World Development Vol. 32, No. 6, pp. 999–1017, 2004
Ó 2004 Elsevier Ltd. All rights reserved
Printed in Great Britain
0305-750X/$ - see front matter
www.elsevier.com/locate/worlddev
doi:10.1016/j.worlddev.2003.12.002
The Comparative Politics of Corruption:
Accounting for the East Asian Paradox
in Empirical Studies of Corruption,
Growth and Investment
MICHAEL T. ROCK and HEIDI BONNETT *
Hood College, Frederick, MD, USA
Summary. — Numerous empirical studies demonstrate that corruption reduces investment and/or
slows growth. But how robust are these relationships? This question is answered by conducting a
series of crosscountry regression tests using four different corruption datasets. We find that
corruption slows growth and/or reduces investment in most developing countries, particularly small
developing countries, but increases growth in the large East Asian newly industrializing economies.
The latter finding provides solid empirical support to a country case literature that explains the East
Asian paradox––the combination of high corruption and high growth––in terms of stable and
mutually beneficial exchanges of government promotional privileges for bribes and kickbacks.
Ó 2004 Elsevier Ltd. All rights reserved.
Key words — East Asian NICs, growth accounting, comparative politics of corruption
1. INTRODUCTION
Several recent empirical studies (Kaufmann,
Kraay, & Zoido-Lobaton, 1999; Knack &
Keefer, 1995; Li, Xu, & Zou, 2000; Mauro,
1995) demonstrate that corruption reduces
investment and/or slows economic growth.
Several other empirical studies (Smarzynska &
Wei, 2000; Wei, 2000) extend these findings by
demonstrating that corruption retards foreign
direct investment and shifts the composition of
capital flowing into countries with more corruption in speculative directions. 1 These
results are largely consistent with the neoclassical rent-seeking literature (Boycko, Shleifer,
& Vishny, 1995; Krueger, 1974; Murphy,
Shleifer, & Vishny, 1993). Taken together, this
body of theoretical and empirical work provides the basis for a new growth industry on
good governance and development. 2
Just how robust is the relationship between
corruption and investment on the one hand and
corruption and economic growth on the other
hand? This question is answered by conducting
a series of growth accounting, or crosscountry
999
multiple regression tests of the relationships
between corruption, investment and growth.
What follows differs from other work on this
topic in several important ways. To begin with,
we searched for and collected data on all
known published measures of corruption. This
yielded four corruption data sets over four
different time periods that provide the basis for
what appears to be one of the most comprehensive empirical tests of the impact of corruption on growth and investment. 3 Unlike
several other studies on this topic, corruption is
defined as the use of public office for private
* We would like to thank the Summer Research Institute (SRI) at Hood College for supporting this research.
The SRI provides opportunities for particularly promising undergraduates to work closely with a faculty
member on a research project. We would also like to
thank Sang Kim, Jonathan Krieckhaus, Allen Hicken
and his graduate students, as well as four anonymous
reviewers for their helpful comments and suggestions.
Final revision accepted: 1 December 2003.
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WORLD DEVELOPMENT
gain, rather than as institutional quality,
bureaucratic inefficiency or the degree of red
tape within a bureaucracy. 4 This provides a
clearer test of the relationship between corruption, investment and growth.
Our crosscountry regression tests are partially motivated by the observation that the
relationship between corruption and investment and growth in our data sets appears to be
different for small and large counties. 5 There
are several reasons to suspect why this might be
so. On the one hand, large countries have relatively large internal markets and similarly
large supplies of labor. This enables governments in large developing countries to focus on
import substitution (ISI) policies for longer
periods of time than in smaller developing
countries. This may help them fend off pressures from international institutions and
foreign investors to curb corruption, particularly the kind of corruption associated with
selective industrial policies and money politics
(Khan & Jomo, 2000). 6 On the other hand, a
large internal market and a large pool of labor
may also mean that foreign investors are more
likely to accept corruption as a way of doing
business, if doing so enables them to gain
unrestricted access to local goods and labor
markets.
Neither of these advantages is available to
small developing countries. Their small market
size means that they reach the limits of ISI fairly
quickly and this should push, at least the
development-oriented governments in small
developing countries, to be more open to aid,
trade and investment. By itself, this should
expose small countries to more pressure to
conform to emerging international norms
regarding governance and corruption. 7 Similarly, small domestic markets and small pools
of labor may mean that foreign investors are
likely to be less understanding of local corrupt
business practices. This combination may
explain why governments in several prominent
small developing economies with low levels
of corruption––Singapore, Hong Kong, Chile,
Botswana and Malaysia 8––have such high
growth rates and why some large countries––
China, India, Brazil, and Mexico––with relatively high levels of corruption have such
differing growth rates. 9 It may also at least
partly explain why small countries, particularly
those in sub-Saharan Africa, with high levels
of corruption have experienced such poor
development performances. Because of this,
in Section 3, we test the hypothesis that cor-
ruption is more damaging to investment and
growth in small developing countries than in
large ones.
Country size is not however, the only thing
that matters. As will be demonstrated, the impact of corruption on investment and growth
also depends on the domestic politics of corruption. This can be seen in Figure 1 10 and in
the comparative politics literature on corruption
(Gomez, 2002; Haber, 2002; Hope & Chikulo,
2000; Kang, 2002; Khan, 1996; Khan & Jomo,
2000; Olson, 1993; Shleifer & Vishny, 1993;
Szeftel, 2000; Tulchin & Espach, 2000; Wedeman, 1997; Weyland, 1998). Both suggest that
the relationships between corruption, growth
and investment are not nearly as simple as suggested by either the traditional rent-seeking literature or standard crosscountry regression
tests. Figure 1 highlights what Wedeman
(2002a, p. 34) labels the East Asian paradox––
the achievement of very high growth rates in real
income per capita over relatively long time
periods in the face of quite high levels of corruption. As will also be demonstrated, the
region specific and country case literatures 11
can be used to understand the pattern observed
in Figure 1 and to construct several new corruption variables that permit the testing of
hypotheses based on Figure 1. Because of this,
our research strategy is aimed at assessing the
degree to which corruption slows or increases
growth and investment in different regions and
countries of the developing world characterized
by substantially different political economies of
corruption.
To anticipate results, we find that the
empirical relationships between corruption,
growth and investment are not very robust
unless one controls for both country size and
the regional and/or country differences in the
political economy of corruption. After making
these adjustments, we find that corruption
tends to slow growth and/or reduce investment
in small countries in most of the developing
world, but increase it in a subset of large East
Asian economies characterized by relatively
stable and strong governments with close and
corrupt ties to big business. The next section
suggests how the regional, case-based and
theoretical literatures on the political economy
of corruption can be used to test hypotheses
linking different political economies of corruption to growth and investment. Section 3
describes the data and reports statistical results.
The concluding section outlines the implications of our findings.
COMPARATIVE POLITICS OF CORRUPTION
1001
Average Rate of Growth of Real GDP per Capita
6
5
LEANICS
SINGHKMA
4
3
SASIAP
2
MENA
1
0
0
1
2
3
4
5
6
-1
LAC
-2
SSA
-3
Business International Corruption Index
Figure 1. Corruption and growth, 1980–83. Source: Business International corruption data are from Mauro (1995, pp.
708–710). Average real GDP per capita growth data are from Penn World Tables PWT (6.0). Country groupings are
SINGHKMAL ¼ Singapore, Hong Kong and Malaysia. LEANICS ¼ China, Indonesia, Korea, Thailand and Japan.
SASIAP ¼ South Asia and the Philippines. MENA ¼ Middle East and North Africa. LAC ¼ Latin America and the
Caribbean and SSA ¼ sub-Saharan Africa. Rationale for country groupings is given in Note 10 and in body of text in
Section 2.
2. THE COMPARATIVE POLITICS OF
CORRUPTION, INVESTMENT AND
GROWTH
The region specific and country case literatures suggest that the politics of corruption, or
what Shleifer and Vishny (1993) label the
industrial organization of corruption, and its
effects on investment and growth are quite
similar within different regions of the world,
but quite different across those regions. For
example, much of the literature on corruption
in Latin America focuses on the role of hyperpresidentialism 12 in very costly high-level
political corruption (Whitehead, 1989, 2000).
As Whitehead (1989) demonstrates, in a significant number of cases presidents in this
region have harnessed ‘‘. . .the whole apparatus
of the state to the task of their personal
enrichment’’ (Whitehead, 1989, p. 783). Interestingly enough, this tendency has not been
affected by the substantial differences in
underlying political economies. Both the
region’s weaker states with relatively strong
distributional coalitions (Argentina), and the
region’s relatively strong and more autonomous states with rather weak distributional
coalitions (Mexico) have been afflicted by high-
level political corruption emanating from the
president’s office (Manzetti, 1994, 2000). Governments (Brazil) with socio-political structures
between these extremes (Evans, 1995) have
been similarly afflicted by high-level political
corruption (Geddes & Ribeiro Neto, 1999).
