costs. In this respect, the
purpose of the current study is to show the importance of quality costs’ reporting.
The paper contributes to the literature by documenting the concepts of quality,
quality costs, and the classification of quality costs and quality costs measurement.
On the basis of literature review, a case study will be handled and lastly, the analysis
and results will be given in last section.
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Journal of Economic and Social Studies
Measuring and Reporting Cost of Quality in a Turkish Manufacturing Company:
A Case Study in Electric Industry
Literature review
To be able to analyze the measuring and reporting costs of quality, some concepts
should be clear first. The three basic concepts of this paper will be introduced. These
concepts are quality and quality costs, classification of quality costs and lastly, quality costs measurement.
The concept of quality has been defined for many quality gurus. So, there are many
definitions for quality. Quality is the features of products which meet customer
needs and thereby provide customer satisfaction. Quality means freedom from deficiencies (Juran & Godfrey, 1998). According to D. C. Montgomery, Quality means
fitness for use, and also he defined quality as inversely proportional to variability
(Montgomery, 2005).
In addition to those definitions, some of other quality gurus defined quality as;
- Crosby (1979, p. 7)defines quality as “conformance to requirements”
- Feigenbaum’s(1983, p. 7) definition of quality is “the total composite product and service characteristics of marketing, engineering, manufacture and
maintenance through which the product and service in use will meet the expectations of the customer.”
- As Ishikawa (1985, p. 45) suggests, quality means “quality of work, quality of
service, quality of information, quality of process, quality of division, quality
of people, including workers, engineers, managers and executives, quality of
system, quality of company, quality of objectives, etc.”
- Pirsig’s definition (1984,p. 206) of quality is that “Quality is a characteristic
of thought and statement that is recognized by a nonthinking process. because definitions are a product of rigid, formal thinking, quality cannot be
defined.”
To sum up those definitions, quality is the whole good and service characteristic
features of fulfillment power for stated and demanded needs. In other words, many
quality gurus defined quality in terms of the degree of the product’s conformance
to its requirements to maintain customer satisfaction and in terms of a product that
contains no defects (Ömürgönülşen, 2009).
Quality Cost is a cost for detection and anchoring of low quality about goods and
services. Simply, costs of quality are the costs which occur because poor quality
may or does exist (Hansen & Mowen, 2006). Quality costs are a measurement of
the costs particularly related with the accomplishment or non-accomplishment of
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Hilmi KIRLIOĞLU / Zülküf ÇEVİK
product or service quality. To make those explanations more specific, Jack Campanella(1999, p. 4) defined cost of quality as;
“More specifically, quality costs are the sum of the cost incurred by (a)
investing in the prevention of non-conformances to requirements, (b)
appraising a product or service for conformance to requirements, and
(c) failing to meet requirements.”
In the definitions of Campanella, it is understood that the quality costs consist of
three main parts; Prevention Costs, Appraisal Costs, Failure Costs.
The required quality activities would incur costs and quality costs arecategorized
into three main parts – Prevention, Appraisal and Failure Costs – Those can be also
stated as PAF (Prevention-Appraisal-Failure) model (Jaju & Lakhe, 2009). Failure
costs should be taken into consideration as two subtopics which are called internal
and external failure costs.
(Figure 1. Classification of Quality Costs(Rodchua, 2006
Cost of Quality
Prevention costs
AppraisalCosts
Failure Costs
Internal Failure
External Failure
In Figure 1, three main classifications of quality activities costs have been shown.
Those costs do not occur at the same period of the production process. So, it should
be also classified as time periods in which they occurred.
Prevention Costs are the preliminary activities’ costs to reach quality goals for producing goods and services and avoid deviations of those goals (Kırlıoğlu, 1998).
Prevention costs are occurred to prevent low quality in the goods or services being produced (Hansen & Mowen, 2006). Prevention costs are related with quality
planning, designing, implementing and managing the quality system, auditing the
system, supplier surveys, and process improvements (Rodchua, 2006).
Appraisal Costs are activity costs of measuring the suitability of the product to customers’ needs. It is incurred to identify non-conformance to requirements (Oliver &
Qu, 1999). Those costs are related with the supplier’s and customer’s assessment of
90
Journal of Economic and Social Studies
Measuring and Reporting Cost of Quality in a Turkish Manufacturing Company:
A Case Study in Electric Industry
purchased materials, processes, intermediates, products and services to assure conformance with the specified requirements (Tsai, 1998).
Internal Failure Costs are the costs of low quality product which are realized before
sales of the product. In other words, these costs arise when the outcomes of production fail to meet stated quality specifications and are noticed before transfer of those
low quality products to the customers (Vahevanidis et al., 2009).
External Failure Costs are failure costs which come up after delivering the products to
the customers(Kaner, 1996).Those costs take place for the reason that the products
and services do not conform to specification or requirements and those products do
not satisfy customer needs after being delivered to customers (Hansen & Mowen,
2006). It is also incurred by amending failures after transferring the finished goods
and products to the customers (Low & Yeo, 1998).
Additionally, Quality cost classification can be grouped in time periods. For example, prevention costs encompass the stage of both pre-production and during
production and appraisal costs cover the three stages of production –preproduction,
production and after production stage. Failure costs are divided into two subtopics
which internal failure costs and external failure costs. Internal failure costs encompass the period of both production and after production stages. External failure
costs just related with the stage of after sale (Barfield et al., 2002).
Figure 2. Time-Phased Model for Quality Costs(Barfield et al., 2002)
Before Production
During Production
Prevention
Costs
After Production
After Sale
Appraisal Costs
Internal Failure
Costs
External Failure
Costs
Feedback Loop
The Quality Costs Measuring helps to find out where unnecessary quality costs are
occurred, thus management can take actions to eliminate that kind of costs and this
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Hilmi KIRLIOĞLU / Zülküf ÇEVİK
elimination will reduce the occurrence of poor quality costs. In other saying, the
quality costs measurement serves management to determine which area of operation
requires preventive measures (Low & Yeo, 1998).
To measure quality costs, one should collect related data from quality activities of a
company. After the collection of data which are related with quality costs components, they should be analyzed before using in an action. This analysis consists of the
relationship between a costs component and other costs components and searches
the effect on total costs.
Quality costs are analyzed in weekly, monthly, quarterly, yearly, etc. periods. Company structure should be taken into account in determining the period of analysis
(Şimşek, 2001). In order to analyze quality costs, companies need to use some techniques. The analysis techniques for quality costs can be listed as;
I. Pareto Analysis,
II. Ratio Analysis,
III. Correlation Analysis,
IV. Trend Analysis,
V. Regression Analysis.
Pareto Analysis is one of the most used techniques in quality costs analysis. This technique was developed by Wilfredo Pareto who is a nineteenth century Italian social
scientist and economist. He gave his surname to the technique. Pareto principle is
universally known as the 80/20 rule. Pareto found out this principle by pinning
down that 80 percent of Italy’s national income is shared by 20 percent of the Italy’s
populations. With the help of Pareto diagrams, problems can be put in order of importance, problems of costs analysis can be easily performed and relative occurrence
numbers could be searched simply (Sarıkaya, 2003). In other words, Pareto analysis
can be utilized to recognize cost drivers which are accountable for the most of cost
occurred by ranking the cost drivers in order of value (Tsai, 1998).
The Technique of Ratio Analysis is aimed to identify the aspects of the quality costs’
performance to aid decision making.Ratio analysis consist of rationing quality costs
to revenue, production costs, direct labor costs and rationing total quality costs
within themselves (Özcan, 2012).
Correlation analysis represents the direction and the power of the relationship between variables. In correlation analysis, the results do not give cause-effect relation-
92
Journal of Economic and Social Studies
Measuring and Reporting Cost of Quality in a Turkish Manufacturing Company:
A Case Study in Electric Industry
ship, because there is no dependent and independent variable in this technique
(Altunışık et al., 2005).
Trend Analysisis a useful picture of how the quality improvement program has been
doing since its inception. It provides management with information concerning
the within-period progress measured relative to specific goals (Hansen & Mowen,
2006).
Regression analysis examines the relationship between one dependent variable and
one or more than one independent variables. In other words, this technique tries to
explain the changes in dependent variable with the help of independent variables
(Altunışık et al., 2005).
Data and Methodology
The data of this study is gathered from X Electric Inc. Company which was founded
in 1990 in Adapazarı, Turkey. The company is a Low Voltage Circuit Breaker manufacturer company.
The data has been collected from this company’s accounting department. The company’s accounting director gave the raw data of the company quality costs. We have
analyzed these costs for reporting quality costs.
According to the data, we drew table 1, 2, and 3. With the help of these tables, we
made ratio and trend analysis of company’s quality costs. The data consists three
years which are 2008, 2009, 2010. In the study, trend and ratio analysis have been
performed for measuring and reporting the firm quality costs.
Analysis of Quality Costs in the Firm
The table below displays the company’s sales and production amount in Turkish Liras
(here after TL). The sales and production amount have been given for three years. Additionally, the table contains of total quality costs in the firm for three years.
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Hilmi KIRLIOĞLU / Zülküf ÇEVİK
Table 1. Some Ratios and Ratio Components in the Firm
Years
Data
2008
2009
2010
Total Sales (TL)
629.053.415
695.866.750
786.859.486
Total Production Costs (TL)
515.326.274
563.708.245
643.590.468
Total Quality Costs (TL)
10.028.516
11.712.822
12.642.655
1,59%
1,95%
1,68%
2,08%
1,61%
1.96%
The Ratio of Quality Costs to Sales
The Ratio of QC to Production Costs
According to the firm information, the ratios of total quality costs to total sales have
been calculated for given three years. And the ratios of total quality costs to total
production costs have also been calculated. In the aspect of the information in the
previous section, these calculations have been performed as follows.
In 2008, the company’s total sales are 629.053.415 TL. In the same year, total quality costs are 10.028.516 TL. So the ratio of total quality costs to sales can be found
out as follows;
10.028.516
629.053.415
= 1,59%
It can be concluded that the amount of total quality costs is only 1.59% of the total
sales in 2008.
10.028.516
515.326.274
= 1,95%
The calculation above demonstrates that the ratio of total quality costs to total production costs is about 1.95%. For the years of 2009 and 2010, total quality costs
to sales and total quality costs to total production costs have been calculated by the
same way and written down in the figure above.
This ratio is not too much for an early stage of quality costs analysis applier’s company.
In other words, the firm analyses its quality costs not long ago, so the rates is in the acceptable limits. Besides this ratios can be reduced for more efficient quality costs system.
When analyzing quality costs data for year 2010 as quality costs components, it
will be useful for monitoring quality costs. Regarding this classification, quality
costs component will be given as costs items. With the help of this costs items, the
percentage amount of each costs item will be also calculated and given for the year.
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Measuring and Reporting Cost of Quality in a Turkish Manufacturing Company:
A Case Study in Electric Industry
Table 2. Total Quality Costs as Each Cost Items for the Components in the year of 2010
Components of Quality Costs
Prevention Costs
Quality Planning
Quality Circle
The Training of Quality
Inspection and Tests Instructions
Supplier Quality Planning
Preventive Maintenances
Other Prevention Costs
Appraisal Costs
Inspection and tests of purchased materials
Costs (TL)
1.782.614,36
518.348,86
75.855,93
202.282,48
113.783,90
214.925,14
480.420,89
176.997,17
5.031.776,69
1.036.697,71
Ratio (%)
14,1
4,1
0,6
1,6
0,9
1,7
3,8
1,4
39,8
8.2
Control, maintenance and calibration of measurement instruments
101.141,24
0,8
Process inspection and tests
Consumable materials for laboratory and tests
Products inspection and tests
Other appraisal costs
Internal Failure Costs
Salvage
Reproduction and Repairs
Re-inspection
Corrective actions
External Failure Costs
Products Returns
Transportation Damage
Warranty Costs
1.150.481,61
581.562,13
1.984.896,84
176.997,17
4.450.214,56
2.225.107,28
1.656.187,81
480.420,89
88.498,59
1.378.049,40
998.769,75
50.570,62
328.709,03
9,1
4,6
15,7
1,4
35,2
17,6
13,1
3,8
0,7
10,9
7,9
0,4
2,6
Total Quality Costs
12.642.655
100,0
In the figure 2010, the non-conformance costs are under the half of the total quality
costs. This demonstrates that the firm is going in the right way. The company gives
more importance for conformance costs day by day, so the non-conformance costs
decreases naturally. These changes will benefit the company in more ways than one.
The figures below should be reported to the managers for monitoring quality costs
activates by management. The importance of quality costs increases day by day.
The next table shows the total quality costs as categorization groups. As it is mentioned before, the quality costs have two components which are conformance and
non-conformance costs. And these components costs are given in the chart. Moreover, conformance costs are divided into two cost elements that are prevention costs
and appraisal costs. The amounts of these costs are also given yearly in the table. The
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conformance costs are increasing for the given years. It rose up two times from the
amount of 2008 to 2010 amount. It is good for a company to increase its prevention activities in order not to confront defects after selling the products out. Besides,
the amount of prevention costs in conformance costs is too small. The firm should
concentrate more on prevention costs.
Table 3. The Amount of Quality Costs in Classification through the Years
Quality Costs
Conformance Costs
Prevention Costs
Appraisal Costs
Non-Conformance Costs
Internal Failure Costs
External Failure Costs
Total Quality Costs
2008
3.098.811,45
631.796,51
2.467.014,94
6.929.704,56
4.693.345,49
2.236.359,07
10.028.516
2009
5.177.067,33
1.147.856,56
4.029.210,77
6.535.754,67
4.767.118,55
1.768.636,12
11.712.822
2010
6.814.391,05
1.782.614,36
5.031.776,69
5.828.263,96
4.450.214,56
1.378.049,40
12.642.655
On the other hand, in the table above, the non-conformance costs have been shown
in two parts which are internal and external failure costs. The company has endured
too much internal failure costs. And, the company should increase its preventive
activities and decrease the internal failure costs. When it comes to external failure
costs, the firm is going in a right way, because the amounts of external failure costs
are going down for each given year.
With the help of Table 3, it can be seen that conformance costs – prevention and
appraisal costs – are increasing for each year. Additionally, non-conformance costs
– internal and external failure costs – are decreasing for each year. It also shows that
the huge amounts of total quality costs are occurred after production stage. The internal failure costs are the biggest costs in the total quality costs for every year. This
situation represents that the defects are realized after the stage of production.
Figure 3. The Trends of Quality Costs’ Categorization in percentage
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Journal of Economic and Social Studies
Measuring and Reporting Cost of Quality in a Turkish Manufacturing Company:
A Case Study in Electric Industry
In general, the movements of quality costs components are in a right way, even
though the non-conformance costs are more than conformance costs. In the chart,
it can also be seen that the amount of prevention costs is under the 15% of the total
quality costs which means the firm do not pay enough importance for the prevention activities. Although the trend of external failure costs is declining, the external
failure costs have too much portion of total quality costs. Having too much external
failure costs brings more costs than the firm can measure.
Figure 4. The Trends of Quality Costs’ Categorization in TL
In Chart 2, it is again shown the trend of quality costs components. Chart 1 shows
the trends as percentage value; Chart 2 shows these trends as Turkish Liras amounts.
The inferences of the Chart 2 are similar to Chart 1.
The Application Results
The quality costs activities in X Electric Inc. are concentrated in non-conformance
activities. In other words, the firm is highly interested in internal and external costs.
So, non-conformance costs are monthly reported to management. Besides, the firm
does not give required importance for prevention and appraisal costs’ measurement.
Therefore, conformance costs are just reported yearly period, even though the firm
is giving more importance to conformance costs than before.
On the other hand, while paying the non-conformance costs more importance than
the conformance costs in the firm, the company endures more costs than it can measure. That is to say, the firm can bear the quality costs more than in numbers; there
may be a non-visual negative effect on the firm. For instance, the firm may confront
the loss of customers, bad brand recognition and poor employee motivation and so
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on. Furthermore, the efficient quality system causes to benefit the company in more
ways than one. It decreases the non-conformance costs and increases profitability of
the firm. The firm would have sustainable competitive advantage in the market.
It is found out that the company cannot measure its quality costs adequately, for this
reason quality reporting system in the company is not efficient. The company needs
to give more importance to the quality costs measuring and reporting activities.
Conclusion
Previously, the company thought that quality control was just a waste of time. But
this thought changed in course of time. With the help of effective quality control
system, company can reduce the salvage, loss of labor hours and so on, which increase the productivity level.
