Journal of Economic Studies Are shocks to national income persistent? New global evidence Article information

Journal of Economic Studies Are shocks t o nat ional income persist ent ? New global evidence Seema Narayan, Paresh Kumar Narayan, Article information: To cite this document: Seema Narayan, Paresh Kumar Narayan, (2011) "Are shocks to national income persistent? New global evidence", Journal of Economic Studies, Vol. 38 Issue: 2, pp.218-230, https:// doi.org/10.1108/01443581111128433 Permanent link t o t his document : Downloaded by RMIT University Library At 18:57 11 June 2017 (PT) https://doi.org/10.1108/01443581111128433 Downloaded on: 11 June 2017, At : 18: 57 (PT) Ref erences: t his document cont ains ref erences t o 9 ot her document s. 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New global evidence 218 Seema Narayan RMIT University, Australia, and Received 19 December 2008 Accepted 25 February 2010 Paresh Kumar Narayan Downloaded by RMIT University Library At 18:57 11 June 2017 (PT) School of Accounting, Economics and Finance, Faculty of Business and Law, Deakin University, Burwood, Victoria, Australia Abstract Purpose – This paper aims to investigate the integrational properties of real GDP for 125 countries. Design/methodology/approach – The paper applies the Kwiatkowski et al. univariate test and a KPSS-type univariate test that accounts for multiple structural breaks – a test procedure proposed by Carrion-i-Silvestre et al. The panel versions of the KPSS-type test, proposed by Carrion-i-Silvestre et al. with and without structural breaks, are also applied. Findings – The paper finds that, while univariate tests with and without structural breaks provide mixed results on persistence, the panel test suggests that shocks to national output are persistent. Originality/value – This is a multi-country study that focuses on both developed and developing countries and uses more recent data to provide new and comparable evidence on the persistence of output. Keywords Breaks, Gross domestic product, Developing countries Paper type Research paper Journal of Economic Studies Vol. 38 No. 2, 2011 pp. 218-229 q Emerald Group Publishing Limited 0144-3585 DOI 10.1108/01443581111128433 1. Introduction The literature on unit root hypothesis for macroeconomic variables owes to the influential work of Nelson and Plosser (1982), who found the US real gross domestic product (GDP) to be a non-stationary process. While a common representation of real output was the trend stationary model, where business cycles were modelled as stationary fluctuations around a linear deterministic trend, the Nelson and Plosser (1982) findings were inconsistent with the notions of the business cycle. Because their findings questioned the business cycle behaviour of real output, the issue of whether or not real output is stationary has become an intensively researched topic in macroeconomics. While there are several studies on developed countries, evidence on developing countries is scarce (see a review of studies on developing countries in Narayan (2004, 2008). The aim of this paper is to extend this line of research by testing the persistence of output for large group of countries using more recent data. In doing so, we analyse a total of 125 countries. The objective of testing for persistence is met through using the Kwiatkowski et al. (KPSS, 1992) univariate test, which does not take into account structural breaks and the KPSS univariate test that accounts for multiple structural JEL classification – C22, O1, O4 Downloaded by RMIT University Library At 18:57 11 June 2017 (PT) breaks – a test procedure proposed by Carrion-i-Silvestre et al. (2005) – in the data series. Equally importantly, using Monte Carlo simulations, we compute specific sample size critical values, which is also contingent on the location and number of structural breaks for each of the countries. We conclude our empirical analysis by using a panel unit root test developed by Carrion-i-Silvestre et al. (2005) that allows for multiple structural breaks. This study is novel for two reasons. First, given the importance of knowledge on the integrational properties of the real output