High-level political corruption has been
identified as a problem during periods of
substantial government intervention in the
economy, but it has also been a significant
problem during periods of market-oriented
economic policies (Weyland, 1998, pp. 109–
112). Recent experiences with double transitions––from authoritarianism to democracy
and from interventionist to market-oriented
economic policies––have been accompanied by
even higher levels of high-level political corruption (Geddes & Ribeiro Neto, 1999; Manzetti, 2000; Whitehead, 2000). O’Donnell (1994,
p. 55 & 62) suggests that this occurred because
the severity of the socioeconomic crises
attending double transitions enabled newly
elected presidents to draw on long political
traditions of caudillismo to rule by executive
order or fiat. Manzetti (2000) argues that this
facilitated the rise of unscrupulous business
politicians (Manzetti, 2000, p. 130 & 135)––
those who engaged in politics to acquire
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WORLD DEVELOPMENT
personal wealth. As he (Manzetti, 2000, p. 130)
and Geddes and Ribeiro Neto (1999) argue
business politicians in Argentina, Mexico, and
Brazil took advantage of severe socioeconomic
crises and weak checks and balances on presidential rule to engage in high-level political
corruption. There is little evidence that such
high-level corruption increased either investment or growth (Lopez, 1998; Schneider, 2002).
A similarly distinct politics of corruption is
visible in Africa. As Sandbrook (1993) argues,
Africa’s post-colonial governments emerged
under extremely inauspicious circumstances.
To begin with, the region’s newly independent
governments inherited skeletal states––bureaucracies with extremely limited technical capabilities and equally limited capacities to
mobilize resources (Sandbrook, 1993, p. 25).
These skeletal states were immediately burdened with overcoming the underdevelopment
associated with their skewed export-oriented
primary product economies and the legacies of
slavery, racism, and foreign exploitation. Given
the deep mistrust among Africans of markets, trade, and foreign investment, it is not
surprising that both market-oriented and
socialist-oriented governments adopted highly
interventionist development strategies (Bates,
1981, pp. 29, 30–44, 62–77), including prominent roles for state-owned enterprises (Steel &
Evans, 1984, pp. 16–28). These interventionist
strategies ultimately failed because governments lacked both the political will and the
capacity to support productive activities as
opposed to predatory rent-seeking activities
(Sandbrook, 1993, p. 22).
To make matters worse, most of Africa’s
newly independent governments came to power
lacking even the most rudimentary political
legitimacy (Sandbrook, 1993, p. 27). Under
these circumstances, governments were forced
to create some basis in civil society for their own
right to rule. While political leaders in Africa
might have tried to cultivate legitimacy by
delivering development, most opted instead to
foster their own personal legitimacy, rather than
that of the state, by building patron–client ties
with a tribalized peasantry (Szeftel, 2000, p.
432). As Szeftel (2000, p. 432) says, this ensured
the domination of politics by ethnic leaders who
mobilized their disenfranchized voters by offering them material benefits for their votes. Once
in power, ethnic leaders were obliged to reward
their supporters (Sandbrook, 1993, p. 26).
This meant that the primary basis of politics
and of cohesion within the state and between
the state and civil society lay in the personal ties
between government patrons and their client
networks within government and in civil society. As Bratton and Van de Walle (1994, p. 458)
say, neo-patrimonialism, political regimes
where chief executives maintained authority
through personal patronage, became the most
distinctive and the core feature of African
politics. Within government, political behavior
was driven by competition for and, in the worst
cases, outright bidding (Coolidge & RoseAckerman, 2000, p. 72) for those public offices
that provided the most substantial basis for
private gain (Sandbrook, 1993, p. 28). Outside
the state, clients used their access to their
patrons in the civil service to create, expand,
and sustain lucrative unproductive rent-seeking
activities. 13
Not surprisingly, Africa’s neo-patrimonial
regimes spawned a wide range of exceedingly
corrupt behaviors––from outright stealing of
state assets, to padding of public sector payrolls, smuggling of export crops and precious
metals, rigged bidding on government contracts, and kickbacks on subsidized loans and
import licenses (Osei-Hwedie & Osei-Hwedie,
2000, p. 48–49). 14 Often incomes earned on
corrupt transactions were either stashed away
in foreign bank accounts or spent on luxury
consumption. Given the short life of many, but
not all, of Africa’s neo-patrimonial governments, corruption takes tended to increase in
anticipation of regime collapse (Szeftel, 2000, p.
439). The effect on investment and growth of a
political environment that encouraged chief
executives, high-ranking civil servants and
ordinary bureaucrats to loot state assets and
heavily tax all productive activities was simply
catastrophic (Szeftel, 2000, p. 427). 15
This pattern of neo-patrimonial corrupt
activities thrived in a wide range of political
economies in Africa. It took its most corrosive
form in the region’s personal dictatorships––as
manifested by Idi Amin in Uganda, Bokassa in
the Central African Empire, and Mobutu in
Zaire (Bratton & Van de Walle, 1994, p. 475).
But neo-patrimonialism is also visible in the
region’s plebiscitary one party governments
typified by president Eyadema in Togo and
president Bongo in Gabon (Bratton & Van de
Walle, 1994, p. 477). Africa’s military oligarchies, or the military regimes ruled by a junta,
committee or a cabinet, as in Jerry Rawlings in
Ghana and Ibrahim Babangida in Nigeria,
have also governed by relying on a neo-patrimonial politics (Bratton & Van de Walle, 1994,
COMPARATIVE POLITICS OF CORRUPTION
p. 480). So have the region’s competitive one
party states as in Zambia under Kaunda and
the Ivory Coast under Houphouet-Boigny
(Bratton & Van de Walle, 1994, p. 483). There
is also some evidence that corruption based on
a neo-patrimonial politics is not limited to subSaharan Africa. In at least one of the continent’s Arab regimes, Morocco, corruption
rooted in neo-patrimonialism appears to have
been essential to regime survival (Waterbury,
1973). 16
Unlike Latin America and Africa, no single
unifying politics of corruption is visible in Asia.
In three of this region’s high growth economies,
Hong Kong, Singapore and Malaysia, high
growth and investment have gone hand in hand
with relatively low levels of corruption
(SINGHKMAL in Figure 1). For the rest of the
East Asian newly industrializing economies,
including Japan, relatively high levels of corruption have accompanied high growth and
investment regimes (LEANICS in Figure 1). In
a number of other economies in this region,
particularly in South Asia and the Philippines
(SASIAP in Figure 1), relatively high levels of
corruption appear to have been growth and
investment reducing. It turns out that differences in growth and corruption outcomes in
Asia can be explained by differences in the
domestic politics of corruption. In Hong Kong,
Singapore and Malaysia relatively strong
autonomous states have worked very hard to
limit corruption. 17 Given the openness of these
economies to foreign trade and investment and
development strategies rooted in linking these
economies to the West, it is not surprising that
high growth and investment in these small
economies have been complemented by relatively low levels of corruption.
Elsewhere in Asia high levels of corruption
have been combined with political economies
dominated by patron–client networks (Khan,
1996, 2000). As Khan (1996, p. 691) argues
governments in Asia have historically relied on
these networks to implement their economic
and political strategies. Their ability to do so
has been determined by the form that patron–
client networks take. In patrimonial patron–
client networks, the distribution of power
between government patrons and clients in civil
society is tilted toward the state. Because state
patrons are strong relatively to their clients in
civil society, polities driven by patrimonial
patron–client networks have sometimes been
able to allocate and protect new growth
enhancing property rights. 18 But in political
1003
economies, where patron–client networks are
dominated by clients rather than by patrons,
governments typically lack the power, relative
to their clients in civil society, to allocate and
enforce existing or new property rights. 19 In
the former case, corruption can be growth and/
or investment increasing, while in the latter
case, it typically reduces investment and/or
slows growth.
The regional and country case literature
linking corruption to investment and growth is
largely consistent with the recent theoretical
literature on corruption, investment and
growth. In an influential essay, Shleifer and
Vishny (1993) argue that the impact of corruption on growth depends on the industrial
organization of corruption networks. When
those networks are organized and managed by
a strong centralized state, as in a monopoly
industry, corruption is likely to be less corrosive to investment and growth than when it is
organized by numerous government officials
acting as independent monopolists. In fact,
when the latter happens, bribes rise to infinity
and growth and investment collapse (Shleifer &
Vishny, 1993, p. 606). How might these differences in the organization of corruption networks account for what we see in the regional
and country case literature on corruption and
in Figure 1? Perhaps the large East Asian NICs
high-corruption high-investment and growth
outcomes reflect monopoly control of corruption networks by strong overcentralized states,
while South Asia’s and the Philippines’ highcorruption, low-investment, low-growth outcomes reflect control of corruption networks by
competing monopolists in government. There is
substantial case study evidence (Bardhan, 1997,
p. 1324; Hutchcroft, 1994; Johnson, 1987, 1999;
Kang, 2002; Khan, 1996, 2000; Rock, 2002 and
Notes 18 and 19) to support this conclusion.