Yearly reporting of total quality costs is not efficient for making decisions on these
costs. The measurement of prevention and appraisal costs is not made appropriately.
The allocation key is generally labor costs which are not suitable for measurement of
every costs item in the quality costs.
The firm should establish an efficient quality costs system and determine this system
specification for effective measurement and reporting of quality costs. By having
reliable and sufficient data in quality costing, company can reduce its non-conformance costs. And it causes to reduce total quality costs and increase profitability of the
firm. The firm should prepare instructions and procedures for making measurement
more efficient especially in prevention and appraisal costs. Every person in the firm
should be informed about these instructions and procedures.
On the other hand, only the quality assurance department is responsible for quality costing in the firm. As it is mentioned in the previous parts, quality is not a
person or a department job; it should be responsibility of every person and every
department in the firm. The quality costs reports should be prepared and reported
monthly. The accounting department should determine more suitable allocation
keys for the measurement of quality costs and according to this measurement, the
accountants in the firm should make the necessary journal entries for these costs.
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Measuring and Reporting Cost of Quality in a Turkish Manufacturing Company:
A Case Study in Electric Industry
By measuring and reporting quality costs, the managers can recognize that there is
a huge amount of costs which they do not take into consideration while making
managerial decisions. They can realize that the non-quality issues increase the evitable costs by too much.
In the short run, investing in preventing activities can increase total quality costs in
the firm, but in the long run, these investments will cause decreasing in failure costs.
So, the firm will reduce its evitable costs in the long run.
In the globalizing world, the firm should take the products quality into account. Also,
it needs to be noted here that a company cannot survive in a highly competitive market with its low quality products. Last, but not the least, it must be kept in mind that
the amounts of quality costs never excess the amount of poor quality costs.
References
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Crosby, P. B. (1979). Quality is Free. New York: McGraw-Hill Book Co.
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Şimşek, M. (2001). Toplam Kalite Yönetimi. İstanbul: Alfa Yayınları.
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Quality and Reliability Management, 719-752.
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100
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Journal of Economic and Social Studies
Social Anxiety and Usage of Online
Technological Communication Tools
among Adolescents
Bilal Sisman
Economics and Administrative Science Faculty
Afyon Kocatepe University, Turkey
bilalsis@hotmail.com
Sinan Yoruk
Education Faculty, Department of Education Science
Afyon Kocatepe University, Turkey
syoruk@aku.edu.tr
Ali Eleren
Economics and Administrative Science Faculty
Afyon Kocatepe University, Turkey
aeleren@hotmail.com
AbstrAct
With the growing popularity of Internet communication among
adolescents, the Internet, social media, instant messaging and cell phones
have become important social tools in their life. This study examines teens’
use of social interactive technologies and the role that social anxiety plays on
how adolescents communicate with others (technology or face-to-face). A
questionnaire was designed and distributed to selected sample in the cities
of Afyonkarahisar, Manisa and Uşak in order to analyze the relationship
between adolescents’ social anxiety and their preference of communication
tool. The data were gathered from 544 respondents among High School
adolescents (ranged from 15-18; freshman, sophomore, junior and senior).
Findings show that adolescents rarely use messenger sites and mail addresses.
They generally send instant messages with their cell phones. They spend
1-2 hours for listening music and averagely 30 minutes for Facebook in
a day. More than half of teens have hi-tech cell phones that enable to call,
send message and access to Internet. The findings of the present study also
reveal that females use text messaging more than males. However, males
spend much more time than females to play games. In addition, females
feel themselves more uncomfortable than males for face-to-face talking with
others. And, on the contrary to males, females also prefer to some extent,
to communicate with other on internet instead of face-to-face talking.
Similarly, females prefer more than males to make new on internet.
KEYWOrDs
Social Anxiety, Communication
Tools, Technology, Adolescents
ArtIcLE HIstOrY
Submitted: 22. Jun 2012
Resubmitted: 25 September 2012
Resubmitted: 9 October 2012
Accepted: 22 November 2012
JEL codes: C12, I12
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Introduction
The use of socially interactive technologies, such as social media, text messaging or
instant messaging rises among young people (Pierce, 2009). Among adolescents, the
Internet has become indispensable for instrumental purposes such as school work
information gathering as well as for communication purposes. The communication
applications of Internet, such as e-mail, instant messaging (IM), blogs and chat
rooms have entrenched themselves in the lives of adolescents and Internet has
become an important social context in the lives of adolescents today. In fact, a
national survey of adolescents (10-17 years of age) revealed that in the year before
they were surveyed 25% of Internet users had formed casual online friendships
(Wolak et al., 2002; Subrahmanyam and Lin, 2007).
Instant messaging is also an increasingly popular form of communication. A study
by the Pew Internet and American Life Project found that 53 million Americans use
IM, and 36% of these users reported using IM on a daily basis (Shiu and Lenhart,
2004). IM is a text based form of communication in which two or more people
exchange text messages in real time using the Internet (Lenhart, 2005).
Some researches suggest that socially interactive technologies allow users to avoid
or replace face-to-face communication (Nie and Erbring, 2000). If the person is
shy (socially anxious) and feels uncomfortable with face-to-face interactions, these
technologies may serve as a useful tool for avoiding such unpleasant situations and
therefore may replace face-to-face communication (Pierce, 2009).
US, Canadian and Dutch studies have shown that the vast majority of adolescents
spend several hours daily online. Further surveys show that adolescents consider the
Internet a highly important medium in their everyday social life and use it to form
and maintain social relationships (Selfhout et al., 2009).
Motivation
Today, social anxiety, social phobia and shyness are features that seen every individuals
of all ages. Both adolescents and adults who have social anxiety against life and their
environment scope, has led to more research on them. This study is related on teens
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Social Anxiety and Usage of Online Technological Communication Tools among Adolescents
that high school level about 15-18. The beginning of puberty and the end of puberty
is the reason why we selected this age range. Because, puberty is a vital phase for
growing of young people and determine their personalities. This study is not been
applied only Afyonkarahisar teens but also Uşak and Kütahya provinces are included.
The purpose of this study is to research adolescents’ use of social media, computers,
text messaging, cell phones and instant messaging related to social anxiety effective’s
technological tools versus face-to-face communication. Because, especially 15-20
years-old-teens have been noticed to use on-line communication means having
faster and interactive features rather than having face-to-face communication while
talking to their friends or their parents. Consequently, in this study, the reason for
this choice has a connection with whether social anxiety or gender will be researched.
Literature Overview
Internet Use among Teens
Use of Internet continues to increase worldwide. Colley and Maltby (2008) indicated
that, 57% of households now have access, in comparison to 46% four years ago in
the UK (National Statistics, 2006). The Digital Future Project in the US has found
that 78.6% of Americans went online in 2005, with an accompanying increase in
the amount of time spent per week on the Internet (Center for the Digital Future,
2005).
Many of the studies in this area have been conducted with university students, in
part because of their widespread use of the Internet as a social tool; indeed such use
among students is increasing. In addition, a number of studies have found a high
prevalence of social anxiety among university students who may then turn to the
Internet as a way of regulating, challenging or escaping their social fears (Shepherd
and Edelmann, 2005). Many university students commenting that they are shy in
social situations, but are more open, easy going on the net, in chat rooms. They are
shy about approaching people at a party or in large group, for example, but not
about talking with people in chat rooms.
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Cell Phone Use among Adolescents
Auter (2007) researched that some of them related to adolescents and young adults
use the cell phone differently than their parents and other older users. They prefer to
consider it their primary phone –traditional landline phone – for its. Some studies
have found little or no difference in use based on gender (e.g., DeBaillon, 2003;
DeBaillon and Rockwell, 2005). Other studies have found, however that boys tend
to be more intrigued with technical aspects of the devices, while girls tend to prefer
the interpersonal connectivity – and spend more time using their phones for voice
calls (Henderson et al., 2002; Rakow and Navarro, 1993; Skog, 2002). In fact, while
women in one study felt the phones resulted in more freedom, male teens found the
additional connectivity a constraining inconvenience.
A recent Pew Internet research study found that approximately 33% of teens have a
cell phone. Of the 33% of teens who reported owning a cell phone, approximately
64% said they had sent text messages. In addition, the Pew study found that of
the young cell phone users, teenage girls tended to use text messaging much more
than their male counterparts. Older teens (17 year olds) also reported sending more
text messages on average than younger teens. Although cell phone use and text
messaging have risen among U.S. teens, their popularity remains considerably less
than European teens (Lenhart et al., 2005; Pierce, 2009).
Seventy-five percent of teenagers now own cell phones, and 25% use them for social
media, 54% use them for texting, and 24% use them for instant messaging. Thus, a
large part of this generation’s social and emotional development is occurring while
on the Internet and on cell phones (Hinduja and Patchin, 2007).
Instant Messaging
The two previously mentioned theoretical approaches might adhere to different
types of Internet activities that may have differential effects on well-being. One type
of activities surfing, which can be described as visiting web sites on the Internet
for non-communication purposes. In contrast to surfing, Instant Messaging (IMing) consists of sending messages directly to others one has invited to the online
conversation. Because of its dyadic, real-time, and private format, IM-ing has
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Social Anxiety and Usage of Online Technological Communication Tools among Adolescents
been as an excellent ‘training ground’ for adolescents in terms of their social skills
(Morgan and Cotten, 2003; Valkenburg and Peter, 2007). A survey study showed
that among freshmen college students whereas increased time spent IM-ing was
uniquely associated with less reported depression, increased time spent surfing was
uniquely associated with more reported depression (Morgan and Cotten, 2003).
Social Anxiety and Gender Differences
Social anxiety has variously been referred to as both shyness and social phobia.
Social phobia, (also known as social anxiety disorder) is at the more extreme end of
the continuum of social anxiety and “includes a collation of symptoms which unlike
shyness can vary in severity throughout one’s life” these symptoms are only elicited
in certain social situations (Leary, 1983). In contrast shyness while at the less severe
en of the social anxiety continuum is more likely to be a life long characteristic
of an individual’s temperament which is experienced in every social occurrences
(Lecrubier et al., 2000; Shepherd and Edelmann, 2005).
Individuals are often motivated by a need to feel a sense of belonging; however,
those with social anxiety may find it difficult to fulfill this social need because of
the Internet. For socially anxious individuals, the Internet and socially interactive
technologies (text messaging) can have both positive and negative results. Kraut et al
(1998) found that online interaction greatly reduced face-to-face social interaction.
Females usually have more negative attitudes toward computers and greater computer
anxiety than males. Researches on computer self-efficacy in general also revealed that
males on average have better computer self-efficacy than females (Hackett, 1985).
Similarly, one might expect adolescent girls to be more worried than boys about peers’
negative evaluations of them. Indeed, surveys have found that adolescent girls are
more concerned than boys about others’ judgments of their appearance and behavior.
Moreover, rates of internalizing problems are higher among girls than boys and adult
women are about twice as likely to be socially phobia as men (Schneier et al., 1992).
Thus, adolescent girls may be more vulnerable than boys to feelings of social anxiety,
and this may have implications for their social functioning (La Greca and Lopez, 1998).
Jackson et al. (2001) predicted that women would use e-mail more and men use the
Web for information more, based on the greater interpersonal orientation of women
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and greater task orientation of men. This prediction was supported in a large sample
of Anglo-American undergraduates, even after computer self-efficacy, loneliness and
depression were controlled for. Wasserman and Richmond-Abbott (2005) found
that women use e-mail slightly but not significantly more than men but that men
use chat rooms more. Shepherd and Edelmann (2005) study social anxiety and
Internet use to explore in relation to regulation of social fears. It is hypothesized that
high social anxiety will be associated with low ego strength as well as greater scores
on the Internet.
Methods
Purpose
It is very important to analyze of instant messaging, text messaging and other
socially interactive technologies among teens due to significant popularity. Since
social anxiety can affect one’s type of social interaction, it is prominent to examine
if social anxiety is influencing how adolescents communicate with others and
which technology. The purpose of this study is to research adolescents’ use of
online social sites, cell phones, test messaging and instant messaging and if social
anxiety influences technology versus face-to-face communication. So, the following
hypotheses are proposed:
•
•
•
•
•
•
106
H1: Females use socially interactive technology (text messages, cell phones,
e-mail, and instant messages) more than males.
H2a: There is a relationship between not feeling comfortable talking with
others in person and feeling more comfortable talking with others online.
H2b: There is a relationship between not feeling comfortable talking with
others in person and feeling more comfortable messaging with others.
H2c: There is a relationship between the amount of their families’ monthly
income and social anxiety.
H3: Males are more social anxiety with face-to-face interactions than females.
H4: Males are feeling more comfortable talking with others through a social
interaction technology than females.
Journal of Economic and Social Studies
Social Anxiety and Usage of Online Technological Communication Tools among Adolescents
Participants and Data
The data was gathered from 544 students among High Schools in Afyonkarahisar,
Kütahya and Uşak cities. The age of the participants ranged from 15 to 18. 32.4%
were freshman, 24.1% were sophomore, 28.1% juniors and 15.4% were seniors.
The sample consisted of 227 (41.7%) males and 317 (58.3%) females.
We first were contacted the principals and asked permission in order to survey
some classes on school. After that, teacher was chosen to gain a sample of students
from each school year. After obtaining permission from teachers, each student was
warned about survey able to tell it their parents. The survey was applied in the
students’classrooms and teachers were present during all testing. All students received
the same instructions and their identity would remain secret. Each participant
completed a report questionnaire.
Measures
The first two questions of the questionnaire consisted of primarily demographic
questions such as age, sex, year in school, and general information. The next series
ten questions included items of the students’ comfort level in interacting with others
face-to-face, online talking, cell phone or text messaging. Questions were prepared
by using both nominal (yes or no) and 5 point likert-type scales. All hypotheses
were developed by us to measure the relationship between social anxiety and usage
of technological tolls among teens. The reliability of tests confirms our measurement
(Cronbach α=72.4). This test can be acceptable according to rule of thumb for
describing internal consistency 0.7 ≤ α ≤ 0.8
Results
3.7% stated the amount of children who separate from their families is not adequate
for measuring the relationship between social anxiety and family situation. First of
all, participants were asked about type of technological tools they had use.
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• 88.9% reported having personnel computer.
• 79.2% reported having Internet on their PC.
• 92.6% stated that having messenger address.
• 73% reported having e-mail accounts.
• 96.7% reported having cell phones.
• 72.2% reported having text messaging capabilities on their cell phones.
• 84.3% stated having social media sites and most of them are using Facebook
(49.2%). Most of the other has more than one membership in social sites (twitter,
MySpace, LinkedIn etc).
The following next questions asked how much time adolescents use each of their
time on their technological tools on average day. Table 1 shows the results.
Table 1. Technological tools use
9 h + (%) 7-8 h (%) 5-6 h (%) 3-4 h (%) 1-2 h (%)
Msn
Instant message
Cell phone
Social sites
Music
Game
Mail
Internet
0.4
3.7
0.6
0.7
3.9
0.7
0.9
1.1
0.4
2.2
0.2
1.7
2,4
0.9
0.2
0.4
0
4.6
0.4
1.5
5.0
1.3
0.2
1.1
0.6
10.8
2.2
8.0
10.3
4,3
1.1
6.7
4.3
17.5
11.9
29.0
39.0
17.7
3.9
26.8
30 min
(%)
13.6
23.6
56.9
33.3
31.8
24.0
12.8
40.1
None (%)
80.7
37.5
27.8
25.8
7.6
51.0
80.9
23.8
As shown in Table 1, adolescents rarely use messenger sites and mail address. They
generally send instant message with their cell phones. They spend 1-2 hours for
listening music and averagely 30 minutes for Facebook in a day. More than half
of teens have cell phones that enable to call, message and access to Internet. All
following hypothesis were examined to 95% level of confidence.
Regression analysis was made to see the relationship between feeling anxiety and
family income with technological tools usage among adolescents; T-test, Chi-square
test and one way ANOVA test was performed in the study to see gender differences
with technology use, face-to-face interaction, talking online, making friends online
and playing games.
