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All rights reserved. Where specified, individual articles are the
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Table of Contents
Financial Services and Inequality in New York
B. Warf
The Organizational Structure & Spatial Dynamics of Investment Advisory Services: The Case of
Metropolitan Philadelphia, 1983-2003
J. Bodenman
A Borderless World of Hypermobile and Homeless Money?
C. Williams
111
128
147
Globalization of Banking and Local Access to Financial Resources: A Case Study form Southeastern
Mexico
159
J. Biles
Is the Geography of Banking Services Converging toward Markets? The Case of Illinois
B. Zhou
Guidelines for Contributors
172
Financial Services and Inequality In New York
Barney Warf
Dept. of Geography
Florida State University
Tallahassee, FL 32306
ABSTRACT
As global cities have mushroomed in significance, mounting concern has
accompanied the visible inequality that such centers contain. Sassen’s influential
dual city thesis maintains that the growth of the finance industry is largely to
blame for inequality by generating an elite of well-paid occupations and large
numbers of poorly paid ones. This approach, however, suffers from an inadequate
explication of inter-industry linkages. This paper tests Sassen’s thesis in light of
the growth of the securities industry in the New York metropolitan region in the
1990s using an input-output model. Its findings bring the dual city thesis into
question and suggest other, more complex causes of inequality might be at work.
INTRODUCTION
Global cities are the command and
control centers of the global economy,
host vast complexes of skilled, high
value-added activities with globespanning consequences (Taylor 2000).
At the top of the international urban
hierarchy, this handful of specialized
metropolises are simultaneously: (a)
centers of creative innovation, news,
fashion, and culture industries, (b)
metropoles for raising and managing
investment capital, (c) centers of
specialized expertise in advertising
and
marketing,
legal
services,
accounting, computer services, etc.,
and (d) the management, planning
and control centers for corporations
and nongovernmental organizations
(NGOs) that operate with increasing
ease over the entire planet (Knox
1995). New York, London, and Tokyo,
and to a lesser extent, secondary
metropoles such as Paris, Toronto, Los
Angeles, and Singapore, lie at the core
The Industrial Geographer, Volume 2, Issue 1, pp. 110-126
of a worldwide chain of value-added
linkages that have steadily fostered a
pronounced concentration of strategic
headquarter functions in a few
conglomerations and a persistent
dispersal of unskilled functions to the
world’s periphery.
This process
reinforces the long-standing transition
of employment in such regions from
low-wage, low value-added, blue-collar
occupations to high-wage, high valueadded, white-collar employment. At
their core, global cities allow the
generation of specialized expertise
upon which so much of the current
global economy depends. Numerous
authors have pointed out the ways in
which global cities are as much shaped
by the world economy as they are
shapers of it (Friedmann and Wolff
1982; Sassen 1991; Taylor 2000).
New York holds pride of place among
global cities.
Since its inception,
©2004 Warf
The Industrial Geographer
worldwide economic shifts and forces
have been so interpolated so deeply
with New York that it is impossible to
comprehend the metropolis without
reference to its international ties.
New York’s global standing is not new,
having been shaped by decades of
trade, finance, and immigration
(Hackworth 1998), or in Castells’
(1996) famous phrase, the “space of
flows.”
Few locales offer such a
stunning glimpse into the ways in
which planetary-wide processes are
telescoped
into
local
contexts.
Following the fiscal crises of the
1970s, during which the region
tottered on the brink of fiscal
bankruptcy, New York re-established
its long-held role as a formidable
juggernaut in the global financial
system (Mollenkopf and Castells 1991;
Fainstein, Gordon, and Harloe 1992;
Fainstein 1994), rivaled only by
London and, to a lesser extent, Tokyo.
World
trade
in
goods,
which
dominated
New
York’s
global
connections for centuries, has been
eclipsed by transnational shifts in
capital and information, activities in
which New York enjoys a special
competitive niche. Wall Street has
long symbolized New York's dominant
role in financial markets of the U.S.,
and
Manhattan
remains
the
headquarters of most of the largest
money-center banks in the nation,
including Citicorp, Chemical, Chase
Manhattan, and Morgan Guaranty.
In the securities markets, New York
remains the unquestioned leviathan of
the nation; a sizeable share of all stock
sales in the U.S. (861 billion in 2002,
or 43 percent) are traded on the New
York Stock Exchange (NYSE), the
Warf
world’s largest. By attracting the
headquarters of many multinational
corporations and by serving as both an
importer and exporter of people, goods,
information, and services, New York
has
been
both
producer
and
beneficiary of globalization, i.e., it has
been both a generator and in turn
constituted by international flows and
forces.
The analysis of global cities has been
accompanied by growing concern
regarding mounting inequality within
them. Particularly in the U.S., with
its increasingly frayed safety net of
social services, cities such as New
York exemplify sharp contrasts
between
wealthy
elites
and
impoverished
working
class
communities populated by immigrants
and minorities. An oft-cited suspect
for the creation of inequality is the
financial sector, which is held to create
“masters of the universe” and their
counterparts toiling in dead-end
service jobs, but few positions in
between.
The prevailing interpretation, put
forth by Saskia Sassen (1991), holds
that the external functions of global
cities such as New York as repositories
of highly skilled corporate functions,
particularly in finance, engender
internal labor markets marked by
great degrees of social polarity. While
a small elite earns millions buying and
selling stocks, this argument holds,
the spin-offs are to be found in lowpaying, unskilled jobs in retail trade,
hotels, and personal services. Sassen’s
argument
has
become
widely
influential, as we shall see, it is not
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The Industrial Geographer
without criticisms. In particular, her
claims rest upon anecdotal evidence,
which while rich, may fail to capture
the complexity of regional economic
systems typified by high degrees of
inter-industry dependency.
emerged in the 1970s, which was
marked by:
the collapse of the
Bretton-Woods agreement in 1971 and
the shift to floating currency exchange
rates; the oil crises of 1974 and 1979
and associated growth of Third World
debt; the deindustrialization of much
of Europe and North America and the
concomitant rise of the East Asian
newly industrializing nations; the
steady
growth
of
multinational
corporations and their ability to shift
vast
resources
across
national
boundaries; technological changes
unleashed by the microelectronics
revolution; the global wave of
deregulation, privatization, and the
lifting of government controls, all of
which reflect the hegemony of
neoliberalism
worldwide;
the
integration of world financial markets
through telecommunications systems;
and the initiation of new trade
agreements and trade blocs and
agreements that accelerated the
freedom of capital to transcend
national borders.
These changes
produced
a
highly
volatile,
deregulated,
globalized
form
of
capitalism that greatly accentuated
the position of global cities in the
world space-economy (Knox 1995;
Taylor 2000).
The purpose of this paper is to test
Sassen’s thesis of the dual city using a
rigorous analytic methodology.
It
begins by reviewing the critical role of
finance to the New York metropolitan
region’s economy, focusing on the
causes of the growth of the securities
industry throughout the 1990s.
Although investment banking suffered
in the downturn following the year
2000, the 1990s boom had lasting
effects on the city, and as the industry
has recently returned to its former
heights, is likely to do so again. Next,
the paper turns to New York’s labor
markets and the inequalities present
therein, including a large underclass
of poorly skilled minorities. Third, it
offers a means to explore the relations
between the growth of finance and
inequality
using
input-output
analysis.
The evidence from this
exercise suggests that the distribution
of jobs and incomes among industries
and occupations is much more complex
than the dichotomy that Sassen
suggests. The conclusion calls for a
nuanced understanding sensitive to
the multiple causes of inequality.
New York’s position as a global city is
closely bound up with the ability to
move vast quantities of money and
information rapidly (Wheeler 1990;
Mitchelson
and
Wheeler
1994).
Financial firms utilize an extensive
worldwide web of electronic funds
transfer networks that form the
nervous system of the international
economy, allowing them to move
FINANCE
EMPLOYMENT
CHANGE, AND INEQUALITY IN
NEW YORK
New York's hegemonic position in the
international
economy
may
be
interpreted as an outcome of the postFordist global division of labor that
Warf
112
The Industrial Geographer
capital around at a moment's notice,
arbitrage interest rate differentials,
take advantage of favorable exchange
rates, and avoid political unrest (Warf
1995; Solomon 1997). Such networks
create an ability to move money – by
some estimates, more than $3 trillion
daily (Solomon 1999) – around the
globe at the speed of light: subject to
the process of digitization, information
and capital became two sides of the
same coin. A global web of fiber optics
lines firmly links New York securities
traders to their counterparts in
London and elsewhere (Longcore and
Rees 1996), allowing money to be
switched in enormous volumes. The
world's currency markets, for example,
trade roughly $800 billion every day
(Solomon 1999). Every two weeks the
sum of funds that passes through New
York's fiber optic lines surpasses the
annual product of the entire world;
Salomon Brothers, which routinely
buys 35% of U.S. government bonds,
runs the equivalent of the nation's
total bank holdings through its
computers every year, while the New
York bond market trades on the order
of $150 billion daily (Cohen 1998).
The volatility of trading, particularly
in stocks, has also increased as hairtrigger computer trading programs
allow fortunes to be made (and lost) by
staying microseconds ahead of (or
behind) other markets.
heights. Between 1990 and 2000, the
total average volume of shares traded
per day on the NYSE rose from 170
million to 1.2 billion, a 705% rise, and
total capitalization in 2000 surpassed
$7.2 trillion. Although the New York
region has lost some of its dominance
in securities, its 150,000 jobs in this
sector still account for almost 30
percent of the nation's securities
employment.
Several reasons explain the recent
surge in stock prices and trading
volumes.
First, the U.S. economy
underwent a sustained period of rapid
GNP
and
productivity
growth.
Following the recession of 1990-1991,
a booming economy, low interest rates,
and a global glut in raw materials
(particularly
cheap
petroleum)
combined to fuel a highly profitable
boom.
In the wake of the
deindustrialization and restructuring
of the 1980s, U.S. manufacturing,
bolstered by the microelectronics
revolution, regained its competitive
strength internationally, fueling the
demand for investment capital.
National productivity growth, boosted
by the microelectronics revolution,
averaged more than three percent
annually in the 1990s. Meanwhile, a
wave of corporate downsizing and
layoffs constrained the growth in labor
income. (Note there is some dispute
as to whether current measures of
productivity reflect real productivity
gains accurately; some observers point
out the discrepancies between rising
returns to capital and constant
returns to labor as evidence that
marginal productivity gains have been
exaggerated by official statistics or
In the 1990s, New York’s stock
markets experienced a pronounced
"bull market."
Deregulation, a
booming national economy, and a
wave of corporate mergers, takeovers,
and leveraged buyouts propelled the
Dow Jones Industrial Average to new
Warf
113
The Industrial Geographer
that the link between the marginal
cost and productivity of labor has been
annulled).
These factors raised
corporate earnings and profitability, if
not wages, to record levels.
nation (Lord 1992). Other changes
included the removal of restrictions
governing pension and mutual fund
portfolios, the abolition of fixed
commissions
on
stock
market
transactions, the approval of foreign
memberships on stock markets, and
the current debate over the repeal of
the
Glass-Steagall
Act,
which
separated
commercial
from
investment banking since 1933.
Second,
the
financial
industry
witnessed widespread deregulation,
including the removal of numerous
federal
and
state
government
restrictions in savings, commercial
and investment banks.
In 1980,
Congress passed the Depository
Institutions
Deregulation
and
Monetary Control Act, and in 1982,
the Garn-St. Germain Act, which
permitted thrifts to compete directly
with commercial banks and eliminated
geographic limitations on Savings and
Loan lending.
Third, demographic changes, i.e., the
economic behavior of the enormous
baby boom generation, accentuated
these trends.
Entering its prime
earning and savings years, this
generation continues to pour resources
(primarily via mutual and pension
funds) into the stock market as well,
viewing it as the best long-term
investment. The growth of Internet
banking also encouraged numerous
small investors to play the market.
Accordingly,
the
proportion
of
American households that own stock
directly has risen to almost 50
percent, and millions more own them
indirectly.
For investment bankers, key issues
included the abolition of fixed
commissions
on
stock
market
transactions and the approval of
foreign
memberships
on
stock
exchanges.
Simultaneously, new
sources
of
investment
capital,
particularly mutual funds and pension
funds, for which controls had been
abolished,
were
introduced.
Deregulation unleashed an enormous
wave of investor-driven demand for
investments, most of which found its
way into commercial real estate and
the stock market, particularly in the
form of large investors who buy and
sell enormous quantities of stocks,
enhancing
volatility
and
marginalizing small traders.
The
relaxation of interstate banking
restrictions also heavily favored New
York, whose money-center banks
penetrated local markets around the
Warf
Of course, after 2000 the stock market
bubble burst in a classic “market
correction” that initiated a period of
decline. In the wake of the dot com
crash and national recession, the Dow
Jones dropped from its high of 11,000
in 2000 to 8,500 in 2002. The attacks
of September 11, 2001 accentuated
this decline, spurring rounds of panic
among the financial community in
lower Manhattan. However, in 2003
most of the ground lost since 2000 has
been recouped. Such swings indicate
that
volatility
has
become
114
The Industrial Geographer
institutionalized within the market.
immigration,
a
polarized
wage
structure characteristic of many
services, and public policy have
contributed to the yawning gap
between the poor and wealthy in many
such conurbations. The “jobs-skills
mismatch” between employers who
seek increasingly skilled labor and a
workforce that possesses insufficient
human capital exacerbates central city
unemployment. A literature on urban
poverty and the “underclass” has
documented the travails of those
caught under these circumstances
(Chakravorty
1996;
Fortin
and
Lemieux 1997; Small and Newman
2001; Strait 2000, 2001; Galster et al.
2003). White (1998) criticizes the dual
city thesis on the grounds that it is
economically reductionist and ignores
the state. More broadly, inquality
reflects an entire system of social
stratification – including occupational
change, racial and ethnic segregation,
poor educational systems, lack of
affordable housing, and spatial
isolation – that has evolved over time,
fed by various waves of immigration.
Sociologists often tie wage inequality
to shifts in family structures,
demographics, and educational levels
(Levy and Murnane 1992; Morris and
Western 1999; McCall 2000). National
level
policies,
particularly
the
increasingly regressive income tax
structure and the growth of unearned.
Perhaps no city in the U.S. more
dramatically
illustrates
the
globalization of finance and associated
inequalities than does New York
(Godfrey 1995). The New York region’s
shift into relatively highly skilled,
white-collar
service
occupations,
virtually all of which require a
LABOR
MARKETS
AND
INEQUALITY IN NEW YORK
The emergence of a global economy
centered upon producer services,
telecommunications, and hypermobile
capital has certainly not favored all
social groups equally. Even within the
most digitized of cities there remains
large pockets of "off-line" poverty, in
which the poor and disenfranchised
suffer the costs, but enjoy few of the
benefits, associated with globalization.
A lively debate over inequality in
global cities has thus emerged.
Sassen (1991), whose famous volume
The Global City initiated the debate,
maintained that globalization leads
directly to social polarization. She
held that the growth of the financial
sector, in particular, led to the
formation of a cadre of well-paying
positions on the one hand, typified by
managers, executives, and stock
brokers, and on the other hand, large
numbers of low-paying jobs, typically
filled by women and minorities, in
unskilled positions that cater to the
elite. For the former, large annual
bonuses are the norm (Figure 1); for
the latter, often struggling in
minimum wage jobs and with a steady
supply of workers moving to the region
from abroad, daily life becomes
increasingly difficult. For those at the
bottom of the socioeconomic ladder,
globalization can lead to diminished
social mobility (Badcock 1997).
Critics of Sassen, notably Hamnett
(1994a, 1994b, 1996a, 1996b, 1998),
focus on different causes of inequality,
including the relative degree to which
Warf
115
The Industrial Geographer
Figure 1: Total New York Securities Bonuses, 1990-2002 (nominal dollars).
25
$ billions
20
15
10
5
0
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002
Source: Securities Industry Association data. incomes, also contribute to this trend (Pinch 1993; Levine 1996).
As Castells and Mollenkopf (1991) note, such broad processes and divisions are too complex to be easily
summarized by the notion of a “dual city.”
university education, has stimulated
few opportunities for blue collar
workers who traditionally worked
with their hands (Warf 1990).
Deindustrialization and the limited
job mobility frequently exhibited by
workers unable (or often too old) to
retrain for new positions have thus
conspired to depress incomes for many
segments of the population. Thus,
New York is an ideal laboratory for
the empirical analysis of Sassen’s dual
city thesis.
employment were retail trade (997,000
in the 18 county MSA), health services
(823,000),
and
wholesale
trade
(565,000).
Such industries are
generally considered “non-basic,” i.e.,
reliant upon locally-earned incomes.
Propulsive sectors, in contrast, which
generate extra-local incomes, include
banking and securities (SIC 60 and 62,
totaling 379,000), legal services
(110,000), insurance (138,000), and
engineering
and
architecture
(223,000).
Labor markets in New York reveal a
diverse and complex mosaic (Table 1).
In the 1990s, total MSA employment
stayed constant at 6.5 million, but
declined in New York City and
Manhattan, testimony to the steady
growth of the suburbs. In 2000, the
largest industries in terms of
Whereas commercial banking in the
region suffered a 27% decline in
employment in the 1990s (from
225,000 to 181,000), securities grew by
16.9%, from 154,000 to 198,000.
Manhattan continues to enjoy an
unparalleled position of dominance
Warf
116
The Industrial Geographer
Table 1: Regional Distribution of Employment in New York City Metropolitan
Region, 1990-2000 (thousands).
1990 1990
1990
MSA NYC Manhattan
SIC
Total Employment 6,354.3 3,257.6 2,015.1
Total Manufacturing 1,062.0
368.4
215.6
23
27
48
50,51
52-59
60
62
63
65
70
73
78
79
80
81
82
86
87
Apparel
Printing/Publishing
Communications
Wholesale Trade
Retail Trade
Banking
Securities
Insurance
Real Estate
Hotels/Motels
Business Services
Motion Pictures
Entertainment
Health Services
Legal Services
Education
Nonprofits
Engin./Architect
129.1
164.4
112.4
590.6
1,047.3
225.1
153.9
127.2
155.7
64.8
499.0
44.5
73.8
716.5
114.6
184.3
112.9
223.0
91.7
93.0
61.3
157.8
388.3
145.7
130.0
57.6
99.2
35.4
258.9
35.0
36.6
352.4
76.0
117.5
59.5
117.9
60.0
80.7
49.3
150.9
202.8
126.7
129.1
51.7
73.2
32.2
214.8
32.1
29.5
134.3
70.3
78.3
40.3
103.0
2000
MSA
2000
2000
NYC Manhattan
6,503.5 3,277.8
825.7
264.7
93.6
128.8
126.2
564.8
997.3
181.2
197.9
138.2
149.6
54.0
542.5
32.8
81.3
823.4
110.0
199.8
115.7
223.3
66.6
66.6
62.3
196.5
372.8
113.8
153.6
65.1
100.2
30.4
246.1
21.5
42.7
408.3
68.6
123.8
56.1
112.3
---------% Change-------MSA
NYC Manhattan
1,858.5
151.2
2.3
-22.3
-5.9
-28.1
-7.8
-29.9
42.4
58.0
47.6
125.8
200.0
91.9
150.9
61.2
68.1
27.3
201.3
18.6
34.4
151.7
63.1
79.3
36.1
96.8
-27.5
-21.7
12.3
-4.4
-4.8
-19.5
28.6
8.7
-3.9
-16.7
8.7
-26.3
10.2
14.9
-4.0
8.4
2.5
0.1
-27.4
-28.4
1.6
23.8
-4.0
-21.9
18.2
13.0
1.0
-14.1
-4.9
-38.6
16.7
15.9
-9.7
5.8
-5.7
-4.7
-29.3
-28.1
-3.4
-16.6
-1.4
-27.5
16.9
18.4
-7.0
-15.2
-6.3
-42.1
16.6
13.0
-10.2
1.3
-10.4
-6.0
New York Metropolitan Statistical Area defined as New York City and Nassau, Suffolk, Westchester,
Putnam, Rockland counties in New York State and Bergen, Essex, Hudson, Middlesex, Morris, Passaic,
Somerset and Union counties in New Jersey
Source: calculated from County Business Patterns
within the regional economy: many
firms prefer to concentrate there even
though it exhibits the highest
commercial rents, wages, taxes and
congestion in the country.
This
primacy, however, is gradually being
eroded as firms have relocated to the
suburbs; continued change in this
direction will eventually make the
employment landscapes of New York
more closely resemble those of other
U.S. metropolitan regions, in which
the vast majority of jobs are found on
the metropolitan periphery.
Warf
Despite a booming regional economy
in the 1990s, life for many New
Yorkers got harder in the 1990s.
Whereas per capita income between
1990 and 2000 rose from $21,291 to
$22,402, median family income
actually declined, from $44,828 to
$41,887
(http://www.nyc.gov/html/dcp/pdf/cens
us/sociopp.pdf).
Poverty is still
widespread in New York City: in 2001,
1.4 million people, or 20%, lived below
the poverty line, including 28.7% of
Latinos, 25.1% of non-Latino blacks,
and 45% of all female-headed
117
The Industrial Geographer
households with children (Levitan
2003). While the poverty rate among
largely white professionals and
managers was 2.8%, it was 10.7% for
blue-collar
workers,
who
are
disproportionately minorities. Onequarter of the city’s population
receives public assistance.
The
homeless population may range as
high as 100,000.