By itself, however, differences in the industrial organization of corruption may not be
entirely sufficient to explain all the different
patterns observed in Figure 1. Olson (1993)
suggests what else matters. His objective is to
explain why economic agents in any domain
(country) might prefer a government of stationary bandits to one of roving bandits. As he
(1993, p. 568) says, rational (and successful)
stationary bandits will monopolize theft (corruption) in their domain while limiting what
they steal because they know they will be able
to extract more in the long run if their subjects
have an incentive to invest and produce additional income and wealth. The prospect of a
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WORLD DEVELOPMENT
future income stream from the monopolization
of theft may even encourage governments of
stationary bandits to provide the public goods
that enable economic agents in stationary
bandits’ domains to generate even higher
incomes and more wealth. Since roving bandits
have short time horizons, they have few
incentives to limit theft and no incentives to
provide the public goods necessary to entice
residents in their domains to invest and increase
their incomes. Because of this, Olson suggests
that investment and growth should be lower in
countries governed by roving bandits. On the
other hand, he asserts that if stationary bandits
are committed to growth and development as a
way of maximizing their long-run corruption
takes, investment and growth might be substantially higher in countries governed by stationary bandits.
What this means is that the impact of corruption on growth and investment depends on
both the industrial organization of corruption
and the time horizon of those who control
corruption networks. Table 1 presents a twoby-two table of four possible growth–investment–corruption outcomes based on differences
in the industrial organization of corruption and
in time horizons of those who control corruption networks. Governments (bandits) can
either be roving bandits with short time horizons or stationary bandits with long time
horizons. Corruption networks can either be
monopolized by a strong centralized state
(bandit) or fragmented and controlled by a
significant number of independent monopolists
(bandits). In all but one instance, exhibited by
stationary bandits with long time horizons,
corruption should reduce investment and/or
slow growth. This combination appears to
capture the essence of the role of corruption in
East Asia’s large developmental states. In these
states, relatively strong, stable and autonomous
central governments have used their discretionary power to create, allocate and protect
new property rights (promotional privileges)
for new groups in civil society (capitalists and
entrepreneurs). These governments’ developmental orientation appears to have led them to
take a long-run view of banditry (corruption).
Because of this they have invested heavily in
public goods and they exert near monopoly
control over the corruption networks they created. This enables them to offer promotional
privileges in exchange for bribes and kickbacks
that they use to consolidate their political
power and enrich themselves.
In each of the other combinations in Table 1,
corruption reduces investment and/or slows
growth. 20 When corruption networks are
controlled by a significant number of roving
bandits who act as independent monopolists, as
is typical in at least some of the countries in
sub-Saharan Africa, extremely weak states have
been sustained by multiple patron–client networks controlled by one or more ethnic groups
with extremely short time horizons. In this
world, each independent monopolist within the
state extracts as much as they can as fast as
they can from both the state and the private
sector. Because those who control each corruption network expect to be replaced in a
relatively short period of time, there is little
Table 1. Corruption and growth regimes
Industrial organization of
corruption networks
Strong centralized governments, at least for executives,
who exert monopoly control
over corruption networks
Weak and fragmented governments with multiple independent monopolists controlling
corruption networks
Time horizon of government officials (bandits)
Short for roving bandits
Long for stationary bandits
Business politicians in
hyper-presidential regimes in
Latin America (as in
Argentina, Brazil and Mexico)
East Asia’s developmental states establish
beneficial relations with capitalists by
providing promotional privileges in exchange
for bribes and kickbacks
Effects of corruption on
growth ())
Effects of corruption on growth (+)
Africa’s neo-patrimonial regimes, particularly those with
substantial political instability
India and the Philippines in the late Marcos
and post-Marcos era
Effects of corruption on
growth ())
Effects of corruption on growth ())
COMPARATIVE POLITICS OF CORRUPTION
incentive to invest in public goods or develop
mutually beneficial relationships with anyone in
the private sector. Simple looting and plunder
dominate decision-making.
This is not the only way in which corruption
can reduce investment and slow growth. Corruption networks, particularly the costly highlevel corruption networks that predominate in
a number of countries in Latin America, can
also be monopolized by business-politicians
turned presidents with short time horizons.
These presidents, especially in Argentina, Brazil, and Mexico, have routinely demonstrated a
lack of interest in public investment, except to
the degree that it provides an additional
opportunity for corruption, and they have
routinely used their presidential powers to
enrich themselves as quickly as possible. Said
another way, these presidents (monopolists)
have shown a predilection to behave as roving
bandits reducing investment and slowing
growth. Finally, corruption networks can be
controlled by a significant number of independent monopolists in governments who tend to
have long time horizons. This condition exists
in India, the Philippines, and in several regimes
in sub-Saharan Africa, such as in Zambia under
President Kaunda and Kenya under President
Moi. Governments in these conditions tend to
be weak and easily penetrated by their clients in
civil society who routinely use their ties to their
patrons in government to extract unproductive
re-distributive rents. Sometimes those rents go
to some in the emerging middle classes, particularly when they are offered jobs in the
public sector. Sometimes those rents go to
capitalists and landlords who use their ties to
their patrons in government to gain and keep
protection. In neither instance is corruption
likely to exert a positive effect on investment or
growth.
3. DATA AND EMPIRICAL TESTS
Empirical tests of hypotheses relating corruption to investment and growth are motivated by the vast growth accounting literature
as well as by the need to test for the robustness
of regression coefficients of particular interest
(Levine & Renelt, 1992). 21 Data constraints,
particularly on corruption variables, led to
estimation of four different sets of crosscountry
regressions for four different time periods––
1980–83, 1988–92, 1984–96 and 1994–96. In
each instance, variables are calibrated as close
1005
as possible to the time period covered by each
measure of corruption. This enables us to avoid
the pitfall evidenced in Mauro (1995, pp. 690,
699 & 702–703) of assuming that the average
level of corruption measured in one period
(1980–83) is the same as the average over a
much longer period (1960–85). 22 As the Political Risk Services’ (Political Risk Service, 2002)
time series data on corruption during 1984–96
shows, this assumption is a not a particularly
good one. 23
We made four adjustments to these basic
corruption variables. As is well known, each of
our corruption variables was originally scaled
so that an increase in the measured variable
indicated a decline in corruption. To begin
with, we simply re-scaled each corruption variable so that an increase signifies an increase in
corruption. To capture the impact of corruption on investment and growth in developing
countries we created several new corruption
variables. The first is a simple developing
country corruption variable where, for example, for the Business International corruption
score BILDC ¼ 0 if the country is a developed
country and BILDC ¼ the country’s corruption
score if the country is a developing country.
This particular developing country corruption
variable is constructed on a traditional neoclassical rent-seeking hypothesis that increases
(reductions) in corruption anywhere in the
developing world slow (increase) investment
and reduce (raise) growth.
Since the region and country case literature
suggests that corruption is likely to be investment and growth reducing everywhere in the
developing world except in the large East Asian
newly industrializing countries (NICs) we created two other developing country corruption
variables. The first is an ‘‘other developing
country’’ corruption variable. For this variable,
as in BIOLDC for the Business International
corruption variable, BIOLDC ¼ 0 if a country
is a developed country or one of our large East
Asian newly industrializing economies and BIOLDC ¼ the country’s corruption score if the
country lies elsewhere in the developing world.
Finally, we created a ‘‘large East Asian NIC’’
corruption variable. 24 For this variable, as in
BILEANIC for the Business International corruption variable, BILEANIC ¼ 0 if a country is
a developed country, a developing country
outside East Asia, or an East Asian non-NIC
developing country and BILEANIC ¼ the
country’s corruption score if the country is
a large East Asian NIC. This process was
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WORLD DEVELOPMENT
repeated for each corruption variable in each
time period. In all, this yielded 12 new developing country corruption variables, three for
each corruption variable. 25
Following standard practice in growth
accounting (Barro, 1991; Levine & Renelt,
1992; Mankiw, Romer, & Weil, 1992), dependent variables include the average investment
share in real GDP in PPP$ and the average rate
of growth of real GDP per capita in PPP$ over
certain time periods. As is typical of crosscountry regression studies of corruption
(Knack & Keefer, 1995; Li et al., 2000; Mauro,
1995) initial regressions focus on the re-scaled
redefined regional corruption variables on the
dependent variables. To these simple regressions of corruption on investment and growth,
a standard basic list of regressors including
initial income per capita in 1960 (GDPN60), the
average population growth rate (POPG), and
the secondary school enrollment ratio in 1960
(SEC60) is added. 26 To these base regression
equations, robustness tests are carried out by
adding a small list of other variables generally
agreed to affect crosscountry differences in
investment to GDP ratios and growth rates in
real GDP per capita. These other variables
include the share of exports plus imports or
trade in GDP, TRDY/GDP, the share of
government consumption in GDP, GOVCY/
GDP, price distortions in the investment
deflator, PPIDEV60, in 1960, and ethno-linguistic fractionalization, ETHNIC. 27 All variable definitions and their sources appear in the
Appendix.