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Table 2. Regression estimates and correlation
Variables
Dependent
Gender (technology use)
Gender (face-to-face interaction)
Gender (talking online)
Gender (making friends online)
Game
Feeling anxiety
İncome (monthly)
Males
Females
Males
Females
Males
Females
Full sample (n:544)
Standart
Significant
Coefficient
deviation
(p)
1.52
2.31
0.019
1.08
1.90
1.86
0.99
0.003
2.12
0.92
3.48
1.05
0.009
3.71
0.96
Males
3.62
1.19
Females
Males
Females
Instant message
Social sites
Msn
Cell phone
Instant message
Social sites
Msn
Cell phone
4.14
0.30
1.06
0.069
0.139
-0.005
0.308
173,737
-270,341
-8,104
-38,099
1.04
0.75
1.66
0.054
0.052
0.025
0.045
119,286
115,816
55,636
99,021
Independent
Correlation
coefficient (r)
0.000
0.000
0.201
0.008
0.851
0.000
0.146
0.020
0.884
0.701
0.449
0.125
After T-test was made for hypothesis 1, table 2 shown that females (M: 1.08, SD:
1.9) reported that they are using text messaging more than males and significant
relationship between text messaging and interactive technology (M: 1.52, SD: 2.31,
p: 0.019). In addition, males (M: 0, 3, SD: 0.75) spend much more time than females
to play games and there is a gender differences between playing games on computer
and social technology using (M: 1.06, SD: 1.66, p: 0.000). There are not gender
differences in use of instant messaging, e-mail, social network sites and chat rooms.
When someone have to talk face-to-face, feeling anxiety was positively correlated
with feeling comfortable with others through cell phones and social media sites
(r:0.449, p: 0.000). There isn’t a relationship between social anxiety of face-toface interaction and feeling comfortable with others via messaging (p: 0.204). The
regression analysis showed, there isn’t a relationship between the amount of families’
monthly income with social interaction technologies (p: 0.230, r: 0.125).
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According to the results of Chi-square test, significance was not found for
hypothesis 3. However, a female feels more uncomfortable than males for face-toface talking than males (Levene’s test p: 0.017). There is just significant differences
feeling comfortable by talking with social media sites with gender (p: 0.003), that
is; famales (M: 2.12, SD: 0.92) are more uncomfortable than do males (M: 1.86,
SD: 0.99, p: 0.000).
There is significant difference for hypothesis 4, after One-way Anova test was made,
teens prefer talk with someone on computer instead of talking and make new
friends with someone on computer. Females (M: 3.71, SD: 0.96) prefer talking with
some on computer instead of talking face-to-face than males (M: 3.48, SD: 1.05,
p: 0.009). Similarly, females (M: 4.14, SD: 1.04) prefer making new friends with
someone on computer more than males (M: 3.62, SD: 1.19, p: 0.000).
Conclusion
In Turkey, cell phone, text messaging, instant message and social sites membership are
recognized as the most important medium of communications among adolescents.
Internet access via PCs and mobile phones plays very significant role Turkey
adolescents. Technology tools effect teens’ social emotions against their families and
friends. This study demonstrated that teens are using socially interactive technology
to communicate with others and it serves social anxiety and decreasing face-to face
communication.
The findings of the current study found that females are using text messaging more
than males. However, males are playing games for a long time than females. In
addition, females are feeling more uncomfortable talking with others face-to-face
than males. And, females also prefer talking with some on computer instead of
talking face-to-face than males. Similarly, females prefer making new friends with
someone on computer more than males.
Beyond the results of this study, we examined something very important situation
related to adolescents’ today currents. While the age of participants were increasing,
the time spend in social media is decreasing. The reason for such conclusion revealed
that, senior students have to work more for university exams during education
session. So, they can’t spend much more time on social media sites.
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Social Anxiety and Usage of Online Technological Communication Tools among Adolescents
Many studies in this area is conducted for university students. The use of Internet as
a social tool is more common among at this age adolescents. But this study is related
to high school level for students and we examined the relationship between social
anxiety and the use of Internet, cell phone as a technological tool. Further studies
may apply for university students.
Finally, adolescents who may be shy, have social phobia, and feel anxiety about talking
with someone, various and different technologies provide reliable opportunity for
them to contact with them. It is possible to reproduce the contributions of technology
for our world. Although this technology facilities the lives of people, it sometimes
breaks the peace. Technology has changed the way we live today and also changing
our communication skills with high costs. Only time will tell what is going on in the
future. Parents and teachers have great responsibilities for this subject.
References
Auter P. J., (2007). Portable Social Groups: Willingness To Communicate, Interpersonal
Communication Gratifications, and Cell Phone Use Among Young Adults, Inetrnational J. Mobile
Communications, 5(2) 139-156.
Colley, A., and Maltby, J., (2008). Impact Of The Internet On Our Lives: Male and Female Personal
Perspectives, Computers In Human Behavior, 24, 2005-2013.
Hinduja S, Patchin J. (2007). Offline Consequences Of Online Victimization: School Violence And
Delinquency. J Sch Violence. 6(3): 89 –112.
La Greca, A. M. and Lopez N., (1998). Social Anxiety Among Adolescents: Linkages With Peer
Relations and Friendships, Journal of Abnormal Child Psychology, 26(2), 83-94.
Lenhart, A. (2005). Protecting Teens Online. Pew Internet and American Life Project. URL: http://
www.pewInternet.org/.
Morgan, C., and Cotten, S. R. (2003). The Relationship Between Internet Activities and Depres-sive
Symptoms in a Sample of College Freshmen. CyberPsychology and Behavior, 6(2), 133–142.
O’Keeffe, G. S., and Pearson, C., (2011). The Impact of Social Media on Children, Adolescents and
Families, Journal of American Academy Of Pediatric, 800-805.
Pierce, T., (2009). Social Anxiety and Technology: Face-To-Face Communication Versus Technological
Communication Among Teens, Computers İn Human Behavior, 25, 1367-1372.
Selfhout, M. H. W., Branje, S. J. T., Delsing, M., Bogt, T. F. M., and Meeus W. H. J., (2009). Different
Types Of Internet Use, Depression, and Social Anxiety: The Role Of Perceived Friendship Quality.
Journal of Adolescence, 32 819-833.
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Shepherd, R. M., and Edelmann, R. J., (2005). Reasons For İnternet Use and Social Anxiety, Personality
and Individual Differences, 39, 949-958.
Subrahmanyam S. and Lin, G., (2007). Adolescents On The Net: Internet Use and Well-Being,
Adolescence, 42(168), 659-677.
Valkenburg P. M., and Peter J., (2007). Online Communication and Adolescent Well-Being: Testing the
Stimulation Versus the Displacement Hypothesis, Journal of Computer-Mediated Communication,
12(4), 1169-1182.
Appendix 1
The purpose of this questionnare is to research 15-20 year old adolescents’ use of online social sites,
cell phones, test messaging and instant messaging and if social anxiety influences technology versus
face-to-face communication.
Assoc. Prof. Ali Eleren
Asst. Prof. sinan Yörük
reserch
Assist.
bilal Şişman
1.
What is your sex?
2.
What is your year in school? (select only one)
------(9)
------Male ------Female
------(10) ------(11) -----(12)
3.
What is your families’ total income?
------------TL
4.
Does your mother and father live together?
---Yes
---No
5.
Do you have a daily computer?
---Yes
---No
6.
Do you have a Internet access on your computer?
---Yes
---No
7.
Is your Internet connection wireless?
---Yes
---No
8.
Do you have a instant messaging address?
---Yes
---No
9.
Do you have e-mail address use actively?
---Yes
---No
10. Do you have a cell phone?
---Yes
---No
11. Do you have access to the Internet on your cell phone?
---Yes
---No
---Yes
---No
12. Do you have a social networking account?
(Twitter, Facebook, MySpace etc)
13. If yes on 12, which of the following social networking do you have?
------Facebook
------Twitter
------Linkedin
------Youtube
------Classmates
------Other (please specify)--------------------14. On an average day, how much time do you spend with each of the following?
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Social Anxiety and Usage of Online Technological Communication Tools among Adolescents
9+
7-8
5-6
3-4
1-2 30 min- None
hours/ hours/ hours/ hours/ hours/ utes/
daily
daily
daily
daily
daily
daily
Instant messaging
Text messaging with cell phone
Talking with cell phone
Social networking
Listening music
Playing game
E-mail
Online (surfing on the Internet)
15. How comfortable are you talking with friends, family and teachers face-to-face?
---Very comfortable ---Comfortable ---Normal
---Uncomfortable
---Very uncomfortable
16. Do you find yourself getting anxious when you have to talk with someone face-to-face?
---Always
---Frequently
---Sometimes
---Rarely (very few)
---Never
17. How comfortable are you talking with others using text messaging?
---Very comfortable ---Comfortable ---Normal
---Uncomfortable
---Very uncomfortable
18. (If yes on 12) How comfortable are you talking with others on your social networking sites?
---Very comfortable ---Comfortable ---Normal
---Uncomfortable
---Very uncomfortable
19. How comfortable are you talking with others on your instant messaging?
---Very comfortable ---Comfortable
---Normal
---Uncomfortable
---Very uncomfortable
20. How comfortable are you talking with others on your cell phone (talking)?
---Very comfortable ---Comfortable ---Normal
---Uncomfortable
---Very uncomfortable
21. How often dou you text message someone instead of talking to them face-to-face?
---Always
---Frequently
---Sometimes
---Rarely (very few)
---Never
22. How often do you talk with someone on the computer instead of talking to them in person?
---Always
---Frequently
---Sometimes
---Rarely (very few)
---Never
23. How often dou you text message someone instead of talking with them on the cell phone?
---Always
---Frequently
---Sometimes
---Rarely (very few)
---Never
24. How often dou you make new friends with someone on the computer?
---Always
---Frequently
---Sometimes
---Rarely (very few)
---Never
25. When confronted with a difficult stuation with another person, which of the following would you
typically use to talk with other person?
------Text messaging with cell phone
------Talking with cell phone
------E-mail
------Instant messaging
------Social networking sites
------Face-to-face communication
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State as the Source of Wealth: In
Ottoman Economic Thought: A different
approach to reflections in the aftermath
of the global crisis
Birol Çetin
Gaziosmanpasa University
Faculty of Economics and Administrative Sciences,
Department of Economics / 60110 Tokat TURKEY
birol.cetin@gop.edu.tr
AbstrAct
This study aims to deal with the ways of creating wealth by economic
activities, presenting experiences within Ottoman state tradition and a
role of Ottoman state during this period. In this context, the economic
power achieved by the state will be explained through examples of
practices.
The role of the state in the economy has been raised with the latest global
crisis and despite the historical expriences, this role has been started to
debate in the economics. In fact, the corrupted state concept should be
re-evaluated and re-established. Otherwise, re-evaluation of fundamental
issues such as market system or freedom of enterprise wouldn’t contribute
much to the solution of the problem.
KEYWOrDs
Ottoman, Global Crisis, Market
Sistem
ArtIcLE HIstOrY
Submitted:21 Jun 2012
Resubmitted:08January 2013
Accepted:25 March 2013
JEL codes: N00,N20,B10
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Birol Çetin
Introduction
In the traditional Islamic thinking, economy was subsistence and economic activities were mainly based on the supplement of daily requirements. Although there
was no prohibition of becoming prosperous or accumulating wealth, owners of the
wealth were advised to spend it for charity. According to Holy Quran and the Sunna,
words and acts of the prophet Mohammad, basic sources of Islamic knowledge, and
principles of justice were important in economical affairs, and legal way of earning
were accepted equal to worshipping. However, after the establishment of sultanate
tradition, the state transformed a source of income mechanism into a distrubition
of wealth mechanism.
Ibn-i Haldun,a famous philosopher of Islamic world,addressed the both normative
and positive sides of the issue and stated that the state got power in the area where it
shouldn’t have had it. According to Ibn-i Haldun, there were three ways of subsistence and income: agriculture, industry (crafts) and trade. It seems that he considered agriculture and industry affirmative while trade was doubtful. He considered
agriculture and crafts honorable, because they rely on one’s direct labor and effort.
But they both did not make a person rich. In addition, Ibn-i Haldun mentioned
public service as a means of getting rich, despite the fact that it was not a regular way
of subsistence. He thought that people should get close to either the state or trade
in order to be rich.
Imaret, described as a state governing by Ibn-i Haldun Imaret, was the way of collecting taxes through confiscating someone’s wealth using political power and administrative office. Therefore, state work is not a natural way of make for a living. He
described the civil cervants as feminine people who cannot do their own business.
According to Ibn-i Haldun the ones who cannot come close to the state in order to
protect his capital and to be rich, in his own words “the ones who do not indulge
and lick someones’ boots” cannot have wealth because wealth is produced by public
office. The ones who seize the power and who come close to the rulers became rich.
Therefore, this study aims to describe the ways of getting rich appropriate to Ibn-i
Haldun and reveal the formation of them in Ottoman Empire. Trade, public services and companies were predominantly analized in this study.
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Role of the State in the Economy
It is not possible to state that trade was excluded in the powerful central administration of Ottoman Empire. In terms of the state intervention to the markets, the central administration was parallel with the system of administration apart from some
applications.The purpose of the state was to suppress all kind of power and influence
of local authority over the economic life and to obtain a great influence over all kind
of goods as well as people by means of eliminating the intermediate agents between
the subjects and the Sultan (Güçer, 1987).
Although, the main purpose seems beneficial for the citizens as it is frequently appears on the documents such as “public good”, “development and prosperity of the
country” or “increasing the welfare of the citizens” (Tabakoğlu, 1994), it was actually decreasing the state’s reserves as it was frequently appears on documents such as
“working to increase the state’s wealth without taking inadequate taxes”. Some interventions aimed to take taxes while others aimed to buy goods and services below
the market price by the state.
Dominant state Policy in Markets: Although,the prices were formed by a system
determined by the state,the markets were not competitive in mant big towns,notably
İstanbul had had a dynamic economic life.It can be claim that the narh system,the
state intervention on the market prices,had negatively affected this dynamism.
Aims of The Narh system: In addition to economic aims,there were political,moral
and administrative aims at the narh system.A brief study of these aims will show the
functions of the narh system.Although to separte these aims is diffucult,significant
ones can be determined based on the classification of examples.These can be listed
as follows:
Administrative and Politicial Aims: Sultans and “sadrazam”s sometimes had attempted to lower the narh or to keep it low in order to reinforce their positions as
well as to get the support of the general public. These attempts were embodied in
expressions found in “hatt-ı humayun” (decree of sultans) issued by Selim III to
“sadrazam” Musa Paşa (“make sure that the price checks are strict and satistaction of the
citizens is ensured. Also affairs of citizens should be facilitated through your day-andnight efforts. Blackmarketing should be prevented in order to supply the needs of people
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in Istanbul. The behaviours against rules should be punished (Pakalın, 2004). According to Tevkii Abdurrahman Paşa, a regulator, the narh should not be haphazardly
dertermined. According to Şehit Ali Paşa, the form of “putting into effect the prices
by the state should not be controlled by the judges and municipal police, also it should be
checked on a daily basis. Overcharging should be eliminated. You should be aware of the
fact that the narh is the most crucial work of the state.”
Therefore,the narh system was not only for regulating the price stability but also
played a significant role in maintaining the order of the community. In his book
entitled “Fusul-i Hall’ü Akd and Usul-i Harc-i Nakd”, Gelibolulu Mustafa Ali points
the following justifications as the purpose of the book: “... with increasing population, narh system could not be effectively practised. Thus, order of the society deteriorated, judiciary corrupted, and the system got into the hands of the dishonest.
The sultan cannot be thought of accepting this( Yücel, 2003). ‘’
In this concept, deterioration of the narh, judiciary and social order are accepted as
the same. Since the price instabilities which had the same meaning with the weakness of the state authority were taken as an indicator of administers’ and public’s
weakness. This issue was taken seriously. It was also taken serious because speculations were forbidden religiously for the public.
The narh system was not only to protect the consumers but also was necessary for the
protection of produces and traders.Thus, the aim was to prevent non-standard and
fraudulent good’s trade. There were various restrictions for traders who acted against
the narh. For example, in a decree issued to Judge of Istanbul and municipality police in 1676, the Sultan himself dealt with the packaging and selling procedures for
pears brought to marketplace: “Order to the Judge of Istanbul and Municipality Police
Chiefs: As “Pazarbaşı” Veli and his deputies complained, since pears come into the marketplace, they are put into small boxes and sold as boxes, the poor cannot buy these boxes.
