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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/orslows growth. But how robust are these relationships? This question is answered by conducting aseries of crosscountry regression tests using four different corruption datasets. We find thatcorruption slows growth and/or reduces investment in most developing countries, particularly smalldeveloping 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 EastAsian paradoxthe combination of high corruption and high growthin terms of stable andmutually beneficial exchanges of government promotional privileges for bribes and kickbacks. 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 reducesinvestment and/or slows economic growth.Several other empirical studies (Smarzynska &Wei, 2000; Wei, 2000) extend these findings bydemonstrating that corruption retards foreign

direct investment and shifts the composition ofcapital flowing into countries with more cor-ruption in speculative directions. 1 Theseresults are largely consistent with the neoclas-sical rent-seeking literature (Boycko, Shleifer,& Vishny, 1995; Krueger, 1974; Murphy,Shleifer, & Vishny, 1993). Taken together, thisbody of theoretical and empirical work pro-vides the basis for a new growth industry ongood governance and development. 2

Just how robust is the relationship betweencorruption and investment on the one hand and

corruption and economic growth on the otherhand? This question is answered by conductinga series of growth accounting, or crosscountry

multiple regression tests of the relationshipsbetween corruption, investment and growth.What follows differs from other work on thistopic in several important ways. To begin with,we searched for and collected data on allknown published measures of corruption. Thisyielded four corruption data sets over fourdifferent time periods that provide the basis forwhat appears to be one of the most compre-hensive empirical tests of the impact of cor-

ruption on growth and investment. 3 Unlikeseveral other studies on this topic, corruption isdefined as the use of public office for private

www.elsevier.com/locate/worlddev

World Development Vol. 32, No. 6, pp. 9991017, 2004 2004 Elsevier Ltd. All rights reserved

Printed in Great Britain0305-750X/$ - see front matter

doi:10.1016/j.worlddev.2003.12.002

*We would like to thank the Summer Research Insti-

tute (SRI) at Hood College for supporting this research.

The SRI provides opportunities for particularly prom-

ising 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.

999

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gain, rather than as institutional quality,bureaucratic inefficiency or the degree of redtape within a bureaucracy. 4 This provides aclearer test of the relationship between cor-ruption, investment and growth.

Our crosscountry regression tests are par-tially motivated by the observation that therelationship between corruption and invest-ment and growth in our data sets appears to bedifferent for small and large counties. 5 Thereare several reasons to suspect why this might beso. On the one hand, large countries have rel-atively large internal markets and similarlylarge supplies of labor. This enables govern-ments in large developing countries to focus onimport substitution (ISI) policies for longerperiods of time than in smaller developing

countries. This may help them fend off pres-sures from international institutions andforeign investors to curb corruption, particu-larly the kind of corruption associated withselective industrial policies and money politics(Khan & Jomo, 2000). 6 On the other hand, alarge internal market and a large pool of labormay also mean that foreign investors are morelikely to accept corruption as a way of doingbusiness, if doing so enables them to gainunrestricted access to local goods and labormarkets.

Neither of these advantages is available tosmall developing countries. Their small marketsize means that they reach the limits of ISI fairlyquickly and this should push, at least thedevelopment-oriented governments in smalldeveloping countries, to be more open to aid,trade and investment. By itself, this shouldexpose small countries to more pressure toconform to emerging international normsregarding governance and corruption. 7 Simi-larly, small domestic markets and small poolsof labor may mean that foreign investors are

likely to be less understanding of local corruptbusiness practices. This combination mayexplain why governments in several prominentsmall developing economies with low levelsof corruptionSingapore, Hong Kong, Chile,Botswana and Malaysia 8have such highgrowth rates and why some large countriesChina, India, Brazil, and Mexicowith rela-tively high levels of corruption have suchdiffering growth rates. 9 It may also at leastpartly explain why small countries, particularlythose in sub-Saharan Africa, with high levels

of corruption have experienced such poordevelopment performances. Because of this,in Section 3, we test the hypothesis that cor-

ruption is more damaging to investment andgrowth in small developing countries than inlarge ones.