Results of estimation 28 for each of the ‘‘all
developing country’’ corruption variables,
BILDC, TILDC, IRLDC and WBLDC appear
in Table 2. 29 Several important results stand
out.
First, two of the four ‘‘all developing country’’ corruption variables, BILDC and TILDC,
are not statistically significant in either the
investment or the growth equation. In two out
of four instances, these variables have the
wrong sign. On the other hand, IRLDC has the
expected sign ()) and is robust for the investment equation, but not for the growth equation, while WBLDC has the expected sign ())
and is robust for both the investment and
growth equations. These findings, particularly
for IRLDC and WBLDC, provide what
appears to be modest support for the neoclassical rent-seeking literature, which hypothesizes
that corruption reduces investment and/or
slows growth.
But when Chow F breakpoint tests for large
and small countries are applied to the robustness test equations in Table 2, they reveal statistically significant structural breaks in
investment equations for TILDC, IRLDC and
WBLDC and structural breaks in growth
equations for BILDC and WBLDC. Moreover,
when the robustness test equations are re-estimated for large and small countries for IRLDC
and WBLDC (Table 3), empirical results are
substantially different. To begin with, none of
the large country ‘‘all developing country’’
corruption variables are statistically significant
and in two out of four cases, those corruption
variables have the wrong sign (+). On the other
hand, the ‘‘all developing country’’ corruption
variables for small countries are statistically
significant with the expected sign ()) and
robust for the investment equation for IRLDC
and they are statistically significant with the
expected sign ()) and robust for the investment
and growth equations for WBLDC. This finding offers powerful support for the hypothesis
that corruption is more damaging to investment and growth in small developing countries
than it is in large developing countries. By
itself, this may explain why developmentoriented governments in small developing
countries that adopt strong anti-corruption
programs such as Singapore, Hong Kong,
Malaysia, Botswana and Chile tend to grow
faster than those with more corruption.
Replacing the ‘‘all developing country’’ corruption variables, such as BILDC, with the
‘‘other developing country’’ corruption variables, such as BIOLDC, and the ‘‘large East
Asian newly industrializing economies’’ corruption variables, such as BILEANIC, yields
other interesting results (Table 4). Several
deserve mention. To begin with, the ‘‘other
developing countries’’ corruption variables,
BIOLDC, TIOLDC, IROLDC and WBOLDC
are statistically significant with the expected
sign ()) in three out of four investment equations and in one of the growth equations (for
WBOLDC). At the same time, the ‘‘large East
Asian NIC’’ corruption variables, BILEANIC,
TILEANIC, IRLEANIC and WBLEANIC,
always have the expected sign (+) and are
always statistically significant in the growth
equations, but none are statistically significant
in the investment equations. One additional
finding, pointed out by an anonymous
reviewer, deserves mention. As is well known,
Kaufmann et al. (1999, p. 9) use an unobserved
components model to generate the World
0.49
0.62
58
1
17.52
7.95E)05
(0.22)a
)0.99
()0.94)
0.09
(1.38)
0.08
(8.10)
)0.19
()1.50)
)0.06
(2.80)
)2.87
(0.98)
)0.03
()0.06)
I/Y
2.61
0.48
47
)0.62
()0.85)
2
24.17
)0.0004
()0.80)
)1.96
()1.42)
0.06
(0.78)
0.05
(2.70)
)0.03
()0.19)
)0.01
()2.21)
)4.82
()1.23)
I/Y
6.11
0.54
79
)2.05
(2.58)
3
21.64
)0.0005
()1.06)
)0.82
()0.72)
0.13
(2.24)
0.05
(3.01)
)0.20
()1.34)
)0.01
()2.62)
)2.75
()1.06)
I/Y
)3.77
()2.42)
5.21
0.49
90
4
18.26
)0.0001
()0.49)
)1.68
()1.19)
0.10
(1.77)
0.03
(2.13)
)0.09
()1.11)
)0.01
()2.02)
)4.62
()1.76)
I/Y
2.56
0.14
58
5
0.06
)0.0001
()1.02)
)0.65
()0.98)
0.04
(1.94)
0.02
(3.95)
)0.05
()0.95)
)0.002
()0.21)
)0.35
()0.17)
0.21
(0.77)
GDPNG
1.79
0.28
47
0.15
(0.60)
6
4.90
)0.0002
()1.68)
)0.91
()1.73)
0.01
(0.61)
0.01
(2.44)
)0.11
()1.37)
0.002
(0.84)
)2.76
()1.59)
GDPNG
1.37
0.29
79
)0.16
(0.53)
7
5.72
)0.0003
()2.67)
)1.04
(2.87)
0.01
(0.93)
0.01
(3.17)
)0.09
()1.55)
)0.0008
()0.23)
)1.12
()1.08)
GDPNG
)2.14
()2.62)
1.99
0.26
90
8
6.75
)0.0002
()2.08)
)1.25
()2.61)
0.02
(0.71)
)0.001
()0.32)
)0.09
()2.28)
0.0002
(0.02)
)0.68
()0.57)
GDPNG
a
Numbers in parentheses are t values. Estimation is with White’s heteroskedasticity-consistent standard errors. The Chow F statistic is a structural breakpoint test
statistic.
*
Significant at the 0.10 level.
**
Significant at the 0.05 level.
***
Significant at the 0.01 level.
Chow F
2
R
N
WBLDC
IRLDC
TILDC
BILDC
ETHNIC
PPID60
GOVCY
TRDY
SEC60
POPG
Equation
C
GDPN60
Dependent variable
Table 2. OLS robustness test regression equations for all developing country corruption variables––BILDC, TILDC, IRLDC and WBLDC a
COMPARATIVE POLITICS OF CORRUPTION
1007
0.74
POP < 20
50
1
6.58
0.0002
(0.58)
1.30
(1.15)
0.16
(2.17)
0.07
(3.76)
)0.04
()0.24)
)0.009
()1.85)
)1.74
()0.63)
)1.49
()2.06)
I/Y
0.63
POP > 20
29
2
33.10
)0.0008
()1.51)
)5.59
()2.52)
0.08
(0.99)
0.16
(3.45)
)0.60
()1.60)
)0.01
()0.85)
)1.60
()0.35)
)1.47
()0.93)
I/Y
0.26
POP < 20
50
3
3.51
)0.0001
()0.98)
)0.69
()1.42)
0.01
(0.36)
0.01
(4.19)
)0.07
()0.97)
0.002
(0.96)
)2.00
()1.40)
0.07
(0.33)
GDPNG
0.49
POP > 20
29
4
0.82
)0.0005
()1.83)
)2.04
()2.74)
0.07
(1.93)
0.04
(3.31)
0.07
(0.67)
)0.02
()1.61)
0.25
(0.17)
0.75
(1.32)
GDPNG
)4.22
()3.09)
0.67
POP < 20
59
5
7.94
0.0005
(1.68)
1.00
(0.85)
0.10
(1.76)
0.03
(2.64)
)0.01
()0.18)
)0.008
()1.84)
)5.50
()1.93)
I/Y
*
a
Numbers in parentheses are t values. Estimation is with White’s heteroskedasticity-consistent standard errors.
Significant at the 0.10 level.
**
Significant at the 0.05 level.
***
Significant at the 0.01 level.
R
POP
N
2
WBLDC
IRLDC
ETHNIC
PPIDEV60
GOVCY
TRDY
SEC60
POPG
Equation
C
GDPN60
Dependent variable
1.36
(0.40)
0.59
POP > 20
31
6
27.76
)0.0006
()1.10)
)8.03
()3.52)
0.12
(1.50)
0.17
(4.39)
)0.52
()1.68)
)0.03
()1.31)
0.09
(0.01)
I/Y
)1.23
()1.81)
0.27
POP < 20
59
7
4.34
)0.0001
()1.13)
)0.67
()1.21)
0.03
(1.28)
0.003
(0.50)
)0.11
()2.72)
0.006
(1.71)
)1.28
()0.87)
GDPNG
)2.85
()1.66)
0.44
POP > 20
31
8
5.67
)0.0004
()0.97)
)1.25
()0.97)
0.03
(0.43)
0.01
(0.79)
)0.08
()0.61)
)0.04
()1.57)
1.33
(0.53)
GDPNG
Table 3. OLS robustness test corruption regression equations for small and large developing countries with IRIS (IRLDC), 1984–96 and World Bank (WBLDC)
corruption variables, 1994–96a
1008
WORLD DEVELOPMENT
*
a
0.66
58
1
18.42
0.0001
(0.35)
)0.04
()0.04)
0.09
(1.36)
0.08
(7.73)
)0.24
()1.92)
)0.04
()2.09)
)3.91
()1.41)
)0.65
()1.23)
0.66
(1.24)
I/Y
0.69
47
)1.18
()2.40)
0.88
(1.17)
2
22.47
)0.0001
()0.26)
)0.35
()0.28)
0.03
(0.48)
0.05
(3.09)
)0.07
()0.48)
)0.01
()2.37)
)5.22
()1.59)
I/Y
0.68
79
)2.08
(2.90)
2.38
(1.52)
3
16.57
)0.0001
()0.34)
0.40
(0.41)
0.12
(2.25)
0.05
(3.38)
)0.15
(1.07)
)0.01
()2.35)
)3.71
()1.58)
I/Y
)4.32
()2.95)
1.47
(0.19)
0.49
90
4
17.97
)0.0001
()0.44)
)1.42
()1.04)
0.11
(1.85)
0.03
(2.06)
)0.09
()1.13)
)0.01
(2.03)
)4.82
()1.84)
I/Y
0.28
58
5
0.90
)0.0001
()0.91)
)0.02
()0.04)
0.03
(1.98)
0.02
(3.56)
)0.08
()1.56)
0.009
(0.93)
)1.01
(0.27)
)0.22
()0.81)
0.63
(2.59)
GDPNG
Numbers in parentheses are t values. Estimation is with White’s heteroskedasticity-consistent standard errors.