series, while the literature is large there is a general absence of multi-country studies, particularly on developing countries. To this end, in this study we examine the largest group of countries in this literature. As a result, this study is timely for researchers and policy makers in terms of comparing experiences of different countries. Second, while the bulk of the literature, in testing the issue of stationarity, treats the null hypothesis as non-stationarity, the KPSS test and its subsequent extensions to cases of univariate multiple structural break test and the panel multiple structural break test treat the null hypothesis as stationarity. This is an important treatment likely to have some influence on the results because the null of stationarity can be considered to be more natural than the null hypothesis of a unit root for many economic problems (see Bai and Ng, 2004). Particularly relevant to the panel data models, this implies that there has to be strong evidence against trend stationarity to conclude in favour of the non-stationarity of the panel. We organise the balance of the paper as follows. In section 2, we present the econometric methodology. In section 3, we discuss the empirical results, while in the final section we conclude. 2. Multiple structural breaks panel unit root test In this section, we describe the test for the null hypothesis of stationarity, a test developed by Carrion-i-Silvestre et al. (2005). This procedure allows for two different types of multiple structural break effects and is based on the panel data version of the KPSS univariate test developed by Hadri (2000). This test takes the following form: yi;t ¼ ai þ mi X k¼1 ui;k DU i;k;t þ bi t þ mi X * gi;k DT i;k;t þ 1i;t ð1Þ k¼1 where subscript i ¼ 1; :::; N individuals and t ¼ 1; :::; Ttime periods; the dummy * variable DT i;k;t ¼ t 2 T ib;k for t . T ib;k and 0 elsewhere; and DU i;k;t ¼ 1 for t . T ib;k and 0 elsewhere, where T ib;k denotes the kth date of the break for the ith individual and k ¼ 1; :::; mi , mi $ 1. Individual structural break effects (break in the mean) result when bi – 0. The temporal structural break effects (break in the trend) results when gi;k – 0[1]. Three features of this test are worth highlighting: (1) structural breaks have different effects on each individual time series; (2) structural breaks are not restricted so they may occur at different times; and (3) series are allowed to have different number of structural breaks. Carrion-i-Silvestre et al. (2005) then use the Hadri (2000) procedure, which is constructed using a simple average of the univariate stationarity test in Kwiatkowski Are shocks to national income persistent? 219 JES 38,2 Downloaded by RMIT University Library At 18:57 11 June 2017 (PT) 220 Table I. KPSS unit root tests without a break Regions/countries Test statistic Regions/ Bandwidth countries Africa Algeria Angola Burkina Faso Cameroon Cote d’Ivoire DR Congo Egypt Ethiopia Ghana Kenya Madagascar Malawi Mali Morocco Mozambique Niger Nigeria Senegal South Africa Sudan Tanzania Tunisia Uganda Zambia Zimbabwe Eastern Europe and Central Asia Albania Armenia Azerbaijan Belarus Bulgaria Croatia 0.1023 0.1464 * * 0.2285 * * * 0.0701 0.1420 * 0.2070 * * 0.2379 * * * 0.2058 * * 0.2071 * * 0.2481 * * 0.1335 * 0.2454 * * * 0.2431 * * * 0.2572 * * * 0.1883 * * 0.1091 0.1548 * * 0.2432 * * * 0.0959 * * 0.1872 * * 0.1984 * * 0.2375 * * * 0.2247 * * * 0.1183 0.1576 * * 5 5 6 5 5 6 6 5 6 5 5 5 5 5 5 5 5 5 5 5 5 6 5 5 5 0.1755 * * 0.1701 * * 0.1696 * * 0.1676 * * 0.1755 * * 0.1667 * * 2 3 3 3 3 2 Czech Republic Czechoslovakia Estonia Georgia Hungary Kazakhstan Kyrgyz Republic Latvia Lithuania Macedonia Moldova Poland Romania Russian Federation 0.1863 * * 0.1816 * * 0.1649 * * 0.1731 * * 0.1804 * * 0.1693 * * 0.1540 * * 0.1861 * * 0.1632 * * 0.1862 * * 0.1643 * * 0.1399 * 0.1898 * * 0.1685 * * 2 2 3 2 2 3 3 2 3 2 3 2 2 3 Asia Bangladesh Cambodia China Hong Kong India Indonesia Japan Malaysia Myanmar Pakistan The Philippines Singapore South Korea Sri Lanka Taiwan Thailand Vietnam Latin America Argentina Barbados Bolivia Brazil Chile Colombia Costa Rica Dominican Republic Ecuador Guatemala Jamaica Mexico Peru