Beset by
unemployment, high crime rates,
inadequate educational opportunities,
and other social pathologies, life for
many unskilled, poorly educated
residents has grown worse, not better,
in the face of increasing globalization.
In poor, predominantly minority
neighborhoods such as Harlem, the
south Bronx, and Brooklyn’s BedfordStuyvesant,
an
“underclass”
disenfranchised by the labor market
lives in the shadow of the world’s
largest collection of financial firms.
Rarely are the contradictions of
capitalism revealed so bluntly and
with such poignancy. The next step in
this analysis offers a methodology for
investigating
these
consequences
analytically to assess the degree to
which inequality in New York is
attributable to the growth of financial
services.
demand for output of the securities
industry.
The increase in final
demand during this period was
calculated using the I-O relationships
between output per employee, x/e,
changes in employment, ∆e, and
changes in final demand, ∆f, in the
securities industry. The I-O relation
among these three variables is
∆fi = (1/mii)(xi/ei)∆ei,
where i denotes the securities
industry; mii is the I-O multiplier
(Type I, excluding consumptioninduced effects) for the securities
industry; ∆f i is the computed change in
final demand for the securities
industry consistent with the increase
in employment in the 1990-2000 time
period. In standard I-O fashion, the
model assumes linear production
functions, no economies of scale, and
infinite elasticities of substitution.
The change in output in each industry
generated by the increase the final
demand for securities services was
computed using the I-O equation
∆x = M-1 ∆fi
(2)
where ∆x is a column vector of output
changes in each of the industries in
the I-O model; M-1 is the Leontief
inverse matrix (see Miller and Blair
1985). Column vector ∆fi indicates the
volume of change in final demand for
securities ($2.1 billion); all elements
other than that representing the
securities industry are zero.
MODELING THE IMPACTS OF
THE 90S BOOM
The analytical approach centered on a
34-sector input-output (I-O) model for
the New York Metropolitan Statistical
Area based on the 2000 Bureau of
Economic Analysis's RIMS II model.
The total effects of new hirings
between 1990 and 2000 – the period of
the great stock market boom – were
analyzed as an increase in final
Warf
(1)
This approach allows estimates of
output
to
be
converted
into
employment change. Total change in
118
The Industrial Geographer
employment
by
industry
were
calculated by multiplying the vector
representing change in output by a
series
of
associated
employment/output ratios derived
from the RIMS II model. The total
number of jobs generated in every
industry, ∆e, was computed by
premultiplying
the
changes
in
industry output by a diagonal matrix
of output-to-employment coefficients
for every industry, N, or
the growth of the securities industry
were computed using the changes in
output calculated in equation (2).
Data regarding the 2000 distribution
of wage and salary income and
business income per unit of output by
industry were obtained from the
Bureau of Economic Analysis’ REIS
system.
Variations among output,
jobs, and incomes thus reflect interindustry linkages and associated
multiplier effects, the relative capital
or labor-intensity among industries,
and the personal and business income
levels per unit of output in each sector.
∆e = N∆x
(3)
Changes in employment by industry
may not be sufficiently accurate to
assess
issues
of
inequality.
Occupations in many ways are a more
meaningful measure of the skills and
income changes associated with
globalization.
Thus, employment
changes by industry were decomposed
into occupational groups using a
rectangular block-diagonal matrix of
coefficients, K, which represents the
distribution of jobs in each industry
among eight occupational groups.
Algebraically, changes in employment
by occupation can be calculated as
The results of this exercise include
growth in output, jobs, and personal
and business income. The 1990-2000
growth in securities and commodities
employment in New York generated
approximately
$3.35
billion
in
additional total output and 119,000
new jobs of employment above the
1990 level (Table 2), indicating an
average output multiplier of 1.6 and
average employment multiplier of 2.45
(118,000/48,000). The impacts varied
widely among sectors.
Because it
enjoyed the both the direct effects of
the stock boom (i.e., increase in final
demand) and some of the indirect ones
generated by the multiplier effects,
the Finance, Insurance, and Real
Estate (FIRE) sector witnessed the
vast majority of increased output ($2.4
billion), or roughly 68% of the total.
FIRE's share of total employment
gains, 47,691 jobs or 41% of the total,
was much smaller than its share of
additions to output, a reflection of the
industry's increasingly high rates of
labor
productivity
and
capital
intensity.
∆o=KN∆x,
(4)
where ∆o is a column vector of the
change in employment by occupation
for each industry. Each block on the
main diagonal of K is a column vector
of
coefficients
that
allocates
employment changes in each industry
among occupations.
Last, changes in each industry's total
wage and salary income induced by
Warf
119
The Industrial Geographer
Table 2: Estimated Increases in Output and Employment due to Growth in Stock
Market, 1990-2000.
Sector
($ Millions) Jobs
368
Agriculture & fishing
9.0
2,149
Mining and petroleum
32.2
5,238
Construction
123.9
1,180
Foods & tobacco
14.1
1,338
Textiles
6.6
2,116
Wood and paper
39.8
2,940
Publishing
82.6
968
Chemicals
44.1
1,033
Rubber and plastics
10.5
35
Leather and footwear
.8
238
Stone and glass
2.6
204
Fabricated metals
30.1
4,094
Electronic equipment
118.4
390
Transport equipment
7.6
180
Scientific equipment
6.1
251
Misc. manufacturing
7.0
2,324
Land transport
17.0
94
Water transport
1.4
1,455
Air transport
3.9
118
Transport services
3.8
2,907
Communications
106.4
4,075
Utilities
35.3
5,365
Wholesale/retail trade
72.6
47,691
FIRE
2,385.4
1,555
Hotels
27.4
11,702
Personal & repair services 207.0
10,290
Business services
272.3
345
Entertainment
5.4
2,436
Health services
142.6
1,197
Legal services
20.3
278
Education
1.7
288
Nonprofit
3.5
2,832
Federal government
49.8
1,212
State & local government 6.2
118,888
TOTAL
3,348.0
Source: calculated by author.
Warf
120
The Industrial Geographer
Other industries that saw significant
increases in output and employment
attributable to the boom included
business services ($272 million and
10,290 jobs), personal and repair
services ($207 million and 11,702
jobs), construction ($123 million and
5,238 jobs), wholesale/retail trade
($72.6 million and 5,365), and
electronic equipment ($118 million
and 4,094 jobs), all of which have
extensive
forward
or
backward
linkages to FIRE. In contrast, most
manufacturing sectors, transportation,
and certain services (e.g., health,
education, government) were only
marginally affected.
These results
speak to the limited inter-industry
linkages exhibited by the FIRE sector;
the relatively self-contained complex
of advanced producer services thus
tends to contain its propulsive effects
within a narrow group of affected
sectors.
patterns of inter-industry linkages
through which multiplier effects
flowed as well as the organization of
occupations
within
each
major
industrial group. The fact that the
bulk of new jobs generated by the
growth of New York’s security
industry are not highly skilled should
not be surprising. Sassen (1994:105)
notes that "there is a tendency to
assume that advanced industries, such
as finance, have mostly good, whitecollar jobs when in fact they also have
a significant share of low-paying jobs,
from cleaners to stock clerks."
Inequality is thus produced within as
well as among industries.
Finally, the personal income (wages
and salaries) and business income
(profits) effects of the stock boom were
considerable
(Table
4),
totaling
approximately $13.6 and $21 billion,
respectively.
As with output and
employment,
the
FIRE
sector
dominated both sets of impacts,
including $4.4 billion in personal
income (including large bonuses paid
to brokers) and $16.9 billion in
corporate profits. Other industries to
receive significant income boosts
included personal and repair services
($3.4 billion and $862 million in
personal
and
business
income,
respectively), communications ($816
and $600 million), and business
services ($787 and $313 million).
The occupational distribution of the
employment generated by the stock
boom differed from that of the U.S.
labor force as a whole (Table 3). The
relative distribution of jobs generated
by the stock boom included fewer in
managerial
and
professional
occupations (19.1%) than the nation as
a whole (29.8%), but significantly
larger shares of craft workers and
operators and laborers (39.8% v.
22.5%).
The stock market boom
appears to have generated larger
numbers of semi-skilled and modestly
paying positions than highly paid ones
in finance, popular stereotypes of Wall
Street
yuppies
notwithstanding.
These
distributions
reflect
the
Warf
CONCLUDING REMARKS
As Knox (1995:236) argues, global
cities "facilitate the articulation of
regional and metropolitan resources
and impulses into globalizing processes
121
The Industrial Geographer
Table 3: Occupational Distribution of Employment Impacts of Stock Market
Increase.
Boom-induced job
Jobs
% U.S. %
Managers
11,425
9.6
12.9
Professionals
11,305
9.5
16.9
Sales brokers
7,496
6.3
4.8
Clerical workers
20,707
17.4
24.8
Unskilled sales
20,589
17.3
18.1
Craft workers
32,847
27.6
9.1
Operators/laborers
14,519
12.2
13.4
Total
118,888 100.0 100.0
Source: calculated by authors
while, conversely, mediating the
impulses of globalization to local
political economies."
gradually
losing
its
share
of
employment, which may indicate its
advantage as a global city may not
last indefinitely (Markusen and
Gwiasda 1994).
Nor is globalization confined to purely
economic processes, for it includes
political and cultural forms as well.
All of these shape local urban
governance,
including
municipal
budgets, expenditure priorities, and
financing strategies (e.g., publicprivate partnerships).
This line of thought leads to two
important conclusions.
First, the
idiographic structure of New York –
its regionally-specific occupational
structure, inter-industry linkages,
patterns of consumption, and regimes
of governance – serves as important
reminders that globalization is not
telescoped into individual contexts
uniformly throughout the world.
Rather, national, regional, and local
factors mediate these trends in
important, contingent, and often
unpredictable ways. Thus, simplistic
claims about the “end of geography”
(e.g., O’Brien 1992) may be dispensed
without
further
consideration.
Second, these results serve to eschew
mechanistic views of global cities that
hold
their
inequalities
a
unproblematic
results
of
the
concentration of financial services.
Thus, to understand globalization and
global cities in all of their complexity,
urban analysis must bring to bear a
nuanced comprehension of how the
generalized dynamics of the worldsystem interact with the unique,
locally-specific contexts of individual
locales in contingent, and often
unpredictable, ways. That the labor
markets and built environment of New
York are intertwined with a variety of
global processes has long been evident
to many observers. Compared to the
U.S. as a whole, New York has been
Warf
122
The Industrial Geographer
Table 4: Personal and Business Income due to Growth in Stock Market,
1990-2000($millions).
Personal Business
Income
Agriculture and fishing
14.4
6.4
Mining and petroleum
84.3
101.8
Construction
579.8
144.8
Foods & tobacco
69.9
26.9
Textiles
38.8
18.6
Wood and paper
75.1
134.7
Publishing
321.1
330.8
Chemicals
41.3
121.5
Rubber and plastics
84.0
36.0
Leather and footwear
8.2
3.0
Stone and glass
28.7
10.4
Fabricated metals
115.8
14.1
Electronic equipment
181.8
79.4
Transport equipment
15.6
29.9
Scientific equipment
221.9
28.1
Misc. manufacturing
14.1
23.1
Land transport
124.3
105.8
Water transport
5.4
3.4
Air transport
257.4
209.5
Transport services
62.6
19.9
Communications
816.1
599.7
Utilities
217.2
68.9
Wholesale/retail trade
173.3
141.1
FIRE
4,420.9
16,899.5
Hotels
185.3
98.8
Personal & repair services
3,450.4
862.8
Business services
787.2
313.8
Entertainment
106.1
17.0
Health services
124.2
8.1
Legal services
167.8
71.2
Education
38.5
4.5
Nonprofit
217.4
20.8
Federal government
487.2
403.2
State & local government
55.3
24.9
TOTAL
Warf
Income
13,591.5
20,982.6
Source: calculated by author.
123
The Industrial Geographer
Sassen’s (1991) well-known model, for
example, examines only Manhattan,
and its loose methodology fails to take
into
account
the
inter-industry
linkages that suture the FIRE sector
to other parts of the regional economy.
It is evident that the processes
producing inequality in New York are
considerably more diverse, including
the proliferating linkages to be found
in business services, law firms,
accounting, advertising, real estate,
and tourism.
Moreover, this view
ignores other causes of inequality,
including the immigration of low
skilled migrants and the offshoring of
manufacturing jobs. To the degree
that the growth of finance may create
inequalities, such effects are dwarfed
by other causes.
Indeed, as this
analysis indicates, the bulk of jobs
created by the great boom of the 1990s
favored low skilled occupations in
personal services, retail trade, and
craft positions. Put simply, New York
is more complex than most current
depictions of global cities have allowed
themselves to admit. In light of these
complexities, it is important to avoid
demonizing the financial sector and to
allow for more subtle understandings
of regional inequality than that
afforded by the “dual city” approach.
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126
The Organizational Structure & Spatial Dynamics of Investment Advisory
Services: The Case of Metropolitan Philadelphia, 1983-2003
John E. Bodenman
Department of Geography and Geosciences
Bloomsburg University
Bloomsburg, PA 17815
ABSTRACT
This article examines the organizational structure and spatial dynamics of the institutional
investment advisory industry, 1983-2003, focusing on the Philadelphia Metropolitan Area.
Traditionally, high order financial services located in Pennsylvania like institutional investment
advisory services have been concentrated in the Philadelphia Central Business District (CBD).
However, analysis of the industry's organizational structure and spatial dynamics over the 19832003 study period indicates significant growth of the industry within the Philadelphia
Metropolitan Area, but relative decline within the traditional core--the Philadelphia CBD. The
Money Management Directory of Pension Funds and their Investment Advisors (1983-2003)
provides the data for the analyses. Maps and tables describe the institutional investment
advisory industry's spatial organization at both the inter- and intrametropolitan scales.
Key words: investment advisory services, financial services, location
INTRODUCTION
The tremendous growth of the multitrillion dollar institutional investment
advisory industry 1 over the 1983-2003
study period, is emblematic of the
nation's transition to an "information
economy" (Hepworth 1990; 1991). With
over $18 trillion in total assets under
management in 2003, the location of
institutional investment advisory firms
represent financial "control points" in the
nation's economic geography (Borchert
1978; Green 1993; Graves 1998;
Bodenman
2000).
Furthermore,
information-intensive financial services
providers like institutional investment
advisory
firms
have
traditionally
anchored downtowns (Stanback 1991;
Carlino 2001), and thus their locational
dynamics should be of particular interest
1 The investment advisory industry consists of investment
advisory firms that manage the securities portfolios of
institutional clients for a fee.
to all concerned with the vitality of urban
centers in the United States.
The great majority of research exploring
the locational dynamics of financial
services
activities
suggests
that
information intensive financial services
are disproportionately concentrated in the
cores of the largest metropolitan areas
due to (1) the importance of trusted faceto-face contacts in the decision making
process at the highest level, (2) the
existence of a business/social milieu, (3)
prestige of a given place, (4) the
importance of fixed assets in the Central
Business District (CBD) that could be
devalued in the case of owner exodus, and
(5) agglomeration of ancillary services,
including networks, telecommunications,
and "knowledge spillovers" (Carlino 2001;
Clark 2000; Daniels 1993; Sassen 1991;
Castells 1989). More specifically, there
is general agreement that spatial
concentration in high order urban centers
promote: (1) opportunities for backward
The Industrial Geographer, Volume 2, Issue 2, pp.128-146 ©2004 Bodenman
The Industrial Geographer
linkages (i.e., database services, business
and financial information services,
computer and other technical services);
and (2) opportunities for forward linkages
(i.e.,
markets).
Theoretically,
concentration allows firms to maximize
opportunities for both forward and
backward linkages, and minimize the
transaction costs associated with the
production and delivery of financial
services (Bloomfield et al. 2000; Lee 2000;
Daniels 1993).
companies to 8%. Though pension funds
(tax-exempt assets) are by far the largest
source of managed funds, investment
advisory firms also take in billions of
dollars
from
profit-sharing
plans,
employee savings plans, unions, state and
local governments, endowments, and
foundations.
The primary investment
vehicles are transferable securities and
equity products that include stocks,
bonds, commercial paper and derivative
products like futures, options and swaps.
Table 1a lists the top twenty investment
advisory firms in the United States
ranked by total tax-exempt assets under
management in 2003. Table 1b lists the
top twenty investment advisory firms
located in the state of Pennsylvania.
Note
that
the
largest
firm
in
Pennsylvania, The Vanguard Group
(Table 1b), is the fourth largest advisory
firm in the United States (Table 1a).
This
article
will
highlight
the
organizational structure and locational
dynamics of the investment advisory
industry in Pennsylvania, 1983-2003,
focusing on Metropolitan Philadelphia.
First, I will provide a general background
of the institutional investment advisory
industry in Pennsylvania. Second, I will
provide an overview of the Money Market
Directory data sets used for the tables,
maps, and figures compiled for analysis.
Finally, I will conclude with several
suggestions for the direction of future
research on this topic.
The purpose of this article is to examine
the locational dynamics of the investment
advisory industry in the state of
Pennsylvania.
The
institutional
investment management business--the
management of pension and endowment
assets for a fee--is an excellent example of
an important information intensive
financial services industry that has grown
dramatically over the 1983-2003 study
period.
Geographical analysis of the
institutional
investment
advisory
industry at both the inter- and intrametropolitan scales will provide a basis
for examining the extent to which
concentration, dispersal and/or both
processes are operating with respect to
the industry's locational pattern within
Pennsylvania as the information economy
continues to mature.
BACKGROUND
Until the 1970s, the vast majority of
investment managers and their traders
worked for banks and insurance
companies.
Independent investment
advisory firms of any size first appeared
in the early 1960s and proliferated in the
1970s and 1980s, when clients began
demanding more aggressive investment
strategies. Figure 1 illustrates that, in
1983, independent investment advisory
firms (also referred to as investment
management firms) managed 30% of the
total assets under management, while
banks and trusts ran 34%, and insurance
companies 35%. By 2003, independent
investment advisory firms had increased
their share of managed assets to more
than 86% of the $21.3 trillion in total
assets under management, with banks
and trusts dropping to 4% and insurance
Bodenman
DATA AND ANALYSIS
The data to map investment management
firm
locations
and
assets
under
management
were
obtained
from
Standard & Poor’s: The Money Market
129
The Industrial Geographer
Directory of Pension Funds and Their
Investment Managers (1983; 2003).
Based on both SEC licensing information
and individual firm surveys, the directory
provides a profile of every institutional
investment management firm managing
assets for a tax-exempt fund sponsor
headquartered in the United States with
over $1 million in total assets. The assets
under management include corporate,
state and local government, and union
plan sponsored employee benefit funds
(all tax-exempt), as well as endowment
and foundation funds (also tax-exempt).
and 76.3% of the total firms with assets
under management in 1983.
By 2003, total tax-exempt assets under
management had grown to $7.9 trillion,
and the number of investment advisory
firms to 897 (Table 2b). Figures 1b and
2b illustrate the tremendous growth of
assets under management in the
traditional core (New York, Boston,
Chicago, Los Angeles and San Francisco),
but also in an increasing number of newly
emerging centers. By 2003, Philadelphia
is ranked 5 ahead of Chicago with 5.4% of
total assets, and 2.8% of total firms.
Overall,
the
total
assets
under
management in the top 20 MSAs
increased to nearly $7.2 trillion, but the
top 20 MSAs share of the total decreased
from 94.4% (Table 3a and Figure 1a) to
91.8% percent (Table 3b and Figure 2a).
Similarly, the top 20 MSAs share of total
firms decreased from 76.3% in 1983
(Table 3a and Figure 2a) to 67.4% in 2003
(Table 3b and Figure 2b).
In short,
industry
deconcentration
at
the
intermetropolitan scale, albeit in a
relatively small number of newly
emerging centers.
Institutional investment advisory firms
produce a constantly evolving and varied
mix of products and services that are sold
to institutional investors, clients with a
minimum of $1 million tax-exempt assets
invested. Defining and measuring the
aggregate value of the output produced by
the industry is problematic. However,
given that investment advisory firm
revenues (fees) are based on a percentage
of the assets they have under
management,
total
assets
under
management serves as a surrogate
measure of the industry's output, and
relative asset size provides an indicator of
the market shares held by individual
firms, as well as the changes in shares
over time.
Geographically, the 532 institutional
investment advisory firms with over $411
billion in assets under management in
19832 were located in 133 cities in 30
states across the nation (Table 2a). By
2003, the total number of firms managing
tax-exempt assets had grown to 897 firms
with nearly $7,937 trillion in assets under
management located in 287 cities in 46
states (Table 2b). By 2003, the state of
Pennsylvania ranked fourth overall, with
nearly $525 billion under management by
51 firms (Table 2b). Figures 1a and 2a
illustrate the spatial distribution of
assets under management and number of
investment
advisory
firms
by
INTERMETROPOLITAN
DISTRIBUTION
Table 3a indicates that in this initial
year, the top ranked MSAs by percent of
total assets and percent of total firms
included New York, Boston, Chicago, San
Francisco, and Los Angeles. The highest
ranked MSA in the state of Pennsylvania
was Philadelphia, ranked 8 th behind
Houston and Baltimore with 2.9% of total
assets, and ranked 6th behind Los Angeles
with 3.8 % of total firms. Overall, the 20
highest-ranking MSAs accounted for
94.4% of the assets under management,
2 All 1983 assets are reported in constant 2003 dollars.
Bodenman
130
The Industrial Geographer
metropolitan area in 1983--a total of $411
billion under management by 532 firms.
$525 billion in tax-exempt assets under
management.