Significant at the 0.10 level. ** Significant at the 0.05 level. *** Significant at the 0.01 level.
R
N
2
WBLEANIC
WBOLDC
IRLEANIC
IROLDC
TILEANIC
TIOLDC
BILEANIC
BIOLDC
ETHNIC
PPIDEV60
GOVCY
TRDY
SEC60
POPG
Equation
C
GDPN60
Dependent variable
0.47
47
)0.12
()0.51)
0.52
(2.12)
6
5.13
)0.0001
()1.20)
)0.28
()0.50)
)0.004
()0.21)
0.01
(2.23)
)0.14
()1.65)
0.002
(0.75)
)2.83
()1.72)
GDPNG
0.37
79
)0.21
()0.69)
0.76
(2.39)
7
4.76
)0.0002
(2.19)
)0.76
()2.16)
0.01
(0.81)
0.01
(3.77)
)0.08
()1.40)
)0.0002
()0.07)
)1.33
()1.28)
GDPNG
Table 4. OLS robustness test regression equations on other developing country and east asian NIC corruption variables a
)2.31
()2.83)
5.41
(4.19)
0.31
90
8
6.24
)0.0003
()2.48)
)0.98
()2.28)
0.03
(1.51)
)0.003
()0.58)
)0.10
()2.31)
0.0001
(0.02)
)0.98
()0.84)
GDPNG
COMPARATIVE POLITICS OF CORRUPTION
1009
1010
WORLD DEVELOPMENT
Bank’s ‘‘aggregated’’ measure of corruption.
They also demonstrate that this ‘‘aggregated’’
measure, which is created by aggregating data
on all available measures of corruption, is a
more accurate (precise) indicator of corruption than any single measure of corruption.
Because of this, the regression results using this
variable should be more robust (standard
errors should be smaller and t values higher)
than for each of the other corruption variables.
Examination of Tables 2–4 shows this to be the
case and this can be taken as one more sign
that our findings, though at odds with the
Bank’s view that corruption always slows
growth and/or reduces investment, are particularly robust.
4. CONCLUSIONS
Taken together, these empirical results provide substantial statistical support for our two
central hypotheses. To begin with, they suggest
that corruption is likely to be much more
damaging to investment and growth in small as
opposed to large developing countries. They
also demonstrate that corruption tends to
slow growth and/or investment in most developing countries but increase growth in the large
East Asian newly industrialized economies.
What are the implications of these results for
policy-makers? Several deserve mention.
Although we found some evidence to support
the conclusions reached in other crosscountry
regression studies of the impact of corruption
on growth and investment, our findings are
more ambiguous and nuanced. By itself, this
should caution those committed to reducing o
eradicating corruption as it suggests that efforts
to reduce corruption may not always yield
the expected economic outcomes. Demonstration that corruption is more damaging to
investment and growth in small developing
countries than in large ones is important
because it tentatively suggests that the international institutions, regional development
banks and bilateral aid donors might have
more to gain by focusing their anti-corruption
programs on small developing countries. 30 It
also suggests why it may be so hard to reform
corrupt governance structures in large developing countries.
Demonstration that corruption tends to be
growth-enhancing in the large East Asian newly
industrializing countries where governments
with long time horizons have centralized cor-
ruption networks with their big business partners is equally important. On the one hand, it
provides solid empirical support to a regional
and country case literature that explains the
East Asian paradox––the combination of high
corruption and high growth seen in Figure 1––
in terms of stable and mutually beneficial
exchanges of promotional privileges for bribes
and kickbacks. On the other hand, it suggests
that there is more than one way to provide
investors in market economies with the protection of property rights they need to get them
to innovate and invest than is suggested by the
current discussion of governance and corruption. 31 This should undermine at least some of
the hubris evident in assumptions about the
universality of a neoliberal governance paradigm.
As our results also show, however, governments in the rest of the developing world have
not been very successful at using corruption
networks to enhance investment and growth. If
we are right, this may well be because all too
often governments elsewhere in the developing
world have failed either to exercise monopoly
control over corruption networks or to behave
as stationary bandits committed to development. There are several other reasons why our
results should not leave one too sanguine about
corruption in general or East Asia’s corruption
cum growth regimes. To begin with, the corruption cum growth regimes in Southeast Asia,
particularly in Indonesia, Malaysia and Thailand, appear to have supported primitive
accumulation and/or technological learning in
simple labor-intensive industries, rather than
technological learning in skill-intensive industries as in Japan, South Korea and Taiwan. 32
Because governments in these economies are
weaker and less autonomous from the organized business groups they helped to create, it is
not clear that Southeast Asia’s softer developmental states can use their corrupt ties to
business to generate the high-speed technological learning in skills intensive industries visible
in Northeast Asia. If they cannot, their corruption cum growth regimes may prove, in the
long run, to be more of an inhibitor to rather
than an incubator for further growth. Second,
there is some evidence that the sustained corruption between political elites and big business
in East Asia undermined the political legitimacy of the region’s developmental states. 33
Since no government can rule for long without
substantial political legitimacy, this loss of
legitimacy is particularly worrisome. Equally
COMPARATIVE POLITICS OF CORRUPTION
worrisome is the carrying over of a legacy of
corruption into the region’s nascent democracies following democratic transitions. This has
the potential to substantially alter the industrial
organization of corruption by replacing
monopoly control of corruption networks
extant in the ancien regimes with more decen-
1011
tralized corruption networks fraught with the
problems associated with corruption networks
dominated by multiple independent monopolists. Such a change could very well presage a
shift from growth and investment enhancing
corruption to growth and investment retarding
corruption. 34
NOTES
1. There is a large companion literature on other aspects
of corruption. Some of it focuses on the microeconomics
of corruption (Clarke & Xu, 2001; Kaufmann & Wei,
1999; Leff, 1964; Lui, 1985) and some of it focuses on the
determinants of corruption (Ades & Di Tella, 1999;
Lederman, Loayza, & Soares, 2001; Treisman, 2000).
2. The World Bank’s anti-corruption activities can be
accessed at http://www1.worldbank.org/publicsector/
igrs.htm and http://www.worldbank.org/wbi.governance.
The Asian Development Bank’s anti-corruption activities can be accessed at http://www1.oecd.org/daf/Asiacom/ and USAID’s anti-corruption activities can be
found at http://www.usaid.gov/democracy/anticorruption/index.html.
3. The Appendix lists each corruption variable and its
source.
4. Both Mauro (1995) and Knack and Keefer (1995)
focus on broad measures of institutional quality rather
than corruption per se.
5. Small countries are defined as those with populations less than 20 million while large countries are those
with more than 20 million people. For example, for the
Business International corruption variable used by
Mauro (1995), the simple regression equation for small
countries is GDPNG ¼ 1.688 ) 0.569 BIC where
GDPNG is the average rate of growth of real GDP
per capita and BIC is the Business International
corruption index. In this equation BIC is statistically
(t ¼ 3:19) significant at the 0.01 level with the expected
sign ()) and R2 ¼ 0:13. The simple regression equation
for large countries is GDPNG ¼ 1.388 ) 0.0327 BIC
where BIC is statistically insignificant (t ¼ 0:15) and R2
is 0.001.
6. Some evidence of this can be found in Ades and Di
Tella (1999, p. 992) who find that corruption is higher in
countries where domestic firms are protected from
foreign competition and in countries with more active
industrial policies (Ades & Di Tella, 1997).
7. Haggard and Low (2002, p. 301) provide some
evidence of this for Singapore.