St. Lucia Trinidad & Tobago Uruguay Venezuela Western Europe Austria Belgium Cyprus Denmark Finland France Germany Greece Iceland Ireland Test statistic Bandwidth 0.2341 * * * 0.2361 * * * 0.2481 * * * 0.2476 * * * 0.2603 * * * 0.2461 * * * 0.1173 * * 0.2438 * * * 0.2057 * * 0.2491 * * * 0.1942 * * 0.2460 * * * 0.2480 * * * 0.2448 * * * 0.2496 * * * 0.2436 * * * 0.2294 * * * 6 5 5 6 5 6 5 6 5 6 5 6 6 6 6 6 6 0.105 0.186 * * 0.151 * * 0.136 * * 0.232 * * * 0.264 * * * 0.249 * * * 4 5 5 5 6 5 5 0.132 * 0.163 * * 0.206 * * 0.146 * * 0.184 * * 0.108 0.232 * * * 5 5 5 6 5 5 6 0.136 * * 0.224 * * * 0.074 5 5 4 0.2100 * * 0.1310 * * 0.2455 * * * 0.1619 * * 0.1672 * * 0.0845 0.1228 * 0.1107 0.1909 * * 0.2201 * * * 5 5 6 5 5 5 5 5 5 6 (continued) Downloaded by RMIT University Library At 18:57 11 June 2017 (PT) et al. (1992), to test the null hypothesis of a stationary panel. To obtain the location and the number of breaks, Carrion-i-Silvestre et al. (2005) recommend using the Bai and Perron (1998) procedure, which computes the global minimisation of the sum of squared residuals. 3. Empirical results 3.1 Data Annual real GDP data for 125 countries across seven regions, namely, Africa, Asia, Eastern Europe and Central Asia, Latin America, Middle East, North America, and Western Europe are used. The countries of these regions are displayed in Table I. The real GDP data covers the period 1950-2008 for most countries. The only exceptions are Eastern European and Central Asian countries with a study period 1989-2008. These country data are extracted from the Groningen Growth and Development Centre and The Conference Board, Total Economy Database, August 2004, www.ggdc.net. All data was converted into natural logarithmic form before the empirical analysis. Are shocks to national income persistent? 221 3.2 Results 3.2.1 KPSS univariate tests. We begin the empirical analysis with an examination of the univariate unit root properties of real GDP for each of the regions using the KPSS Regions/countries Serbia and Montenegro Slovak Republic Slovenia Tajikistan Turkmenistan USSR Ukraine Uzbekistan Yugoslavia Middle East Bahrain Iran Iraq Israel Jordon Kuwait Oman Qatar Saudi Arabia Syria UAE Yemen Test statistic Regions/ Bandwidth countries 0.1719 * * 0.1706 * * 0.1721 * * 0.1631 * * 0.1682 * * 0.1687 * * 0.1656 * * 0.1704 * * 0.1643 * * 2 2 2 3 3 3 3 3 2 0.2444 * * * 0.1049 * * 0.1736 * * 0.2377 * * * 0.2369 * * * 0.1255 * 0.2482 * * * 0.1133 0.0903 0.2237 * * * 0.1572 * * 0.2306 * * * 5 5 6 6 5 5 6 5 5 6 5 6 Italy Luxembourg Malta Netherlands Norway Portugal Spain Sweden Switzerland Turkey United Kingdom North America Canada United States Oceania Australia New Zealand Test statistic Bandwidth 0.1811 * * 0.2356 * * * 0.2177 * * * 0.2043 * * 0.2382 * * * 0.2172 * * * 0.2144 * * 0.1343 * * 0.1496 * * 0.2694 * * * 0.2241 * * * 5 6 6 5 6 5 5 5 5 5 6 0.2267 * * * 0.2404 * * * 5 6 0.2347 * * * 0.1764 * * 6 5 Notes: *Denotes statistical significance at the ????? per cent (query author); * *denotes statistical significance at the 5 per cent level; * * * denotes statistical significance at the 1 per cent level. The finite sample critical values for the KPSS test are 0.119, 0.146, and 0.216 at the 10 per cent, 5 per cent, and 1 per cent levels, respectively Table I. JES 38,2 Downloaded by RMIT University Library At 18:57 11 June 2017 (PT) 222 test with a time trend but without a structural break. We report the results in Table I and organise them as follows. Columns 2 and 4 contain the test statistics for real GDP and its associated bandwidth is reported in columns 3 and 5. Our main results for the real GDP series can be summarised as follows. First, the cases of trend stationary real GDP are limited to a few countries in Africa, Latin America, Middle East, and Western Europe. In the African region, only four (Algeria, Cameroon, Niger, and Zambia) out of 21 countries are found with trend stationary real GDP series over the period 1950 to 2008. In Latin American, only three out of 17 cases of stationarity are found. These countries with trend stationary real GDP are Argentina, Peru, and Venezuela. Of the 12 Middle Eastern countries, only Qatar and Saudi Arabia are found