The sales should be like before, i.e. Pears should be brought to the marketplace in big boxes and sold by kilograms based on consumer’s need.”(Çağatay,1981).The administrative
interest abaout conforming to the narh system also involved quality and standard of
the goods. For example, when it was noticed that the quality of fabrics produced in
Bursa deteriorated, an inspector was sent to Bursa in 1477. The inspector found out
that a cheaper production method was adopted due to increased raw material prices.
This reason was approved and new product was allowed (İnalcık, 1993).
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Financial reasons: Fixed prices due to the narh system provided major advantage for
the state, because state was the major buyer. The state could buy for lower prices. For
example, grain prices formed as free market and the state had had to buy on that price.
Free market prices were usually monitored on heritage notebooks and the prices on
“tereke” notebooks were always higher than official ones. The reason was the higher
“resm-I kısmet” (a kind of heritage tax) taken by judges because of higher “tereke”
price. Although, price of wheat per kg was 11 “guruş” and the price of barley per
“kile” (a weight in unit) was 5 “guruş” in 1799 at Tokat, according to official purchases
by the state, price of wheat flour was 4.0 “guruş” and barley was 2.25 “guruş” (Öztürk,1987). However, it would not be realistic to say that official prices were always
kept low and the narh prices were continuously suppressed by the state. Considering
the fact that vast amount of agricultural products were sold in the market, it would be
true to assume that suppressed prices were only common in extraordinary situations.
Direct Interventions To Trade: Other than mentioned above,there were another
intervention methods in trade. These were “yedd-i vahid” (monopoly) practices,
regulations about market places and trade regions, gedik method (a kind of quota
imposed on the craftsman about the number and location of businesses) and various confiscation procedures applied to traders. The aim here was to prevent speculations, blackmarketing, deceptive sale practices, and to establish the order in the
country. Food supply in big cities was an issue to which much significance was
attached and attention was paid. Ottoman administrators were deeply taking into
account that a well running economic life would make other state affairs smooth.
Otherwise,there would be many social and administrative problems. “Gedik” and
“yedd-i vahid” practices aimed to facilitate the work of the tradesman and to keep
things well organized establishment content.
Although, confiscation procedures mainly involved state afficials, it applied traders who were thought to have become unjustly rich. Even in financially difficult
times, state did not covet traders’ wealth. There was a significant explanation about
this subject in “hatt-ı humayun”s issued by Selim III.During 1787-1792 AustrianRussian Wars,the state was in financial difficulty and Sultan asked for financial solutions. This was explained by Selim III as follows: “Kaymakam Paşa” what I say to
you is: “There can be no answer if the state has no money, then how can we live such a
pretentious lives and what did we consume? We showed our enemies that we are weak.
And looking at your situation,I am surprised. Just tell me how it could be possible. You
have been in public service for so long, you are the one who knows where the extra five
akçe(a currency unit) is, and you are asking me. You said that this is away from here, and
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didn’t I take it? (Karal, 1999) Although, upon this decree, Sadrazam wanted to confiscate heritage and merchandise of some traders, the Sultan strongly prohibited and
saying: “Seizing the belongings of orphans is something contrary to my opinion. I
can not allow to touch them.Whatever accumulated by someone should be left to
his or her heirs after the death, whether it is accumulated through trade, farming or
crafts, should be left to his heirs, after his death. Don’t ever touch them! Only the
wealth of public servants belong to state treasury, neither to me or to his heirs. All of
them should be spent for public. Our ascendants did so. If the accountant is afraid
of God, he shouldn’t touch the heritage of craftsmen, otherwise he will be severely
punished.”
One of the clearest examples of direct interventions to market was obligatory migrations practiced upon traders in order to develop trade in some areas. However,
these exchanges were provided some tax exemptions. After the conquest of Kefe,
300 traders, and their families, were deported to Istanbul. It is known that livestock
traders and butchers worked under coercion in order to keep meat supply running
in large towns, and free trade conditions were not applied in this area of work (Pamuk, 1994).
Corporate Movements and Status of the State
Being dominant in trade through the narh system, the state closely followed developments in the west regarding market economy and corporate movements, also tried
to be involved in these activities.As a matter of fact,the first corporation “Şirket-I
Hayriye” was established by the state. In this subtitle, the state’s effort to manage the
process of capitalist development without losing power will discuss.
Partnerships in Ottoman Trade Life: Although, tradesmen and craftsmen were
confined with the strict laws which entrepreneurs had sufferd a lot,it seems that
Ottoman State closely watched the corporate movements in the west.There is no
doubt that partnership culture and practices always survived as an indicator of a
deep rooted tradition. However, there were major differences between the corporate
tradition of the west and Ottoman applications.
There are three types of contract based on partnership in Islamic law consisting of
capital, labour and credibility.These were in the form of “Şirket-i Inan” (a kind of
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labor-capital partnership) and “Mufavada Şirketi”, a kind of cooperation based on
the equal rights of family members. Records about these partnerships were taken
from “Mecelle” was common in “Şeriyye” Records. “Şirket-i Inan” practice was
common among vegetable oil and honey markets, especially in far away trades. They
had started from the supply of the product and ended when the product reached to
Istanbul where it was shared. In some practices, it was seen that people became the
joint-owner of ships through giving loans to ship owners as similar to the western
practice (Farooqhi, 1993). Apart from this small scale partnerships which did not
require much capital. Especially after beginning of the “Iltizam” practice, privatization of tax revenues, partnerships involved the merging of large companies had
started to be common (Gedikli,1999). However, this kind of partnerships which
require great amount of capital accumulation was formulated based on some privileges provided under certain circumstances and uncertain conditions (Cezar,1986).
Private entrepreneurship and corporate culture had not developed adequately due to
the fact that the capital accumulation was in the hands of high officials and profitable business was possible only between privilegers.
As a result of “iltizam” practice, owner of “dirlik” (money obtained from the state
land used for soldier training (similar with latifundia in Rome) were disappeared.
Life-long “mültezim” concept appeared and provinces were left to “mültezim”s.
Therefore, non-muslim traders gained power by means of the governor’s policy. Towards the end of the 18th century, some of this “sarraf ” s had fortunes more than a
million pounds. These minority members were in close contact with foreign traders
and they played significant role about providing loans to the state (Tezel, 1986).
They acted like the treasury of the state during the hard times for financing military
expences and like financial crisis. For example, in 1878 460,000 pounds were taken from banker Zarifi for military expences. Another document shows that “miri”
farms in Yanya were given away for paying a previous loan of 25,000 Turkish liras. 1
Embassies and consulates of foreign countries started to market their own goods
in modernization and especially in the later half of the 18th century. In this period,
partnerships with minorities had become more and more common.These minority
traders were also benefiting from various privileges given to foreign traders through
merging. There were many minority members who changed their nationality. After
securing minority rights through “Küçük Kaynarca” Treaty, this practice had become even more common and disguised traders became registered ones.Thus,the
state could not stop this trend and gave the rights to its own minorities which were
1
- B.O.A. Yıldız Tasnifi, Sedaret Resmi Maruzat Evrakı no:1-40
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previously given to foreign traders and “European Mechanthood” was established.
In order to keep balance,these privileges were given to Muslim traders with some
extras,thus “Hayriye Merchanthood” was established. Unlike the former traders, later ones were also given the privilege of trade to Persia and India (Tabakoğlu, 1994).
Corporate Movements in Ottoman Empire: There were some opinions in “Tanzimat” period that the economic problems country experienced could be overcome
through corporate development. Sultan Abdülmecid stated that he struggled a lot
to take loans but he failed and and revenue-increasing measures, such as forming
companies as in other countries, were necessary to overcome the financial problems (Koraltürk, 1999). Ministry of Trade was established in 1840 and “Kanunname-i Ticaret” act of 1850 decelerated some developments about corporate
development.”Kanunname-I Ticaret” was a translation of French law titled “Code
de Commercé” of 1807 with some minor modifications.This act was current until
1926 and provisions about companies were mentioned in its 11th,13th,14th,19th articles (Şekerci,1981). According to an expression in 13th article, constitution which
was formed in 1876 “Ottoman subject has rights to establish all kind of companies
for trade,crafts and agriculture provided that they obey the rules and order”. Cevdet
and Fuat Paşa established the first Ottoman share company, “Şirket-i Hayriye”,in
1851. At first, operating ferries were between Bosphourus and Karaköy. “Şirket-i
Hayriye” increased its activities year by year, and became a modern business after
obtaining the privilege of Bosphourus transportation. As a consequence of these
developments, many maritime businesses were formed using state protection and
practices after 1910 (Eldem,1994).
Board of Industrial Development operated between 1860 and 1873 focues on corporate development and worked on restoration of craftsmen unions.The purpose
was to collect the craftsmen operating as scatterd under share company system with
a common capital investment. However, when the board started to dominate every
decision from appointment of company executives to profit margins and sale prices,
desired benefits were not achieved. An example of these efforts was a share company
run by leather craftsmen of Istanbul with a capital of 10.000 golden coins.
Corporate development gained speed in the second half of the 19th century. Following Şirket-i Hayriye, Bank-ı Osmani and Şirket-i Osmaniyye that run Aydın-İzmir
railway were established. A majority of companies formed in this period were privileged foreign companies and they conducted banking, insurance, railways, mining,
utiliy gas aand tramway operations.These were foreign companies.Until 1908, the
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A different approach to reflections in the aftermath of the global crisis
number of share holding formed and involved in economic activities in Ottoman
land was 86. However, a total of 236 companies were established in 1908-1918
period only (Toprak, 1997).
In the process of corporate development and strengthening the capital structures
Galata Bankers who had been operating since the time of Sultan Mehmed made
significant contributions. During the reign of Abdülhamid,not only public debt
securities but also shares of companies which had been operating in transportation business such as railways, tramway , tunnel, and in mining, water, natural
gas, electricity and manufacturing areas were being traded in Galata Stock Maket.
Galata Stock Market started to buy and sell state bonds and company shares.Sultan
Abdülhamid,himself,was involved in these affairs by means of his private banker
Zarifi and it took public attention to this area (Kazgan,1995). By the act of “Development of Industry” which had been put into effect after “Meşrutiyet”, corporate
development was encouraged and domestic companies were started to be established. Most of these companies were included in the list of Shares and Bonds Stock
Market. Companies quoted in the stock market were in different ındustries such as
such as Thread and Linen Goods Share Company (with a capital of 10.000 Lira),
Ottoman Anonymous Ittihat Company (with a capital of 100.000 Lira), Ottoman
Anonymous Rubber Company (with a capital of 20.000 Lira), Ottoman Marble
Company (with a capital of 25.000 Lira), Turkish Naphta Industry (with a capital
of 250.000 Lira) and “Dersaadet Cheesemaker Teavün” Company Company (with
a capital of 25.000 Lira)( Fertekligil, 2000). Figures about factories and manufacturing plants in a statistical record dated 1897 gives information about trade life.
Under the title of “Memalik-i Mahrusa-ı Şahane’de mevcut fabrika ve değirmen
vesairenin nev’i” (number and kinds of factories and mills in Istanbul) 23.837 business places were mentioned (Güran, 1997).
Corporate concept in Ottoman Empire appeared as privileges of share corporations.
In the study of Mehmet Cavid Bey entitled “İlm-i İktisat” after explaining various
corporate types, the following information regarding share corporations were given
(Mehmet Cavid Bey,2001). “A majority of companies are share companies. They performed profitable activities and much of work especially in trade and industry is done
by these companies.As other European countries establishment of these companies are
subjected to Sultan’s approval.Besides the company has to follow some procedures in order
to get privilege”.Therefore,the key condition for the company was to obtain a privilege. While the corporates in the west formed around the capital accumulation.They
were quite different in Ottoman Empire in terms of their logic since they did not
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fit to partnership cooperation.Ottoman corporate development process completely
relied upon privileges, and getting rich through trade which was possible only via
the permission of the state.
Public Service and Its Monetary Advantages
Strong bureaucratic structure in Ottoman Empire was a result of an effort which
was to keep permanently the government in the hand of centralized administration.Therefore, the public service officers were pleased financially to create a strong
bureaucracy.The richest top ranking officers known as “devletlü” were remarkably
in large numbers.The methods to obtain a fortune for high ranking officers will be
clarify in this chapter.
Monetary Awards: The issues such as great military achivements, excellent pursuance of assigned duties, and neutralization of oppositions taken place against the
Sultan were the prominent awarding examples within the bureaucratic structure of
Ottoman Empire.
Since entering the public service had been a matter of good chance,young people
were accepted to the palace after passing all tests.They had been hardly training.
Entering to the palace was not easy and selected ones had to have certain qualifications (Ricaut,1686). According to Gökyay ‘’When Architect Mehmet Ağa, who built
the Blue Mosque, entered the office in the Palace, he saw the attention paid towards the
musicians and wanted to be a part of this profession. He convinced his master to give
him lectures on music. However, after a dream he gave up this profesion and decided that
it would conflict with his belief.After getting know the various artisans in the palace,
he was interested in the art of “sedefkar”s, inlay workers using mother-of-pearl, and
decided to perform this art.” Although the training given in the palace and criteria the
young people were subjected to decide the occupations to be assigned were out of
the present study’s scope.It is important to note that the trainees could select the occupation themselves. It seems that this practice had aimed high productivity from
the very first day in public service (Gökyay,1988).
In fact, there was no need for additional awards since Ottoman administration system.
The upper office was quite awarding financially and the state officers had done their
best to get upper offices. In order to understand the income of the high officers the
following incidence reported by Mustafa Nuri Paşa is interesting “During the end of
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the reign of Sultan Mahmud II, Paris ambassador Ahmet Fethşi Paşa was appointed to
“Sancak” of “Aydın” and then the commander of division and former chief commander
Namık Paşa was appointed as a “müsellim” with 25,000 “guruş” monthly salary. After
a while,Ahmet Fethi Paşa came to Istanbul and then went to Aydın. He offered Namık
Paşa 25,000 “guruş” in addition to income of all “mukataa”s and under-door revenues
and other income for his sustenance. Since Namık Pasha did not accept the offer, he appointed Ahmet Efendi, one of his relatives as his müsellim. After earning two million guruş
of income that year, Sultan Mahmud II notified the Minister for Mukataas Nazif Pasha
and allowed Ahmed Fethi Pasha to keep only the half of the income and returned the
other half to treasury. The aim of this example is to show that governors and mutasarrıfs
of sancaks with good incomes had very high incomes and they hadn’t needed extra money
from taxes imposed on the people.Here, salary differences between administrator and deputy
classes were significant. According to accountant records of Istanbul Palace in the period of
1555-1556,daily income of “Dar’ül Saadet Ağası” was 45 “guruş”,while 24 “ağa”s which
had worked under his supervision was only 5 guruş (Barkan, 1979). In statuebooks,
chapters had not only the job description but also had the salary aspects of the officers.
For example, “and beğlerbeğilik is the path of four people: province chief accountants,
approval officer on behalf of the Sultan, judges whose incomes were five hundred
“akçe” and province “bey”s whose incomes reached four hundred thousand akçe (Akgündüz, 1990)”. Therefore, significance of officers were defined based on the income
income obtained. Besides,statue changes were also remarkable.High officals called
“devlet erkanı” such as Prime Minister, “Şeyh’ülislam”, Navy Commander, Ministers,
Minister “Kethuda”s,accountants and lawyers had residences and as many as 200 service personnel such as kethuda, mühürdar (sealer), cook, stableman, boatman, residence keepers and tailors. These service personnel attended to wars and conducted
their service during the war. Although this practice was criticized heavily, it was not
changed (Aksan, 1997). Wealth of high officers were staggeringly high. When a messenger from India said to Halil Hamid Pasha that they could give five thousand sacks
of golden coins to Ottoman Empire in return for helping them, the Pasha said “I and
Kaptan Paşa present here alone could give that much”. The amount mentioned was
about two hundred fifty thousand golden coins.
It is seen that regular payments were done for the central officers until 18th century.
However, along with the deteriorating financial structure, a “grant based service
fee” system was adopted in place of regular salary payment. In this system, the
grant received by bureucrats increased as he worked harder and did his job properly
(Findley, 1996).
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Distinction should be made between two aspects of material award system: first,
appointing one or more level above offices in return for the accomplishments and
the second giving big bonuses. The former was common and effective in use. This
practice continued after Tanzimat, although regulations regarding public officials
were subjected to certain rules Ahmet Muhtar Pasha was promoted from colonel
to Marshall after his extraordinary success in Yemen only in 9 months. He talks
about this: “When the boat which was carring the document showing my promotion and
accompanying officers came to Kunfuda and Şakik Edip Efendi and aide of the sultan
set out to come near me. However,I had already a herald from Kunfuda,so I was higly
affected and cried. I was closed up in my tent and did not accept anybody for an hour.