Furthermore,
the
Philadelphia MSA (ranked 5th ahead of
Chicago) and the Pittsburgh MSA
(ranked 11th ) had a combined $520 billion
in tax-exempt assets under management
between them in 2003, or over 98 percent
of the total assets under management in
the state of Pennsylvania (Table 3b).
But what about the investment advisory
industry's ties to the central business
district (CBD)? Are these weakening as
well? Are the deconcentration trends at
the intermetropolitan level also occurring
at the intrametropolitan level? Tables 4a
and 4b indicate that the top 20 ranked
Cities (the urban cores of MSAs) share of
total assets and total firms declined from
90.2% and 65.2% respectively in 1983
(Table 4a), to 88.3% and 39.7%
respectively in 2003 (Table 4b). Certainly
of note is New York City’s drop from 1st to
2nd
behind Boston in the wake of
September11, 2001. However, also of
note is the emergence of new centers such
as Malvern (6), Plainsboro (7), Pasadena
(13), Cambridge (18), Purchase (19), and
Westport (20). Overall, the emergence of
new centers, and the decreasing relative
shares of the traditional investment
advisory urban cores 1983-2003, suggests
that deconcentration is also taking place
at the intrametropolitan level.
However, data at the intrametropolitan
scale (Tables 4a and 4b) indicate
significant relative decline for the city of
Philadelphia relative to the suburbs.
Table 4a indicates that in 1983 the city of
Philadelphia ranked 9th overall in assets
under management, and 6th overall in
total firms. By 2003, however, Table 4b
indicates that the city of Philadelphia
falls out of the top 20 with $32 billion
under management. The Philadelphia
suburb of Malvern, however, appears in
the top 20, ranked 6th overall in total
assets with $291 billion, more than the
city of Pittsburgh ($119 billion) and
Philadelphia ($32 billion) combined.
In Figure 3a, Philadelphia stands out as
the investment management center of
Pennsylvania, the location to firms with
$8.9 billion in tax-exempt assets under
management in 1983, representing 65.7
percent of the total tax-exempt assets
under management in Pennsylvania
(Table 5).
By 2003 (Figure 3b), the
southeast corner of the state still appears
to be the center of the industry, but
Philadelphia is no longer the top city in
terms of total assets under management.
INTRAMETROPOLITAN
DISTRIBUTION
As discussed earlier, the investment
advisory firms with tax-exempt assets
under management in 1983 were located
in 133 cites in 30 states across the nation
(Table 2a). By 2003, the number of cities
and towns with firms managing taxexempt assets had grown to 287 in 46
states (Table 2b). Where is investment
advisory industry growth occurring? In
the traditional financial centers of each
respective state? Or in new locations
outside of the traditional financial
centers?
Table 5 indicates that Malvern, home of
The Vanguard Group, is ranked first in
2003 with over $291 billion in total
assets, followed by Pittsburgh (2nd) with
nearly $120 billion, almost four times the
assets under management in the city of
Philadelphia (4th ) with $32 billion. Also
ahead of Philadelphia is the suburb of
Focusing on Pennsylvania, Table 2b
indicates that the state ranks 4th behind
New
York,
California,
and
Massachusetts, and is home to 51
investment advisory firms with nearly
Bodenman
131
The Industrial Geographer
Figure 1: Percent of Total Assets Under Management by Type of Investment Manager,
1983 and 2003.
100
90
80
70
60
50
40
30
20
10
0
Investment Advisors
Banks and Trusts
Insurance Companies
Real Estate Advisors
Type of Investment Manager
Percent of Total Assets, 1983
Percent of Total Assets, 2003
Source: Money Market D irectory, 1983; 2003.
Table 1a:
Top 20 Investment Advisory Firms in United States Ranked by
Total Tax-Exempt Assets Under Management, 2003
Rank
1
2
3
4
5
6
Firm Name
Barclays Global Investors
State Street Global Advisors
Fidelity Management & Research Co.
The Vanguard Group
Merrill Lynch Investment Managers
Capital Research Mangement Co.
7
Pacific Investment Management Co.
8
9
10
11
12
13
14
15
16
17
18
19
20
J.P. Morgan Fleming Asset Management
UBS Global Asset Management
Alliance Bernstein Inst. Investment Management
Deutsche Asset Management
INVESCO
Morgan Stanley Investment Management
Goldman, Sachs & Co., Asset Management
Banc One Investment Advisors Co.
Evergreen Investments
General Motors Investment Management
CDC IXIS Asset Management North America
BlackRock, Inc.
Western Asset Management
Source: Money Management Directory, 2003.
Bodenman
132
City
San Francisco
Boston
Boston
Malvern
Plainsboro
Los Angeles
Newport
Beach
New York
Chicago
New York
New York
Atlanta
New York
New York
Columbus
Boston
New York
Boston
New York
Pasadena
$
Millions
CA
696,276
MA
613,840
MA
339,500
PA
290,494
NJ
254,054
CA
247,382
CA
229,317
NY
IL
NY
NY
GA
NY
NY
OH
MA
NY
MA
NY
CA
212,562
194,345
193,048
148,548
140,233
133,618
122,723
112,863
111,447
107,400
93,000
87,511
87,502
The Industrial Geographer
Table 1b:
Top 20 Investment Advisory Firms in Pennsylvania Ranked by
Total Tax-Exempt Assets Under Management, 2003
Rank
Firm Name
City
$ Millions
1
The Vanguard Group
Malvern
290,494
2
Mellon Bond Associates
Pittsburgh
62,250
3
Gartmore Group
Conshohocken
39,758
4
Federated Investors
Pittsburgh
32,367
5
Mellon Equity Associates
Pittsburgh
18,425
6
Delaware Investment Advisers
Philadelphia
18,036
7
Rittenhouse Financial Services
Radnor
9,019
8
Aronson & Partners
Philadelphia
6,311
9
Rorer Asset Mgmt.
Philadelphia
5,862
10
Turner Investment Partners, Inc.
Berwyn
4,674
11
Chartwell Investment Partners
Berwyn
4,492
12
Geewax, Terker, & Co.
Chadds Ford
3,382
13
MDL Capital
Pittsburgh
3,127
14
Wellington Management Company
Radnor
2,971
15
1838 Investment Advisors
King of Prussia
2,877
16
McGlinn Capital Mgmt. Inc.
Wyomissing
1,937
17
Valley Forge Asset Management
Valley Forge
1,850
18
C.S. McKee & Co. Inc.
Pittsburgh
1,791
19
Schneider Capital
Wayne
1,581
20
Cooke & Bieler, Inc.
Philadelphia
1,329
Source: Money Management Directory, 2003.
Table 2a:
Percentage of Total Tax-Exempt Assets and Percentage of Total Firms with Tax-Exempt Assets
Under Management in the Top 20 States, 1983.
Rank
State
Millions*
Firms
% of
Total
Assets
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
New York
Massachusetts
California
Illinois
Connecticut
Texas
Pennsylvania
Maryland
Minnesota
Georgia
New Jersey
Washington
Oregon
Wisconsin
Florida
Ohio
Virginia
Missouri
Kentucky
Colorado
Others (10 states)
Total (30 states)
139,654
77,343
31,871
30,549
26,312
26,163
13,569
13,336
7,663
6,627
5,552
5,175
3,733
3,616
2,820
2,730
2,288
2,258
1,986
1,432
6,663
411,339
154
50
77
27
19
18
27
10
8
13
14
6
4
8
8
19
9
9
2
12
38
532
33.95
18.80
7.75
7.43
6.40
6.36
3.30
3.24
1.86
1.61
1.35
1.26
0.91
0.88
0.69
0.66
0.56
0.55
0.48
0.35
1.62
100.00
1983
$ in
# of
*1983 Assets reported in constant 2003 dollars.
Source: Money Market Directory, 1983.
Bodenman
133
% of Total
Firms
28.95
9.40
14.47
5.08
3.57
3.38
5.08
1.88
1.50
2.44
2.63
1.13
0.75
1.50
1.50
3.57
1.69
1.69
0.38
2.26
7.14
100.00
The Industrial Geographer
Table 2b:
Percentage of Total Tax-Exempt Assets and Percentage of Total Firms with
Tax-Exempt Assets Under Management in the Top 20 States, 2003.
2003
$ in
# of
% of Total
% of Total
Rank
State
Millions
Firms
Assets
Firms
1
California
1,880,253
138
23.69
15.38
2
Massachusetts
1,766,633
74
22.26
8.25
3
New York
1,616,884
163
20.37
18.17
4
Pennsylvania
524,131
51
6.60
5.69
5
Illinois
359,823
57
4.53
6.35
6
New Jersey
298,585
26
3.76
2.90
7
Connecticut
258,329
42
3.25
4.68
8
Georgia
222,970
20
2.81
2.23
9
Ohio
180,442
24
2.27
2.68
10
Minnesota
129,639
25
1.63
2.79
12
Maryland
92,368
25
1.16
2.79
13
Colorado
81,592
21
1.03
2.34
14
Missouri
60,377
12
0.76
1.34
15
North Carolina
52,470
13
0.66
1.45
16
Virginia
44,062
27
0.56
3.01
17
Florida
43,676
19
0.55
2.12
18
Wisconsin
28,332
20
0.36
2.23
19
Michigan
21,149
14
0.27
1.56
20
Tennessee
20,271
12
0.26
1.34
Others (26 states)
133,070
87
1.68
9.70
Total (46 states)
7,936,568
897
100.00
100.00
Source: Money Market Directory, 2003.
Bodenman
134
The Industrial Geographer
Table 3a:
Percentage of Total Tax-Exempt Assets and Percentage of Total Firms with
Tax-Exempt Assets Under Management in the Top 20 MSAs, 1983.
$
in
1983
# of
%
of %
Total
Total
Rank
Metro Area
State Millions* Firms Assets
Firms
1
New York
NY
139,155
150
33.83
28.20
2
Boston
MA
77,307
49
18.79
9.21
3
Chicago
IL
30,549
27
7.43
5.08
4
26,680
30
6.49
5.64
5
San Francisco
CA
Los
Angeles-Long
Beach
CA
17,424
35
4.24
6.58
6
Houston
TX
13,463
12
3.27
2.26
7
Baltimore
MD
13,134
8
3.19
1.50
8
Philadelphia
PA
11,730
20
2.85
3.76
9
Stamford-Norwalk
CT
11,400
6
2.77
1.13
10
Minneapolis-St. Paul
MN
7,663
8
1.86
1.50
11
Atlanta
GA
6,627
13
1.61
2.44
12
CT
5,489
8
1.33
1.50
13
Hartford
Seattle-BellevueEverett
WA
5,167
5
1.26
0.94
14
Anaheim-Santa Ana
CA
3,880
7
0.94
1.32
15
Newark
NJ
3,741
5
0.91
0.94
16
Portland
OR
3,733
4
0.91
0.75
17
Bridgeport
CT
3,398
5
0.83
0.94
18
Milwaukee-Waukesha WI
3,235
6
0.79
1.13
19
Kansas City
MO
2,333
6
0.57
1.13
20
Louisville
KY
1,986
2
0.48
0.38
406
94.35
76.32
Total
388,094
*1983 Assets reported in constant 2003
dollars.
Source: Money Market D irectory, 1983.
Bodenman
135
of
The Industrial Geographer
Table 3b:
Percentage of Total Tax-Exempt Assets and Percentage of Total Firms with
Tax-Exempt Assets Under Management in the Top 20 MSAs, 2003.
2003
$ in
# of
% of Total
%
of
Total
Rank
Metro Area
State
Millions
Firms
Assets
Firms
1
New York
NY
1,915,469
179
25.79
15.16
2
Boston
MA
1,763,501
74
23.75
6.27
3
San Francisco-Oakland
CA
1,072,379
58
14.44
4.91
4
Los Angeles-Long Beach
CA
475,671
42
6.41
3.56
5
Philadelphia
PA
400,262
33
5.39
2.79
6
Chicago
IL
369,711
50
4.98
4.23
7
Atlanta
GA
222,508
15
3.00
1.27
8
Stamford-Norwalk
CT
215,777
29
2.91
2.46
9
Anaheim-Santa Ana
CA
141,375
9
1.90
0.79
10
Minneapolis-St. Paul
MN
128,075
20
1.72
1.69
11
Pittsburgh
PA
119,604
12
1.61
1.02
12
Columbus
OH
112,863
2
1.52
0.17
13
Denver-Boulder
CO
90,151
18
1.21
1.52
14
Baltimore
MD
83,794
18
1.13
1.52
15
Houston
TX
58,155
15
0.78
1.27
16
Cleveland
OH
50,680
5
0.68
0.42
17
Kansas City
MO
44,237
3
0.60
0.22
18
San Diego
CA
43,116
12
0.58
1.02
19
Fort Lauderdale -Hollywood
FL
40,386
2
0.54
0.17
20
Dallas-Fort Worth
TX
35,440
9
0.48
0.76
7,383,154
605
93.03
67.44
Total
Source: Money Market Directory, 2003.
Bodenman
136
The Industrial Geographer
Bodenman
137
The Industrial Geographer
Conshohocken with nearly $40 billion
under management, and not far behind
Philadelphia is Radnor (5th ) with $12
billion (Table 5).
location within the Philadelphia MSA,
1983-1993.
Perhaps
equally
dramatic
and
interesting, however, is the growing
number of investment advisory firms
located outside of the top five cities. In
1983, 81.5 percent of the firms with taxexempt assets under management in
Pennsylvania were located in the top five
cities. By 2003, the top five cities share of
total firms had dropped to 47 percent –
the vast majority of this growth again
taking place at the expense of
Philadelphia.
However, most of the
growth in new firms and their tax-exempt
assets under management has taken
place in cities that are part of the
Philadelphia Metropolitan Area (Figures
4a and 4b).
Overall,
the
top
five
cities
in
Pennsylvania (Figure 3b; Table 5) were
home to 22 firms with $13.3 billion in taxexempt
assets
under
management
(reported in constant 2003 dollars),
representing over 98 percent of the total
tax-exempt assets under management in
1983. By 2003, the top five cities were
home to 24 firms with $494.9 billion in
tax-exempt assets under management.
However,
this
absolute
increase
represented a decrease in total share
from over 98 percent in 1983 to 94
percent
in
2003,
especially
for
Philadelphia which saw its share of total
tax-exempt assets under management
decrease from 65.7 percent in 1983 to 6.1
percent in 2003 (Figure 5), a dramatic
decline. Bodenman (1998) reports on the
initial stages of this decline in an earlier
study of investment advisory firm
Bodenman
For example, a number of the cities
experiencing growth in firms and assets,
including Malvern (1st), Conshohocken
(3rd), and Radnor (5th ), are "Main Line"
suburbs of Philadelphia. Considered at
138
The Industrial Geographer
Table 4a: Percentage of Total Tax-Exempt Assets and Percentage of Total Firms with
Tax-Exempt Assets Under Management in the Top 20 Cities, 1983.
1983
Rank
$ in
# of
% of Total
% of Total
Millions*
Firms
Assets
Firms
City
State
1
New York
NY
136,599
147
33.21
27.63
2
Boston
MA
77,267
46
18.78
8.65
3
Chicago
IL
28,949
25
7.04
4.70
4
San Francisco
CA
24,634
18
5.99
3.38
5
Los Angeles
CA
16,085
24
3.91
4.51
6
Baltimore
MD
13,134
8
3.19
1.50
7
Houston
TX
12,043
12
2.93
2.26
8
Stamford
CT
9,448
1
2.30
0.19
9
Philadelphia
PA
8,914
14
2.17
2.63
10
Minneapolis
MN
7,663
8
1.86
1.50
11
Atlanta
GA
6,627
13
1.61
2.44
12
Hartford
CT
5,007
4
1.22
0.75
13
Seattle
WA
3,838
3
0.93
0.56
14
Portland
OR
3,733
4
0.91
0.75
15
Chatham
NJ
3,553
2
0.86
0.38
16
Newport Beach
CA
3,275
4
0.80
0.75
17
Milwaukee
WI
3,235
6
0.79
1.13
18
Beverly Hills
CA
2,890
5
0.70
0.94
19
White Plains
NY
2,046
1
0.50
0.19
20
Louisville
KY
1,986
2
0.48
0.38
370,926
347
90.18
65.23
Total
*1983 Assets reported in constant 2003 dollars.
Source: Money Market Directory, 1983.
Bodenman
139
The Industrial Geographer
Table 4b:
Percentage of Total Tax-Exempt Assets and Percentage of Total Firms with
Tax-Exempt Assets Under Management in the Top 20 Cities, 2003.
2003
Rank
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
City
State
Boston
New York
San Francisco
Los Angeles
Chicago
Malvern
Plainsboro
Newport Beach
Atlanta
Pittsburgh
Minneapolis
Columbus
Pasadena
Stamford
Baltimore
Denver
Houston
Cambridge
Purchase
Westport
Total
MA
NY
CA
CA
IL
PA
NJ
CA
GA
PA
MN
OH
CA
CT
MD
CO
TX
MA
NY
CT
$ in
Millions
# of
Firms
% of Total
Assets
% of Total
Firms
1,705,525
1,531,267
951,378
400,971
349,797
291,196
254,054
231,695
222,508
119,534
117,072
112,863
111,182
89,565
83,794
75,269
58,155
57,976
49,680
47,381
6,860,862
60
136
33
26
41
2
1
7
15
11
19
1
8
6
18
16
13
6
2
5
426
0.02
0.02
0.01
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
88.34
5.08
15.16
2.79
2.20
3.47
0.17
0.08
0.59
1.27
0.93
1.61
0.08
0.68
0.51
1.52
1.35
1.10
0.51
0.17
0.42
39.72
Source: Money Market Directory, 2003.
Bodenman
140
The Industrial Geographer
Table 5:
Percentage of State's T otal Assets and Percentage of State's T otal Firms with T ax-Exempt Assets
Under Management in Pennsylvania's T op Five Cities, 1983 and 2003.
1983
$ in
# of
Firm
% of Total
% of
Total
Rank
City
State
Millions*
Firms
Average
Assets
Firms
1
Philadelphia
PA
8,914
14
637
65.70
51.85
2
Bala Cynwyd
PA
1,488
1
1,488
10.97
3.70
3
Valley Forge
PA
1,125
1
1,125
8.29
3.70
4
Reading
PA
984
3
328
7.25
11.11
5
Pittsburgh
PA
844
3
281
6.22
11.11
13,355
22
607
98.43
$ in
# of
Firm
% of Total
81.48
% of
Total
Total
2003
Rank
City
State
Millions
Firms
Average
Assets
Firms
1
Malvern
PA
291,196
2
145,598
55.56
3.92
2
Pittsburgh
PA
119,534
11
10,867
22.81
21.57
3
Conshohocken
PA
39,758
1
39,758
7.59
1.96
4
Philadelphia
PA
31,991
7
4,570
6.10
13.73
5
Radnor
PA
12,414
3
4,138
2.37
5.88
494,893
24
20,621
94.42
47.06
Total
*1983 Assets reported in constant 2003 dollars.
Source: Money Market Directory, 1983 and 2003.
Bodenman
141
The Industrial Geographer
Bodenman
142
The Industrial Geographer
Figure 5:
Percentage of Total Tax-Exempt Assets Under Management in Pennsylvania's
Top Five Cities, 1983 and 2003.
70
60
50
40
30
20
10
0
Philadelphia
Pittsburgh
Malvern
Radnor
Conshohocken
City
City's Percent of Total Assets, 1983
Source: Money Market D irectory, 1983; 2003.
Bodenman
143
City's Percent of Total Assets, 2003
The Industrial Geographer
Bodenman
144
The Industrial Geographer
the
metropolitan
scale,
therefore,
dispersal of assets under management
more
accurately
suggests
"suburbanization." That is, most of the
growth is in cities located in the
Philadelphia Metropolitan Area.
This
finding supports the initial trends
reported by Bodenman (1998; 2002) in
earlier studies of the industry’s locational
dynamics.
the investment advisory industry
Philadelphia from 1983 to 2003.
At both the inter- and intrametropolitan level,
the industry's spatial dynamics in Pennsylvania
indicate deconcentration and dispersal as the
information economy continues to mature. The
“concentrated dispersal” of the industry over the
1983-2003 study period further indicates that
location in a central city (i.e., Philadelphia CBD)
is no longer a necessary condition. However, the
extent to which suburbanization of the
investment advisory industry is occurring
elsewhere, in other MSAs (i.e., New York) is
unclear—an indication that additional industry
location studies are needed.
SUMMARY AND CONCLUSIONS
Overall, the analysis of data at the
intermetropolitan level indicates that
within the state of Pennsylvania (ranked
4th
in
tax-exempt
assets
under
management in 2003): both Metropolitan
Philadelphia and Pittsburgh increased
their relative shares of assets and firms
during the 1983-2003 study period. By
2003, the Philadelphia MSA had moved
ahead of Chicago (ranked 5th overall), and
the Pittsburgh MSA moved into the top
20 nationally (ranked 11th overall).
REFERENCES
Bloomfield, B. P., Coombs, R., Knights, D., and D.
Littler (eds). 2000. Information Technology and
Organizations:
Strategies,
Networks,
and
Integration. New York: Oxford University Press.
Bodenman, J. E. 1998. "The Suburbanization of
the Institutional Investment Advisory Industry:
Metropolitan
Philadelphia,
1983-1993."
Professional Geographer 50(1): 112-126.