to have a stationary real GDP series. Furthermore, of the 21 Western European countries, only France and Greece, have trend stationary real GDP series. Second, for the remaining countries in the rest of the four regions, namely Asia, the Eastern Europe and Central Asia, North America, and Oceania, we are able to reject the null hypothesis of stationarity in the real GDP. Taken together, these results imply that for around 92 per cent of the countries real GDP is non-stationary. Individual results Table II. KPSS test on real GDP for African countries with break date(s) Algeria Angola Burkina Faso Cameroon Cote d’Ivoire DR Congo Egypt Ethiopia Ghana Kenya Madagascar Malawi Mali Morocco Mozambique Niger Nigeria Senegal South Africa Sudan Tanzania Tunisia Uganda Zambia Zimbabwe Bartlett 0.035 0.023 0.045 0.03 0.028 0.023 0.104 * * * 0.032 0.09 0.054 0.029 0.048 0.034 0.122 * * * 0.018 0.027 0.016 0.027 0.047 * * * 0.023 0.153 * * * 0.145 * * * 0.028 0.029 0.02 Finite sample critical values 99% 95% 90% 0.054 0.157 0.102 0.188 0.053 0.036 0.033 0.07 0.057 0.081 0.107 0.07 0.132 0.053 0.077 0.052 0.103 0.235 0.054 0.164 0.041 0.089 0.097 0.08 0.111 0.042 0.101 0.07 0.124 0.04 0.03 0.026 0.055 0.045 0.06 0.075 0.055 0.087 0.038 0.054 0.038 0.071 0.155 0.04 0.109 0.031 0.061 0.067 0.06 0.079 0.037 0.08 0.055 0.096 0.034 0.027 0.023 0.048 0.039 0.051 0.062 0.048 0.069 0.033 0.044 0.032 0.057 0.12 0.034 0.085 0.027 0.05 0.053 0.052 0.065 Break dates 1961 1974 1969 1977 1962 1957 1957 1962 1959 1965 1969 1962 1972 1962 1966 1962 1969 1981 1962 1975 1960 1967 1968 1964 1969 1983 1992 1977 1985 1980 1975 1966 1990 1974 1991 1994 1980 1980 1975 1974 1972 1980 1996 1980 1998 1975 1987 1978 1993 1997 1995 2000 1985 1993 1991 1990 1975 1995 1999 2000 1983 1991 1982 1995 1991 1984 1983 1999 1991 1984 2000 1990 2000 1995 1994 2000 . 1992 2000 Notes: *Denotes statistical significance at the 10 per cent level; * *denotes statistical significance at the 5 per cent level; * * *denotes statistical significance at the 1 per cent level. We computed finite sample critical values by means of Monte Carlo simulations using 20,000 replications Downloaded by RMIT University Library At 18:57 11 June 2017 (PT) One issue that we have ignored so far is the existence of structural breaks and hence testing for trend stationarity in their presence. It is now well documented that if structural breaks are present but are not taken into account when testing for stationarity then the results are likely to be spurious (see, among others, Vogelsang and Perron, 1998). Hence, we now consider the KPSS test that allows for multiple significant structural breaks in the data series. We report the results from this exercise in Tables II to IX, and organise them as follows. In column 2, we report the KPSS test statistics, generated through accounting for structural breaks; column 3 contains the finite sample critical values at the 5 per cent and 1 per cent levels, respectively, obtained through Monte Carlo simulations; and the final column reports the structural break date(s). Our main finding here is that when we allow for multiple structural breaks, we are unable to reject the null hypothesis of stationarity for a large number of countries at the 5 per cent level of significance or better. All these countries real GDP are found to be affected by one or more significant structural breaks. The region-wise results are as follows. In the African region, 80 per cent of the countries are found to have a stationary real GDP series. Some 64 per cent of these series are found to be stationary only after accounting for structural breaks. The null hypothesis of stationarity is rejected for only five countries, namely, Egypt, Morocco, South Africa, Tanzania, and Tunisia. In terms of the structural breaks, the break dates for Africa seems to be concentrated around the periods: 1971-1974, 1978-1981, and 1987 to 1996. These break dates are mainly associated with oil price shocks and recessions, including financial crises. Bangladesh Cambodia China Hong Kong India Indonesia Japan Malaysia Myanmar Pakistan The Philippines Singapore South Korea Sri Lanka Taiwan Thailand Vietnam Bartlett Finite sample critical values 99% 95% 90% 0.037 0.019 0.084 * * 0.036 0.028 0.032 * * 0.066 * * 0.032 * * 0.07 * 0.075 * * 0.037 0.015 0.062 * * 0.031 0.067 * * 0.022 0.045 0.048 0.069 0.051 0.313 0.201 0.029 0.042 0.032 0.074 0.032 0.056 0.072 0.049 0.085 0.042 0.037 0.078 0.038 0.05 0.04 0.209 0.131 0.023 0.035 0.027 0.054 0.025 0.043 0.049 0.039 0.058 0.032 0.03 0.053 0.034 0.043 0.035 0.159 0.102 0.021 0.031 0.024 0.045 0.022 0.038 0.04 0.034 0.047 0.028 0.027 0.043 Are shocks to national income persistent? 