The reason not having enough time to think about deserving this duty or not and having enough qualification for this duty. I was scared of being humiliated later. For I was
a colonel nine months ago. My brigade and major general period are only nine months.
Giving me these three big ranks meant that they expect a lot from me.” Another example
of this was promotion of Topal Osman Nuri Paşa from colonel to marshall only in
three years.
In the practice, awards called the state awards and promotions were given collectively as well as privately. Collective awards called tip from the Sultan were given
during ceremonies for the Sultan’s claim of throne and during another celebrations
after big military triumphs.Examples of individual awards were decorations of historians appointed by the Sultan to “Divan-ı Humayun” and some other offices. Along
with the formal start of the state historian statue in 1700, famous historian Naima
was rewarded 500 “guruş-u attiye” and one “guruş” payment rise to his daily wage at
customs (İlgürel, 1991). Sometimes there were payments for the officials relieved of
the duty in order to prevent them to get offend and to make them feel good about
the trust of his service. After Halil Paşa removed from the duty,Sultan Mehmed II
(the Conqueror) gave him a village in Filibe Sancak as his own property in order to
dispel his doubts and to decorate him (Çarşılı, 1988).
The available documents show that sometimes there were extravagancies in rewarding. For example, after the Crimmean war, the British and French saw that saw that
Ottoman gun powder was better than the ones produced in their countries. They
offered big rewards to chief of gur powder manufacturing officer Ohannes Dadyan
and wanted to bring him to their countries. He turned down their offers and said
that “I was born in Ottoman Empire and raised here. I dedicate my life to this country”. After heard about it Sultan Abdülmecid donated him a land in Yeşilköy as far
as his eyes could see (Pamukciyan, 1958). This land was in the area known Florya
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today and consisted of 210 pieces of plots, which is almost all of today’s Florya.
Dadyan’s inheritors had disagreements over the land in 1950’s and their cases went
on for years in courts (Dadyan, 1954).
Warrenties and Eliminating the Concerns for the Future: Incentive and awarding
practices applied during the public service continues after termination of the service. Thus, officials conducted their lives without concerns. Besides a pension, the
officials could retain all the wealth they accumulated during their service in their retirement. Although in Ottoman Empire only the Sultan could own property.”Paşa”s
and “Vezir”s also could have properties such as large farms, palaces, residencies,
whose incomes completely belong to them.In order to understand the practices
on this issue, it is necessary to study Has (big Timars such as latifundia in Rome)
concept. Although, “has” term is used for Sultan’s property in Great Seljuks,it has
a meaning of private property land and “dirlik” which had returns at least 100,000
“akçe” in a year was belonged to servants of Sultan and palace officials such as
“Bostaniyan-ı hassa”, “Doğanciyan-ı hassa”, “Mehteran-ı hassa”, as well as dynasty
members, ministers, beylerbeyis, sancak beyis and accountants. For example, there
was a rule regarding the sell of grain from “has”es and farms dated H.945 in Bursa
(Gökbilgin,1988). “Has”es appropriated to “Vezir”s and high officals were abolished
year by year and added to “Mir-i Mukataa”.After “Tanzimat” the principle of making all expenses through the state treasure was put in practice and this system was
cancelled totally after starting regular salary payments.
Divan-I Malikane” (life-long mültezim), a significant type of private property, was
also an example of this privileged land property practice. “Malikane” owners had
right to sell,donate,establish foundations and leave them to their children when
they die (Barkan,1939).Giving to own a property right ,which exclusively belong to
Sultan,to the state officals means that officers could demand nothing from the state
since they had some privileges of sultan. As a result of having all financial needs that
they could dream of the state officials could only focus on their duties.In addition
belongings could have been passed to their heirs, so they did not have any concern
for the future. Against the danger of confiscation or contraversions among family
members, some officials disregarded inheritance rules of Islamic law and established
Foundations special their children, so taking guarantee even the future of their children.In practice, in some cases children of some officials were paid salary.There was
no doubt that confiscation was the main concern of state officials who had considerable amount of wealth accumulation.
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“Müsadere” (confiscation) system took its legitimacy since “devşirme”s were in the
same statue of slavery, the state had right to take their share of heritage according to
Islamic law.Besides, hey had not pay any tax.they had to help the state in hard times
just as the Sultans had paid from their own wealth.If all the wealth were confiscated,
the state had to pay for the livelihood of statesman’s household. There were not any
age limitations for statesman. Service was unlimited except for dismissal, dementia
and impairment. There was an amount given in cash or dismissed officers called
“arpalık”.This could be an annual income of a given land or a given sum appropriated from the treasury (Tabakoğlu, 1994).
Conclusion
Ottoman Empire represents a strong central state tradition and this subject is the
source of its economic power.These facts literally show that the state is the source
of wealth.The fact that the state was the sole owner of the land restricted the ways
of getting rich by trading and working in public service.Strict state control and
getting low profit margins made it difficult to be rich through the trade. However,
“sahaf ”s operating in financial markets and especially later period’s non-muslims
dealing with trade were exceptions.
On the other hand civil service semms to be the only way of getting rich in Ottoman
Empire.Confiscation establishment was one which could eliminate all concerns.The
state was not complaining about high officials who were getting rich because it was
thought that this wealth belonged to the state.The main reason for a conviction was
the fact that statesmans could not leave this wealth to their inheritors.
According to Ottoman political system took its power from economic strength.The
state had to be as strong as possible within national borders.The state administration under control of financial system debilitated the state and thus hurt the citizen
whose protector is the state. This became apparent with the financial depression
happened in the 17th century.
Present day situation is no different. In the recent recession, states must reconsider
their relationships with financial system and make some reorganizations. It should
not be forgotten that 90% of the public revenues come from taxes. Although cooperation with financial quarters can be conceived to the benfit of the states at first, it
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will result in drying of tax sources as well as the losses in production strength in long
term. The most pressing question to be faced and to be answered is whether it is the
state’s or the bank’s future that is important.
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Journal of Economic and Social Studies
Journal of Economic and Social Studies
Impact of Military Expenditure and
Economic Growth on External Debt: New
Evidence from a Panel of SAARC Countries
Khalid Zaman,
Department of Management Sciences,
COMSATS Institute of Information Technology / Abbottabad, Pakistan
iqtidar@ciit.net.pk
Iqtidar Ali Shah
Department of Management Sciences,
COMSATS Institute of Information Technology / Abbottabad, Pakistan
Muhammad Mushtaq Khan
Department of Management Sciences,
COMSATS Institute of Information Technology / Abbottabad, Pakistan
Mehboob Ahmad
Department of Management Sciences, FUIEMS, Foundation University,
New Lalazar, Rawalpindi Cantt, Pakistan.
AbstrAct
This paper examines the impact of military expenditure and economic
growth on external debt for a panel of five selected SAARC countries
including Bangladesh, India, Nepal, Pakistan and Srilanka, over
the period of 1988-2008. Using Pedroni’s (2004) test for panel
cointegration, it was found that there is a long-run relationship between
external debt, economic growth and military expenditure. The study finds
that external debt is elastic with respect to military expenditure in the
long run and inelastic in the short run. In the long run, 1% increase in
military expenditure increase external debt between 1.18 % and 1.24%,
while 1% increases in economic growth reduce external debt between
0.64% and 0.79%, by employed DOLS and FMOLS estimator
respectively. In the short run, 1% increase in military expenditure increases
external debt by 0.15%, while 1% increase in economic growth reduces
external debt by 0.47 %.
KEYWOrDs
External Debt, Economic Growth,
Military Expenditure, Panel
Cointegration, SAARC Countries.
ArtIcLE HIstOrY
Submitted: 2 April 2012
Resubmitted: 28. February2013
Accepted: 25. March 2013
JEL codes: O1, O4, O5 and H5
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Bilal Sisman / Sinan Yoruk / Ali Eleren
Introduction and Literature Review
The relationship between military expenditure and economic growth has been examined extensively in the literature. However, the effect of military expenditure on
external debt has received less attention. In countries with large military expenditure, the role of military spending in contributing to external debt is important because of the potential adverse economic effects of external debt as excessive foreign
debt accumulation can cause deterioration in the terms of trade, an overvaluation of
the domestic currency and slower economic growth.
Benoit (1973, 1978) in his pioneered study examined the relationship between military expenditure and economic growth in 44 less developed countries and found
that there is a positive correlation between military expenditure and economic
growth. Dakurah et al. (2000) studied 62 LDCs and found 13 countries showing
unidirectional causality from military expenditure to growth; 10 countries from
economic growth to military expenditure; 7 countries suggest bidirectional causality
and the rest 18 countries displaying no meaningful relationship. Yildirim, Sezgin &
Ocal (2005) examined the effect of military expenditure on economic growth for
12 Middle Eastern countries and Turkey using cross-sectional and dynamic panel
data estimation techniques from 1989 to 1999 and found that military expenditure
enhances economic growth in the Middle Eastern countries and Turkey as a whole.
So for as the South Asian Regional Cooperation Council (SAARC) countries are
concerned, a study was carried out by Hassan et al. (2003) to show the relationship between military expenditure and economic growth. They examined the impact of the military expenditure on economic growth and FDI covering five out of
seven SAARC nations using panel data over the 1980-1999 periods. Interestingly
the result suggests positive relationship between military expenditure and economic
growth, and thus supporting the view that military expenditure can bring positive impact on growth. Other studies which have also found a positive relationship
between military expenditure and economic growth include Mueller and Atesoglu
(1993); MacNair et al. (1995), Chlestos and Kollias (1995), Sezgin (1999b, 2000)
and Yildirim and Sezgin (2002).
Equally military spending may have a negative effect on economic growth through
reducing the availability of public funds for spending in the supposedly more productive civilian sector and creating inflationary pressures. Deger (1986) found negative relationship between military expenditure and growth in the less developed
132
Journal of Economic and Social Studies
Social Anxiety and Usage of Online Technological Communication Tools among Adolescents
countries citing that defense expenditure takes resources away from productive
investments and fails to mobilize and create additional savings. Other empirical
studies that found significant adverse effect of defense spending on the economy
include studies by Deger and Smith (1983), Deger and Sen (1983) and Faini et
al. (1984), Antonakis (1997), Heo (1998), Linden (1992), Dunne and Mohammed (1995), Sezgin (1999a) and Dunne, Nikolaidou & Smith (2002). Aizenman
and Glick (2006) studied the long-run impact of military expenditure on growth
and suggested that military expenditure induced by external threats should increase
growth, while military expenditure induced by rent seeking and corruption should
reduce growth. Abu- Bader et al. (2003) found that military expenditure had a
negative effect on economic growth in Egypt, Israel and Syria over the period 1972
to 2001 within a Granger causality framework. DeRouen (2000) reaches the same
findings in a single country study of Israel.
Smyth and Narayan (2009) have examined the relationship between external debt
and military expenditure nexus in the six Middle Eastern countries and found that
external debt is elastic with respect to military expenditure in the long-run while
inelastic in the short-run.
In this paper an analysis has been carried out to find a panel cointegration between
external debt and military expenditure along with economic growth in SAARC
countries, using secondary data from 1988 to 2008. This paper does not include
all dimensions and factors of the external debt and military expenditure problem
from an econometric perspective, the small panel (T=19, N=5) is only sufficient to
accommodate two explanatory variables without a substantial loss in power.
The objectives of this paper are:
1. To empirically investigate the relationship between external debt, economic
growth and military expenditure using a panel unit root and panel cointegration framework in selected SAARC countries.
2. To empirically investigate, whether there is a long-run or short-term relationship between the external debt, economic growth, and military expenditure.
This paper is organized as: after introduction and literature review above, a brief
overview of external debt, economic growth and military expenditure of the selected
SAARC countries is given followed by data source and methodological framework.
Next results and discussion has been carried out and conclusion of the study is given
at the end.
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Overview of External Debt, Economic Growth, and Military
Expenditure in the Selected SAARC Countries
External Debt: Debt service liability as percentage of export of goods and services
has decreased considerably in all the Member States of SAARC countries. In Bangladesh and India debt service liability has been reduced from 25.8 percent and 31.9
percent in 1990 to 3.7 percent and 7.7 percent in 2006 respectively. Pakistan and
Sri Lanka have witnessed decline from 22.9 percent and 13.8 percent in 1990 to
8.6 percent and 12.7 percent in 2006 respectively. Figure 1 below shows the trend.
Figure 1. External Debt in SAARC Region (1988-2008)
EDBAN
EDIND
320
150000
280
140000
130000
240
120000
200
110000
160
100000
120
90000
80
80000
40
70000
0
60000
88
90
92
94
96
98
00
02
04
06
08
88
90
92
94
EDNEP
96
98
00
02
04
06
08
02
04
06
08
EDPAK
4000
40000
3500
36000
32000
3000
28000
2500
24000
2000
20000
1500
16000
1000
12000
88
90
92
94
96
98
00
02
04
06
08
02
04
06
08
88
90
92
94
96
98
00
EDSRI
16000
14000
12000
10000
8000
6000
4000
2000
88
90
92
94
96
98
00
Sources: Asian Development Bank, 2008; World Banks, 2008.
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Economic Growth: SAARC member states have maintained GDP growth rate in
2006 at 8.9%. GDP growth in South Asia is significantly higher compared with
other developing regions. However, trickle down effects of growth would take time
to effect the population of the region. Real GDP growth rate has increased in almost
all the countries. Country-wise analysis shows that Bangladesh’s real GDP growth
at 6.2 percent in 1990 increased to 6.6 percent in 2006. Bhutan during the period
1990-2006 witnessed sharp increase from 5.6 percent to 7.8 percent. India maintained its growth momentum from 5.6 percent in 1990 to 9.6 percent in 2006.
Nepal economy has witnessed low and high GDP growth from 2.3 percent in 2005
to 2.8 percent in 2006. Pakistan was maintaining its growth but has witnessed a low
growth rate of 5.8 percent in 2006. Sri Lankan economy has showed an increase 7.7
percent in 2006 (see, SHRDC, 2008). Figure 2 below shows the trend.
Figure 2. Economic Growth of SAARC Countries (1988-2008)
GDPBAN
GDPIND
24000
1000000
22000
900000
800000
20000
700000
18000
600000
16000
500000
14000
400000
12000
300000
10000
200000
88
90
92
94
96
98
00
02
04
06
08
88
90
92
94
GDPNEP
96
98
00
02
04
06
08
02
04
06
08
GDPPAK
11000
200000
10000
160000
9000
8000
120000
7000
6000
80000
5000
4000
40000
3000
0
2000
88
90
92
94
96
98
00
02
04
06
08
02
04
06
08
88
90
92
94
96
98
00
GDPSRI
40000
35000
30000
25000
20000
15000
10000
5000
88
90
92
94
96
98
00
Source: Human Development Report 2007-08; UNDP, 2008.
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Military Expenditure: An increasing trend has been noticed in military expenditures over the time period. Pakistan and India are in the competitive zone, therefore,
both have increased their military expenditure. In terms of military expenditure as
percentage of GDP, Sri Lanka spent 4.1%, Pakistan 3.5%, India and Nepal 2.5%,
Bangladesh 1.5%. Figure 3 shows individual country assessment of military expenditures over a time period.
Figure 3. Military Expenditure in SAARC Region (1988-2008)
MEBAN
MEIND
70000
26000
24000
60000
22000
20000
50000
18000
40000
16000
14000
30000
12000
20000
10000
88
90
92
94
96
98
00
02
04
06
08
88
90
92
94
MENEP
96
98
00
02
04
06
08
02
04
06
08
MEPAK
160
4800
140
4400
120
4000
100
80
3600
60
3200
40
20
2800
88
90
92
94
96
98
00
02
04
06
08
02
04
06
08
88
90
92
94
96
98
00
MESRI
1000
900
800
700
600
500
400
300
200
100
88
90
92
94
96
98
00
Source: UNDP, 2008 and Human Development Report 2007-08.
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Data Source and Methodological Framework
The data set for five SAARC countries is collected from International Financial Statistics (IFS, 2008), World Bank (2008), SHRDC report, (SHRDC, 2008); Stockholm International Peace Research Institute (SIPRI, 2008) and Economic Survey
of Pakistan (2008-09). The dependent and independent variables used in this study
are listed in Table 1. External Debt is used as a dependent variable for the study. Independent variables are Economic Growth (GDP) and Military Expenditures (ME).