8. But, as one anonymous reviewer pointed out, since
we do not have corruption data on this group of small
economies stretching back to the 1960s when they were
in earlier stages of their development, we do not know
whether corruption was lower then or whether it fell as
they became more developed. While we agree with the
thrust of this comment, there is some evidence that the
governments of Singapore (Lee, 2000, pp. 157–171) and
Botswana (Holm, 2000) addressed corruption rather
early in their development.
9. During 1984–96, real GDP per capita growth
averaged 4.87% per year and the score on the IRIS
corruption indicator averaged a low 1.86 in these small
countries while the average growth rate was only 2.97%
per year and the corruption score averaged 2.93 for these
large countries. Moreover, China experienced high
growth (5.83% per year) and relatively high corruption
(2.82), while Mexico experienced low growth (0.36% per
year) and relatively high corruption (3.05). Growth data
are from Penn World Tables (PWT6.0) and corruption
data are from Political Risk Service (2002).
10. The grouping of countries in Figure 1 is based on
the regional and country-specific corruption literature
discussed in Section 2. Malaysia is grouped with
Singapore and Hong Kong (SINGHKMAL) because it
is a relatively small country with relatively low corruption scores (Lim & Stern, 2002, p. 5). The Philippines is
combined with South Asia (SASIAP) because its client
dominated
patron–client
networks
(Hutchcroft,
1994Hutchcroft, 2000, p. 218) are similar to those in
South Asia (Khan, 1996, pp. 691–695). Countries in the
large East Asian newly industrializing economies (LEANICS) category include China, Indonesia, South Korea,
Thailand and Japan. China (Wedeman, 2002b), Indonesia (Lim & Stern, 2002; Rock, 2002), Korea (Johnson,
1987; Kang, 2002), Thailand (Lim & Stern, 2002; Rock,
2000), and Japan (Babb, 2002; Johnson, 1987, 1999) are
included in this group because of strong similarities in
1012
WORLD DEVELOPMENT
their political economies of corruption. Other country
groupings include the Middle East and North Africa
(MENA), sub-Saharan Africa (SSA), and Latin America
and the Caribbean (LAC).
11. See Section 2.
12. Hyper-presidentialism is defined as a system of
government with strong presidents facing limited institutional and popular checks and balances on their
presidential actions (Whitehead, 2000).
13. As Hope (2000, p. 20) says, neo-patrimonialism
became so pervasive in Africa that even ordinary citizens
learned to adapt to it by shifting their loyalties to the
ruling regime of the day.
14. For discussion of plunder in one African country,
Zaire see Evans (1995, pp. 45–47).
15. Where neo-patrimonial politics was less pervasive
and governments more committed to development and
to limiting corruption, as in Botswana, corruption was
lower and growth and investment were higher (Coolidge
& Rose-Ackerman, 2000, pp. 77–78).
16. While there is some evidence of recent change in
Morocco (Economist, 1998, pp. 58–60), there is also
substantial evidence of continuing and serious problems
with corruption (Transparency International, 2003, pp.
204–207).
17. In Singapore, the government of Prime Minister
Lee Kwan Yew was committed to turning Singapore
into a first world oasis in Southeast Asia (Lee, 2000, pp.
56–57). Part of that commitment included building an
exceptionally clean (anti-corrupt) government (Lee,
2000, pp. 157–171). The British colonial government of
Hong Kong committed to more or less laissez faire
economic policies has a similarly strong history of anticorruption (Lee, 1995). While Malaysia has experienced
more corruption associated with money politics than
either Singapore or Hong Kong, virtually all of this
revolves around UMNO, state-owned enterprises and
bumiputera entrepreneurs (Gomez, 2002, pp. 82–114;
Khan, 1996, p. 86). The foreign investors who have
driven much of Malaysia’s industrial development miracle have been notably exempt from these kinds of
pressures (Khan, 2000, p. 89).
18. In some instances, as in South Korea and Japan,
patrons in government have used performance monitoring to hold their new clients in civil society accountable
for their performance. When this happens and clients use
the rents to grow their own firms and the economy,
government patrons can take credit for growing the
economy while appropriating a share of their clients’
profits in the form of bribes and kickbacks (Johnson,
1987; Kang, 2002; Rock, 2002). Those bribes and
kickbacks can be used to solidify support for the regime
and win election contests. As Kang (2002, p. 15) argues
this outcome is most likely when a small number of
relatively strong and autonomous patrons in government shower promotional privileges (new property
rights) on a small number of new business clients
(indigenous capitalists and entrepreneurs). As he says
(Kang, 2002, p. 7), this combination tends to foster a
mutually beneficial hostage relationship where patrons
offer favored businesses protected promotional privileges in exchange for bribes and kickbacks. Khan (2000,
1996, 2002), Rock (1995, 1999, 2000, 2002) and WooCummings (1999, p. 16) contend that this mutually
beneficial exchange of promotional privileges for bribes
is characteristic of investment and growth enhancing
corruption in South Korea, Indonesia, Thailand and
Japan. Wedeman (2002b, pp. 172–178) argues that such
a mutually beneficial exchange of privileges and protection for bribes and kickbacks characterizes the relationship between government and the private sector,
including the foreign private sector, in China.
19. When this happens, clients use their access to the
state to protect and enhance unproductive rent-seeking
activities reducing investment and growth. This outcome
appears to be typical of the domestic politics of
corruption in most of South Asia and the Philippines.
In South Asia where government patrons lack the power
to allocate and protect (enforce) new property rights,
factional groups in civil society have organized political
competition for unproductive re-distributive rents
(Khan, 2000, p. 92). As Khan (2000, p. 92) says the
deepening of democracy has strengthened the ability of
factional groups to capture re-distributive rents. As he
(Khan, 2000, p. 93) also says, this process allows
capitalists and landlords to seek and protect their
unproductive re-distributive rents simply by expending
resources on lobbying politicians and bribing bureaucrats. As an anonymous reviewer pointed out, something
very similar has been at work in the Philippines,
particularly in the later years of the Macros’ government
and in the governments following Marcos, where a very
weak state has been and is, ‘‘. . .choked with the anarchy
of (business-oriented) rent-seekers’’ (Hutchcroft, 1994, p.
217) who have been capturing the state and chewing off
rents from a shrinking pie.
20. Except for the East Asian NICs, the classification
of countries and regions into one of the four cells in
Table 1 is meant to be illustrative rather than definitive.
COMPARATIVE POLITICS OF CORRUPTION
21. Robustness tests are likely to be particularly
important since some are likely to be skeptical of results
suggesting that the impacts of corruption on investment
and growth depend on country size and on differences
across countries in domestic political economies of
corruption.
22. Mauro assumes this when he regresses the average
investment to GDP ratio over 1960–85 and the average
rate of growth of real GDP per capita during 1960–85 on
bureaucratic inefficiency and corruption indices averaged over 1980–83.
23. For example, Bangladesh’s corruption ‘‘score’’ on
the IRIS corruption variable fell by 33% during 1989–93,
Brazil’s increased by 50% during 1991–96, and China’s
increased by 50% during 1994–96 (Political Risk Service,
2002).
24. Countries in the ‘‘large East Asian NIC’’ category
include China, Indonesia, South Korea, Thailand and
Japan. Given the importance of a Japanese model of
development to these countries (Johnson, 1987; Rock,
1995, 1999) and similarities in domestic political economies of corruption (Kang, 2002; Rock, 2000, 2002;
Wedeman, 2002b) with Japan (Babb, 2002; Johnson,
1987), Japan was included in this group. Although space
constraints make it impossible to report regression results with and without Japan as a large East
Asian NIC, it should be noted that regression findings are not sensitive to the inclusion/exclusion of Japan.
25. These variables are BILDC, BIOLDC and BILEANICS for the Business International corruption variable;
TILDC, TIOLDC and TILEANIC for the Transparency
International corruption variable; IRLDC, IROLDC
and IRLEANIC for the IRIS corruption variable and
WBLDC, WBOLDC, and WBLEANIC for the World
Bank corruption variable.
26. Following Li et al. (2000), Easterly and Levine
(1997), Mauro (1995), Knack and Keefer (1995) and
Barro (1991), the investment rate is not controlled for in
growth equations because it is likely to be endogenously
determined by the other variables in the growth equation.
27. The Business International (BI) corruption regressions are for a sample of 58 developed and developing
countries in 1980–83. The Transparency International
corruption regressions are for a sample of 47 developed
and developing countries in 1988–92. The IRIS corruption regressions are for a sample of 79 developing and
developed countries in 1984–86. The World Bank
1013
corruption regressions are for a sample of 90 developed
and developing countries in 1994–96. Because of data
availability and comparability across sample regression
problems, none of our samples include countries from
the Eastern bloc. Political instability as measured by the
average number of revolutions and coups is often
included in growth accounting regressions. In most
instances in our regressions, a revolutions and coups
variable (REVC) was either dominated by one or two
data points, highly correlated with other variables, or
simply statistically insignificant. Because of this, we do
not report results with it, although they are available on
request. Mauro (1995) uses the ethno-linguistic fractionalization variable (ETHNIC) as an instrument in his
two-stage least squares regression equations, but since
Easterly and Levine (1997) show it to be a determinate
of crosscountry differences in growth, we use it as
another regressor, rather than as an instrument.