223 Break dates 1959 1964 1960 1987 1978 1957 1957 1957 1965 1958 1957 1965 1961 1967 1960 1957 1966 1971 1974 1975 1993 1986 1997 2000 1966 1971 1972 1987 1971 1983 1973 1979 1976 1973 1969 1979 1974 1989 1985 1997 1979 2000 1984 1993 1986 1987 1988 1991 1984 1997 1997 1989 2000 1997 2000 2000 1997 2000 Notes: *Denotes statistical significance at the 5 per cent levels; * *denotes statistical significance at the 1 per cent levels. We computed finite sample critical values by means of Monte Carlo simulations using 20,000 replications Table III. KPSS test on real GDP for Asian countries with break date(s) JES 38,2 Bartlett Downloaded by RMIT University Library At 18:57 11 June 2017 (PT) 224 Table IV. KPSS test on real GDP for Eastern European and Central Asian countries with break date(s) Albania Armenia Azerbaijan Belarus Bulgaria Croatia Czech Republic Czechoslovakia Estonia Georgia Hungary Kazakhstan Kyrgyz Republic Latvia Lithuania Macedonia Moldova Poland Romania Russian Federation Serbia and Montenegro Slovak Republic Slovenia Tajikistan Turkmenistan USSR Ukraine Uzbekistan Yugoslavia 1.068 * * * 0.965 * * * 1.367 * * * 2.101 * * * 0.789 * * * 0.28 * * * 0.787 * * * 0.521 * * * 0.497 * * * 0.595 * * * 1.072 * * * 0.092 0.34 * * * 0.202 * * * 0.058 * * 1.768 * * * 4.53 * * * 0.376 * * * 0.607 * * * 0.161 * * * 0.902 * * * 0.126 * * * 0.061 * 0.509 * * * 0.4 * * * 0.074 * * * 0.076 * * * 1.761 * * * 2.659 * * * Finite sample critical values 99% 95% 90% 0.144 0.052 0.039 0.037 0.039 0.07 0.079 0.09 0.074 0.062 0.062 0.186 0.12 0.106 0.073 0.076 0.074 0.061 0.039 0.046 0.072 0.052 0.078 0.091 0.173 0.073 0.073 0.045 0.071 0.107 0.044 0.034 0.032 0.035 0.058 0.062 0.071 0.057 0.05 0.05 0.134 0.09 0.079 0.058 0.058 0.06 0.049 0.035 0.039 0.058 0.043 0.062 0.07 0.126 0.057 0.057 0.039 0.058 0.09 0.04 0.032 0.03 0.032 0.051 0.054 0.06 0.049 0.044 0.044 0.108 0.077 0.068 0.05 0.048 0.054 0.043 0.032 0.035 0.052 0.039 0.054 0.06 0.104 0.05 0.05 0.035 0.052 Break dates 1992 1991 1991 1991 1991 1992 1991 1991 1993 2001 1991 1997 1991 1991 1991 1993 1993 1991 1991 1991 1992 1992 1991 1991 1997 1991 1991 1991 1992 1994 1994 1995 1994 1998 2002 2003 1998 1994 1996 1999 1994 1995 1994 1996 1999 2000 1996 1994 1998 1998 2002 1996 1994 1995 1995 1998 2000 1998 1998 1997 2004 2003 2002 2005 1999 2005 1998 2000 2003 2004 1999 1997 2005 2004 2004 1998 1998 2002 2005 Notes: *Denotes statistical significance at the 10 per cent levels; * *denotes statistical significance at the 5 per cent levels; * * *denotes statistical significance at the 1 per cent levels. We computed finite sample critical values by means of Monte Carlo simulations using 20,000 replications In Asia, 53 per cent of the countries’ real GDP is found to be stationary after accounting for structural breaks in the series. The null hypothesis of trend stationarity is rejected for eight countries, namely China, Indonesia, Japan, Malaysia, Myanmar, Pakistan, South Korea, and Taiwan. Structural breaks seem to clutter around the periods 1957, early 1980s, 1997, and 2000. Again, these dates are associated with global economic shocks, such as financial crises and recessions. The null hypothesis of stationarity was rejected for an overwhelming 93 per cent of the Eastern European and Central Asian countries. Only two of these countries (Croatia’s and Kazakhstan’s) real GDP series are found to be trend stationary. Two common break dates are found: one in the period 1991-94 and the other in 1998. The first period was marked by the Gulf war while the second period is one associated with the Asian financial crisis. Downloaded by RMIT University Library At 18:57 11 June 2017 (PT) Bartlett Argentina Barbados