Table 1. Variables used for the External debt-Military expenditure Model
Variables
Symbol
Dependent Variable:
External Debt
Independent Variable:
Economic Growth
Military Expenditure
Expected Sign
ED
GDP
ME
Negative
Positive
Panel Econometric Model: There is lack of panel cointegration to explain the relationship between external debt and military expenditure in the SAARC context.
This paper uses panel cointegration analysis to test this relationship in Bangladesh,
India, Nepal, Pakistan and Sri Lanka during 1988-2008. The model used to test the
relationship between external debt and military expenditure is as follows:
ln(ED) = f ln(GDP, ME)
The general representation of the equation mentioned above is as follows:
Log (Yt ) = C + β 1t log( X 1t ) + β 2t log( X 2t ) + ε t
(1)
Where:
Yt
C
βt
Xt
T
i
εt
β1
β2
Volume 3
=
=
=
=
=
=
=
=
=
dependent variable;
intercept;
slope of the independent variables;
independent variables (GDP and ME)
1, 2…21 periods;
1, 2…5 countries;
error term;
coefficient of economic growth;
coefficient of military expenditure;
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In the above model, the sign of β1 is expected to be negative as it is argued that
SAARC countries might have a capacity to repay external debt. Similarly, β 2 is
hypothesized to be positive as it is argued that large military expenditure can result
in large external debt.
This paper uses a panel cointegration method to examine the long-run relationship
between external debt and military expenditure in the selected SAARC countries.
Thus, three different panel unit roots tests [(i.e. Levin-Lin- Chu (LLC) test, ImPesaran-Shin (IPS) test and Maddala-Wu (MW) test)] have been used in this study.
Panel Unit root tests: Panel unit root tests could be considered as an extension of
the univariate unit root test. The LLC test is based on the pooled panel data as follows (Levin & Lin, 1992);
Dy it = ρy it −1 + α 0 + σ t + σ i + θ t + ε it
(2)
Where ρ , α 0 , σ are coefficients, α i is individual specific effect, θ t is time specific
effect.
According to Levin & Lin (1992), the LLC test could be conducted by the following steps. In step1, subtract the cross-section average from data;
N
y = 1 / N ∑ y it
(3)
i =1
In step 2, an ADF test is applied to each individual series and normalizes the disturbance. The ADF model could be expressed as;
Pi
Dy it = ρ i y it −1 + ∑ δ ij Dy i ,t − j + α i + ε it
j =1
(4)
Maddala and Wu (1999) argued that this is equivalent to perform two auxiliary
regressions of Dy it and y i ,t −1 on the remaining variable n equation (3). Let the
residuals from these two regression be eˆi ,t and Vˆi ,t −1 respectively. The, regress eˆi ,t
on Vˆi ,t −1 .
eˆi ,t = ρ iVˆi ,t −1 + ε it
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Levin & Lin (1992) suggest the following normalization to control the Heteroskedasticity in error.
σˆ 2 ei =
1
(eˆi ,t − ρˆ i − Vˆi ,t −1 ) 2
∑
T − Pi − 1 t = p + 2
eˆi ,t
e~ =
σˆ ei
v~i ,t −1
~
vi ,t −1 =
σˆ ei
In the next step, the LLC test statistic could be obtained from the following regression;
~
ei ,t = ρv~i ,t −1 + ε~i ,t
~ = 0 is given by
The t-statistic for testing o
tδ =
δˆ
STD (δˆ )
Where
N
δˆ =
T
∑ ∑ vˆ
i =1 t = 2 + p
eˆ
t −1 it
N
∑ ∑ vˆ
i =1 t = 2 + p
2
it −1
Next, the paper also employs the IPS test which is based on the mean value of
individual ADF statistics or t-bar (Im, Pesaran and Shin, 2003). The IPS test provides separate estimation for each i section, allowing different specifications of the
parametric values, the residual variance and the lag lengths. Their model is given by:
n
DYi ,t = α i + ρ i Yi ,t −1 + ∑ φ k DYi ,t − k + δ i t + u it
(6)
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The null hypothesis and the alternative hypothesis are formulated as:
H 0 : ρi = 0
H A : ρi < 0
for at least one i
Thus, the null hypothesis of this test is that all series are non-stationary process
under the alternative that fraction of the series in the panel are assumed to be stationary. IPS also suggested a group mean Lagrange multiplier test for testing panel
unit roots.
Maddala & Wu (1999) attempted to improve to the same degree the drawbacks of all
previous tests by proposing a model that could also be estimates with unbalanced panels. Basically, Maddala and Wu are in line with the assumptions that a heterogeneous
alternative is preferable, but they disagree with the use of the average ADF statistics by
arguing that it is not the most effective way of evaluating stationary.
Panel cointegration tests: Finally, this paper employs Pedroni’s (1999, 2004) panel-co integration method in order to examine the long-run relationship between
external debt and military expenditure. If the independent and dependent variables
are co-integrated or have a long-run relationship, the residual eit will be integrated
of order zero, denoted I(0). Pedroni used two types of panel cointegration tests. The
first is the “panel statistic” that is equivalent to a unit root statistic against the homogenous alternative; the second is the “group mean statistic” that is analogous to
the panel unit root test against the heterogeneous alternative. Pedroni (2004) argued
that the “panel statistic” can be constructed by taking the ratio of the sum of the
numerators and the sum of the denominators of the analogous conventional time
series statistics. The “group mean statistic” can be constructed by first computing
the ratio corresponding to the conventional time series statistics, and then computing the standardized sum of the entire ratio over the N dimension of the panel. This
paper uses two panel co-integration tests as suggested by Pedroni (1999, 2004),
namely the “panel ADF statistic” and “group mean ADF statistic”. The two versions
of the ADF statistics could be defined as:
Panel
(7)
Group Mean
(8)
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Where eˆi ,t represents the residuals from the ADF estimation, ~
s NT is the contemporaneous panel variance estimator, and ŝ i is the standard contemporaneous variance
of the residuals from the ADF regression. The asymptotic distribution of panel and
group mean statistics can be expressed in:
K N ,T − µ N
⇒ N (0,1)
v
Where K N ,T is the appropriately standardized form for each of statistics, µ m ADF
regression is the mean term and v is the variance adjustment term. Pedroni provides
Monte Carlo estimates of µ and v (Pedroni, 1999).
These statistics are based on the estimated residuals from the following regression:
Where ξ it = η i ξ i ( t −1) + µ it are the estimated residuals from the panel regression.
The null hypothesis tested is whether η i unity is. The finite sample distribution for
the test statistics have been tabulated in Pedroni (2004) using Monte Carlo simulations, if the test statistic exceeds the critical values in Pedroni (2004), the null
hypothesis of no cointegration is rejected, implying the variables are cointegrated.
Panel Long-run relationship: If long-run relationship among the variables were
found then the long-run and short-run coefficients of economic growth and military expenditure on external debt will be estimated. To estimate the long-run effect
of economic growth and military expenditure, the panel FMOLS, proposed by Pedroni (2000) and DOLS developed by Stock and Watson (1993) have been used.
Results and Discussion
To test whether each of ED, GDP and ME contain a panel unit root, the panel
unit root tests proposed by Levin, Lin and Chu Test (2002), Im, Pesaran & Shin
(2003) and Maddala & Wu (1999) have been applied. The results are reported in
Table 2 where they are divided into three panels. Panel A consists of results from the
Levin, Lin and Chu (2002); panel B consists of the results from the Im, Pesaran &
Shin (2003) test and panel C consists of results from the Maddala and Wu (1999)
test. For each of these tests, *, ** and *** indicates the statistical significance at 1
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percent; 5 percent and 10 percent respectively. The results from all three tests, with
or without linear trends; suggest that ED, GDP and ME contain a panel unit root
as mentioned in Table 2.
Table 2. Panel Unit Root Test
Levels
First Differences
Individual Effects
Individual Effects
Individual Effects
and Linear Trends
Panel A: Levin, Lin, Chu Test (2002)
Variables (in logs)
ln(ED)
2.807
2.118
-1.400***
ln(GDP)
2.448
1.725
-1.621**
ln(ME)
-0.432
0.022
-4.294*
Panel B: Im, Pesaran, Shin Test (2003)
Variables (in logs)
ln(ED)
3.664
2.712
-1.815**
ln(GDP)
-0.846
0.356
-3.586*
ln(ME)
-0.071
0.352
-3.256*
Panel C: Maddala and Wu (1999)
Variables (in logs)
ln(ED)
0.015
1.985
20.712**
ln(GDP)
12.285
8.253
38.361*
ln(ME)
10.234
6.213
29.665*
Individual Effects
and Linear Trends
-1.580***
-1.812**
-3.827*
-2.495*
-3.201*
-2.665*
21.321**
32.170*
27.424*
* indicates significance at the 0.01 level.
** Indicates significance at the 0.05 level.
To examine whether there is a long run relationship between the three variables for
the panel of five selected SAARC countries, Pedroni’s (2004) panel Phillips-Perron
(1988) type rho-statistic and group Phillips-Perron (1988) type rho-statistic have
been employed. The panel rho-statistic and group rho-statistic are 2.2 and 2.7, respectively and the associated one-sided p-value is less than 0.01. Thus, both test
statistics suggest that there is panel cointegration between ED, GDP and ME at the
1% level of significance.
After finding that a long-run relationship exists between ED, GDP and ME, the
long-run effect of GDP and ME on ED have been estimated using the panel FMOLS
estimator suggested by Pedroni (2000) and panel DOLS estimator proposed by Kao
& Chiang (2000). The results are reported in Table 3.
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Table 3. Panel Long-run Elasticity
Panel Methods
ln(ME)
1.182
(8.337)*
1.243
(3.210)*
DOLS
FMOLS
ln(GDP)
-0.638
(-11.783)*
-0.796
(-3.974)*
Note: Figures in parenthesis are t-statistics. * denote statistical significance at the 1 % level.
For the DOLS estimator, 1% increase in economic growth decreases external debt
by 0.638 %, while a 1% increase in military expenditure increases external debt
by 1.18%. Both results are statistically significant at the 1% level. On the other
hand, for the FMOLS estimator the coefficient on GDP is 0.796, suggesting that
a 1% increase in growth (GDP) decreases external debt by 0.80%. The coefficient
of military expenditure (ME) is 1.243, which implies that a 1% increase in military
expenditure increases external debt by almost 1.24%.
The results for the short-run impact of economic growth and military expenditure on
external debt for the panel of five selected SAARC countries are reported in Table 4.
Table 4. Panel Short-run Elasticities
Variables
Constant
Coefficient
9.452
t-statistics
19.528*
D ln(ME)
0.149
6.102*
D ln(GDP)
-0.471
-3.761*
ECTt −1
-0.092
-2.183**
Goodness of fit:
R2
= 0.84;
R 2 = 0.81
Note: *, ** and *** denotes statistical significance at 1, 5 and 10 % level.
Table 4 indicates that economic growth has a negative impact on external debt while
military expenditure has a statistically significant positive impact on external debt in
the short-run. The coefficient of the military expenditure is 0.149, suggesting that
a 1% increase in military expenditure increases external debt by 0.15% respectively.
On the other hand, GDP decreases external debt by almost 0.47%. The one period
lagged error correction term, which measures the speed of adjustment to equilibri-
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Bilal Sisman / Sinan Yoruk / Ali Eleren
um following a shock to the system, has a negative sign and is statistically significant
at the 5% level. Its sign and significance level suggests that external debt is able to
revert to its equilibrium following a shock to growth and military expenditure. But,
the magnitude of the coefficient, because it is very small, suggests that the speed of
adjustment to equilibrium is very slow.
Overall military expenditure has a positive and significant impact on SAARC external debt in the short and long-run. The relationship is elastic in the long-run, but
inelastic in the short-run.
Conclusion
In this paper a short term and long term impact of military expenditure and economic growth the external debt for five selected SAARC countries; namely, Bangladesh, India, Nepal, Pakistan and Sri Lanka has been examined using data for the
period 1988-2008 by applying panel unit root and panel cointegration framework.
It was found that the external debt, economic growth and military expenditure were
cointegrated for the panel of five SAARC countries. In the long-run, both estimators (DOLS and FMOLS) suggest that economics growth has a statistically significant negative effect on external debt, while military expenditure has a statistically
significant positive effect on external debt. Using DOLS estimator, it was found that
1% increase in economic growth decreases external debt by 0.638 %, while a 1%
increase in military expenditure increases external debt by 1.18%. Both results are
statistically significant at the 1% level. On the other hand, using FMOLS estimator,
it was found that 1% increase in growth (GDP) decreases external debt by 0.796%.
While 1% increase in military expenditure increases external debt by almost 1.24%.
In the short-run it was found that economic growth and military expenditures have
a statistically significant negative and positive effect on external debt. In short run
it was found that 1% increase in military expenditure increases external debt by
0.15% while 1% increases growth (GDP) decreases external debt by almost 0.47%.
One important limitation on our finding is that, from an econometric perspective,
the small panel (T=21, N=5) is only sufficient to accommodate two explanatory variables without a substantial loss in power. Future studies for the South Asia as well as
other regions in the world could include more potential determinants of external debt
within a panel cointegration framework subject to an increase in data availability.
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146
Journal of Economic and Social Studies
Journal of Economic and Social Studies
Government Expenditure on Nomadic
Education in Nigeria: Implications for
Achieving the Millennium Development Goals
AKIGHIR David Terfa
Department of Economics, Benue State University,
Makurdi, Nigeria.
akighirdavidterfa@ yahoo.com
OKPE. I
Department of Economics, Benue State University,
Makurdi, Nigeria.
AbstrAct
The paper examines government expenditure on nomadic education in
Nigeria and the implications for achieving the MDGs. Secondary data
were used and the data were analyzed with the aid of descriptive statistics.
The study revealed that government expenditure on nomadic education
in Nigeria over time has been on the increase which has necessitated the
increase in the number of nomadic schools and teachers in the country.
The study further found out that there is a wide gap between male and
female enrolments in nomadic schools in Nigeria; factors such as early
marriages and teenage pregnancies, cultural and religious biases as well
as economic issues were believed to be responsible for the gap. Also, it
was discovered that the total increase in nomads’ enrolments in nomadic
schools in the country is not proportionate with the increase in government
expenditure on nomadic education. The study attributed this low school
attendance by the nomads to the problems of under-funding, dearth of
teachers, constant migration of nomads, the involvement of the children
of nomads in the productive system, corruption, among others. The study
concluded that the present form of implementation of the nomadic
education would make it difficult for it to be a panacea for achieving the
MDGs in the country. Recommendations were made on how to improve
on the nomadic education system in the country.
KEYWOrDs
Education, Government
Expenditure, Millennium
Development Goals, Nomads,
Nigeria.
ArtIcLE HIstOrY
Submitted: 20 October 2011
Resubmitted: 10 February 2012
Resubmitted: 12 March 2012
Resubmitted: 24 April 2012
Accepted: 21 May 2012
JEL codes: H5, 015
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AKIGHIR David Terfa / OKPE. I
Introduction
Education is the spring board for social and economic change. It plays a major role
in the socio-economic development of a nation. Education occupies an important
place in most plans for economic and social development. It is important in the
human development as a supplier of the trained man power as well as a requisite
for the accomplishment of other development goals (Adebiye,2004). These roles
played by the educational sector stimulate economic growth and development of a
country. This explains why countries of the world expend so much on this vital sector in order to enhance the level of literacy of their citizenry. Inequality of access to
education and educational marginalization have deleterious effects on the national
development of a country. In Nigeria, however, available records have shown that
expenditure on education is below the internationally acceptable standard. According to the UNDP Human Development Report (2008), Nigeria spends almost an
insignificant proportion of its financial resources on education, the expenditure on
education in Nigeria as a proportion of GDP averaged 5.84 percent, which falls
below the UNESCO’s benchmark of 26 percent of the budgets of developing countries. This accounts for the sluggish educational growth rate of 0.59 in the country.
The poor funding of education in Nigeria has over time deprived a lot of Nigerians
access to education. According to Nafisatu and Abdu (2010), out of the estimated
population of 9.4 million nomads in Nigeria,3.3 million are children of school age,
but the participation of the nomads in the existing formal and non-formal education
programs is abysmally low, with a literacy rate ranging between 0.2% and 2.9%. The
Nigerian nomadic pastoralists are made up of the Fulani (5.3m), Shuwa (1.01m),
Koyam (32,000), Badai (20,000), Dark Buzzu (15,000) and the Buduma (10,000).