Country size is not however, the only thingthat matters. As will be demonstrated, the im-

pact of corruption on investment and growthalso depends on the domestic politics of cor-ruption. This can be seen in Figure 1 10 and inthe 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; Wede-man, 1997; Weyland, 1998). Both suggest thatthe relationships between corruption, growthand investment are not nearly as simple as sug-gested by either the traditional rent-seeking lit-

erature or standard crosscountry regressiontests. Figure 1 highlights what Wedeman(2002a, p. 34) labels the East Asian paradoxthe achievement of very high growth rates in realincome per capita over relatively long timeperiods in the face of quite high levels of cor-ruption. As will also be demonstrated, theregion specific and country case literatures 11

can be used to understand the pattern observedin Figure 1 and to construct several new cor-ruption variables that permit the testing ofhypotheses based on Figure 1. Because of this,

our research strategy is aimed at assessing thedegree to which corruption slows or increasesgrowth and investment in different regions andcountries of the developing world characterizedby substantially different political economies ofcorruption.

To anticipate results, we find that theempirical relationships between corruption,growth and investment are not very robustunless one controls for both country size andthe regional and/or country differences in thepolitical economy of corruption. After making

these adjustments, we find that corruptiontends to slow growth and/or reduce investmentin small countries in most of the developingworld, but increase it in a subset of large EastAsian economies characterized by relativelystable and strong governments with close andcorrupt ties to big business. The next sectionsuggests how the regional, case-based andtheoretical literatures on the political economyof corruption can be used to test hypotheseslinking different political economies of corrup-tion to growth and investment. Section 3

describes the data and reports statistical results.The concluding section outlines the implica-tions of our findings.

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2. THE COMPARATIVE POLITICS OF

CORRUPTION, INVESTMENT ANDGROWTH

The region specific and country case litera-tures suggest that the politics of corruption, orwhat Shleifer and Vishny (1993) label theindustrial organization of corruption, and itseffects on investment and growth are quitesimilar within different regions of the world,but quite different across those regions. Forexample, much of the literature on corruptionin Latin America focuses on the role of hyper-

presidentialism 12 in very costly high-levelpolitical corruption (Whitehead, 1989, 2000).As Whitehead (1989) demonstrates, in a sig-nificant number of cases presidents in thisregion have harnessed . . .the whole apparatusof the state to the task of their personalenrichment (Whitehead, 1989, p. 783). Inter-estingly enough, this tendency has not beenaffected by the substantial differences inunderlying political economies. Both theregions weaker states with relatively strongdistributional coalitions (Argentina), and the

regions relatively strong and more autono-mous states with rather weak distributionalcoalitions (Mexico) have been afflicted by high-

level political corruption emanating from the

presidents office (Manzetti, 1994, 2000). Gov-ernments (Brazil) with socio-political structuresbetween these extremes (Evans, 1995) havebeen similarly afflicted by high-level politicalcorruption (Geddes & Ribeiro Neto, 1999).

High-level political corruption has beenidentified as a problem during periods ofsubstantial government intervention in theeconomy, but it has also been a significantproblem during periods of market-orientedeconomic policies (Weyland, 1998, pp. 109112). Recent experiences with double transi-

tionsfrom authoritarianism to democracyand from interventionist to market-orientedeconomic policieshave been accompanied byeven higher levels of high-level political cor-ruption (Geddes & Ribeiro Neto, 1999; Man-zetti, 2000; Whitehead, 2000). ODonnell (1994,p. 55 & 62) suggests that this occurred becausethe severity of the socioeconomic crisesattending double transitions enabled newlyelected presidents to draw on long politicaltraditions of caudillismo to rule by executiveorder or fiat. Manzetti (2000) argues that this

facilitated the rise of unscrupulous businesspoliticians (Manzetti, 2000, p. 130 & 135)those who engaged in politics to acquire