Bolivia Brazil Chile Colombia Costa Rica Dominican Republic Ecuador Guatemala Jamaica Mexico Peru St. Lucia Trinidad and Tobago Uruguay Venezuela 0.049 0.018 0.048 * * 0.061 * 0.03 0.061 * 0.072 0.254 * * * 0.034 0.104 * * * 0.041 * * * 0.047 0.05 0.184 * * * 0.091 * * * 0.021 0.05 * * * Finite sample critical values 99% 95% 90% 0.143 0.143 0.051 0.085 0.154 0.101 0.136 0.071 0.097 0.058 0.04 0.245 0.161 0.047 0.044 0.039 0.05 0.095 0.094 0.041 0.064 0.1 0.069 0.094 0.053 0.068 0.045 0.032 0.162 0.108 0.035 0.036 0.032 0.04 0.075 0.074 0.036 0.055 0.078 0.056 0.076 0.045 0.056 0.039 0.028 0.127 0.085 0.03 0.032 0.028 0.036 Are shocks to national income persistent? Break dates 1973 1973 1959 1964 1974 1969 1972 1964 1968 1962 1957 1982 1975 1961 1959 1958 1959 1991 1981 1977 1977 1982 1981 1981 1976 1978 1978 1972 1987 1973 1978 1972 1979 2000 1991 1985 2000 225 1998 1998 2000 1998 1986 1980 1981 1993 1981 2000 1988 1994 2000 Notes: *Denotes statistical significance at the 10 per cent levels; * *denotes statistical significance at the 5 per cent levels; * * *denotes statistical significance at the 1 per cent levels. We computed finite sample critical values by means of Monte Carlo simulations using 20,000 replications Bahrain Iran Iraq Israel Jordan Kuwait Oman Qatar Saudi Arabia Syria United Arab Emirates Yemen Bartlett Finite sample critical values 99% 95% 90% 0.079 0.034 0.036 0.058 0.029 0.033 0.028 0.018 0.026 0.075 0.035 * 0.13 * 0.247 0.047 0.198 0.156 0.104 0.107 0.093 0.081 0.038 0.158 0.03 0.107 0.155 0.038 0.128 0.111 0.071 0.074 0.067 0.061 0.031 0.112 0.024 0.07 0.119 0.034 0.099 0.092 0.058 0.061 0.056 0.052 0.028 0.092 0.022 0.055 Table V. KPSS test on real GDP for Latin American countries with break date(s) Break dates 1981 1957 1978 1974 1969 1969 1967 1965 1957 1974 1957 1969 1992 1977 1990 2000 1987 1977 1992 1983 1973 1972 1988 1981 1981 1991 1989 1971 1978 1979 1991 1988 2000 2000 Notes: *Denotes statistical significance at the 1 per cent levels. We computed finite sample critical values by means of Monte Carlo simulations using 20,000 replications For the Latin American region, the null hypothesis is rejected for nine countries at the 10 per cent level of significance or better. The real GDP of the remaining eight countries is found to be stationary. Six of these countries – Barbados Chile, Costa Rica, Ecuador, Mexico, and Uruguay – are found to be stationary only after allowing for structural breaks. At least one significant structural break is found in the real GDP Table VI. KPSS test on real GDP for Middle Eastern countries with break date(s) JES 38,2 Downloaded by RMIT University Library At 18:57 11 June 2017 (PT) 226 series of all the countries in this region. There is a tendency for some of these breaks to commonly appear in the periods: 1972-1973, 1977-1978, 1981-1982, 1998 and 2000. Again, as with structural breaks of other countries, these break dates tend to coincide with the oil price shocks of the 1970s, the recessions of the early 1980s, and the financial crisis of 1997. For most of the Middle Eastern region, around 67 per cent of countries are found to have a stationary real GDP series after allowing for structural breaks. The only exceptions are the real GDP series of the United Arab Emirates and Yemen. The structural break dates for this region is spread across the review period but there seems to be some concentration of breaks around the dates 1974-1978 and 1991-1992. In the case of North American countries, the real GDP series of both Canada and the USA are found to be stationary after allowing for breaks. The Canadian series experienced two significant structural breaks. These occurred in 1979 and 1990. The US series, on the hand, was affected by one break which occurred in 1964. For the Oceania region, we are unable to reject the null hypothesis for the Australian real GDP after allowing for four structural break dates in 1952, 1960, 1971 and 1981. In contrast, the stationarity hypothesis is rejected for the New Zealand series even after accounting for three breaks. For the Western European countries, we are able to reject the null hypothesis for 12 out of 21 countries after allowing for structural breaks. These countries are Belgium, Cyprus, Denmark, Iceland, Ireland, Luxemburg, Malta, Norway, Portugal, Spain, Turkey, and the UK. Around 43 per cent of the region’s countries are found to have a non-stationary GDP despite accounting for structural shifts in the series. Notwithstanding, all countries show two or more significant breaks, several of which appear around the period 1957-1959, 1971-74, 1978-1981, and 1987-1990. 