However,
analysis
of
the
intrametropolitan growth and change of
the investment advisory industry in
Pennsylvania
indicates
that
the
industry's ties to the CBD of
the
traditional financial center, Philadelphia,
continue to break down. The city of
Philadelphia's share of Pennsylvania's
total assets and total firms had declined
to 6.1 percent and 13.7 percent,
respectively, by 2003.
However, the
majority of cities that experienced the
tremendous growth in firms and assets,
were located in the Philadelphia
metropolitan area. Thus, the analysis of
intrametropolitan growth and change,
suggests that (1) investment management
ties to the CBD of the traditional
financial center continue to weaken, but
that (2) spatial proximity to the
traditional financial center is being
maintained.
The analysis, therefore,
suggests significant suburbanization of
Bodenman
in
Bodenman, J. E. 2000. "Firm Characteristics and
Location: The Case of the Institutional Investment
Advisory Industry in the United States, 19831996." Papers in Regional Science 79(1): 33-56.
Bodenman, J. E. 2002. “The Spatial Dynamics of
Pennsylvania’s Institutional Investment Advisory
Industry: Pittsburgh vs. Philadelphia, 1983-2000.”
The Pennsylvania Geographer XL(1): 3-34.
Borchert, J.R. 1978. "Major Control Points in
American Economic Geography." Annals of the
Association of Economic Geographers 68: 214-232.
Carlino, G. A. 2001. "Knowledge Spillovers:
Cities Role in the New Economy." Business
Review: Federal Reserve Bank of Philadelphia Q4:
17-23.
Castells, M. 1989. The Informational City:
Information Technology, Economic Restructuring,
and Urban-Regional Process. Cambridge, MA:
Basil Blackwell.
Clark, G. L. 2000. Pension Fund Capitalism.
New York: Oxford University Press.
Daniels, P.W. 1993. Service Industries in the World
Economy. Cambridge, MA: Basil Blackwell.
145
The Industrial Geographer
Graves, W. 1998. “The Geography of Mutual
Fund Assets.” Professional Geographer 50(2): 243254.
Green, M.B. 1993. "A Geography of Institutional
Stock Ownership in the United States." Annals of
the Association of American Geographers 83(1):
66-89.
Hepworth, M.E. 1990. Geography of the
Information Economy.
New York, NY: The
Guilford Press.
Hepworth, M.E. 1991. Information Technology
and the Global Restructuring of Capital Markets.
In Collapsing Space and Time, ed. S.D. Brunn and
T.R. Leinbach, pp. 132-148.
London: Harper
Collins Academic.
Lee, R.
2000.
What is an Exchange?: The
Automation, Management, and Regulation of
Financial Markets. New York: Oxford University
Press.
Money Market Directories. 1983. Money Market
Directory of Pension Funds and Their Investment
Managers.
New York, NY: McGraw-Hill
Publishers.
Money Market Directories. 2003. Standard &
Poor’s: The Money Market Directory of Pension
Funds and Their Investment Managers. New
York, NY: McGraw-Hill Co.
Sassen, S. 1991. The Global City: New York,
London, Tokyo.
Princeton, NJ: Princeton
University Press.
Stanback, T. M. 1991. The New Suburbanization:
Challenge to the Central City.
Boulder, CO:
Westview Press.
Bodenman
146
A Borderless World Of Hypermobile and Homeless
Money?
AN EVALUATION OF FINANCIAL FLOWS IN THE MUTUAL FUND INDUSTRY
COLIN C WILLIAMS
Professor of Work Organization
Management Centre
University of Leicester
Leicester, LE1 7RH
United Kingdom
ABSTRACT
The aim of this paper is to evaluate critically the hyperglobalist thesis that
with the emergence of fund-manager capitalism, hypermobile and
homeless capital increasingly roams a borderless world in search of
investment opportunities. Drawing upon Standard and Poor’s Micropal
data base to analyze financial flows in the mutual fund industries of nine
developed market economies, evidence is found of some globally orientated
funds as well as more rapid-fire trading, faster fund switching and the
disembedding of capital ownership from place and individuals. However,
little evidence is found that the apogee of financial globalization - a
seamless world of hypermobile and homeless capital - has been achieved.
Most assets in mutual funds are ge ographically ‘ring-fenced’, cannot be
and are not speedily moved around the world and this money is concretely
identifiable as belonging to individuals living in particular places. The
paper thus concludes by cautioning against over-exaggerating the process
of financial globalization.
Key words: mutual funds; financial globalization; fund management;
financial services; geography of money.
INTRODUCTION
It is now widely recognized that
the advent of ‘fund -manager
capitalism’ has transformed the
landscape of money and finance
(e.g., Blommestein 1999; Clark
2000; Corbridge et al 1996;
Graves 1998; Leyshon 1995a,
1997, 1998; Leyshon and Thrift
1997; Martin 1999a; Porteous
1995; Singh 2000; Warburton
1999). Funds managed by large
financial
institutions
(e.g.,
pension funds, life assurance,
hedge funds and open- and
closed-ended mutual funds) have
significantly increased the share
The Industrial Geographer, Volume 2, Issue 2, pp.144-155
©2004 Williams
The Industrial Geographer
of the equity market under their
control. Of all shares listed on the
UK stock market, institutional
investors owned 36 per cent in
1969 but 62 per cent by 1993
(Martin 1999b). In the US, the
proportion owned by these
institutions has risen from 6 per
cent in 1950 to 34 per cent by
1980 and to 48 per cent by 1997
(Singh 2000).
(Castells 1989, 1996; Ohmae
1990, 1995a,b; O'Brien 1992;
Kobrin 1997). For influential
commentators such as Castells
(2000 p. 374), what is thus being
witnessed is
the annihilation of space and time by
electronic means. Its technological
and informational ability relentlessly
to scan the entire planet for
investment opportunities, and to move
from one option to another in a matter
of seconds, brings capital into
constant movement, merging in this
movement capital from all origins, as
in mutual funds (my emphasis).
One prominent argument that
dominates the literature on
money and finance is that
running alongside this growing
concentration of equities in
managed funds has been a
process of financial globalization,
by which is meant ‘the increasing
integration,
hybridization,
convergence and stretching of
economic relationships across
space’ (Martin 1999a p.14).
According to what Held et al
(1999)
refer
to
as
the
‘hyperglobalist
thesis’,
this
process of financial globalization
is composed of at least three
separate but inter-locking trends
so far as the flows of finance are
concerned. Firstly, there is
argued to be a process of time
compression; capital is asserted to
have become more ‘hypermobile’
(e.g. Appadurai 1990; Castells
2000; Warf 1999). Secondly, a
process of space compression is
identified. Here, hypermobile
capital is seen to roam an
increasingly
‘borderless’
or
‘seamless’ world in search of
investment opportunities (e.g.,
O'Brien 1990; Ohmae 1990,
1995a,b; Singh 2000; Warf 1999).
And third and finally, there is
asserted to be the emergence of
‘homeless’ or ‘stateless’ monies
Williams
Given the predominance of this
‘hyperglobalist’ view amongst
commentators, at least when the
process of financial globalization
under fund-manager capitalism is
analyzed, the aim of this paper is
to evaluate critically whether this
is indeed the case. Is financial
capital now composed of homeless
money that is hypermobile and
roaming a borderless world in
search
of
investment
opportunities?
To answer this question, this
paper focuses upon one particular
form of fund-manager capitalism,
namely the mutual fund industry,
and investigates the financial
flows in the mutual fund
industries of nine developed
market economies (i.e., Belgium,
France, Germany, Hong Kong,
Japan, Spain, Singapore, the
USA and UK). The principal
evidence
drawn
upon
to
interrogate this is the data
produced by Standard and Poor’s
Micropal database. This evidence
is primarily produced so as to
enable investment advisors and
individual investors to compare
145
The Industrial Geographer
both sectors and individual funds
in
order
that
investment
decisions can be made. As such,
the focus is upon providing past
performance data for individual
sectors and funds in different
countries. For the purposes of this
paper, the fact that evidence is
also provided on the level of
investment on a sector-by-sector
basis in each nation enables
cross-national
comparative
analyses to be produced on where
mutual fund money is invested.
In so doing, this paper fills a gap
in our knowledge of financial
globalization. Until now, research
on mutual funds has focused upon
either
aspects
of
financial
performance (e.g., Cummings
2000; Gregory et al 1997; Harless
and Peterson 1998; Ibbotson and
Kaplan 2000; Indro et al 1999;
Kahn and Rudd 1995; Mallin et al
1995; Neal 1998) or human
resource
issues
in
fund
management (e.g., Brown et al
1996; Chevalier and Ellison 1997,
1999; Eichberger et al 1999;
Khorana 1996). The only known
study of the geography of mutual
funds investigates the spatial
location of the US mutual fund
industry
(Graves
1998).
Moreover, with the exception of
one case study of the UK unit
trust industry (Williams 2001),
the financial flows in this
industry have tended not to be
explored. Until now, therefore, no
studies have thus analyzed the
broader intensity of the process of
financial globalization in the
mutual fund industry, despite
this industry being widely
heralded as exemplifying this
process and often held up as
epitomizing the drift towards a
borderless world of homeless and
hypermobile monies (c.f., Castells
2000).
Analyzing both this primary data
and other secondary evidence on
the trends in mutual fund
investing, firstly, the degree to
which these mutual funds work
with hypermobile money is
investigated, secondly, the extent
to which they operate in a
seamless world and third and
finally, whether these assets can
be characterized as homeless or
stateless. This will uncover that
although there is evidence of
some
funds
being
globally
orientated, rapid-fire trading,
faster fund switching and the
disembedding
of
capital
ownership
from
place
and
individuals, the mutual fund
industry cannot be described as
operating in a seamless world
with hypermobile and homeless
capital. The vast majority of
mutual
fund
assets
are
geographically
‘ring-fenced’,
money is not and cannot be
speedily moved around the world
in a hypermobile manner and the
capital concretely belongs to
individuals. The paper thus
concludes by urging caution over
the extent and nature of financial
globalization in this industry.
Williams
Before commencing, however, it is
important to outline how mutual
funds operate. Pooling together
the money of individuals who
wish to invest relatively small
amounts in the stock market,
mutual funds spread their capital
across
a
wide
range
of
investments so as to allow
diversification
of
risk,
146
The Industrial Geographer
professional management and
reduced transaction costs. Each
investor is allocated a number of
units in the fund according to how
much they initially invest. Every
day, the price of the investments
(e.g., the share price of the
companies) held in that mutual
fund is priced and the unit (‘offer’)
price recalculated. Any new
investors then pay that ‘offer’
price. The job of the fund
managers is to pick successful
stocks and/or correctly forecast
the movement of the market
(Bangassa
1999).
For
this
expertise, actively managed unit
trusts charge both an annual
management fee of up to 2 per
cent of the value of the fund and a
‘one-off’ entry fee that can be as
high as 6 per cent in some
countries (see Chordia 1996).
analyzed. This has been collecting
data on mutual funds since 1986
and its data coverage includes
52,000 funds in many different
nations. Here, the mutual fund
industries of nine developed
market economies in different
regions of the world are analyzed.
As such, the paper is based on
analysis of 530 mutual funds in
Belgium, 1,872 in France, 1,274
in Germany, 823 in Hong Kong,
1,743 in Japan, 45 in Singapore,
1,621 in Spain, 1,599 in the UK
and 10,754 in the USA.
When examining the proportion
of mutual fund assets in each
country that is in funds that are
global in orientation, it is first
necessary to briefly discuss the
industry-wide
standard
for
classifying mutual funds in
different nations. In all nine
nations
studied,
the
same
variables are used to distinguish
between various types of mutual
fund. Firstly, the geographical
market of the fund is identified.
This categorizes funds by the
region of the world (e.g., Europe,
North
America,
Far
East,
Emerging Markets, global) and/or
by the specific nation (e.g., USA,
UK, Japan) in which they invest.
Secondly, funds are distinguished
by their sectoral scope (e.g.,
whether it invests in technology,
property, smaller companies) and
third and finally, they are
differentiated by their investment
objective (e.g., capital growth or
income). Although each nation
uses different sub-categories of
funds to classify their mutual
funds, all use these three
variables,
in
different
ARE
MUTUAL
FUNDS
OPERATING
IN
A
BORDERLESS WORLD?
For some commentators, financial
globalization is resulting in ‘the
end of geography’ in the sense
that ‘geographical location no
longer matters, or matters less
than hitherto’ (O’Brien 1992 p.1).
To evaluate whether this is
indeed the case, this section
evaluates whether mutual funds
are indeed operating in a
‘borderless’ or ‘seamless’ world
(e.g., Appadurai 1990; Castells
2000; Ohmae 1990, 1995a,b; Warf
1999). As O’Brien (1992 p.5) puts
it, is it the case that ‘the closer we
get to a global, integrated whole,
the closer we get to the end of
geography’?
To investigate whether this is the
case,
Standard
and
Poor’s
Micropal data-base is here
Williams
147
The Industrial Geographer
combinations,
them.
for
categorizing
While Singapore has the highest
share of all its mutual fund assets
in global-orientated funds (37 per
cent), all other countries have less
than a quarter of their mutual
fund assets in such global funds.
As such, there is little evidence
that the mutual fund industries
of these nine countries are
operating in a ‘borderless’ or
‘seamless’ world.
To compare the mutual fund
industries of these nine nations,
Table 1 analyzes the proportion of
all mutual fund assets in each
nation invested in global funds
and the proportions invested in
particular regions and/or specific
nations within each region. This
enables
a
cross-national
comparison of the geographical
allocation of mutual fund assets.
In addition, the last column is
used to display the proportion of
all mutual fund assets in each
nation invested in domestic
funds.
The stark finding is that only a
small proportion of all mutual
fund assets is in ‘global’ funds,
whichever country is analyzed.
In all countries, the vast majority
of capital in mutual funds is
geographically ‘ring-fenced’. In
Japan and the USA, for instance,
mutual fund assets are heavily
concentrated in funds investing in
their own respective domestic
economies markets (85.2 per cent
and 84.0 per cent of all mutual
fund assets respectively).
Table 1A cross-national comparison o f the geographical allocation of
mutual fund assets: by region of the world, December 2000
% of all
assets
Globa
l
Europe
:
general
Europe
: single
country
Far
East &
Pacific:
genera
l
North
Americ
a
Emergin
g
markets:
general
Emergin
g
Markets:
single
country
Home
Marke
t
21.8
Far
East &
Pacific:
single
countr
y
29.3
Singapor
e
Belgium
Spain
Germany
USA
UK
Hong
Kong
France
Japan
37.0
5.5
0.0
1.2
0.7
0.0
(15.2)
24.1
23.3
19.7
14.7
13.2
10.8
31.0
24.1
26.3
0.6
16.6
38.1
17.5
39.4
21.4
0.0
53.4
21.3
3.9
2.7
3.0
0.2
4.1
6.1
6.8
1.1
15.7
0.1
4.7
12.7
10.8
7.9
11.0
84.0
7.0
7.4
5.6
1.5
1.9
0.4
1.0
2.1
0.3
0.0
1.0
0.0
0.0
0.6
(8.0)
(25.4)
(18.2)
(84.0)
(53.5)
(0.4)
9.4
<0.1
16.9
1.2
53.0
0.0
3.6
1.8
6.3
96.7
10.1
0.2
0.6
<0.1
0.1
<0.1
(53.4)
(85.2)
Source: derived from Standard and Poor's Micropal, December 2000 (www.sp-funds.com)
Williams
148
The Industrial Geographer
In European nations, in contrast,
and perhaps reflecting the shift
towards Europeanization, there is
less of a tendency to confine funds
to the national market and a
greater
tendency
towards
investing in other European
nations.
(Obstfeld and Rogoff 2000). In
other part, it can be explained in
terms of the aversion to both risk
and
uncertainty
amongst
investors. Risk increases due to
the additional issue of currency
fluctuations
when
investing
outside of one’s home nation (or
the European Union for Euroland
nations). Uncertainty, moreover,
is perceived to increase the
further one move’s away from
home since there is a perception
that proximity equates with
greater knowledge. The outcome
is a ‘close to home’ tendency in
mutual fund asset allocation.
Indeed, citizens of all nations
appear to invest their mutual
fund assets ‘close to home’. Not
only is this expressed in the vast
bulk of US and Japanese mutual
fund assets being invested in
their domestic economies but also
in the tendency for European
nations to invest in Europe as
well as Far Eastern and Pacific
nations to skew investments
towards their own region of the
world. Some nations, moreover,
notably the USA, display far less
geographical sensitivity of the
heterogeneity of regions and
markets existing outside of their
domestic market than other
nations (e.g., Hong Kong). Some
92 per cent of US assets held
outside domestic mutual funds,
for example, are invested in
‘global’ funds. This is in stark
contrast to Hong Kong and
France where just 10.8 per cent
and 20.2 per cent of the assets
invested outside of the country
are in global funds and the vast
majority in a host of regional- or
nation-specific funds.
However, and whatever the
reason for this ‘close to home’
tendency, the important point so
far as this paper is concerned is
that Table 1 displays the limited
extent of financial globalization.
Only a small proportion of mutual
fund assets have a global reach.
Most mutual fund assets are
tightly
ring-fenced
geographically.
Nevertheless,
Table 1 might be underestimating the extent to which
funds flow around the globe. In
the US mutual fund market
during the 1960s and 1970s, the
average time that units were held
was 12.5 years, a turnover rate of
8 per cent per annum. By the late
1990s,
this
‘churning’
was
equivalent to 31 per cent per
annum of all units, indicating
that typical investors held their
units for barely three years
(Bogle 1999 p.24). If this churning
is due to investors increasingly
treating the globe as their market
and switching money from one
region to another as sentiment
changes, then investors may be
All nations, nevertheless, display
a ‘close to home’ bias in their
investment strategies for mutual
fund assets. In part, this might be
explained in terms of the costs of
trading goods and services
internationally which leads to a
domestic bias in equity portfolios
Williams
149
The Industrial Geographer
actively managing their funds in
a more global manner than is
suggested by Table 1. At present,
however, there is no evidence
available to suggest that this is
the case.
context of the mutual fund
industry the view that it is far too
early to discuss how fund manager capitalism is resulting
in the ‘end of geography’ (see
Cohen 1998; Leyshon 1995b;
Martin 1994).
Other evidence, however, does
point to the idea that Table 1
might be under-estimating the
extent of global financial flows.
Analyzing the securities in which
these funds invest, there is clear
evidence
that
capital
is
increasingly mobile and global in
orientation. As one UK mutual
fund manager puts it, 'With
almost half the earnings of UK
companies now coming from
overseas, the UK equity market is
increasingly exposed to most
regions of the world. This trend
has accelerated' (Maxwell 2000
p.3). Even capital invested in
single country funds, therefore, is
increasingly money invested on a
global level. Consequently, if
funds themselves are not global
in their investment remit, this is
certainly the case for the
companies in which the money is
invested.
ARE
MUTUAL
FUNDS
WORKING
WITH
HYPERMOBILE CAPITAL?
If the mutual fund industry is not
operating in a 'seamless' world, is
it nevertheless the case that it is
operating
with
hypermobile
capital? Do mutual fund assets
pass ‘through national turnstiles
at blinding speed’ (Appadurai
1990 p.8) as they engage in what
Warf (1999 p.230) terms ‘a
syncopated
electronic
dance
around
the
world's
neural
networks’?
The evidence from the mutual
fund industry is that capital is
becoming more mobile. Fund
managers are holding stocks in
their funds for shorter periods.
From the 1940s through to the
mid-1960s, the annual stock
turnover of the average equity
fund was 17 per cent, indicating
that the average stock was held
in a fund for nearly 6 years. By
the late 1990s, this annual
turnover was 85 per cent. In
other words, stocks were on
average held for just over one
year (Bogle 1999 p.25). This
speeding up of the turnover of
holdings is strong evidence of how
capital in these funds is becoming
more mobile as it is being
switched from one investment to
another at an ever-increasing
pace.
Consequently, even if the level of
investment in global-orientated
funds is relatively low, the dual
trends of faster fund switching by
investors and the increasingly
global orientation of companies
signify that mutual funds operate
with capital that is more global
than is suggested in Table 1.
Nevertheless, the mutual fund
industry does not operate in a
‘seamless’ or ‘borderless’ world.
Most fund managers still work
with money that is geographically
‘ring fenced’, reinforcing in the
Williams
150
The Industrial Geographer
Indeed, this trend towards ‘rapidfire trading’ is reflected in the
swift demise of long -term value
investors (epitomized by fund
management houses such as
Templeton and individuals such
as Warren Buffet) and the
emergence
of
more
fluid
investment styles based on only
holding stocks for short periods.
These
include
‘momentum’
investors (who invest in stocks
whose price is rising quicker than
its peers and then exit as soon as
the
momentum
decreases),
‘aggressive growth’ investors (who
invest in quickly growing new
companies and sell when they
plateau)
and
‘deep
value’
investors (who seek stocks with
extremely low valuations and exit
when the market re -values the
stock). This shift in style from
long-term investment to shortterm speculation both reflects and
reinforces the increasing ‘mobility
of money’ thesis.
writing (although facsimiles are
starting to be accepted by some
managers) if they wish to switch
funds and this can often take
several weeks (especially if it is a
transfer
to
another
fund
management group). And third
and finally, companies still
cannot easily move fixed capital
in many industries. The mutual
fund industry, therefore, displays
that although capital is becoming
more mobile, the notion that
there
is
globally
roaming
‘hypermobile’
money
(e.g.,
Appadurai 1990; O’Brien 1992;
Warf 1999) is an exaggeration of
the reality.
ARE
MUTUAL
FUNDS
OPERATING
WITH
HOMELESS MONIES?