The Fulani are found in 31 out of the 36 states of Nigeria, while others reside mainly
on the Borno plains and shores of Lake Chad. The migrant fishing groups account
for about 2.8 million, comprising numerous tribes. They are found in the Atlantic
coastline, the riverside areas and river basins of the country. These groups of people
amongst others do not have access to functional education in the country over time.
In the quest to remove the chronic illiteracy among this mobile population of Nigeria,
the federal government of Nigeria introduced Nomadic Education Program (NEP)
in 1986. NEP was designed to provide the nomads with the relevant and fundamental basic education that would improve their survival skills. This was expected to
provide them with the knowledge and the skills that would enable them raise their
productivity and income; as well as empower them to participate effectively in the
socio-economic and political affairs of the country. In a bid to achieving these goals,
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Government Expenditure on Nomadic Education in Nigeria:
Implications for Achieving the Millennium Development Goals
the National Commission for Nomadic Education (NCNE) was established in 1989
with the mandate to: a) formulate policies and guidelines on all matters relating to
nomadic education in Nigeria; b) provide funds for research and personnel development for the improvement of nomadic education; and develop programs on nomadic
education and provide equipment, instructional materials, construction of classrooms
and other facilities for nomadic education (Nafisatu and Bashir,2010).
Over the years, the government has been spending money on the nomadic education
program so as to provide an unfettered access to quality basic education for the nomads.
The aim is to equip them with the skills and competencies that will enhance their wellbeing and participation in the nation-building process. The Nigerian government considers nomadic education as a veritable measure for the development of the universal
basic education with a view to achieving the Education for All (EFA) goals and the Millennium Development Goals ( National Commission for Nomadic Education,2002 ).
An assessment of the results of the program against its objectives thus far is imperative. Government expenditure on education in Nigeria has been widely studied.
However, attention has not been paid specifically on assessing the impact of government expenditure on nomadic education as a measure aimed at achieving the
MDGs of universal basic education in Nigeria. At best, available literature presents
partial analyses of this issue. Thus, to be area specific, this paper seeks to evaluate the
impact of government expenditure on nomadic education in Nigeria with a view
to ascertaining whether or not, it will be the key for achieving the universal basic
education of MDGs in Nigeria. Following the introduction, the paper is structured
as follows: Section two deals with the review of government expenditure on education in Nigeria and the outline of the MDGs. Section three considers the evolution
and strategies of nomadic in Nigeria; while section four presents the problems of
nomadic education in Nigeria. Section five is the method of the study; section six
presents and analyses the data. Section seven uncovers the findings of the study; and
section eight contains the recommendations and conclusion of the paper.
Government Expenditure on Education in Nigeria
Government funding of education in Nigeria comes from different sources. The major one for all levels of government is the public revenue from taxation and oil (Saavedrea, 2003). Education funds are reported to be distributed among the primary,
secondary and tertiary education levels in the proportion of 30%, 30% and 40%,
respectively ( Balami ,2003). According to Hinclifte (2003) (as cited in Adewale,
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AKIGHIR David Terfa / OKPE. I
Ajaji and Enikanoselu, 2005), Government expenditure on education includes direct government expenditure ( for teachers’ salaries and instructional materials) as
well as indirect expenditure in the form of subsidies to households such as tax reductions, scholarships, loans and grants. It also includes payment from Education
Tax Fund (ETF), mainly for capital expenditure. The main sources of funds that the
Nigerian government has are federal taxes and duties on petroleum, profits, imports
and exports, which form the revenue of the Federation Account, and the centrally
collected Value Added Tax (VAT) introduced in 1996. The federal government allocations to the educational sector from 1995 to 2011 is presented in Table 1.
Table1. Federal Government Allocation to Education between1995-2011
Years
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2008
2009
2010
2011
Capital (N)
3,017,900,000
3,215,800,000
3,807,900,000
9,739,600,000
8,291,800,000
35,000,000,000
35,183,789,000
22,100,000,000
15,723,260,401
21,550,000,000
50,540,287,898
40,005,096,425
53,667,933,553
304,670,538,799
Recurrent (N)
9,798,600,000
12,135,900,000
13,033,200,000
13,828,300,000
19,421,700,000
29,514,932,711
37,676,055,443
59,994,441,815
63,228,742,652
72,217,886,839
145,219,839,130
196,218,973,905
192,594,871,801
518,251,289,348
Total ( N)
12,816,400,000
15,351,700,000
16,841,200,000
23,666,100,000
27,713,500,000
64,514,932,711
72,950,836,443
82,094,441,815
78,952,003,053
93,767,886,839
195,760,127,029
236,224,070,330
246,262,805,354
356,495,828,145
Source: Budget Office of the Federation, Federal Ministry of Finance, 2011.
The table above shows that government expenditure on education consists of recurrent and capital expenditure. In nominal terms, it can be seen from the table that the
budgetary allocations to the education sector are on the increase but the growth rate
is not impressive. For instance, in 2008 the allocation to the capital expenditure on
education was 6.4% of the total budget and it was 3.9% in 2009, and 3.9% in 2010
representing 0.0% increase between 2009 and 2010; while the educational allocation to the recurrent expenditure was 15.1% in 2008,15.0% in 2009, and 14.4%
of the total budget in 2010. This represents a decline of -0.6% in the allocations between 2009 and 2010. These allocations have grossly failed to meet the UNESCO’s
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Government Expenditure on Nomadic Education in Nigeria:
Implications for Achieving the Millennium Development Goals
conventional benchmark of 26% for the budgets of developing countries. Given
the importance of this sector to human and economic development, it would be
important to push the education allocations up to at least half of the international
benchmark requirement so as to attain the universal basic education as described in
the goal two of the Millennium Development Goals (MDGs).
Outline of the Millennium Development Goals(MDGs)
At the Millennium Summit held in September 2000, in New York, United States
of America, members of the United Nations (UN) made the following declaration:
We will spare no effort to free our fellow men, women and children from the abject
and dehumanizing conditions of extreme poverty, to which more than a billion of
them are currently subjected to”. This led to the acceptance and the formulation of
the Millennium Development Goals which are expected to be fully achievable in the
year 2015. These goals are:
Goal 1: Eradication of extreme poverty and hunger by half in 2015;
Goal 2: Achievement of the universal primary education by 2015;
Goal 3: Promotion of gender equality and empowerment of women by 2015;
Goal 4: Reduction of child mortality rate especially the under 5 by two-third in
2015,
Goal 5: Improvement of the maternal health;
Goal 6: Combat HIV/AIDS, malaria and other diseases;
Goal 7: Ensure environmental sustainability; and
Goal 8: Development of a global partnership for development (National Planning
Commission,2004).
The quest to achieve the universal basic education as described by goal two of the
MDGs, the Nigerian government gave a rekindling interest to the Nomadic Education Program as one of the measures of achieving the MDGs in the country by 2015.
Evolution and Strategies of Nomadic Education in Nigeria.
The Nomadic Education program (NEP) started officially in November 1986, after
The Yola National Workshop on Nomadic Education. The workshop resolved that :
“… The nomads needed a fair deal through the provision of education and other social amenities to reciprocate their contribution to the nation-building ….” (Ismail,
2000). Consequently, the Federal Government promulgated the Decree No. 41 of
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December 1989 (now CAP 243 LFN), which established the National commission
for Nomadic Education (NCNE) with the responsibility to implement the National
Nomadic Education Program. The NCNE was mandated to formulate policy and
issue guidelines in all matters relating to nomadic education in Nigeria.
These mandates include: providing funds for research and personnel development
of nomadic education in Nigeria; the development of programs on nomadic education; the provision of equipment and other instructional materials, construction of
classrooms and other facilities relating to nomadic education. Secondly, to establish,
manage and maintain primary schools in the settlements and grazing reserves carved
out for nomadic people. Thirdly, to determine standard of skills to be attained in
the nomadic schools. Also, to arrange for effective monitoring and evaluation of
activities of agencies concerned with nomadic education. It was mandated to liaise
and cooperate with other relevant ministries and agencies. Furthermore, NCNE
was to receive block grants and funds from the Federal Government or any agency
authorized and allocate same to the nomadic schools based on any format approved
by the Federal Executive Council; act as agency for channeling all external aid to
the nomadic schools in Nigeria; ensure effective inspection of nomadic education
activities in Nigeria through the sections in the Federal and State Ministries of Education performing duties relating to nomadic education. Finally, it was mandated to
collate, analyze and publish information relating to nomadic education in Nigeria;
and undertake any other action desirable for the promotion of nomadic education
in Nigeria (National Commission for Nomadic Education, 1989).
The commission has four departments, namely, Program Development and Extension; Monitoring, Evaluation and Statistics; Administration and Supplies and Finance and Accounts. It has six Zonal offices located in Bauchi for the North-East,
Kano for the North-West, Minna for the North-Central, Ibadan for South-West,
Enugu of the South-East and Benin for the South-South. Furthermore, it has four
university-based nomadic education centers located in the University of Port Harcourt for migrant fishermen education, University of Maiduguri for teacher-training, University of Sokoto for curriculum development, and University of Jos for research and evaluation to cater for pastoral nomads (National Commission Nomadic
Education, 2000). The Organogram of the Commission is shown in Appendix I.
Nomadic Education Program Strategies
In pursuance of its functions, the National Commission for Nomadic Education has
between 1990 and 2006 evolved four distinct programs for the effective implemen-
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Government Expenditure on Nomadic Education in Nigeria:
Implications for Achieving the Millennium Development Goals
tation of the nomadic education program. The programs briefly highlighted are:
Provision of primary education – this program is implemented in collaboration with
States and Local governments, as well as local communities, Non-Governmental
Organizations (NGOs) and Collaborative Body Organizations (CBOs). So far, all
the 36 States and Abuja are participating in the program. However, their level of
commitments to the program varies.
Provision of academic support services through the University based centers. The centre
at Jos is responsible for research and evaluation, the University of Maiduguri for
teachers training and outreach programs, Usmanu Dan Fodiyo University for the
development of curricula and textual materials and the University of Port Harcourt
for research, curricula development and teachers training for the education of migrant fishing communities. The Commission has been working closely with the
Centers for the development of curricula materials and pupils’ texts, conduct of
research projects and the organization of teachers training workshops;
Provision of infrastructural facilities – faced with the problem of inadequate infrastructure that has necessitated teaching and learning under trees, the Commission
has adopted the following strategies for addressing the peculiar needs of all the
groups: provision of permanent and semi-permanent structures, provision of mobile collapsible classroom structures, provision of boat schools and dug-out canoes.
Provision of extension services: Actual intervention by the Commission in the provision of educational extension services to the nomads only began in 1996/97. The
major driving force behind the NCNE’s intervention in this aspect of education was
the realization that, the adoption of an integrated approach to education provision
engender nomads participation in support for the program. However, the mandate
of the Commission specifically restricted its operation to the provision of primary
education to the children of the nomads. The dilemma necessitated the convening
of an Experts Meeting on viable strategies for implementing Nomadic Education in
Nigeria in 1995. Having examined the condition of nomadic education in Nigeria,
the meeting came out with recommendations to further strengthen, expand and
sustain the program. Some of the recommendations were that, the provision of education should be for the children as well as the adults, and that tremendous efforts
be made to positively alter the behaviour of nomads towards modern education.
Current Program Implementation
To support effective teaching and learning, the Commission also collaborates with
Nomadic communities, CBOs, NGOs, at all levels, development partners and other
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international support organizations. Over the years, the Commission has embarked
on a number of activities and recorded modest achievements in the following areas,
namely: Broadening access to basic education – providing access to basic education,
the NEP has facilitated 2,354 schools in 36 States and FCT for pastoralist children
(432,411), 451 for fisher folk children (88,288) in 9 states, 260 schools for migrant
farmers in 8 states with 33,164 pupils; The Commission has facilitated the increase
in the number of nomadic schools. The number of Nomadic schools increased from
2,094 in 2005 to 2,294 in 2006 and to 2,526 in 2007. There was progressive teachers recruitment and retention in nomadic schools, there was an increase in the number of nomadic schools teachers from 6,918 in 2005, to 7,989 in 2006 and 8,665
by 2007; there was an increase in Nomadic girl-child education initiative of the
Commission which has increased female enrolment, progression, and transition in
Nomadic schools. The female enrolment has increased from 153,489 in 2006 to
164,769 in 2007 representing 28% increase rate (Nafisatu and Abdu, 2010).
Problems of Nomadic Education in Nigeria
According to Nafisatu and Abdu (2010), the following are the problems militating
against the smooth operation of the NEP in Nigeria: constant migration of the
nomads, the involvement of children in the productive systems, unsuitability of the
formal school curriculum, physical isolation and restriction of the nomads from
social interaction with the larger society, unfavorable land tenure system, underfunding of nomadic education and late release of approved funds, unwillingness of
State and Local Governments to make budgetary allocations for Nomadic Education Program, indiscriminate transfers of the teachers by LGEAs from the Nomadic
primary schools to conventional primary schools without replacements, the dearth
of teachers in terms of quantity and quality, relatively low level of enrolments in
Nomadic schools, general lack of supervision and monitoring of nomadic schools
by the local and state governments, relative exclusion of Nomadic schools from
UBE and other intervention funds accruing to the States, Non-provision of funds
for the Commission’s extension service programs, constant clashes and conflicts between farmers and herders and amongst fisher folks over fishing rights resulting in
displacements. According to Ismail (2000), the under-funding of nomadic education is partly blamed on inaccurate demographic data. Lack of reliable statistics
on the nomads leads to planning based on guessing; there was much confusion
as to the actual number of the nomadic schools, types of school facilities and the
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Implications for Achieving the Millennium Development Goals
number of teachers in various locations. Lack of authentic data in these areas has
made planning for nomadic education very difficult. Schools are stationed inappropriately; few in densely populated areas, and many in sparsely populated areas.
Malinga (2009), observed that, the major hindrances to school attendance are the
daily grazing movements and the lack of labor substitutes. Unlike farmers who use
child labor marginally, the Fulani rely heavily and continuously on the children for
labor. A Fulani man will not send his child to school even if an adult is available to
attend to the animals because the child needs to learn the herding skills. The reliance
on juveniles for shepherding task, explains the poor participation of the pastoralists
in formal education.
From the foregoing, it is apparent that Nafisatu and Abdu, Ismail, and Malinga
have identified various problems of nomadic education in Nigeria. However, in this
study, the problem of underfunding of nomadic education, dearth of teachers in
terms of quantity and quality, corruption, constant migration of the nomads, and
active involvement of the school-going age children of the nomads in the productive system were ranked as the most important problems. Thus, these problems were
critically engaged in the section of data analysis.
Method of the Study
The study used mainly secondary data that were obtained from the National Commission on Nomadic Education (NCNE) and the Federal Ministry of Finance as
well as journals. The data collected were on the number of pupils enrolment, number of nomadic primary schools, number of teachers in nomadic schools and government expenditure on nomadic education in Nigeria from 1990 to 2008 as well as
the corruption perceptions indices in Nigeria. The data were analyzed using tables,
percentages, trend graphs, bar charts and rates.
Data presentation and Analysis
In order to evaluate the impact of government expenditure on nomadic education
in Nigeria, data were collected on the number of schools, teachers and the pupils’
enrolments in nomadic schools from 1990 to 2008 as presented in table 2.
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Table 2. Distribution of the of nomadic schools, Teachers and Pupils enrolment
from 1990 to 2008
Years
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
No of
schools
329
473
626
656
754
860
940
1,103
1,022
1,068
1,494
1,574
1,680
1,820
1,981
2,034
2,354
2,354
2,526
No of
teachers
878
1,489
2,491
2,365
2,822
2,788
2,915
3,265
3,265
3,365
4,748
4,907
5,290
6,306
6,861
6,918
7,989
7,989
8,665
Pupils enrolment
Male
13,763
25,942
33,463
38,335
42,738
56,759
63,638
71,695
69,578
75,601
112,958
118,905
134,930
175,962
211,931
222,061
224,304
224,304
235,064
Female
5,068
10,559
16,689
15,253
19,094
35,751
40,938
47,081
47,366
46,934
80,291
84,939
92,014
127,556
151,622
153,489
164,769
164,769
197,347
Total
18,831
65,019
50,152
53,588
61,832
92,510
104,576
118,776
116,944
122,535
193,243
203,844
226,944
303,518
363,553
375,550
389,073
389,073
432,411
Source: NCNE, 2008
The table reveals that the number of nomadic schools in the country has increased
from 329 in 1990 to 2,526 in 2008 representing a cumulative increase of 87%
in the number of nomadic schools. It further shows that, the number of teachers
employed to handle teaching and learning in the nomadic schools has increased
from 878 in 1990 to 8,665 in 2008 representing 90% increment in the number
of teachers employed during the period. The table also depicts that the number
of pupils’ enrolment in nomadic schools rose from 18,831 in 1990 to 432,411 in
2008, representing a cumulative increase of 96% in the total pupils’ enrolment
over the period. To show clearly these increasing trends, data from table 2 were used
to construct trend graphs as shown in Figures 1 and 2.