3.2.2 Panel unit root test. In this section, we report the results from the KPSS panel stationarity test without breaks and with multiple structural breaks. We present the Finite sample critical values Bartlett Table VII. KPSS test on real GDP for North American countries with break date(s) Table VIII. KPSS test on real GDP for Oceania countries with break date(s) Canada United States 0.068 0.02 0.213 0.133 0.136 0.097 Break dates 0.106 0.081 1979 1964 1990 Notes: We computed finite sample critical values by means of Monte Carlo simulations using 20,000 replications Australia NZ Bartlett Finite sample critical values 99% 95% 90% 0.036 0.048 * 0.057 0.054 0.042 0.042 0.035 0.037 Break dates 1952 1951 1960 1976 1971 1989 1981 Notes: *Denotes statistical significance at the 5 per cent levels. We computed finite sample critical values by means of Monte Carlo simulations using 20,000 replications Downloaded by RMIT University Library At 18:57 11 June 2017 (PT) Austria Belgium Cyprus Denmark Finland France Germany Greece Iceland Ireland Italy Luxembourg Malta The Netherlands Norway Portugal Spain Sweden Switzerland Turkey United Kingdom Bartlett Finite sample critical values 99% 95% 90% 0.072 * 0.052 0.027 0.020 0.115 * 0.090 * * 0.036 * 0.134 * * 0.063 0.026 0.031 * 0.053 0.024 0.065 * * 0.020 0.022 0.020 0.080 * * 0.058 * * 0.046 0.031 0.095 0.083 0.060 0.089 0.086 0.090 0.045 0.035 0.194 0.051 0.103 0.123 0.045 0.036 0.047 0.036 0.042 0.043 0.034 0.082 0.049 0.069 0.061 0.046 0.064 0.066 0.065 0.036 0.029 0.129 0.038 0.07 0.084 0.033 0.029 0.036 0.028 0.034 0.035 0.029 0.058 0.039 0.058 0.052 0.04 0.054 0.057 0.055 0.032 0.026 0.099 0.033 0.057 0.068 0.027 0.026 0.031 0.025 0.031 0.032 0.026 0.048 0.034 Are shocks to national income persistent? Break dates 1957 1957 1959 1958 1975 1960 1959 1958 1978 1957 1969 1971 1961 1957 1957 1959 1959 1959 1957 1966 1959 1977 1974 1973 1973 1990 1973 1973 1971 1991 1982 1981 1985 1971 1973 1980 1974 1973 1976 1974 1979 1980 227 1981 1978 1980 1996 1992 1990 2002 1979 1981 1988 1983 1987 1992 1988 1990 1990 1987 1998 1997 1992 1995 1999 2001 1996 Notes: *Denotes statistical significance at the 5 per cent levels; * *denotes statistical significance at the 1 per cent levels. We computed finite sample critical values by means of Monte Carlo simulations using 20,000 replications results in Table X. Our results for the real GDP series are based on eight panels. Our results are based on the assumption that the long-run variance is homogenous and heterogenous. Under each of these assumptions, we conduct panel tests by allowing for structural breaks and by not allowing for structural breaks. The results can be summarised as follows. First, we find that for all the panels when we do not allow for structural breaks, we reject the null hypothesis of panel stationarity. This is indicated by the p-value, which has a value of zero for all the panels. When we allow for multiple structural breaks, we reject the null hypothesis of stationarity for all, except, the panel consisting of the North American countries. 4. Conclusion In this paper, we examined the integrational properties of real GDP of 125 countries from seven regions of the world, namely, Africa, Asia, Eastern Europe and Central Asia, Latin America, Middle East, North America, and Western Europe, using annual data for the period 1950-2004. Knowledge on the integrational properties is important because if income is found to be non-stationary then it is inconsistent with the notion that business cycles are stationary fluctuations around a deterministic trend. Our main innovation, which distinguishes our work from the literature, is that we used a recently developed technique by Carrion-i-Silvestre et al. (2005) that tests the