Finally, there is the issue of
whether, as some commentators
assert, we are witnessing the
advent
of
‘homeless’
and
‘stateless’ money (Castells 1989,
1996,
2000;
Ohmae
1990,
1995a,b; O'Brien 1992; Kobrin
1997). At first glance, this
appears to be increasingly the
case. There is little doubt that
over the long wave of history,
there has been a disembedding of
capital ownership from place and
individuals. Owner-management
and family capitalism have been
slowly but surely displaced by
private
shareholders
and
increasingly
large
financial
institutions (see Martin 1999b;
Singh 2000). However, this is not
the same as asserting that capital
has
become
‘stateless’
or
‘homeless’. At least so far as the
mutual
fund
industry
is
concerned, all the assets belong to
specific individuals. Indeed, and
Again, however, although the
combined trends toward rapidfire trading by fund managers,
faster fund switching by investors
and the increasingly global
orientation of companies, point to
capital becoming more mobile,
they do not signify the advent of
hypermobile capital passing at
‘blinding speed’ through the
world's ‘neural networks’. Firstly,
most capital is geographically
ring-fenced in that investors put
it in funds that are only allowed
to invest the money in specific
geographical areas and are not
allowed to put the money
elsewhere in the world. Secondly,
investors in many countries must
still contact fund managers in
Williams
151
The Industrial Geographer
as investors in ethical funds
(French,
2003)
and
those
demanding ethical investment
practices by fund managers
recognize, the only result of
‘othering’ money by conceptually
separating it from its individual
owners is to encourage them to
abstain from taking responsibility
for its impacts. Conceptualizing
the capital of mutual funds as
homeless and stateless is thus not
only a misnomer but also
deleterious. It concretely belongs
to individuals and even if the
management of that money is
delegated to fund managers, it
ultimately remains within the
control of individuals (and is their
responsibility) as to how it is
used.
place
under
fund -manager
capitalism are to be understood,
therefore, far more investigation
will
be
required
of
the
geographical location of the
investors for whom wealth is
being generated and where funds
are investing money on a local
and regional level. Up until now
however, the circuitry of money
flows in the mutual fund industry
has not been investigated due to
the dominance of the view that
these assets are homeless or
stateless.
In sum, although there has been
a
disembedding
of
capital
ownership
from
place
and
individuals with the growth of
mutu al funds, this does not mean
it has become homeless or
stateless. Indeed, unless such a
perception is tackled, not only
will the individuals who own
mutual
funds
(and
those
belonging to pension funds that
invest in mutual funds) abstain
from taking responsibility for
their investment decisions but
the uneven geographies that
result from the financial flows of
the mutual fund industry will
remain uninvestigated.
To understand the impacts of the
disembedding of capital from
place and individuals, it is thus
perhaps far more salient to
investigate
the
uneven
geographies being created by this
form of fund -manager capitalism
than to assert that money is
homeless.
Mutual
funds
continuously collect monies from
localities and regions, invest it in
different places and eventually
return it to the places from which
it was first collected. Given their
size and growth, mutual funds
are
increasingly
dominant
‘powerhouses’. Along the power
lines that flow out from them,
capital is transmitted to and fro
at varying strengths and it is
these transmissions that shape
the ability of any place to
generate
production,
employment, income and welfare.
If the uneven impacts of the
disembedding of capital from
Williams
CONCLUSIONS
Recent years have seen much
discussion
about
financial
globalization and its impacts on
the space economy. It has been
asserted that with the advent of
fund-manager
capitalism,
hypermobile and homeless capital
has emerged that circulates a
borderless globe in search of
investment (e.g., Appadurai 1990;
Ohmae 1995a, 1995b; O’Brien
1992; Warf 1999). In order to
152
The Industrial Geographer
evaluate whether fund managers
do indeed operate on a global
level with such hypermobile
‘homeless’ money, this paper has
analyzed
the
mutual
fund
industries of nine nations.
achieved. Future research on the
disembedding of capital from
place
and
individuals,
in
consequence, needs to move
beyond this hyperglobalist thesis
to explore how the uneven
financial flows of the mutual fund
industry differentially shape the
prospects of varying places. It is
hoped that this paper will
encourage such a research agenda
to be pursued. Indeed, unless
such research is conducted, the
uneven spatial impacts of one of
the
powerhouses
of
the
contemporary
economy
will
remain unknown.
This has revealed that at least so
far as the mutual fund industry is
concerned, financial globalization
should not be over-exaggerated.
Firstly, the degree to which these
mutual
funds
work
with
hypermobile money has been
investigated, secondly, the extent
to which they operate in a
seamless world and third and
finally, whether these assets can
be characterized as homeless or
stateless. This has revealed that
despite some funds being globally
orientated as well as evidence of
greater rapid -fire trading, faster
fund
switching
and
the
disembedding
of
capital
ownership
from
place
and
individuals, the mutual fund
industry is not operating in a
seamless world with hypermobile
and homeless capital. Most
mutual
fund
assets
are
geographically ring-fenced and
thus cannot be invested anywhere
in the world, assets are not and
cannot be speedily moved around
the world and this money
concretely belongs to specific
individuals living in particular
places.
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Williams
155
Globalization of Banking and Local Access to Financial Resources:
A Case Study from Southeastern Mexico
James J. Biles
Department of G eography
W estern Michigan University
Kalamazoo, MI 49008, USA
jbiles@wmich.edu
ABSTRACT
Since 1999 foreign financial institutions have acquired six of Mexico’s eight largest banks as
part of a process of wholesale financial liberalization and economic integration. To date,
however, no empirical research has been carried out to assess the implications of the
transformation of Mexico’s financial system on access to credit among low and moderateincome households. The primary objective of this study is to assess how the processes of
globalization and economic liberalization have affected access to formal and informal
financial resources in Mexico. A case study approach, based on a household survey in
Valladolid, Mexico, is presented to determine how low and moderate-income households
gain access to financial resources. In addition, the study quantifies the distribution of formal
and informal credit and identifies the relative importance of formal and informal financial
institutions.
Keywords: G lobalization, banking, financial exclusion, informal economy
INTROD UCTION
In May 2001, the parent company of
Citibank acquired Banamex, Mexico’s
flagship banking institution, completing a
process of liberalization begun more than
a decade earlier. The transformation of
the financial system was aimed at
“expanding, diversifying and modernizing
financial services to…foster greater
participation in the global economy”
(Federal Reserve Bank of Atlanta 2001).
To date, however, no empirical research
has been carried out to assess the
consequences of globalization and
liberalization on access to credit among
low and moderate-income households in
Mexico. Consequently, the primary goal
of this study is to assess how the processes
of
globalization
and
economic
liberalization have affected access to
formal and informal financial resources in
southeastern Mexico.
The case study presented below provides a
concrete example of how global processes
bring about profound local consequences.
Furthermore, since many other nations in
Latin America have recently opened their
financial systems to foreign intervention,
this study offers some insights into the
potential ramifications of such a strategy
for the poor households that comprise the
vast majority of the region’s population.
The section that follows provides a brief
overview
of recent
research
on
globalization of finance. Subsequently, the
role of financial systems and the
transformation of the Mexican banking
sector
are
discussed.
The Industrial Geographer, Volume 2, Issue 2, pp 159-173. © 2004 Biles
The Industrial Geographer
The next section identifies the formal and
informal institutions that have emerged to
meet the credit needs of low and
moderate-income households in Mexico.
The case study of formal and informal
financial systems in Valladolid, Mexico is
then presented. The final section assesses
the implications of the case study and
identifies opportunities for future research.
the allocation of financing as a
consequence of credit rationing or
discriminatory practices (Christopherson
and Hovey 1996). Research on financial
exclusion reveals that liberalized financial
markets are not necessarily efficient and
may increase inequalities in access to and
distribution
of
financial
resources
(Leyshon 1995).
GLOBALIZATION OF FINANCE
G lobalization, defined as the increasing
liberalization
and
integration
of
economies in terms of trade and
investment, has transformed financial and
capital markets during the past two
decades (Hausler 2002). G lobalization of
finance is associated with deregulation of
banking activities within particular
countries and consolidation of institutions
and bank mergers that cross national
borders (Baliño and Ubide 2000). These
trends have emerged from the belief that
liberalization leads to greater profitability,
more efficient allocation of resources and
diversification of risk. Banks, like other
sectors of the economy, must compete
with each other globally as part of a
broader process of political and economic
integration (Leyson and Pollard 2000).
Substantial research has been carried out
on financial exclusion in the United
States. Graves (2003), for example,
documents how deregulation has led to
the emergence of a two-tiered financial
system. In particular, he focuses on the
proliferation of payday lenders that serve
poor, urban areas of the U.S. Caskey
(1994) also suggests that elimination of
regulatory barriers is associated with
expansion of “fringe” banking, reflecting
increasing disparities in economic wellbeing. He concludes that households
without financial assets must pay more for
financial services than other households.
Research on financial exclusion has been
somewhat limited in developing countries.
In the case of Fiji, Sharma and Reddy
(2002) conclude that institutional forces
are the primary determinants of financial
exclusion in rural areas (where two-thirds
of households do not have access to
financial services). Christopherson and
Hovey (1996) also describe a “bimodal”
financial system in Mexico, comprised of
large financial and industrial groups
integrated with global financial markets
and local and regional finance (provided
by domestic banks), which serves small
and medium businesses and households.
They conclude that access to financial
resources is highly uneven, exacerbating
inequalities in economic opportunity
among Mexican states.
The liberalization of banking and financial
services has also been justified as a means
of addressing financial repression.
According to G ruben and McComb
(1997), financial repression stems from
government control of interest rates,
reserve
requirements,
and
lending
priorities. With high levels of financial
repression people choose to invest in other
assets and the banking system captures a
relatively small share of savings.
During the past decade, much of the
research on globalization of finance has
focused on financial exclusion – biases in
Biles
160
The Industrial Geographer
TRANSFORMATION OF MEXICO’S
FINANCIAL SYSTEM
From a purely economic perspective,
financial systems exist to reduce
transaction costs and offset asymmetries
in information among economic agents
(Ayala 2003). As such, the primary role of
a financial system is to allocate resources
efficiently under conditions of uncertainty
and risk. In order to allocate resources
efficiently, banks collect the surplus
(savings) of economic agents by offering a
return
on
investment
(interest).
Concomitantly, resources are channeled
to borrowers through lending activities,
which include interest rates reflecting the
return paid to investors, the costs of
intermediation (and profit), and the risk
involved in making the transaction (Allen
and Gale 2004).
Each of these periods, as well as the
consequences of globalization and
liberalization on access to credit, is
discussed below.
Nationalization (1982-1988)
In the wake of the 1982 debt crisis, the
Mexican government nationalized private
banks on the grounds that they had
generated excessive profits, created
monopolistic markets and facilitated
capital flight (Unal and Navarro 1997).
Expropriation was viewed as a means of
regaining government control over the
financial system and promoting economic
development by channeling credit to small
and medium firms (Maxfield 1992).
G overnment controls remained in place
on interest and exchange rates, reserve
requirements and the distribution of
credit. Although profits increased 19
percent annually between 1982 and 1989,
bank penetration beyond Mexico City
remained
limited
(Mansell-Carstens
1996a).
The operation of the financial system
brings about a different, purportedly more
efficient, allocation of resources than
would otherwise occur (Hernández 2003).
From a theoretical perspective, because
financial institutions reduce risk, they
promote greater savings, which in turn
generates greater economic growth.
Several authors, including King and
Levine (1993), have found that level of
financial development is positively
associated with economic growth. In
addition, Levine and Zervos (1998) have
offered empirical evidence that welldeveloped financial systems are associated
with greater levels of productivity and
capital accumulation. Mexico’s financial
system, however, has been notorious for
its inefficiency, spurring the reforms of the
past two decades.
The period of state-owned banks led to
important lags in training, innovation and
regulation, and large capital investments
were needed to modernize the financial
system (Unal and Navarro 1997). In 1988,
the Mexican government proposed
reprivatization in order to create a more
efficient financial system and increase
competition (Peek and Rosengren 2000).
Liberalization and financial crisis
(1988-1994)
During a 14-month period in 1988-89, the
Mexican government deregulated interest
rates, eliminated restrictions on bank
deposits and minimum reserves, and
opened the financial system to limited
foreign intervention (Hernández 2003).
The goals of liberalization were to
increase domestic savings, improve the
The transformation of Mexico’s financial
system may be divided into three stages:
nationalization;
liberalization
and
financial crisis; and foreign intervention.
Biles
161
The Industrial Geographer
allocation of financial resources, and
increase the supply of credit in order to
promote greater economic growth and
productivity (Ayala 2003). In the short
run, the newly privatized financial system
met expectations – financial penetration
improved, more credit was made available
to the private sector and the costs of credit
were reduced (Mansell-Carstens 1996a).
In December 1994, the Mexican
government responded to balance-ofpayment problems by devaluing the peso
by more than 100 percent. Devaluation
resulted in a sharp decline in real income
coupled with significant increases in
interest rates and inflation. As a result, the
share of non-performing loans exploded to
more than 35 percent by 1997. At that
point, the Mexican government was
forced to intervene, absorbing almost $100
billion 2 in bad debts and taking over 12
banks that were responsible for about 20
percent of all outstanding loans (G raf
1999).
The success of Mexico’s reprivatized
banking system, however, was short-lived.
Privatization and deregulation led to
concentration of resources among a
handful of industrial and financial
conglomerates.
Consequently,
many
banks extended large amounts of credit
without
sufficient
analysis and/ or
collateral. In addition, the interest rate
spread 1 increased by more than 60
percent, decreasing relative returns on
savings and making credit more costly
(Calva 2000). Due to poor management,
questionable lending practices and
relatively high interest rates, many
borrowers were increasingly unable to
repay loans (G raf 1999).
Bank
Foreign intervention (1994-present)
Starting in the mid-1990s, two policy
reforms opened Mexico’s financial system
to greater foreign intervention. The North
American
Free
Trade
Agreement
(NAFTA) gradually eased restrictions on
foreign bank participation, initially
limiting firms to small subsidiaries
engaged in wholesale non-lending banking
activities.
Table 1. Ownership of Eight Largest Banks in Mexico
Market Share
Majority Ownership
Bancomer
25.6%
BBVA (Spain)
Banamex
22.3%
Citigroup (USA)
Banorte
11.4%
G rumasa (Mexico)
Bital
9.3%
HSBC Holdings (UK)
Santander Mexicano
6.5%
Banco Santander (Spain)
Banca Serfin
6.4%
Banco Santander (Spain)
Scotiabank Inverlat
5.0%
Scotiabank (Canada)
Inbursa
3.3%
G rupo Carso (Mexico)
Source: Comisión Nacional Bancaria y de Valores (2003)
Biles
162
The Industrial Geographer
Faced with a desperate need to raise
capital following the financial crisis and
the failure of many privatized banks, the
M exican government further relaxed
restrictions on foreign intervention. By
1995, foreign banks were allowed to hold
a controlling stake in domestic institutions
that accounted for less than six percent of
Mexico’s banking system. Ownership of
the country’s three largest banks, which
controlled 60 percent of all loans, was
limited to 20 percent (Peek and Rosengren
2000).
amount of funding available, improve
quality, costs and availability of financial
services, modernize financial system
infrastructure and increase transparency of
the banking sector (Dages et al. 2000).
Although liberalization of Mexico’s
financia l system may have achieved some
of these objectives, reforms were
undertaken first and foremost for macro economic motives (generation of foreign
exchange, reorganization of government
finances, etc.) with little interest in
impacts on local economic development
(Ferraz and Hamaguchi 2002). Since
foreign banks concentrate on serving
corporate clients and providing consumer
credit and currencies to domestic banks,
rather than financing activities that
expand local production capacities and
employment, the financial sector risks
becoming “detached” from the local
economy
with
large-scale
foreign
intervention (G irón and Correa 1999).
Simply put, foreign institutions may have
no real commitment to domestic
borrowers; consequently, they may not be
responsive to domestic credit needs (Peek
and Rosengren 2000). Detachment of the
banking sector may result in financial
exclusion.
In 1999, all restrictions on foreign
intervention were eliminated. At that
time, international firms took control of
two of Mexico’s six largest banks and held
minority stakes in three others (Dages et
al. 2000). W ith the Citibank takeover of
Banamex in 2001, the liberalization
process was essentially complete – the
Mexican financial system was comprised
of 11 domestic and 19 foreign banks
(Bubel and Skelton 2002). As shown in
Table One above, foreign financial
institutions currently control six of
Mexico’s eight largest banks, representing
about 75 percent of all deposits and
outstanding loans. Mexico is the largest
economy in the world where foreign
interests control such an overwhelming
majority of bank assets (Bubel and Skelton
2002).
Substantial evidence of financial exclusion
exists in Mexico’s banking system.
Following the 1994 financial crisis and
subsequent foreign intervention, banks did
not renew their lending activities to the
private sector. For example, between 1994
and 2000 bank lending fell from 74
percent to seven percent of G DP (Serrano
2001). According to a study by Banamex,
reported in Serrano (2001), only 19
percent of small and medium businesses
in Mexico had access to credit from the
banking sector in 2000, seriously
jeopardizing firms’ ability to undertake
Consequences of liberalization and
foreign intervention
The transformation of Mexico’s financial
system was aimed at creating a more
efficient, competitive, decentralized and
inclusive banking system (MansellCarstens 1996a). Participation of foreign
financial institutions was the primary
vehicle for effecting this transformation.
Foreign banks would purportedly diversify
sources of capital and credit, increase the
Biles
163
The Industrial Geographer
new capital expenditures or expansion.
Furthermore, the lending patterns of
foreign-owned banks vary markedly from
those of domestic institutions – only six
percent of foreign-bank loans are made to
households compared to about 18 percent
among domestic banks (Dages et al.
2000).
and Banco Azteca, the first bank chartered
in Mexico since the 1994 financial crisis.
Cajas populares are
member-owned
cooperatives, whose basic premise is to
promote savings and provide occasional
financing. In general, members are
required to make regular deposits,
according to their household budgets.
Cajas differ from banks in that the total
amount of their lending activities
generally does not exceed their deposits.
As access to bank credit has waned, cajas
have proliferated – more than 1.7 million
Mexicans were caja members in 2002
(COMACREP 2002). In the Yucatán
Peninsula, Sistema Coopera, with 120
offices serving 97,000 members, is the
largest caja popular (A. Torres, personal
communication, December 16, 2003).
These negative consequences have been
confirmed by recent reports in both the
Mexican and U.S. press. Several New York
T imes articles have documented the
obstacles encountered by small businesses
and individuals when soliciting credit
through private banks (Thompson 2002;
Malkin 2002). One Mexican newspaper
confirmed that lack of financing from the
formal banking sector had forced many
low and moderate-income families to turn
to informal sources of credit, such as
pawnshops and moneylenders, in order to
rebuild their homes and businesses
following Hurricane Isidore in September
2002 (Diario de Yucatán 2002).
Monte de Piedad is a non-profit institution
that provides short-term loans, which are
guaranteed by personal property, at
relatively low interest rates. Montepío, as it
is known, operates 80 offices throughout
Mexico serving more than eight million
people annually. In 2003, Montepío
authorized more than $300 million in
financing to eight million Mexicans.
Monte de Piedad operates three offices in
Mérida, the capital of Yucatán. Residents
of rural areas of the state frequently travel
to Mérida to seek financial assistance
from Montepío.
FORMAL
AND
INFORMAL
RESPONSES TO LIBERALIZATION
As the Diario de Yucatán article attests, a
host of organizations have emerged to fill
the void created by Mexico’s foreigncontrolled
banking
system.
The
proliferation of these organizations
indicates that the transformation of the
financial system has failed to promote
more complete participation in the formal
economy.
Banco Azteca is a subsidiary of Grupo
Elektra,
a
large
Mexican
retail
conglomerate. With more than 900
branches located in Elektra stores
throughout the country, the bank began
operations in October 2002. By December
2002, more than 250,000 accounts had
been opened. Banco Azteca also manages
installment plans of more than 800,000
Elektra costumers (Conger 2002). Banco
Formal institutions
The institutions that have cropped up to
meet the needs of low and middle-income
families may be classified as formal or
informal, depending on whether they are
subject to government regulation. Formal
institutions include cajas populares, Monte
de Piedad, Mexico’s national pawnshop,
Biles
164
The Industrial Geographer
Azteca has 15 offices in Yucatán, serving
about 18,000 accountholders. Only three
branches, however, are found in rural
areas of the state.
them institutions of last resort. Tied credit
involves financing linked to transactions
outside the financial sector. This form of
credit is commonly encountered in corner
stores in Mexico. Suppliers allow store
owners to purchase merchandise on
credit; in turn, shop-owners sell goods to
local residents on credit (called fiado in
Mexico). Interest, in the case of both the
supplier and the storeowner, is included in
the price of goods. At least two-thirds of
micro-enterprises in Mexico obtain credit
by this means (Heino and Pagán 2001).
Informal Institutions
The informal credit sector exists because it
resolves problems the formal sector fails to
address. According to Hernández (2003),
the informal sector offers a wide array of
services with a high degree of flexibility,
promotes savings, and motivates a sense
of responsibility and reciprocity among
participants. In addition, the informal
sector allows lenders to obtain a relatively
high return on savings and permits
borrowers to access credit, though at
interest rates higher than those in the
formal sector.
Lending groups include cooperative
efforts to generate resources to satisfy
credit needs. G rameen Bank and Banco Sol
are perhaps the best-known examples.