The trends show clearly that both the number of nomadic schools and teachers have
increased over time in Nigeria. The main reason for the trend may be the government’s continued grant-in-aid to the nomadic education.
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Government Expenditure on Nomadic Education in Nigeria:
Implications for Achieving the Millennium Development Goals
Figure 1 Trends of the number of Nomadic schools and the number of Teachers
employed over time
The chart in Figure 2 further shows that the number of pupils’ enrolment by gender in nomadic education in Nigeria is on the increase.
Source: Constructed from the data in table 2
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Figure 2. Pupils’ enrolments in Nomadic school by gender
A close examination of the chart reveals that there is a wide gap between male and
female enrolments over the years. In a bid to explain the gender gap in nomadic
education in Nigeria, we considered the general causes of low female school enrollments in Nigeria. Some of the factors are early marriages and teenage pregnancies.
These are common experiences in the country, especially in the northern part of
the country where the nomads are dominant. In that part of the country, many
school-age girls often drop out of school because of pregnancies to marry. Secondly,
cultural and religious biases adversely affect girl-child education in Nigeria. Many
Nigerian parents, especially in large families with limited resources, tend to enroll
boys in school instead or before girls. Some parents also keep their daughters out of
schools due to misinterpretation of the tenets of the Islamic religion. This practice
is typical of illiterate Muslims of which the nomads are part of. They generally believe that their female children will face sexual harassment in schools. Nonetheless,
poverty and economic issues are equally contributory factors to this gap. Given the
high level of poverty in Nigeria, many parents, including the nomads, often send
their daughters to sell wares in the market or on the street in order to generate additional incomes for the families. For the Fulani nomads, their school-age daughters
are commonly involved in the hawking of extracted cow milk. These factors are
responsible for the disproportionate male-female enrolments in Nigerian schools,
especially at the primary school level. Thus, it may be said that nomadic education
in the country also faces these general problems.
This male-female gap in school enrolments has a very serious implication for attaining the two educational Millennium Development Goals of Universal Primary
Education(UPE) and the elimination of gender disparities in the primary and secondary schools in 2015. This is so because, the EFA goals and MDGs in Nigeria
aimed at raising the gender parity rate to 80% in primary 1-6 and 50% in JS1-3 by
2015, using nomadic education as a potent tool.
Furthermore, the growth rate of government expenditure on nomadic education
in Nigeria was compared with that of pupils’ enrolments in nomadic schools. The
results are presented in table 3.
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Table 3. Government Expenditure on Nomadic Education and Pupils Enrollment
in Nigeria
% D in EXP
% D in Enrollment
YEAR
EXP(N)
1990
4227139.00
1991
5284802.00
25.02
65019.00
245.28
1992
2958582.00
-44.02
50152.00
-22.87
1993
11225544.00
279.42
53588.00
6.85
1994
6930438.00
-38.26
61832.00
15.38
1995
3153896.00
-54.49
92510.00
49.62
1996
8929536.00
183.13
104576.00
13.04
1997
8876172.00
-0.60
118776.00
13.58
1998
6613698.00
-25.49
116944.00
-1.54
1999
15676272.00
137.03
122535.00
4.78
2000
17382572.00
10.88
193243.00
57.70
2001
81352364.00
368.01
203844.00
5.49
2002
87872301.13
8.01
226944.00
11.33
2003
50000000.00
-43.10
303518.00
33.74
2004
51163143.22
2.33
363553.00
19.78
2005
59890663.01
17.06
375550.00
3.30
2006
70162576.31
17.15
389073.00
3.60
2007
70373063.00
0.30
389073.00
0.00
2008
70584183.00
0.30
432411.00
11.14
ENROLLMENT
18831.00
Source :NCNE, Annual Report,2000.
The table shows that government expenditure on nomadic education has been on
the increase over the years, even though the increase has not been consistent. As it
can be seen from the table, in nominal terms, the expenditure has increased over
time from N4,227,139.00 in 1990 to N70,548,183.00 in 2008. However, in terms
of the growth rate, the trend of the expenditure on nomadic education has not demonstrated any definite trend. For instance, in 1991, the expenditure increased by
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25.05% and declined by 44.02% in 1992, it then rose tremendously by 279.42%
in 1993 and thereafter, decreased by 38.26% in 1994. The declining trend continued and again, appreciated by 183.13% in 1996 and peaked in 2001 by 368.01%
. The Expenditure dropped by 43% in 2003 and afterwards, increased moderately.
Pupils’ enrolments as depicted in the table increased continuously during the review
period except in 1992 and 1998 when a decline was recorded. The enrolments increased from 18,831 pupils in 1990 to 43,244 pupils in 2008 representing a cumulative increase of 56.45% in the number of pupils enrolled.
In order to clearly see whether the increases in the government expenditure are commensurate with the changes in the enrolments, percentage rates for the expenditure
and enrolments over time as contained in the table 3 were used to construct a trend
graph as shown in Figure 3.
Source: Constructed from the data in Table 3.
Figure 3. Trends in Percentage change in Expenditure on Nomadic Education and
School Enrollment in Nomadic school in Nigeria
A close examination of the trends reveals that the percentage increases in school
enrolments by the nomads are not proportionate with the increases in government
expenditure on nomadic education over time. Having discovered this, we tried to
ascertain the possible causes for the disproportionate relationship between government expenditure on nomadic education and nomadic school enrolment in Nigeria.
In doing this, we have engaged some variables critically to see whether they are
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Journal of Economic and Social Studies
Government Expenditure on Nomadic Education in Nigeria:
Implications for Achieving the Millennium Development Goals
responsible for this relationship . First, we considered the problem of underfunding
of nomadic education in the country. We used the ratio of government allocations
to nomadic education as the proportion of the total education allocations in the
country over the years as a proxy for underfunding problem as shown in the table 5.
Table 5. The ratio of Government Allocations to nomadic Education as a proportion of the total allocation to the Education sector in Nigeria.
Year
Government
allocation to
Education (N)
Government
allocation
to Nomadic
Education (N)
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
12,816,400,000
15,351,900,000
16,841,200,000
23,666,100,000
27,713,500,000
64,514,932,711
72,950,836,443
82,094,441,815
78,952,003,053
93,767,886,839
195,760,127,029
236,224,070,330
246,262,805,535
356,495,828,145
3,153,896.00
8,929,536.00
8,876,172.00
6,613,698.00
15,678,272.00
17,382,572.00
81,352,364.00
87,872,301.13
50,000,000.00
51,163,145.22
59,890,663.01
70,162,576.31
70,373,063.00
70,584,183.00
Ratio of Government
allocation to Nomadic
Education as a percentage of
Total allocation to Education
(%)
0.02
0.06
0.05
0.06
0.03
0.03
0.11
0.06
0.06
0.05
0.03
0.03
0.03
0.02
Source: Computed from Tables 1 and 4
The table shows that government expenditure on nomadic education as a percentage of the total allocations to the education sector averaged 0.05%. This proportion
is indeed ,too meager to exert any meaningful impact on nomadic education as per
increased enrolment rates. Secondly, we considered the teacher-student ratio as a
proxy for the problem of inadequacy of teachers in nomadic schools over the years
as shown in the table 6.
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Table 6. Teacher-Student Ratio in nomadic Education Schools in Nigeria
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Number of Teachers
875
1489
2491
2365
2822
2788
2915
3265
3265
3365
4748
4907
5290
6306
6861
6918
7989
7989
8665
Number of Pupils
18,831
65,019
50,152
53,588
61,832
92,510
104,576
118,776
116,944
122,535
193,243
203,844
226,944
303,518
363,553
375,550
389,073
389,073
432,411
Teacher-Student ratio
25
44
20
23
22
33
36
37
36
36
41
42
42
48
53
55
49
49
50
Source: Computed from Table 2
By taking the average of the teacher-student ratio over the years as contained in the
table 6, it was discovered that the ratio is 1:40, implying that there are 40 students
to a teacher. These number of students to a teacher is relatively high since such a
teacher may find it difficult to discharge responsibilities effectively as required. The
net effect may be abstentism by the students due to ineffective control over them
which could degenerate into subsequent drop- out of many nomads of school-age
from school. Furthermore, we examined the menace of corruption, where we used
the Corruption Perceptions Indices with a view to demonstrating how corrupt practices affect public funds in Nigeria, of which nomadic education is no exception.
Transparency International introduced the corruption perceptions Index in 1995 to
measure the level of corruption in countries. The CPI scores relate to the perceptions of degree of corruption as seen by business people and country analysts. The
scores range between 10( highly clean) and 0 (highly corrupt). The CPI scores for
Nigeria from 2003 to 2010 are shown in the table 7.
Table 7. The Corruption Perception Indices for Nigeria
Year
CPI
2003
1.6
2004
1.4
2005
1.6
2006
1.9
2007
2.2
2008
2.2
2009
2.7
2010
2.8
Source: Transparency International, 2011
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Government Expenditure on Nomadic Education in Nigeria:
Implications for Achieving the Millennium Development Goals
From the above table, Nigeria has an average of 2.0. This implies that Nigeria is hypercorrupt. The implication is that, even with the meager allocations to nomadic education, corrupt practices may have weakened the supposedly positive impact. Thirdly,
we looked at the constant migration of the nomads as a factor that may have caused
low school attendance of the nomads. The nomads are typically people that travel
from one place to another due to the nature of their occupations. These constant
migrations have deleterious impact on school attendance of their children. Once they
relocate from a given place, they abandon the schools their children were attending.
Thus, it normally takes the children some time to settle down and start school in the
new settlement. Lastly, we took cognizance of the factor of active involvement of the
children of the nomads in the productive system. The mentality of nomads is such
that they believe in training their young ones who are of school-age in their trades.
This practice has made them to place more preference for their productive system than
the education of their children. Consequent upon these analyzed factors, we submit
that low school attendance of the nomads may be as a result of the synergy of these
factors. Generally, the growth rates in school enrolments of the nomads in Nigeria is
not encouraging because, of the estimated 3.3 million nomads of school going age, the
available statistics show that only 432,411 nomads were enrolled for nomadic education as at 2008. This implies that, about 2,867,589 nomads representing 86.9% of
the school-age nomads were not going to school. The implication is that, with all the
efforts made by the government over time to ensure equal access to education among
the various groups in the country with a view to achieving the MDGs in the country by 2015; only 13.1% of the total nomads of school-age were going to nomadic
school as at 2008. This school enrolment rate of the nomads is too low to make any
meaningful contribution to the overall achievement of the universal basic education
as described in the Millennium Development Goal two.
In Nigeria generally, the Millennium Development Goals are influenced by some of
these socio-economic and political factors: First, there is a disconnection between the
tiers of government in the implementation of the MDGs. However, the constitutional
responsibility for the implementation of almost all the goals rest with the States and
Local governments in Nigeria’s Federal structure; but in spite of remarkable strides at
Federal level, appreciation of the requirements for meeting these goals, as well as institutional capacity remain relatively low at these levels of government. Poor governance and
integration of the MDGs into national development strategies have also been a challenge. This is aggravated by policy inconsistencies, for instance, Obansanjo regime introduced NEEDS I and II, Yar’adua’s administration instituted Seven-point Agenda and
Vision 20:20:20 and President Goodluck has now introduced Transformation Agenda.
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All these policies are at variance in principle but targeted at achieving the MDGs in the
country. Other challenges include, lack of transparency and accountability in ministries, lack of the political will; a weak monitoring mechanism for the MDGs and low
stakeholders involvement( private sector and civil society organizations ). Lastly is the
unavailability of up to date data on most of the indicators. This is compounded by the
limited funding available for data generation and management in the country.
Findings of the Study
Emergent from the above discussion, it was found out that the government over the
years has demonstrated concern to ensure equality in the literacy level among the
various groups in the country by initiating nomadic education in order to boost the
literacy rate among the nomads who are educationally disadvantaged. This concern
can be seen from the perspective of continued and sustained expenditure on nomadic education over the years. It was discovered that increases in government expenditure on nomadic education have precipitated increases in the number of nomadic
schools in the country across the states vis-à-vis the number of teachers employed
by the government to ensure smooth teaching and learning in nomadic schools in
the country. The study revealed that enrolments by the nomads in the schools have
also increased over time but not proportionate with the increases in the government
expenditure. Factors such as underfunding, dearth of teachers, corruption, constant
migration of the nomads and active involvement of the children in the productive
system by the nomads may have been responsible for this gap. It was also found out
that, there is wide gap between male and female enrollments in nomadic schools
over the years. Factors such as early marriages and teenage pregnancies, cultural and
religious biases as well as poverty and economic issues may have been responsible for
gender gap in the enrolments in nomadic schools in the country.
Conclusion and Recommendations
Based on the above findings, it is concluded that the present implementation of the
nomadic education in the country may make it difficult for it to be a panacea for
achieving Millennium Development Goals(MDGs) in terms of universal basic education attainment by 2015. This is so because, the growth focus of the Millennium
Development Goals( MDGs) is more concentrated at the importance of achieving
clear and real progress in human capital development measured through educational
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Government Expenditure on Nomadic Education in Nigeria:
Implications for Achieving the Millennium Development Goals
foundation. Consequent upon the foregoing, the following recommendations are
submitted:
First, there should be continuous mobilization and sensitization of the nomads to
send their children to these schools especially the female children so as to bridge the
gap between the male- female enrolments in nomadic schools.
Second, the states and local governments should be made to supplement the federal
government funding of the nomadic education, as this will go along way boosting
the achievements in nomadic education in the country.
Third, nomadic educational development initiatives should be planned and aligned
with other community improvement and development programs such as agricultural extension, rural development and social welfare services. This approach will
attract the interest and involvement of more stakeholders as this will encourage the
stakeholders to support the program.
Fourthly, there should be selection of more individuals from nomadic communities
for training as teachers, this is because they are more acquainted with the cultural
values of the nomads. Thus, they will be better placed to inculcate the necessary
knowledge in the targeted nomads.
Fifthly, the government should provide support to animal health issues especially
on major diseases and vaccines as well as provision of support in the area of water
development for improvement of livestock production and reduction of incident of
conflicts between the nomads and the hosting communities. This practice will make
the nomads more stable in a place to receive nomadic education.
Sixthly, government should seek more new partnerships and greater collaboration
with development partners and other stakeholders in other to boost the financing of
nomadic education for higher results.
Seventhly, NCNE should adopt a flexible timetable that adjusts itself to seasons favorable to nomads, as this would enhance their enrollments.
Finally, the government should actively consider the issue of language barrier to
communication, and find contextually appropriate language policies.
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Appendix I
Figure1. An Organogram showing the organizational Chart of National Commission for Nomadic
Education
ORGANISATIONAL CHART OF NATIONAL COMMISSION FOR NOMADIC
EDUCATION
MINISTER OF EDUCATION
BOARD
EXECUTIVE SECRETARY
Finance
& Accounts
Administration
General
Admin.
Establishment
Transport
Monitoring
Supply
Budget &
Funds
North West
Zone
North Central
Zone
North East
Zone
Academic
Planning
Computer
Unit
Documentation
Unit
Evaluation
Statistics
South South
Zone
Legal
Services
Unit
Information
Unit
Animal
Husbandry &
Extension
North East
Zone
Special
Services
Section
Mobilization & Public
Enlightenment
University Centers
Graphics
Unit
Usmanu Danfodiyo
University, Sokoto
Source: NCNE, 2000
Field Operation
Final Accts.
South West
Zone
Physical
Planning &
Maintenance
Programme Development
& Extension
Monitoring Evaluation
& Statistics
University
Of Jos
University
Of Maiduguri
University
Of Port-Harcourt
Audit
Unit
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