28. Because Hausman (1978) tests for endogeniety for
our truncated corruption variables rejected the hypothesis that these corruption variables were endogenous,
estimation of all regression equations is by ordinary least
squares.
29. Because of space constraints, we only report the
robustness test equations. Results for other equations
are similar and are available on request.
30. We say tentative because, as one anonymous
reviewer pointed out, we really do not have sufficient
data to demonstrate that some of the small countries
with high growth and low corruption started their
development with low corruption. Case data from
Singapore (Lee, 2000, pp. 157–172) and Botswana
(Holm, 2000) suggest that this may be the case in these
two economies, but it may well be that corruption fell in
one or more of the other small high-growth countries as
they developed.
31. Much of the current focus in anti-corruption
programs emphasizes what might best be called AngloAmerican governance structures and Anglo-America
rule of law. But as Rodrik (2002, pp. 4–5) argues, the
historical evidence suggests that there is no unique
mapping of the institutional requirements of market
economies into such specific institutional forms. Or as
Campos (2002, p. 3) argues, ‘‘. . .the proponents of ‘good
governance’ are confronted with the exact opposite of
their revered gospel: in East Asia, weak legal institutions
have existed side by side with high levels of investment
(not to mention) rapid rates of growth. In different ways
a number of authors argue that institutions that promote
the credible enforcement of contracts have indeed
existed in many of these East Asian countries. (These)
1014
WORLD DEVELOPMENT
. . .authors argue that rents and corruption have been
essential to the credible enforcement of contracts. . .’’
33. For discussion of this in Indonesia see Schwarz
(1999, pp. 159–161).
32. Aswicahyono, Hill, and Basri (2000) and Dehanini
(2000) discuss this problem in Indonesia. Jomo and
Felker (1999) and Jomo, Felker, and Rasiah (1999)
cover this problem in Malaysia. Felker (2001) and
Brimble (1993) discuss this problem in Thailand.
34. Kang (2002, pp. 158–171) suggests that this has
happened in Korea, Rock (2000, pp. 197–199) sees this
as a problem in Thailand and Dick (2001, p. 13)
discusses this problem in Indonesia following the fall of
Suharto.
REFERENCES
Ades, A., & Di Tella, R. (1997). National champions and
corruption: some unpleasant interventionist arithmetic. The Economic Journal, 107(443), 1023–1042.
Ades, A., & Di Tella, R. (1999). Rents, competition and
corruption. American Economic Review, 89(4), 982–
993.
Aswicahyono, H., Hill, H., & Basri, M. C. (2000). How
not to industrialize: Indonesia’s automotive industry.
Bulletin of Indonesian Economic Studies, 36(1), 209–
241.
Babb, J. (2002). Political business, and the inescapable
web of structural corruption in Japan. In E. T.
Gomez (Ed.), Political business in East Asia (pp. 324–
338). London: Routledge.
Bardhan, P. (1997). Corruption and development: a
review of the literature. Journal of Economic Literature, 35(3), 1320–1346.
Barro, R. (1991). Economic growth in a cross-section of
countries. Quarterly Journal of Economics, 106, 407–
443.
Bates, R. (1981). Markets and states in tropical Africa.
Berkeley, CA: University of California Press.
Boycko, M., Shleifer, A., & Vishny, R. (1995). Privatizing Russia. Cambridge, MA: MIT Press.
Bratton, M., & Van de Walle, N. (1994). Neo-patrimonial regimes and political transitions in Africa. World
Politics, 46(July), 453–489.
Brimble, P. J. (1993). Industrial development and productivity change in Thailand. Unpublished doctoral
dissertation, Johns Hopkins University, Baltimore,
MD.
Campos, J. E. (2002). Corruption: the boom and bust of
East Asia. Manila, Philippines: Ateneo De Manila
University Press.
Clarke, G. R. G., & Xu, L. C. (2001). Ownership,
competition, and corruption: bribe takers versus bribe
payers Development research group. Washington,
DC: World Bank, Paper was downloaded from
http://papers.ssrn.com/sol3/results.cfm.
Coolidge, J., & Rose-Ackerman, S. (2000). Kleptocracy
and reform in Africa. In K. R. Sr., Hope & B.
Chikulo (Eds.), Corruption and development in Africa
(pp. 57–85). London: Palgrave.
Dehanini, S. (2000). Indonesia: strategy for manufacturing competitiveness (Vol. II). Main Report, UNIDO,
UNDP/UNIDO Project No. NC/INS/99/004. Jakarta,
Indonesia: UNIDO, November.
Dick, H. (2001). Survey of recent developments. Bulletin
of Indonesian Economic Studies, 37(1), 7–41.
Easterly, W., & Levine, R. (1997). Africa’s growth
tragedy: policies and ethnic divisions. Quarterly
Journal of Economics, 111, 1203–1250.
Economist (1998). Road to freedom. Economist September 19, 348(8086), 58–60.
Evans, P. (1995). Embedded autonomy: states and industrial transformation. Princeton, NJ: Princeton University Press.
Felker, G. (2001). The politics of industrial investment
policy reform in Malaysia and Thailand. In K. S.
Jomo (Ed.), Southeast Asia’s industrialization: industrial policy, capabilities and sustainability (pp. 129–
182). London: Palgrave.
Geddes, B., & Ribeiro Neto, A. (1999). Institutional
sources of corruption in Brazil. In K. S. Rosenn & R.
Downes (Eds.), Corruption and political reform in
Brazil (pp. 21–48). Miami, FL: North–South Center
Press of the University of Miami.
Gomez, E. T. (2002). Political business in Malaysia. In
E. T. Gomez (Ed.), Political business in East Asia (pp.
82–114). London: Routledge.
Haber, S. (Ed.). (2002). Crony capitalism and growth in
Latin America: theory and evidence. Stanford, CA:
Hoover Institution Press.
Haggard, S., & Low, L. (2002). State politics and business
in Singapore. In E. T. Gomez (Ed.), Political business
in East Asia (pp. 301–323). London: Routledge.
Hausman, J. (1978). Specification tests in econometrics.
Econometrica, 46, 1251–1271.
Holm, J. D. (2000). Curbing corruption through democratic accountability: lessons from Botswana. In K.
R. Sr., Hope & B. Chikulo (Eds.), Corruption and
development in Africa (pp. 288–304). London: Palgrave.
Hope, K. R. (2000). Corruption and development in
Africa. In K. R. Sr., Hope & B. Chikulo (Eds.),
Corruption and development in Africa (pp. 17–39).
London: Palgrave.
Hope, Sr., K. R., & Chikulo, B. (Eds.). (2000). Corruption and development in Africa. London: Palgrave.
Hutchcroft, P. (1994). Booty capitalism: business-government relations in the Philippines. In A. MacIntyre
(Ed.), Business and government in industrializing Asia
(pp. 216–243). Ithaca: Cornell University Press.
Hutchcroft, P. (2000). Obstructive corruption: the politics of privilege in the Philippines. In M. H. Khan &
K. S. Jomo (Eds.), Rents, rent-seeking and economic
development (pp. 207–247). Cambridge: Cambridge
University Press.
COMPARATIVE POLITICS OF CORRUPTION
Internet Center for Corruption Research (2002). Historical comparisons. Available: http://www.gwdg.de/
~uwvw/histor.htm.
Johnson, C. (1987). Political institutions and economic
performance: the government-business relationship
in Japan, South Korea, and Taiwan. In F. C. Deyo
(Ed.), The political economy of new Asian industrialism (pp. 136–164). Ithaca: Cornell University Press.
Johnson, C. (1999). The developmental state: odyssey of
a concept. In M. Woo-Cumings (Ed.), The developmental state (pp. 32–60). Ithaca: Cornell University
Press.
Jomo, K. S., & Felker, G. (Eds.). (1999). Technology,
competitiveness and the state. London: Routledge.
Jomo, K. S., Felker, G., & Rasiah, R. (Eds.). (1999).
Industrial technology development in Malaysia. London: Routledge.
Kang, D. C. (2002). Crony capitalism. Cambridge:
Cambridge University Press.
Kaufmann, D., & Wei, S. (1999). Does ‘grease money’
speed up the wheels of commerce? Working Paper
7093. Cambridge, MA: National Bureau of Economic Research.
Kaufmann, D., Kraay, A., & Zoido-Lobaton, P. (1999).
Governance matters. Policy Research Working Paper
No. 2196. Washington, DC: World Bank.
Khan, M. H. (1996). The efficiency implications of
corruption. Journal of International Development,
8(5), 683–696.
Khan, M. H. (2000). Rents, efficiency and growth. In M.
H. Khan & K. S. Jomo (Eds.), Rents, rent-seeking
and economic development (pp. 21–69). Cambridge:
Cambridge University Press.