Lending groups also include rotating
savings
and
credit
associations
(ROSCAs), known in Mexico as tandas or
mutualistas. T andas are usually formed by
a small group of people who know each
other through their work or residence.
Members deposit money regularly, which
is distributed to participants following a
cyclical schedule. This form of credit is
particularly effective in that it creates not
only liquidity, but also reciprocity
(Hernández 2003). Because tandas are an
efficient form of financial mediation that
distributes risk and economizes on
transaction costs, they are found at all
socio-economic
levels
in
Mexico
(Mansell-Carstens 1996b).
Mutualista
financing is similar to the tanda system.
However, the mutualista administrator,
frequently a professional moneylender,
charges a commission for managing the
group.
The informal sector accounts for between
one-third and three-quarters of all credit in
developing countries (Montiel, Agenor
and Ul Haque 1993). Although interest
rates are higher than in the formal
economy,
debts are
usually
not
guaranteed by physical collateral; other
mechanisms, such as social capital, are
employed to minimize risk. Montiel,
Agenor and Ul Haque (1993) have
grouped informal financial institutions
into four categories: 1) occasional lending;
2) regular moneylending; 3) tied credit;
and 4) group lending.
Occasional lending takes place directly
among family and friends when one party
has surplus funds; interest is usually not
charged. Regular moneylending is
performed on an ongoing basis by
institutions (pawnshops, for example) or
persons who make their living from such
activities. In Mexico, these individuals are
known as agiotistas; interest rates are
relatively high and loans are usually
secured by jewelry or real estate, making
Biles
CASE STUD Y
The municipio3 of Valladolid is located
halfway between Mérida and Cancún,
two of the major cities in the Yucatán
Peninsula
(Figure
1).
165
The Industrial Geographer
Figure 1. Location of study area
According to recent census data, the
population of the municipio is 56,776, with
two-thirds of residents living in the city
proper (INEGI 2000). Relative to other
locations outside the state capital,
Valladolid is relatively prosperous, with
an average annual household income of
about $3500.
percent of employees earn less than $2800
annually (INEGI 2000).
Household survey
During December 2003, a detailed survey
was conducted of 101 households in
Valladolid. In general, adult members of
households residing in the city were
contacted in person and asked to respond
to 15 detailed questions regarding their
families’ access to and use of financial
services during the previous 12 months.
Respondents were chosen randomly in
several areas of the city. Questions
included personal information; access to
and use of formal financial services; and
access to and use of informal sources of
credit. The sample size (n= 101), though
relatively small, allows inferences to be
drawn about access to financial resources
among households in Valladolid with a
reasonable degree of accuracy. 4
Due to its population and relative
location, Valladolid’s economy is fairly
well-developed and autonomous. In fact,
based average income and economic
structure, the city is fairly representative of
state and national populations. As shown
in Table 2 below, agriculture comprises
about 20 percent of the local economy,
whereas the service sector accounts for
more than half. Although Banco Azteca,
Sistema Coopera, and several foreignowned banks operate offices in Valladolid,
only 0.2 percent of the workforce was
employed in financial services in 2000.
Census data also reveal that about 46
percent of employment is concentrated in
the informal economy. Almost 30 percent
of workers are self-employed and 73
Biles
Because access to financial resources in
less developed regions is closely
associated with income (Aportela 2001),
the survey was stratified according to
166
The Industrial Geographer
household earnings. 5 Local representatives
of Banco Azteca and Sistema Coopera were
also contacted to gain a better
understanding of their role in meeting
financial needs. The primary objective of
the case study was to understand
differences in access to formal and
informal financial resources, including
bank loans, credit cards, cajas populares,
credit from family and friends, and a
variety of other informal sources
(pawnshops, tandas, mutualistas, agiotistas,
etc.). In addition, the survey sought to
quantify the distribution of formal and
informal credit and identify the relative
importance of formal and informal
financial institutions in the study area.
the high cost of maintaining banking
services (minimum deposits, fees, etc.)
was the main reason for closing their
accounts.
Among formal institutions, Sistema
Coopera also plays a prominent role in
providing financial resources. Sistema
Coopera serves about 950 clients in
Valladolid. The average caja member has
an account balance between $200 and
$500. In general, caja members seek
financing once or twice a year; the
majority of loans are between $500 and
$2,500 and interest rates average between
1.5 and two percent monthly (A.
Rodríguez, personal communication,
December 19, 2003).
Access to formal financial resources
Several foreign-owned banks operate
branches in Valladolid. In addition, Banco
Azteca opened an office in 2002, which
now serves about 4600 clients. However,
only 500 Banco Azteca clients in Valladolid
are savings accountholders, with an
average balance of between $500 and
$600. The office also services 440 local
loan recipients, with an average debt of
about $500 (C. Cupul Majay, personal
communication, December 18, 2003).
Caja officials rely on social capital in order
to ensure timely repayment of loans. A
prospective borrower must procure
signatures from two other caja members
(typically family or friends) in order to
quality for credit. If a caja member falls
behind in repaying a loan, the cosigners
are contacted and asked to remind the
borrower of his/ her obligations. If the
borrower defaults on the loan, the
cosigners must repay the debt. As a
consequence, less than three percent of
borrowers default on loans from Sistema
Coopera.
Notwithstanding the recent advances of
Banco Azteca, bank penetration in
Valladolid is quite limited. Survey results
indicate that only 38 percent of
households
have
bank
accounts.
Furthermore, only 21 percent of
households had obtained bank financing
in the past (11 percent had current bank
loans) and about 10 percent of
respondents had access to a credit card.
The survey also indicated that access to
banking services has become more
difficult – 39 percent of households had
closed a bank account at some point in the
past. Respondents generally indicated that
Biles
According to survey results, about 24
percent of households in Valladolid are
members of cajas populares. Seventy six
percent of respondents using caja services
had accounts in Sistema Coopera; other
households were members of a local
church cooperative (Caja San Bernadino)
and Compartamos, a caja based in Mexico
City that provides financing to women
who operate micro-enterprises. The
majority of caja members (68 percent) had
167
The Industrial Geographer
Table 2. Economic structure of Valladolid, Yucatán and Mexico
Sector
Valladolid Yucatán Mexico
Agriculture and mining
19.9
17.4
16.1
Manufacturing
19.6
18.6
19.0
Construction
10.4
8.9
7.9
Public utilities
1.9
0.5
0.4
Transportation and
3.3
4.3
4.7
communications
W holesale and retail trade
15.9
15.9
16.7
Hotels and restaurants
4.3
4.6
4.5
Financial services
0.2
0.7
1.3
Other services
20.3
25.0
25.2
Public administration
4.3
4.1
4.2
Source: X II Censo General de Población y Vivienda (2000)
obtained financing during the past year; at
the time of the survey, 36 percent
of caja members had loans averaging
slightly more than $750.
that borrow from each other are indeed
more likely to lend to each other.
Access to informal financial resources
According to the survey, informal credit
comprised more than two-thirds of the
total financial resources distributed among
the 101 households surveyed in
Valladolid. The vast majority of
households (82 percent) had made use of
informal institutions to access financing
during the past year. Fifty-nine percent of
respondents indicated that they had
borrowed money from family and/ or
friends; one-third of households had
family debts at the time of the survey. The
average family debt was about $900.
Thirty-five
percent
of respondents
revealed that they had used the services of
a moneylender during the previous year.
Almost 75 percent of households
borrowing from moneylenders had
obtained financing from a tanda or
mutualista; 31 percent had received a loan
from a pawnshop (casa de empeño); and
about 11 percent had borrowed money
from
a
professional
moneylender
(agiotista). The average amount borrowed
from these informal sources was about
$600. Interest rates were high, averaging
between five and ten percent monthly
As mentioned above, occasional lending
among family and friends is viewed as a
means of promoting reciprocity. Fortyseven percent of respondents indicated
that they had lent an average of $300 to
family and/ or friends during the previous
12 months. Chi-square analysis indicates
that a significant relationship exists
between the incidence of occasional
borrowing and lending among family
members (? 2 = 7.866). Family and friends
D istribution of financial resources
Between the formal and informal sectors,
95 percent of the population has access to
some form of credit. Results indicate that
51 percent of all households were carrying
some debt at the time of the survey. The
average level of debt was about $1250. As
shown in Figure 2 below, informal
sources accounted for about 68 percent of
the total credit accessed by survey
respondents.
Biles
168
The Industrial Geographer
Figure 2. Distribution of financial resources according to sector and level of income
When the distribution of credit is
analyzed according to income level,
access is highly uneven. Very low and
low-income households comprise about
70 percent of survey respondents.
However, as Figure 2 reveals, the
moderate to high-income group received
70 percent of all formal credit distributed
among survey respondents. Surprisingly,
wealthier households also accounted for
more than half of total informal credit
obtained by all households. Overall, more
than 60 percent of all financial resources
were concentrated among the wealthiest
households in Valladolid.
income respondents display a surprising
reliance on informal credit, using family
and friends and moneylenders for more
than half of their financial resources.
The distribution of financial resources by
income level may be used to estimate an
informal-to-formal credit ratio, which
reveals relative dependence on the
informal financial system. As shown in
Table 3, the differences between low and
moderate to high-income households are
relatively small. For every peso obtained
from formal institutions, these households
accessed about two pesos of credit from
informal sources. Among the poorest
households,
however,
reliance
on
informal sources of credit is striking; they
obtained more than eight pesos from
family and friends and moneylenders for
every peso borrowed from the formal
financia l sector.
Table 3 below displays additional
information regarding access to financial
resources by level of income. Among the
poorest households, the informal sector
comprises virtually the only source of
credit
(89
percent).
Low-income
households also acquire the vast majority
(71 percent) of their financial resources
informally. Again, moderate to high -
Biles
Statistical analysis provides additional
insights into the relationship between the
169
The Industrial Geographer
Table 3. Distribution of financial resources by income level in Valladolid, Mexico
Income
Level
Bank
Credit
Cajas
Populares
Family/
Friends
Very Low
Low
Mod/ High
0%
5%
34%
11%
24%
4%
83%
6%
8.5
50%
21%
2.4
27%
35%
1.6
Though the formal sector fails to meet the
needs of low-income clients, informal
financial institutions serve 82 percent of
the households in the study area.
Unfortunately, the informal sector is
usually able to provide only limited, shortterm financing. In addition, informal
institutions are relatively inefficient in that
they charge interest rates far above those
of the formal economy.
distribution of formal and informal financial
resources and income level.
Table 4 below reveals a comparable
incidence of debt among households in
the study area regardless of income.
Although the wealthiest households
display a higher level of indebtedness,
substantial variation exists within income
groups and differences are not statistically
significant. Not surprisingly, access to
bank accounts, bank financing, and credit
cards does vary significantly according to
income. Membership in cajas, however, is
similar among income groups. Although
reliance on financing from moneylenders
appears to increase with level of income,
differences are not statistically significant.
Finally, notwithstanding some variability,
reliance on informal credit from family
and friends is comparable within all three
groups.
I/ F credit
ratio
From
another
perspective,
the
transformation of Mexico’s financial
sector may be construed as a concerted
effort to replace informal institutions,
based on social capital, with formal
institutions that operate on an arms-length
basis. Unfortunately, economic reforms
aimed at promoting greater participation
in the formal economy have actually
restricted access to credit and impelled
low-income households and small
businesses to seek financing from informal
sources.
CONCLUSIONS
An efficient, inclusive financial system is a
necessary condition for economic growth.
Although the transformation of Mexico’s
financial system may have promoted
greater efficiency, it has failed to promote
greater equity (accessibility). The case study
from southeastern Mexico, where the
majority of households lack access to
the
formal
banking
system,
corroborates this assertion.
Biles
Money
Lenders
The case of Mexico’s cajas populares,
however, which provide credit at below
market rates with low levels of default,
demonstrates that social capital may be
employed
successfully
by
formal
institutions to improve access to financial
resources.
Finally, it is somewhat naive to classify
formal and informal financial sectors as
separate entities. Consumers may not
170
The Industrial Geographer
Income
Level
Very Low
Low
Mod/ High
X 2 statistic
Table 4. Use of formal and informal resources in Valladolid, Mexico
Pct
Ave
Bank
Bank
Credit Caja
Money
D ebt
D ebt
Use
Loan
Card
Popular Lender
59%
$625
0%
0%
0%
29%
24%
51%
$850
38%
8%
2%
20%
33%
45%
$2450
55%
41%
28%
27%
45%
0.651
4.340
14.190* 9.071* 14.181* 0.893
2.275
* indicates statistical significance at a confidence level of 95 percent
Family/
Friends
65%
51%
72%
4.520
distinguish between institutions operating
within or outside the formal economy.
The author would like to acknowledge the
collaboration of José Antonio Zamora García
and Manuel Martín Castillo from the Centro
de Estudios Regionales Avanzados in
developing this research project. In addition,
the assistance of first-year students in Social
Anthropology and Archaeology at the
Universidad Autónoma de Yucatán was
critical in carrying out survey research.
Finally, the comments and suggestions of
three anonymous reviewers resulted in
substantial improvements to the paper and
were much appreciated.
Furthermore, direct and indirect linkages
exist between both sectors and some
agents operate in formal and informal
financial
systems
simultaneously.
Consequently, additional research is
needed to describe the operations of
regional financial systems in Valladoli d
more completely and to identify linkages
between formal and informal sectors.
Ultimately, the goal of such research is to
promote economic development by
improving the operation of the regional
financial system and expanding access to
credit within formal financial institutions.
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Biles
173
Is the Geography of Banking Services Converging toward Markets? The
Case of Illinois
Bin Zhou
Department of G eography
Southern Illinois University Edwardsville
ABSTRACT
In this paper, we explore whether the geography of bank services has been converging
toward the market since banking geographic deregulation. W e use Illinois as a study area
and examine changes in various market segments such as metro and non-metro markets,
and regional markets. We adopt the Spatial Concentration Index (SCI) and the related
supply and demand SCI deviations to measure changing supply-demand mismatch. We find
that supply distribution was more dispersed than demand distribution in most market
segments in the early 1980s when geographic restrictions on banking were in place.
However, discrepancies in supply-demand distribution declined during the geographic
deregulation and banking consolidations of the last two decades, especially in the 1990s. In
the Chicago market, bank offices were more dispersed, but deposit distributio n more
concentrated, than demand distribution before deregulation. Since deregulation, both office
and deposit distributions have become more aligned with the demand distribution. In
N orthern Illinois metro markets, and to a certain extent in the Central and Southern Illinois
non-metro markets, supply-demand distribution discrepancies have declined only in the
period of 1992 to 2002. In Central Illinois metro markets, while bank office distribution has
become more in line with that of demand, deposit distribution has become more dispersed
than demand distribution during the 1990s. We also find a reduction of the average bank
office size, particularly in larger markets, which provides further support to the hypothesis
of bank market convergence.
Key w ords: bank market, geographic deregulation, spatial concentration index.
Is the Geography of Banking Services
Converging tow ard Markets? The Case
of Illinois
Amid
changing
macroeconomic
conditions and financial realities in the
late 20th century, the U.S. banking
industry has undergone unprecedented
restructuring in the past twenty years
(Rhoades 2000), leading to fundamental
changes in the geography of banking. This
paper investigates one aspect of the
changing banking geography since the
early 1980s, the change in the geography
of banking services. Specifically, using
Illinois as an example, we explore
whether banking services have become
more aligned with the demand for
banking amid
banking geographic
deregulation. In other words, we study
whether there has been any convergence
of the geography of bank services toward
the market.
GEOGRAPHIC RESTRICTIONS AND
BANK GEOGRAPHIC MARKETS
The traditional Arrow-Debreu model of
resource allocation places a seamless
The Industrial Geographer, Volume 2, I3sue 2, pp.174-192 ©2004 Zhou
The Industrial Geographer
market as the focal point in household
and firm interactions, and gives no role to
financial intermediaries (banks included),
and by extension to their locations (Allen
and Santomero, 1998). However, financial
intermediation theory suggests otherwise.
Transaction costs involving customer
credit information, monitoring loan
performance and knowledge of specific
activities financed by bank lending carries
real risks and thus help break down bank
markets into disjoined segments (G urley
and Shaw, 1960). These transaction costs
in many ways are associated with distance
and locations, and thus contribute to
geographic fragmentation of local retail
banking. Regulatory restrictions may also
erect barriers to market entry, adding to
and altering the pattern of market
fragmentation. Even the cost of
overcoming distance helps delineate space
into self-contained sub-markets, as
illustrated in central place theory (Berry
and Parr, 1988). Indeed, as Cooperman et
al (1991) observe, the U.S. banking system
operates as a collection of segmented
markets involving retail customers, and
some
integrated
banking
systems
involving regional and national (even
international) corporate clients.
Historical geographic restrictions on
banking, however, occurred largely due to
political reasons and under specific
historical circumstances (Calomiris 2000).
They came as a result of policy choices to
redirect economic benefits. Local special
interest groups such as small banks, local
businesses, and governments in the 19th
century persuaded state legislatures to
erect geographic restrictions on banking
out of self-interest against financial
instability
associated
with
outside
financial power. The costs of overcoming
such local protectionism led to a system of
semi-independently operating local retail
banking markets (Kroszner 2000), adding
to the fragmentation and inefficiency of
the whole banking system (Calomiris
2000). In the last two decades when the
survival of the banking industry came
under threat due to competition from
overseas and domestic non-bank financial
institutions, the purpose of banking
regulation
(including
geographic
deregulation) and efficiency gain have
converged (Calomiris 2000).
Traditional geographic restrictions may
generate inefficiency by limiting the
locations and numbers of bank offices
from the level desirable for a market
(Evanoff 1988). Although there have been
numerous studies comparing bank service
availability
under
different
branch
restrictions (Kaufman et al 1983; Savage
and Soloman 1980; Berger et al. 1999),
very little has been said about how, under
the same geographic restrictions, places of
different
sizes and
socioeconomic
characteristics (rural vs. metropolitan)
may develop different bank service
availability. However, in an early study on
Alabama banking, Guttentag and Thomas
(1979) present data revealing interesting
characteristics. Their data reveal that
within the pool of unit banking counties,
Although transaction costs and the cost of
overcoming distance are real expenses and
thus reduce efficiency, they arise mostly
due to unavoidable factors. For example,
transaction costs are closely associated
with asymmetric information in which the
borrower asks for credit but attempts to
conceal as much information on him as
possible for self-protection (Leland and
Pyle, 1977). Such a desire is deeply rooted
in the human psyche and constitutes an
integral part of human nature. Costs
associated with distance arise since
physical distance is an inherent element of
every reality in human life.
Zhou
175
The Industrial Geographer
metro counties have a per capita income
27% higher than, and a population density
nearly 4 times higher than, in non -metro
counties. However, the number of metro
bank offices per 1000 people is 30% lower
than that in non-metro counties. Counties
with limited branching demonstrate
similar metro-rural disparity, though at a
lower level than observed in unit banking
counties. In other words, there seems to
be under-served markets in metro counties
compared with non-metro counties.
corporate structure may result in larger
office sizes substituting for fewer
locations. Bank customers received basic
banking services at the cost of waiting
longer, traveling further, enduring traffic
jams, etc. though they may also have
enjoyed the benefits of cross-selling and
the diverse lines of products available at
larger offices. However, providing a whole
spectrum of services in every office may
not be the ideal business strategy. This
means that office size may not be a perfect
substitute for office locations in order to
accommodate large markets. W ith
geographic deregulation, along with bank
consolidation, increasingly larger banks
may consolidate offices in small markets,
establish more branches in larger bank
markets, alter office size distribution and
re-bundle the service mix among offices of
various sizes. The results are that banking
services increasingly come in line with the
distribution of bank markets, and the
geography of banking services converges
toward the market. We investigate
whether this has occurred over the last
twenty
years
amid
fundamental
geographic deregulation.
Traditional branch limitations reduce
efficiency by prohibiting banks’ desire for
expansion through branching. Banking
institutions desiring growth in a large
market may be forced to choose a multibank holding company structure as a
substitute. A bank requires a full corporate
governance structure, which is much more
expensive than a branch office. Such an
expensive structure may discourage bank
holding companies from establishing
adequate banks, leading to inadequate
services by bank offices. In comparison,
small markets were traditionally served by
small banks. Their simple corporate
structure, and in many cases state
charters, may have given them a cost
advantage in setting up operation in small
places. Legislation allowing limited
branching may have given them just
enough space to expand business locally,
while curtailing the invasion by powerful
outside institutions. The result would
have been that larger markets had fewer
bank service locations than banks would
like to have, leading to under-banking
compared with smaller markets. This may
be particularly true in states with many
small,
and
often
agricultural,
communities, which would encourage
bank legislation designed to protect these
small communities. In larger markets,
costly banking locations associated with
Zhou
W e choose Illinois as our study area
largely because Illinois is a state known
until recently for its unit banking system.
Given such a unit banking structure, the
dispersion and concentration mechanism
described above may particularly apply. In
addition, Chicago, one of the largest
banking centers in the United States, is
located in Illinois. The confluence of these
two characteristics, a unit banking
tradition and the dominance of Chicago
banks, raises the question of whether
changes in the geography of banking
services in Illinois go along different paths
with the Chicago market, dominated by
the Chicago banks, going one way, and
other market segments in the state going
176
The Industrial Geographer
another. The changing geography of
banking services occurs within a specific
historical-geographical
configuration.