null of stationarity by allowing for multiple structural breaks in both univariate and panel data. Table IX. KPSS test on real GDP for Western European countries with break date(s) Downloaded by RMIT University Library At 18:57 11 June 2017 (PT) JES 38,2 Africa Asia Eastern Europe and Central Asia Latin America Middle East North America Oceania Western Europe 228 Table X. Panel test for stationarity of real GDP Regions No breaks (homogeneous) p-value No breaks (heterogeneous) p-value Breaks (homogeneous) p-value Breaks (heterogeneous) p-value 15.844 * 17.894 * 13.136 * 9.632 * 6.002 * 5.878 * 5.667 * 15.215 * 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 13.990 * 16.312 * 13.395 * 10.428 * 9.578 * 5.648 * 4.701 * 13.217 * 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.214 15.142 * 75.192 * 13.741 * 5.572 * -0.051 3.592 * 5.936 * 0.415 0.000 0.000 0.000 0.000 0.520 0.000 0.000 19.153 * 14.970 * 383.100 * 24.985 * 9.653 * 0.783 2.950 * 16.230 * 0.000 0.000 0.000 0.000 0.000 0.217 0.002 0.000 Notes: *Denotes statistical significance at the 1 per cent level Downloaded by RMIT University Library At 18:57 11 June 2017 (PT) Our main finding is that when we do not account for structural breaks only 11 countries have a stationary GDP series; in other words, around 91 per cent of the countries have a non-stationary GDP series. However, when we allow for multiple structural breaks, the number of cases of stationary GDP series increases to 53 countries, implying that for around 42 per cent of the countries GDP is non-stationary. Finally, when we apply panel data models, both with and without structural breaks, we unravel overwhelming evidence in favour of panel non-stationary GDP for the eight panels that we considered. In sum then, our results suggest that while based on univariate tests, slightly over half of the 125 countries have a GDP series where shocks have a transitory effect, regional panel results suggest that shocks to GDP are persistent. This means that country-specific results are somewhat different from region-based results. Note 1. It is straightforward to follow multiple structural breaks in a univariate series, starting again with equation (1) by simply dropping off the subscript i. References Bai, J. and Ng, S. (2004), “A new look panel testing of stationarity and the PPP hypothesis”, in Andrews, D. and Stock, J. (Eds), Identification and Inference in Econometric Modelling: Essays in Honour of Thomas J. Rothenberg, Cambridge University Press, Cambridge. Carrion-i-Silvestre, J.L., Barrio-Castro, T.D. and Lopez-Bazo, E. (2005), “Breaking the panels: an application to the GDP per capit”, Econometrics Journal, Vol. 8, pp. 159-75. Hadri, K. (2000), “Testing for stationarity in heterogenous panel data”, Econometrics Journal, Vol. 3, pp. 148-61. Kwiatkowski, D., Phillips, P.C., Schmidt, P.J. and Shin, Y. (1992), “Testing the null hypothesis of stationarity against the alternative of a unit root: how sure are we that economic time series have a unit root”, Journal of Econometrics, Vol. 54, pp. 159-78. Narayan, P.K. (2004), “Are output fluctuations transitory? New evidence from 24 Chinese provinces”, Pacific Economic Review, Vol. 9, pp. 327-36. Narayan, P.K. (2008), “Evidence of panel stationarity from Chinese provincial and regional income”, China Economic Review, Vol. 19, pp. 274-86. Nelson, C. and Plosser, C. (1982), “Trends and random walks in macroeconomic time series”, Journal of Monetary Economics, Vol. 10, pp. 139-62. Vogelsang, T.J. and Perron, P. (1998), “Additional tests for a unit root allowing for a break in the trend function at an unknown time”, International Economic Review, Vol. 39, pp. 1073-100. Further reading Liu, J., Wu, S. and Zidek, J.V. (1997), “On segmented multivariate regressions”, Statistica Sinica, Vol. 7, pp. 497-525. To purchase reprints of this article please e-mail: reprints@emeraldinsight.com Or visit our web site for further details: www.emeraldinsight.com/reprints Are shocks to national income persistent? 229 This article has been cited by: Downloaded by RMIT University Library At 18:57 11 June 2017 (PT) 1. Huiming Zhu, Peng Guo. 2016. 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