Khan, M. H., & Jomo, K. S. (Eds.). (2000). Rents, rentseeking and economic development. Cambridge: Cambridge University Press.
Knack, S., & Keefer, P. (1995). Institutions and
economic performance: cross-country tests using
alternative institutional measures. Economics and
Politics, 3, 207–227.
Krueger, A. O. (1974). The political economy of the
rent-seeking society. American Economic Review,
64(3), 291–303.
La Porta, R., Lopez-de-Silanes, F., Shleifer, A., & Vishny,
R. (1999). The quality of government. Journal of Law,
Economics and Organization, 15(1), 222–279.
Lederman, D., Loayza, N., & Soares, R. R. (2001).
Accountability and corruption: political institutions
matter. Mimeo. Washington, DC: World Bank.
Lee, K. Y. (2000). From third world to first. New York:
Harper Collins Publishers.
Lee, M. Q. C. (1995). Business and the rule of law in
Hong Kong. Columbia Journal of World Business
(Summer), 28–32.
Leff, N. (1964). Economic development through bureaucratic corruption. American Behavioral Scientist,
8(3), 6–14.
Levine, R., & Renelt, D. (1992). A sensitivity analysis of
cross-country growth regressions. American Economic Review, 82, 942–963.
Li, H., Xu, L. C., & Zou, H. (2000). Corruption, income
distribution and growth. Economics and Politics,
12(2), 155–182.
1015
Lim, L. Y. C., & Stern, A. (2002). State power and
private profit: the political economy of corruption in
Southeast Asia. Asian–Pacific Economic Literature,
16(2), 18–52.
Lopez, J. J. (1998). Private investment response to neoliberal reform in a delegative democracy: reflections
on Argentina. Quarterly Review of Economics and
Finance, 38(3), 441–457.
Lui, F. T. (1985). An equilibrium queuing model of
bribery. Journal of Political Economy, 93(4), 760–
781.
Mankiw, N. G., Romer, D., & Weil, D. N. (1992). A
contribution to the empirics of economic growth.
Quarterly Journal of Economics (May), 407–437.
Manzetti, L. (1994). Institutional decay and distributional coalitions in developing countries: the Argentine riddle reconsidered. Studies in Comparative
International Development, 29(2), 82–114.
Manzetti, L. (2000). Market reforms without transparency. In J. S. Tulchin & R. H. Espach (Eds.),
Combating corruption in Latin America (pp. 130–
172). Washington, DC: Woodrow Wilson Center
Press.
Mauro, P. (1995). Corruption and growth. Quarterly
Journal of Economics (August), 681–712.
Murphy, K., Shleifer, A., & Vishny, R. (1993). Why is
rent-seeking so costly to growth? American Economic
Review, 83(2), 409–414.
O’Donnell, G. (1994). Delegative democracy. Journal of
Democracy, 5(2), 55–69.
Olson, M. (1993). Dictatorship, democracy and development. American Political Science Review, 87(3),
567–576.
Osei-Hwedie, B. Z., & Osei-Hwedie, K. (2000). The
political, economic and cultural bases of corruption
in Africa. In K. R. Sr., Hope & B. Chikulo (Eds.),
Corruption and development in Africa (pp. 40–56).
London: Palgrave.
Penn World Tables (2002). PWT6.0. Available: http://
webhost.bridgew.edu/baten/.
Political Risk Service (2002). IRIS dataset. Available for
purchase and download at https://www.countrydata.com/datasets/purchase.phtml?code ¼ iris.
Rock, M. T. (1995). Thai industrial policy: how irrelevant was it to export success? Journal of International
Development, 7(5), 745–757.
Rock, M. T. (1999). Reassessing the effectiveness of
industrial policy in Indonesia: can the neo-liberals be
wrong? World Development, 27(4), 691–704.
Rock, M. T. (2000). Thailand’s old bureaucratic polity
and its new semi-democracy. In M. Khan & K. S.
Jomo (Eds.), Rents and rent-seeking and economic development: theory and the Asian evidence
(pp. 183–206). Cambridge: Cambridge University
Press.
Rock, M. T. (2002). The politics of development policymaking in New Order Indonesia. Paper presented at
seminar on economic policy reform in Asia at the
department of political science and the William
Davidson Institute, University of Michigan, Ann
Arbor, September 12.
Rodrik, D. (2002). Feasible globalizations. Mimeo.
Cambridge, MA: Harvard University.
1016
WORLD DEVELOPMENT
Sandbrook, R. (1993). The politics of Africa’s recovery.
Cambridge: Cambridge University Press.
Schneider, B. R. (2002). Why is Mexican business so
organized? Latin American Research Review, 37(1),
77–118.
Schwarz, A. (1999). A nation in waiting: Indonesia’s
search for stability. St. Leonard’s, NSW, Australia:
Allen and Unwin.
Shleifer, A., & Vishny, R. (1993). Corruption. Quarterly
Journal of Economics, 108, 599–617.
Smarzynska, B. K., & Wei, S. (2000). Corruption and
the composition of foreign direct investment: firm level
evidence. Working Paper 7969. Cambridge, MA:
National Bureau of Economic Research.
Steel, W. F., & Evans, J. W. (1984). Industrialization in
Sub-Saharan Africa. World Bank Technical Paper
No. 25. Washington, DC: World Bank.
Szeftel, M. (2000). Clientelism, corruption and catastrophe. Review of African Political Economy, 85, 427–
444.
Transparency International (2003). Global corruption
report, 2003. Berlin, Germany: Transparency International. Available: http://www.globalcorruptionreport.org.
Treisman, D. (2000). The causes of corruption: a cross
national study. Journal of Public Economics, 76(3),
399–457.
Tulchin, J. S., & Espach, R. H. (2000). Combating
corruption in Latin America. Washington, DC:
Woodrow Wilson Center.
Waterbury, J. (1973). Endemic and planned corruption
in a monarchial regime. World Politics (July), 533–
555.
Wedeman, A. (1997). Looters, rent-scrappers and dividend-collectors: corruption and growth in Zaire,
South Korea and the Philippines. Journal of Developing Areas (Summer), 457–478.
Wedeman, A. (2002a). Development and corruption: the
East Asian paradox. In E. T. Gomez (Ed.), Political
Business in East Asia (pp. 34–61). London: Routledge.
Wedeman, A. (2002b). State predation and rapid
growth: the politicization of business in China. In
E. T. Gomez (Ed.), Political Business in East Asia
(pp. 155–181). London: Routledge.
Wei, S. (2000). Local corruption and global capital
flows. Brookings Papers on Economic Activity, 2,
303–354.
Weyland, K. (1998). The politics of corruption in Latin
America. Journal of Democracy, 9(2), 108–121.
Whitehead, L. (1989). On presidential graft: the Latin
American evidence. In A. J. Heidenheimer, M.
Johnston, & V. LeVine (Eds.), Political corruption:
a handbook (pp. 781–800). New Brunswick, NJ:
Transaction Publishers.
Whitehead, L. (2000). High-level political corruption in
Latin America: a transitional phenomenon. In J. S.
Tulchin & R. H. Espach (Eds.), Combating corruption in Latin America (pp. 107–129). Washington,
DC: Woodrow Wilson Center Press.
Woo-Cummings, M. (1999). Introduction: Chalmers
Johnson and the politics of nationalism and development. In M. Woo-Cummings (Ed.), The developmental state (pp. 1–31). Ithaca: Cornell University Press.
World Bank (2000). World development indicators, 2000.
CD-ROM disk. Washington, DC: World Bank.
COMPARATIVE POLITICS OF CORRUPTION
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APPENDIX A. BASE VARIABLES AND SOURCES
Variable name
GDPNG
GDPN60
I/Y
POPG
PPIDEV60
SEC60
TRDY
GOVCY
BI
TI
WB
IRIS
ETHNIC
Definition and source
Average real GDP per capita growth rate in PPP$ 1996 from Penn
World Tables (PWT6.0)
Real GDP per capita in 1960 PPP$ 1996 from PWT6.0
Average ratio of gross domestic investment to GDP from PWT6.0
Average rate of population growth from PWT6.0
Deviation of purchasing power parity value of the investment deflator
from its sample mean in 1960 from PWT6.0
Secondary school enrollment ratio for 1960 from World Bank (2000)
Average share of trade in GDP from World Bank (2000)
Average share of government consumption expenditures in GDP from
World Bank (2000)
Business International corruption index for 1980–83 from Mauro
(1995, pp. 708–710)
Transparency International corruption index for 1988–92 from Internet
Center for Corruption Research at http://www.gwdg.de/~uwvw/histor.
htm
World Bank corruption index for 1997–98 from Kaufmann et al. (1999)
IRIS/Political Risk Service (PRS) corruption index for 1984–96 from
Political Risk Service (2002)
Ethno-linguistic fractionalization, a measure of ethnic diversity from
La Porta, Lopez-de-Silanes, Shleifer, and Vishny (1999, Appendix B)