Illinois offers a unique case study to
observe such a contextual based change.
nation’s railroad hub and a major market
center amid the westward movement
(Nelson, 1978). In the process, the
economic center of gravity in Illinois
shifted from southern Illinois to northerly
locations, especially the Chicago area. In
1835, a new State Bank of Illinois opened
for business with the main office in
Springfield and branches in many central
and northern Illinois’ cities. A great many
more banks were opened during "banking
inflation" in the subsequent two years
(Knox 1903), only to collapse during the
business panic in 1837. The state was left
without chartered banks. Private banks
(unchartered and privately held) and
illegal banks (non-bank institutions such
as insurance companies) filled the void.
Many of these private and illegal banks
were Chicago institutions.
A BRIEF HISTORY OF ILLINOIS
BANKING
During most of the 18th century, in the
area of present day Illinois, European
settlers established communities along
wooded riverbanks in southern Illinois,
while northern and central Illinois was
still occupied by Native Americans
(Foster, 1968). Since the early 19th
century, steamboats facilitated trade and
commerce, leading to several thriving
towns near and along the rivers. In 1813,
the first bank in present day Illinois was
established in Shawneetown, the leading
city in southern Illinois and perceived
gateway from the East, near the
confluence of the Ohio and the W abash
rivers. In 1816, the bank received a charter
from the territorial legislature. The
following year, three additional banks
were incorporated at Edwardsville, Cairo,
and Kaskaskia. In 1818 Illinois gained
statehood and within a few years, a new
State Bank of Illinois was established with
the main office at the state capital
Vandalia and branches in a few other
southern cities.
In 1851, Illinois adopted “free banking".
Any individual could issue bank notes as
long as the notes were backed by federal
or state bonds. Some private and/ or
illegal banks took advantage of this law
and reorganized into legal banks.
Examples include the Chicago Marine
and Fire Insurance Company reorganized
into the Chicago Marine Bank, and
G eorge Smith and Company reorganized
into the Bank of America, also a Chicago
bank. By this time, Chicago had become a
leading banking center for Illinois and the
Northwest (Huston, 1926). At the turn of
the century, it was one of the few reserve
centers in the nation, along with New
York City and San Francisco.
The “Internal Improvements” movement
opened vast lands in central and northern
Illinois to settlers by building canals and
railroads. The completion of the Erie
Canal in 1825, and the final removal of
the Native Americans allowed white
settlers to arrive in Chicago via the Great
Lakes (Foster, 1968). Chicago, a small
village of 150 inhabitants in 1833 when
incorporated (Huston, 1926), grew rapidly
in the next three decades, reaching
100,000 by 1860. Chicago became the
Zhou
The national banking movement since
1864 adopted many provisions for "free
banking" by lowering the barrier to entry
into banking. Banks were chartered
through regulatory agencies instead of
legislative process. Lower barriers to entry
into banking made it possible for sma ll
177
The Industrial Geographer
communities to start their own banks.
This, along with dispersed population, the
agriculturally based economy, relatively
lower income and limited banking needs,
and transportation conditions at the time,
contributed to a unit banking system
(Fischer, 1968). Banking was viewed as a
local concern and banking institutions
were to draw deposits from local
depositors and were mainly dedicated to
local funding needs (G atton, 1991). In
1870, the Illinois Constitution prohibited
branch banking. For the next one hundred
years, Illinois remained a unit bank state.
The 1970 state Constitution reaffirmed the
prohibition on branching. In 1966, while
over a quarter of the banks in the United
States were branch banks, less than 0.4%
of Illinois banks had branches.
consolidations in Illinois. From 1980 to
1998, there were over 750 mergers and
consolidations between different banking
institutions in Illinois. The number of
commercial banks declined from 1253 in
1980 to 692 in 2001. During the same
period, the number of branch offices
increased from 534 to 2899. In 2001, 66%
of the commercial banks in the state were
branch banks. The number of branch
offices per bank increased from 0.4 per
bank in 1980 to 4.2 in 2001. While the
number of banks declined by 45% between
1980 and 2001, the average size of banks
measured in assets more than doubled
from $135.9 million to $355.7 million,
adjusting for inflation. Following the
national trend, Illinois banking has
become more concentrated, and multilocational in nature.
W ith the emergence of an urban-based
economy,
changing
population
distribution,
improvement
in
transportation and communication, and
increasing
income,
the
legislative
obstacles to modern banking were
incrementally overcome by the need to
meet demand in a new world of banking.
From 1967 to 1976, Illinois loosened
branch restrictions allowing limited intra city branching. The banking crisis of the
1980s that swept the country and brought
down the Continental Illinois Bank helped
stir the state legislature to allow more
freedom in banking such as inter-city
branching within the same county, and
limited out-of-county branching. In 1986,
the state allowed out of state bank holding
companies to acquire banks in Illinois. In
1993 unrestricted statewide branching was
allowed. Illinois also opted into the 1994
Riegle-Neal Interstate Banking and
Branching Efficiency Act, which allows
nationwide interstate banking and
branching. These legislative changes have
come in conjunction with significant bank
Zhou
METHOD S AND D ATA
Operationally, exploring whether banking
services are converging toward the market
requires the comparison of two sets of
variables that represent locations of bank
service supply and demand. Although
banking services are reflected through
avenues such as bank offices, the Internet,
telephones, and even informal personal
contacts and exchange, difficulties in
obtaining relevant information force us to
confine ourselves to bank office data,
supplemented by bank deposit data. Bank
office locations are where many retail
bank services (loan origination, safe
deposit, teller banking, and retail
insurance selling and investment advising,
etc.) are delivered. There are still over
80% of bank customers who use an office
once a month, and 30% use an office 4 to
5 times each month (Wall Street Journal,
2003a). Building branches has been one of
the most effective ways for banks to
compete for retail customers (W all Street
Journal, 2003b).
178
The Industrial Geographer
To the extent that deposits are the
consequence of bank deposit taking,
locations of deposits reflect the geography
of bank services and their magnitudes.
However, deposits at the offices of large
banks may come from retail as well as
corporate customers, the latter of which
may be locally, regionally, nationally, or
even internationally based. In most
deposit statistics, deposits from local and
non-local markets are lumped together.
The deposit figures from published data
may not mirror the magnitude of services
rendered locally. To the extent that localmarket based deposits dominate outside
deposits, deposit information may still be
useful in addressing location-specific
issues. However, the unknown amount of
non-local deposits calls for caution in
interpreting the results.
Historical limitations on branching and
cost differential inherent in bank vs.
branch operation may have led to underbanking in large markets and overbanking in smaller markets. Hence,
elimination of geographic restrictions may
cause a shifting of banking services to
previously under-served, larger markets.
Thus, our focus here is on changing
banking service availability in markets of
different sizes. That is, whether
concentration (or dispersion) of bank
services among markets of different sizes
has become increasingly aligned with the
sizes of bank markets. To this end, we use
indices of spatial concentration for bank
supply and demand, constructed with
supply variables and demand variables
respectively. These indices in turn are
used to measure the market mismatch
between bank supply and demand.
On the demand side, many proxies can
arguably represent demand for banking.
W e use population and personal income
because of the ease in obtaining historical
data. Sizes of population are related to
the potential numbers of customers for
bank office visits. However, banks do not
make branch decisions by merely
following the size of population. They
also consider the earning potential of a
given population. This consideration
favors using personal income as a proxy
for banking demand. Personal income (the
total income received by all persons in a
market from work related earnings, rental
income, dividend income, personal
interest income, and transfer payments) is
conceivably related to personal wealth.
W e use both population and income
measures since each has its own merit.
The index we adopt is a spatial version of
the Herfindahl-Herschman Index (HHI). 1
The HHI is used in antitrust enforcement
as a measure of market concentration. In
that context, it quantifies the degree of
concentration resulting from the operation
of all firms in a market. The HHI belongs
to a family of indices that also includes the
Rosenbluth Index and the Entropy Index
(Jacquemin, 1987). All these indices
utilize shares of individual firms in a
market. The difference resides in how
such percentages are weighted (Shephard,
1979). Different indices also vary in terms
of their emphasis on different aspects of
market structure. While the HHI gives
weight to the influence of large firms, the
Entropy Index tends to emphasize small
firms in shaping the overall index. The
Rosenbluth Index incorporates both firm
market shares and firm ranks. Studies
have found strong correlations between
different concentration indices (Nelson,
1963).
As discussed above, our interest in
banking service geography is derived from
a particular context of U.S. banking: the
geographic restrictions on banking.
Zhou
179
The Industrial Geographer
The spatial version of the HHI quantifies
the degree of spatial concentration of an
economic activity across all spatial units
involved in a market segment. It replaces
the firm shares in the HHI with shares of
spatial units. For this reason, it can be
called the Spatial Concentration Index
(SCI). The SCI is the sum of squared
market share of all spatial units.
Specifically,
change. The maximum value of the SCI is
10,000.
Since the focus of the study is whether
bank supply converged toward the
demand, we calculate both the demand
SCIs using bank demand variables
(population and income) and the supply
SCIs using supply variables (offices and
deposit). The differences between a
demand SCI and a supply SCI indicate
bank service mismatch. Specifically, we
subtract a demand SCI from a supply SCI
to find a deviation. A negative deviation is
defined as a dispersion deviation where
supply distribution is more dispersed than
demand distribution. On the other hand, a
positive deviation can be called a
concentration deviation in which supply
distribution is more concentrated than
demand distribution. Since the traditional
geographic restrictions are believed to
contribute to under-banked larger markets
and over-banked smaller markets in
relation to their demand, the basic
premise of banking deregulation is to
loosen shackles on banks and allow them
greater freedom to chase the market for
profits. If this were the case, we would
expect the supply-demand mismatch to be
manifested in larger dispersion deviations,
when geographic restrictions were in
place. Over time, when geographic
restrictions were eroded and eventually
eliminated, we would expect diminishing
supply-demand mismatch, manifested in
declining magnitudes of dispersion
deviations. Essentially, we use demand
SCIs as benchmarks for comparison to see
whether supply SCIs have been catching
up to demand SCIs.
n
SCI = ∑ S i = S1 + S 2 + S3 + ... + Sn
2
2
2
2
2
i =1
.
In the above, S is the share of a market in
a market segment, and n the number of
markets within the market segment.
Because we will be calculating SCI for
various market segments such as the entire
state, metro markets, and non -metro
markets, n takes on different values
depending on the number of markets in
these segments. We also consider regional
market segments. To this end, we use a
modified Illinois regional delineation
developed within Illinois Strategic
Planning, a state initiative to promote
statewide economic development in the
new millennium. It divides Illinois into
four strategic regions (Figure 1). We
combine
the
Northeastern
and
Northwestern regions due to geographical
proximity to form a Northern region, and
retain the original Central and Southern
regions.
The market shares of the spatial units
involved
ultimately
determine
the
magnitude of the SCI. A higher (lower)
SCI indicates a higher (lower) degree of
spatial concentration, as a result of more
(less) uneven distribution among markets.
Changes in spatial distribution will
necessarily alter the shares of different
markets, which will cause the SCIs to
Zhou
W e construct the SCIs and the related
supply and demand SCI deviations for
three landmark years, 1982, 1992, and
2002. The early 1980s marked the
180
The Industrial Geographer
beginning of U.S. banking deregulation,
manifested in the Depository Institutions
Deregulation and Monetary Control Act
of 1980 and the Gain-St. Germain
Depository Institutions Act of 1982. These
laws unleashed significant portfolio
changes for depository institutions and
helped trigger the bank merger wave in
the 1980s. Throughout the course of the
1980s to the early 1990s, Illinois
increasingly lifted branch limitations. In
1992, the U.S. economy came out of a
recession. The number of bank mergers
were on the rise again, which led to the
bank consolidation of the 1990s. In 1993,
Illinois abolished limitations on in -state
branching altogether. By 2002, amid
bursting stock market bubbles and slow
economic growth, bank mergers all but
died out. W ith the merger announcements
of the Bank of America with FleetBoston
Financial in late 2003, and J.P. Morgan
with Bank One in early 2004, U.S.
banking seems to have entered a new
round of consolidation. Therefore, the
SCIs for 1982 take stock of priorderegulation banking concentration or
dispersion patterns; SCIs for 1992
measure the result of the 1980s bank
consolidation, and SCIs for 2002 measure
the result of 1990s bank consolidation.
institutions. Population and personal
income data are obtained from the
Commerce Department’s Bureau of
Economic Analysis.
RESULTS
Increasing Market Accessibility
Table 1 shows rates of growth in demand
and supply measures (the left side) and the
shares of bank demand supply measures
(the right side) for various market
segments with and without the Chicago
market. In all cases, bank supply variables
grew faster than did demand variables,
and growth was more rapid in the second
sub-period from 1992 to 2002 than in the
first sub-period from 1982 to 1992. The
Chicago market experienced faster growth
in all four variables than all other market
segments; metro markets, excluding the
Chicago market, experienced faster
growth than non-metro markets. Some
exceptions occurred to patterns in the two
sub-periods. In the first sub-period, the
Chicago market suffered negative growth
in deposits. This may largely be attributed
to problems in major Chicago banks in the
1980s associated with the agricultural
recession in the Midwest, the Third World
debt crisis, and resultant troubles
experienced by large Chicago banks such
as the First Chicago and Northern Trust
and manifested in the collapse of the
Continental Illinois Bank and Trust
Corporation in 1984, then the largest
Chicago bank and the 7th largest bank in
the U.S. The fortunes of the Chicago
banks have reversed since the mid 1990s
with a series of consolidations involving
large
banking
institutions,
which
revitalized the Chicago market as a
dominant banking center in the United
States. 3
Following Federal Reserves Banks, we use
metropolitan
statistical
areas
as
metropolitan bank markets, and counties
as non-metropolitan bank markets. 2 Bank
office and deposit data are obtained from
Bank Data Books for various years
published by the Federal Deposit
Insurance Corporation (FDIC). Since
commercial banks are increasingly
competing with many other financial
institutions in the same market, we
incorporate office and deposit information
for both commercial banks and saving
Zhou
181
The Industrial Geographer
Figure 1. Illinois Strategic Planning Regions
Zhou
182
The Industrial Geographer
Table 1 Changes in Supply and Demand Variables: Illinois
Market segment
All markets
All markets
excluding
the Chicago
market
Non-metro
markets
All metro
markets
Metro markets
excluding the
Chicago
market
The Chicago
market
Change (%)
Variable 1982-1992 1992-2002 1982-2002
Population
2.4
7.1
9.6
Income
21.2
24.9
51.4
Office
28.2
74.2
123.2
Deposit
1.7
54.5
57.1
Population
-2.4
1.8
-0.6
Income
8.7
14.8
24.8
Office
17.8
45.4
71.3
Deposit
6.8
30.4
39.2
Population
-5.1
0.2
-5.0
Income
3.5
10.7
14.6
Office
13.7
38.3
57.3
Deposit
0.9
19.5
20.6
Share as State Totals (%)
1982
1992
2002
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
36.5
34.8
33.1
31.2
28
25.7
61.5
56.5
47.2
27.7
29.1
25.6
17.2
15.9
14.9
13.9
11.8
10.5
37.3
33.1
26.3
14.8
14.7
11.4
Population
3.9
8.4
12.6
Income
24.1
26.8
57.3
Office
36.8
91.9
162.5
Deposit
1.8
60.6
63.5
Population
0.1
3.2
3.3
Income
12.9
17.7
32.8
Office
24
55.4
92.8
Deposit
13.5
41.5
60.6
Population
5.1
9.9
15.5
Income
26.9
28.8
63.4
Office
44.8
111.5
206.4
Deposit
-0.3
64.4
64.0
Sources: FD IC, D ept of Commerce. Calculated
82.8
86.1
62.7
85.2
19.3
17.3
24.2
12.9
63.5
68.8
38.5
72.3
by author
The first sub-period also saw slow
population growth in metro markets,
negative population growth in non -metro
markets, and slow deposit growth in non metro markets. This slow non-metro
deposit growth may reflect the impact of
the Midwestern agricultural crisis at the
time. The dynamics of growth in various
market segments have caused changing
distributions of demand and supply
variables. For the entire period of 1982 to
2002, the Chicago market gained shares in
supply and demand variables at the
expense of non-Chicago markets, except
for a loss of deposit share to other metro
markets in 1992. Outside the Chicago
Zhou
84.1
88.2
66.9
85.3
18.9
16.2
23.4
14.4
65.2
72.0
43.5
70.9
85.1
89.5
73.7
88.6
18.2
15.2
20.9
13.2
66.9
74.3
52.8
75.4
market, metro markets gained shares at
the expense of non-metropolitan markets.
At the regional level (Table 2), we find the
growth pattern in all Illinois regions and
in most market segments within each
region to be largely comparable to those
found at the state level. That is, faster
growth in supply variables than in
demand variables, faster growth in metro
markets than in non -metro markets, and
in most cases, faster growth in the second
sub-period than in the first sub-period for
most variables. 4 Among the three regions,
Northern Illinois gained at the expense of
the other two regions. W ithin each region,
metro markets gained at the expense of
183
The Industrial Geographer
non-metro markets. One feature from the
above analyses stands out. In most market
segments, and at both the state and
regional levels, supply variables grew
faster than demand variables. This means
that at all levels and within most market
segments, bank services have become
more accessible. To determine whether
improvement in market accessibility is
more significant in larger markets than in
smaller ones, we now turn to the analysis
using the SCIs and the related supply and
demand SCI deviations.
importantly, the general trend is that the
magnitudes of deviation decrease over
time. This is especially true for deviations
involving bank offices. In deviations
involving deposits, non -metro markets
conform to such a pattern.
In all cases including the Chicago market
and in the case of metro markets
excluding the Chicago market, depositdemand deviations reduced in the first
sub-period but rose again in the second.
The reversal in the second sub-period for
all cases including the Chicago market
occurred because the deposit decline in
the Chicago market between 1982 and
1992 was so significant that any recovery
would give an appearance of rising
dominance. However, even here, the
magnitudes of concentration deviations
have not reversed to the level reached in
1982. Within metro market deposit
deviations, excluding the Chicago market,
there seems to be a real case of deposit
dispersion during the second sub-period.
Declining
Supply-D emand
SCI
D eviations
As discussed previously, changing SCIs
indicate shifting distribution among
markets of different sizes. Changing
deviations between a supply SCI and a
demand SCI indicate changes in market
mismatch over time. Table 3 contains
dispersion/ concentration
deviations
measured as the percent of demand SCIs.
For all cases including the Chicago
market, office-population and officeincome deviations have negative values,
while most deposit-population and
deposit-income deviations have positive
values. This suggests that the spatial
distribution of bank offices was more
dispersed than population and income,
while the distribution of deposits was
more concentrated than population and
income. However, when the Chicago
metro market is excluded, offices and
deposits show a greater level of spatial
dispersion than population and income.
Apparently, it is in the Chicago market
where office distribution was more
dispersed than, and deposit distribution
more concentrated than, the demand
distribution. In all other markets
segments, there is a consistent pattern of
supply distribution being more dispersed
than
demand
distribution.
More
Zhou
This occurred largely due to the
diminishing significance in the Metro East
and to a certain extent, the Peoria metro
market. The Metro East is the Illinois
portion of the St. Louis metro market. Its
share of demand variables in the state’s
metro markets, excluding the Chicago
market, declined in the 1990s when
banking activities in the St. Louis metro
market increasingly shifted to the
Missouri portion of the market (Zhou
1997), leading to declining deposit
concentration or deposit dispersion. The
Peoria metro market is a traditional
manufacturing center that has suffered
from economic restructuring and loss of
population in the 1980s. In the 1990s, the
region struggled to recover economically
but today it still has over a third of its
civilian labor force in manufacturing,
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The Industrial Geographer
Table 2 Changes in Supply and Demand Variables: Regional
Variable
Population
1982-1992
4.2
Change (%)
1992-2002
9.2
1982-2002
13.8
1982
72.4
Income
Office
Deposit
25
38.3
0.9
27.5
95.7
61.1
59.3
170.7
62.6
76.7
52.2
78.9
79.1
56.1
78.2
80.7
63.3
81.7
All Northern
metro
markets
Population
Income
Office
Deposit
4.6
25.8
41.7
0.5
9.5
28
103
62.7
14.6
61
187.5
63.5
69.2
73.9
45.4
76.1
70.7
76.7
50
75.1
72.3
78.6
58.6
79.2
All Northern
non-metro
markets
Population
Income
Office
-4.5
3.6
16
1.2
11.6
36.6
-3.3
15.6
58.4
3.2
2.8
6.8
3.0
2.4
6.1
2.8
2.2
4.8
Deposit
12.1
23.2
38.1
2.8
3.1
2.5
All Northern
markets
excluding the
Chicago market
Population
Income
Office
-2.3
8.4
18.6
4.1
13.9
44.7
1.8
23.4
71.1
8.9
7.9
13.8
8.5
7.1
12.7
8.3
6.5
10.6
Deposit
Population
Income
12.6
-1
11
30.7
5.7
15
47.2
4.6
27.7
6.7
5.7
5.1
7.4
5.5
4.7
6.2
5.4
4.3
Office
Deposit
21.1
5.2
51.6
36.3
83.6
54
7
3.8
6.5
4.2
5.8
4.1
Population
Income
-2.8
7.8
1
16.2
-1.8
25.2
15.8
13.9
15
12.3
14.2
11.5
Office
Deposit
Population
14.9
1.9
-0.01
47.8
40.2
2.7
69.8
42.9
2.7
28.8
12.3
8.5
25.7
12.4
8.3
21.9
11.2
7.9
Income
Office
Deposit
13.3
19
5.2
20.4
60
56.8
36.4
90.5
64.9
7.8
11.4
6.1
7.3
10.6
6.3
7.1
9.7
6.4
All Central
non-metro
markets
Population
Income
Office
Deposit
-6.0
0.7
12.2
-1.2
-1.0
9.9
39.3
23.0
-7.0
10.7
56.3
21.5
7.3
6.1
17.4
6.3
6.7
5.0
15.2
6.1
6.2
4.4
12.2
4.8
All Southern
markets
Population
Income
Office
-1.9
10.4
23.6
1.2
13.5
40.5
-0.8
25.2
73.6
11.8
9.4
18.8
11.3
8.6
18.2
10.7
7.8
14.7
Deposit
10.7
15.5
27.8
8.7
9.5
7.1
All Southern
metro
markets
Population
Income
Office
1.5
14.5
39.3
1.5
15.9
49.7
3.0
32.7
108.4
5.1
4.4
5.8
5.1
4.1
6.3
4.8
3.8
5.4
Deposit
Population
Income
32.5
-4.6
6.8
21.1
0.9
11.2
60.4
-3.6
18.7
3.0
6.7
5.0
3.9
6.2
4.4
3.0
5.9
3.9
Office
Deposit
16.6
-0.6
35.6
11.6
58.1
10.9
13.1
5.7
11.9
5.6
9.3
4.0
All Northern
markets
All Northern
metro markets
excluding the
Chicago market
All Central
markets
All Central
metro
markets
All Southern
non-metro
markets
Share in state totals
1992
2002
73.7
75.1
Sources: FD IC, D ept of Commerce. Calculated by author
Zhou
185
The Industrial Geographer
Table 3 Dispersion and Concentration Deviations as the Percent of Demand SCIs (%)
Office vs. Population
Market segment
All markets
Deposit vs. Population
Office vs. Income
Deposit vs. Income
1982
1992
2002
1982
1992
2002
1982
1992
2002
1982
1992
2002
-61.2
-53.8
-27.0
28.3
17.4
26.2
-66.8
-61.9
-48.5
9.9
-3.1
3.0
-39.4
-35.0
-29.7
-21.9
-15.0
-11.4
-43.5
-40.3
-36.5
-27.2
-22.0
-19.9
All non-metro
markets
-11.7
-10.1
-6.5
-7.5
-6.9
2.3
-16.1
-13.3
-10.6
-12.1
-10.2
-2.2
All metro
markets
-29.8
-27.7
-16.0
27.7
14.1
16.4
-38.3
-34.5
-24.2
12.4
3.5
5.1
-7.9
-2.7
-2.8
-8.1
-1.1
-8.9
-6.5
-1.0
0.2
-6.8
1.1
-6.5
-28.6
-22.8
-12.1
8.7
4.7
7.0
-31.5
-27.0
-17.5
4.2
-1.0
1.0
Northern markets
excluding the
Chicago market
-26.8
-28.2
-25.4
-10.3
-16.2
-11.6
-29.0
-31.2
-27.4
-15.6
-19.8
-14.0
Northern
non-metro
markets
-9.2
-8.7
-5.6
-8.5
-8.1
1.0
-11.1
-8.1
4.6
-10.4
-7.6
2.0
-14.1
-10.7
-4.7
6.9
4.5
5.9
-16.4
-13.7
-8.6
4.1
1.0
1.6
-4.4
-7.2
-6.4
0.8
-2.2
-1.0
-6.0
-9.2
-7.0
-0.9
-4.4
-1.6
-36.8
-34.4
-27.9
-16.3
-13.8
-4.0
-42.4
-41.2
-37.7
-23.8
-22.8
-17.0
-6.1
-3.9
0.1
-5.7
-1.8
-6.0
-8.0
3.0
0.1
-7.6
-1.8
-6.2
-17.0
-14.1
-11.8
-8.0
-12.1
-6.6
-18.4
-16.1
-13.4
-9.6
-14.1
-8.3
Southern
markets
-44.3
-36.5
-29.4
-33.9
-15.8
-8.6
-51.1
-44.5
-40.3
-41.9
-26.4
-22.8
Southern nonmetro markets
-10.0
-19.5
-3.9
-7.6
-8.8
-3.7
-11.5
-10.8
-7.8
-9.1
-10.1
-7.6
All markets
excluding the
Chicago market
All metro markets
excluding the
Chicago market
Northern
markets
Northern
metro markets
Northern metro
markets excluding
Chicago market
Central markets
Central metro
markets
Central
non-metro
markets
Sources: FD IC, D ept of Commerce. Calculated by author
Zhou
186
The Industrial Geographer
which contributed to its diminished
position in banking.
The declining
importance of the Peoria market is also
largely responsible for the similar deposit
deviation reversal in the second subperiod for Central Illinois metro markets.
the delayed
deviations.
in
office
Changing Bank Office Sizes
As suggested earlier, under geographic
restrictions, banks in the metropolitan
environment may substitute office sizes
for fewer locations in order to
accommodate large markets. If bank sizes
and locations are perfect substitutes,
increasing bank
demand
in
the
marketplace can be equally met by
increasing either the bank office size or the
number of bank offices. W hen market
participants randomly choose between the
two strategies to accommodate changing
markets,
office
sizes would
not
demonstrate clear pattern of changes
along markets of different sizes.
There is one other exception to the
general trend of declining supply and
demand SCI deviations at the regional
level. This can be called delayed
convergence where the supply-demand
SCI deviations rose in the first sub-period
but fell in the second. The delayed
convergence occurred in the Central and
Southern non-metro markets depositdemand deviations, and in Northern
metro market supply-demand deviations,
excluding the Chicago market. In the case
of Central and Southern non -metro
deposit-demand deviations this may be
explained by the banking problems in
large non-metro markets attributable to
the agricultural crisis during the 1980s. 5 In
the Northern metro market, excluding the
Chicago market, the delayed convergence
may have occurred as a result of the close
relationship between the Chicago banks
and banks in other Northern metro
markets, through loan participations and
correspondent banking. It is important to
note that while the delayed convergence
occurred only in deposit deviations in
Central and Southern Illinois markets, it
occurred to both office deviations and
deposit deviations in Northern metro
markets, excluding the Chicago market.
However, as explored earlier, if the
location and office size are not perfect
substitutes, the erosion of branch
restriction
would
cause
banking
institutions to rationalize the distribution
of office sizes and the related services.
Specifically, banks may consolidate
specialized services in a small number of
larger offices on the one hand and saturate
the market with branch offices to provide
basic services and compete for low cost
deposits on the other. The result would be
that while a few offices with special
functions become larger, the overall office
size would on average decline, especially
for large markets. Although a lack of
bank portfolio information at the office
level prevents a complete empirical
investigation of this issue, some evidence
seems to support the above statement
concerning changing bank office sizes.
Table 4 lists the average bank office sizes
(adjusted for inflation) for various market
segments and rates of change. A common
pattern is the declining average office sizes
This is mainly due to a rare case in
Northern metro markets where the
population and income SCIs rose more
rapidly than the office SCI. This means
that during that sub-period, the pace of
demand concentration in larger markets
was faster than that for offices, leading to
Zhou
convergence
187
The Industrial Geographer
throughout the study period, especially
the second sub-period. In nearly all cases,
the standard deviations also reduce over
time, indicating a stable process of
declining office sizes. More significantly,
metro markets tend to experience higher
rates of size reduction than non -metro
markets, and the Chicago market, the
largest market of all, experienced the
largest rate of reduction of office size.
Although all metro markets excluding the
Chicago market seemed to experience a
smaller rate of size reduction than in all
non-metro markets, a breakdown at the
regional level shows a pattern generally
consistent with the overall pattern of office
size change. For example, in Northern
Illinois, metro markets excluding the
Chicago showed higher rates of size
reduction than non-metro markets in the
north. Metro markets in Central Illinois
also demonstrated higher rates of size
reduction than in non-metro markets. The
only exception is in Southern Illinois
where only the Metro East portion of the
St. Louis metro market is accounted for
and showed a higher rate of size reduction
only during the second sub-period.
Changing office sizes demonstrate a clear
pattern with larger markets experiencing
the larger office size reductions.
This suggests that larger markets tended to
experience negative office size change
(size reduction) or smaller size increase
than smaller markets, and that markets
with larger sized offices tend to experience
size reduction or smaller size increase.
Changes in the average size of bank
offices in the 1980s seemed to alter the
relationship between the market size and
the office size. In 1992, the correlation
between the average office size and the
size of markets reduced to 0.69. However,
the tendency for office size change
continued. The correlation between
changes in the average office size from
1992 to 2002 and the market size in 1992
is -0.32, and the correlation between
changes in the average office size from
1992 to 2002 and the average office size in
1992 is -0.63. Apparently, larger markets
in the 1990s were still somewhat
associated with large bank offices, and
these larger offices were still associated
with office size reduction or smaller
increase as a result of bank restructuring
in the 1990s.
Our earlier analysis suggests the existence
of widespread market mismatch in the
form of more dispersed supply than
demand. Although the actual mismatch
may be less than the supply and demand
SCI deviations would suggest due to
larger office sizes, especially in larger
markets, declining average office sizes in
larger
markets
amid
geographic
deregulation seems to indicate that when
banking firms are given more freedom,
they choose more locations over the larger
office sizes. In other words, larger office
sizes are indeed not a perfect substitution
for fewer locations.
It is likely that
changes in the average office sizes in
markets of various sizes may not be
independent of the overall rationalization
of bank services, and may be indeed an
The Pearson correlation coefficients
between relevant variables seem to point
in the same direction. In 1982, the
correlation between the average office size
and the size of markets (using either
population or deposit as market size) is
0.82, suggesting that larger markets tend
to have larger bank offices. The
correlation between changes in the
average office size from 1982 to 1992 and
the market size in 1982 is -0.51. The
correlation between changes in the
average office size from 1982 to 1992 and
the average office size in 1982 is -0.60.
Zhou
188
The Industrial Geographer
Table 4 Average Office Size* and Changes in the Average Office Size: Illinois and
Regional
Mean
St.d**
Mean
St.d
1982
($)
31468
14516
30189
8768
1992
($)
30389
11730
29525
8800
2002
($)
26718
9305
25987
7037
19821992
-3.4%
-19.2%
-2.2
0.4
19922002
-12.1%
-20.7%
-12.0
-20.0
19822002
-15.1%
-35.9%
-13.9
-19.7
Mean
St.d
Mean
St.d
Mean
48680
31720
38801
5836
29143
44403
20611
37988
3882
28496
39290
15537
34574
4620
24943
-8.8
-35.0
-2.1
-33.5
-2.2
-11.5
-24.6
-9.0
19.0
-12.5
-19.3
-51.0
-10.9
-20.8
-14.4
St.d
8507
8685
6564
2.1
-24.4
-22.8
Mean
St.d
Northern metro markets Mean
excluding Chicago mkt
St.d
All Northern non-metro Mean
markets
St.d
31931
7009
38531
6027
29730
6056
33421
10549
39239
5289
31482
11361
30251
5417
35219
4023
28595
4895
4.7
50.5
1.8
-12.2
5.9
87.6
-9.5
-48.6
-10.2
-23.9
-9.17
-56.9
-5.3
-22.7
-8.6
-33.3
-3.8
-19.2
The Chicago
market
137589
102130
81737
-25.8
-20.0
-40.6
-
-
-
-
-
-
Market segment
All markets
All markets excluding
the Chicago market
All metro markets
Metro markets
excluding Chicago mkt
All non-metro
markets
All Northern markets
Mean
St.d
*In the 1996 dollar
**St.d stands for standard deviation
integral part of emerging bank market
convergence, though more studies are
needed to confirm this.
smaller metro markets, and larger non metro over smaller non-metro markets.
Similar biases concerning changes in bank
service accessibility favorable for larger
markets have also occurred at the regional
level. In addition, in most market
segments, the sub-period of 1992 to 2002
saw greater rates of concentration than the
sub-period of 1982 to 1992.
SUMMARY AND CONCLUDING
REMARKS
In this study, we explore whether the
geography of bank services has been
converging toward the market since
banking geographic deregulation. Our
findings can be summarized as follows.
2. Evidence suggests that there was bank
supply-demand mismatch, manifested in
more dispersed bank services than
demand in larger markets at least during
the earlier points of observation. This
finding underscores the notion of underbanked larger markets. Under-served
larger markets are such a pervasive
phenomenon that they existed to different
extents in all market segments, such as the
state as a whole, metro, non -metro, cases
1. There has been a process of general rise
in bank service accessibility in all market
segments, and larger markets benefit
particularly from such improvement. The
general trend has been one of increasing
bank service concentration in the Chicago
market over non-Chicago markets, metro
over non-metro markets, larger metro over
Zhou
189
The Industrial Geographer
including or excluding the Chicago
markets, and market segments at the
regional level. However, in the last two
decades,
amid
fundamental
bank
restructuring and geographic deregulation,
the supply-demand mismatch seemed to
continue to diminish in most market
segments.
Although our findings lend support to a
convergence hypothesis, they by no means
provide undisputable proof due to several
shortcomings in the study. First, we use
only three points in time to anchor our
empirical
observations.
Although
strategically selected at the historical
turning points of U.S. banking, more
observation points would be helpful to
confirm the changing pattern, as suggested
by this study. Furthermore, the bank
supply and demand measures we use may
not be the most suitable, especially given
the possible problem associated with
substituting income for the measure of
wealth. In addition, the outcome of a
study may be sensitive to the methodology
utilized. The Spatial Concentration Index
and the related supply and demand SCI
deviations we use may have the potential
for exaggerating the effect of larger
markets. Comparative studies involving
alternative approaches are desirable.
Finally, changes in the average office size
only reflect one aspect of strategies in
rationalizing size distribution and bank
service mix. More insights can be gained
by observing service portfolios provided at
offices of various sizes. Despite these
shortcomings, our study does provide a
starting point to explore the issue of
banking
spatial
supply-demand
convergence. Its findings may help lay a
stage for more sophisticated future studies.
3. Declining supply-demand mismatch
has occurred in several ways. For most
market segments, it is via a diminishing
dispersion deviation process. In the
Chicago market, offices have been in a
process
of
dim inishing
dispersion
deviation while deposits have generally
been in a process of diminishing
concentration deviation. In Northern
metro markets, and to a certain extent the
Central and Southern non-metro markets,
there has been delayed convergence in
which dispersion deviations declined only
in the sub-period of 1992 and 2002. In
Central Illinois metro markets, while bank
office distribution has experienced
diminishing dispersion deviation, deposit
dispersion deviation has expanded from
1992.
4. Evidence also indicates the reduction of
the average office size in all market
segments in the last twenty years,
especially during the second sub-period
from 1992 to 2002. The office size
reduction is particularly significant in
larger markets compared to smaller
markets, especially in the Chicago metro
market and metro markets in Northern
and Central Illinois. As a result, the larger
markets’ hold on larger bank offices has
declined. Assuming office sizes and
locations are not perfect substitutions,
reduction of the average office size in
larger markets provides additional support
to the notion of the bank market
convergence.
Zhou
ENDNOTES
1. The HHI was first used by Hirschman
in the 1940s, followed by Herfindahl
(1959) in the 1950s. The index came to be
known as the Herfindahl Index after
studies by Rosenbluth (1955, 1957). After
H irschman (1964) claimed original
ownership of the index, it has been known
by its current name.
190
The Industrial Geographer
2. The precise boundaries of a
metropolitan bank market may not follow
exactly those of a metropolitan area. For
the purpose of this study, such
discrepancies are not a major distortion
factor.
larger non-metro markets led to higher
dispersion deviations.
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192
Manuscript Reviewers, Volume 2
The guest editor and the editors greatly appreciate the assistance of the many reviewers and the editorial board who have worked to insure that The Industrial Geographer establishes a record of publishing quality scholarship. The reviewers for
Volume 2 were:
A. Angelhart UNC Charlotte
J. Bodenman, Bloomsburg
F. Calzonetti, Toledo
H. Cambell, UNC Charlotte
S. Cobb, North Florida
J. Gatrell, Indiana State
A. Glasmeier, Pennsylvania State
S. Graves, California State University at Northridge
M. Green, Western Ontario
R. Greene, Western Illinois
R. Hanham, West Virginia
R. Hayter, Simon Fraser
R. Kashian,Wisconsin-Whitewater
D. Keeling, Western Kentucky
T. Klier, Federal Reserve-Chicago
D. Knudsen. Indiana
D. Lord, UNC Charlotte
K. Oshiro, Wright State
J. Pollard, Birmingham UK
D. Purcel, Florida State
M. Robbins, Connecticut
J. Strait, Louisiana Tech
B. Warf, Florida State
J. Wheeler, Georgia
C. Williams, Leicester UK
D. Wojcik, Oxford UK
B. Zhou, Southern Illinois at Edwardsville
M. Zook, Kentucky
91
Guidelines for Contributors
Review Process
All manuscripts will be subject to double-blind peer review. Upon receipt
of the manuscript, a paper will be sent out for review to three (3)
professionals with expertise in the core area investigated. The three (3)
reviewers will be comprised of at-least one (1) editorial board member and
one (1) non-board member. Ideally, the initial review process will be
completed within six (6) to eight (8) weeks from initial submission. No
initial review should exceed twelve (12) weeks. Please note July
submissions will not be sent out for review until the first week of August.
Submissions
All submissions must represent the original work of the authors. It is the
responsibility of the author to obtain copyright permission, if necessary.
Simultaneous submissions of works to other journals are not acceptable.
It is expected that work submitted to review are not under consideration
elsewhere.
Abstracts and Key Words
All articles must include a 150-200 word abstract that summarizes
methods and key findings. Both articles and research notes should
include a maximum of five (5) key words for the purposes of indexing.
Ideally, the keywords would detail location, topic, method, and two (2)
other related descriptors.
Headings & Tables
The format of headings and tables will be left to the discretion of authors.
In the case of tables, it should be acknowledged that the portrait
orientation is always preferred.
Illustrations
Color, grayscale, or black and white illustrations are acceptable. Authors
should be mindful that all illustrations must be high quality and submitted
in their final form as a TIF file with a 360 dpi resolution.
Electronic submissions are encouraged.
MS Word (for
Win3.1/95/98/00/ME) documents are the preferred submission format.
Submissions in other MS Word (for Win3.1/95/98/00/ME) accessible
formats are also accessible. Please do not embed tables, maps, or other
figures. Tables, maps, and figures should be submitted separately as
individual files.
Citations & References
Parenthetical citations are used in the body of the text. Examples are
presented below:
Paper submissions should be made in triplicate to the appropriate section
editor with any potential identifiers (acknowledgements, names, etc)
placed on the first, or cover, page.
References should be arranged alphabetical and chronologically. The
general style for publication types is presented below:
Articles
Articles should conform to the standard format found in the traditional
academic journals. Alternative article formats should be presented to the
co-editors before submission. Generally, articles should not exceed 5000
words (including abstract, text, and bibliography).
Submit articles to:
Neil Reid, Editor—Articles
The Industrial Geographer
Department of Geography & Planning
The University of Toledo
Toledo, OH 43606
Research Notes & Discussion
Notes that present short ‘data-driven’ case studies, examples of applied
industrial geography, explore methodological issues, or concisely discuss
or review the trajectory of industrial geography or related conceptual
issues are encouraged. Additionally, ‘creative’ or non-conventional
research notes are encouraged that may provide new insights into
industrial geography and related social sciences or the humanities.
Creative notes might include “wide format” posters or other unique formats
that are more easily published in an electronic format. Research notes
should not exceed 2500 words (including text and bibliography).
Submit research notes and discussion items to:
Jay D. Gatrell, Editor—Notes
The Industrial Geographer
Department of Geography, Geology, & Anthropology
Indiana State University
Terre Haute, IN 4780
Single Author—(James 1934)
Multiple Authors—(Smith 1992; Billings 1989; Jones & Hanham 1995)
Direct Quote—(Billings 1989 p. 12)
1. Articles
Lindahl, D. & Beyers, W. 1999 The creation of competitive advantage by producer
service establishments. Economic Geography 75:1-20.
2. Chapters
Swyngedouw, E. 1997 Neither global nor local: “Glocalization” and politics of scale.
In Spaces of Globalization: Reasserting the Power of the Local, edited by K. Cox,
pp. 137-166. New York: Guilford Press.
3. Presentations
Graves, W. 1997 Mapping the new economy: Estimating intellectual capital
distributions form [sic] balance sheet data, Presented at the Southeast Division
of the American Association of Geographers (SEDAAG).
4. Books
Illeris, S. 1996 The Service Economy: A Geographical Approach. New York: Wiley.
5. Working Papers or Other Resources
Atchison, S. 1993 Care and feeding of lone eagles. Business Week, November 15,
p. 58.
DeVol, R. 1999 America’s High-Tech Economy: Growth, Development, and Risks for
Metropolitan Areas. Milken Institute, Santa Monica, CA.
Rickman, P. 2001 Official, United Auto Workers Local 12, Toledo, OH, telephone
interview August 15.
McKinnon, J. 2001 Liberty a symbol of Jeep’s rebirth in insecure times. Toledo
Blade, February 18 [http://toledoblade.com], accessed January 1, 2002.
Hypertext
Authors are encouraged to use hypertext (or WWW links) within their
manuscript. However, authors are responsible for the overall validity of
the link. To insure the shelf life of submitted manuscripts, links should be
limited to ‘root’ directories—not individual web pages. Also, authors
should seek to limit the use of hypertext to more stable internet sites, such
as government agencies, non-governmental organizations, and/or major
corporations.