Business International Corruption Index-3

-2

-1

0

1

2

3

4

5

6

0 1 2 3 4 5 6

AverageRateofGrowthofRealGD

PperCapita

SINGHKMA

SSA

LAC

MENA

SASIAP

LEANICS

Figure 1.Corruption and growth, 198083. Source: Business International corruption data are from Mauro (1995, pp.708710). Average real GDP per capita growth data are from Penn World Tables PWT (6.0). Country groupings areSINGHKMALSingapore, Hong Kong and Malaysia. LEANICSChina, Indonesia, Korea, Thailand and Japan.SASIAPSouth Asia and the Philippines. MENA Middle East and North Africa. LACLatin America and theCaribbean and SSA sub-Saharan Africa. Rationale for country groupings is given in Note 10 and in body of text in

Section 2.

COMPARATIVE POLITICS OF CORRUPTION 1001

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personal wealth. As he (Manzetti, 2000, p. 130)and Geddes and Ribeiro Neto (1999) arguebusiness politicians in Argentina, Mexico, andBrazil took advantage of severe socioeconomiccrises and weak checks and balances on presi-

dential rule to engage in high-level politicalcorruption. There is little evidence that suchhigh-level corruption increased either invest-ment or growth (Lopez, 1998; Schneider, 2002).

A similarly distinct politics of corruption isvisible in Africa. As Sandbrook (1993) argues,Africas post-colonial governments emergedunder extremely inauspicious circumstances.To begin with, the regions newly independentgovernments inherited skeletal statesbureau-cracies with extremely limited technical cap-abilities and equally limited capacities to

mobilize resources (Sandbrook, 1993, p. 25).These skeletal states were immediately bur-dened with overcoming the underdevelopmentassociated with their skewed export-orientedprimary product economies and the legacies ofslavery, racism, and foreign exploitation. Giventhe deep mistrust among Africans of mar-kets, trade, and foreign investment, it is notsurprising that both market-oriented andsocialist-oriented governments adopted highlyinterventionist development strategies (Bates,1981, pp. 29, 3044, 6277), including promi-

nent roles for state-owned enterprises (Steel &Evans, 1984, pp. 1628). These interventioniststrategies ultimately failed because govern-ments lacked both the political will and thecapacity to support productive activities asopposed to predatory rent-seeking activities(Sandbrook, 1993, p. 22).

To make matters worse, most of Africasnewly independent governments came to powerlacking even the most rudimentary politicallegitimacy (Sandbrook, 1993, p. 27). Underthese circumstances, governments were forced

to create some basis in civil society for their ownright to rule. While political leaders in Africamight have tried to cultivate legitimacy bydelivering development, most opted instead tofoster their own personal legitimacy, rather thanthat of the state, by building patronclient tieswith a tribalized peasantry (Szeftel, 2000, p.432). As Szeftel (2000, p. 432) says, this ensuredthe domination of politics by ethnic leaders whomobilized their disenfranchized voters by offer-ing them material benefits for their votes. Oncein 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 tiesbetween government patrons and their clientnetworks within government and in civil soci-ety. As Bratton and Van de Walle (1994, p. 458)say, neo-patrimonialism, political regimes

where chief executives maintained authoritythrough personal patronage, became the mostdistinctive and the core feature of Africanpolitics. Within government, political behaviorwas driven by competition for and, in the worstcases, outright bidding (Coolidge & Rose-Ackerman, 2000, p. 72) for those public officesthat provided the most substantial basis forprivate gain (Sandbrook, 1993, p. 28). Outsidethe state, clients used their access to theirpatrons in the civil service to create, expand,and sustain lucrative unproductive rent-seeking

activities. 13

Not surprisingly, Africas neo-patrimonialregimes spawned a wide range of exceedinglycorrupt behaviorsfrom outright stealing ofstate assets, to padding of public sector pay-rolls, smuggling of export crops and preciousmetals, rigged bidding on government con-tracts, and kickbacks on subsidized loans andimport licenses (Osei-Hwedie & Osei-Hwedie,2000, p. 4849). 14 Often incomes earned oncorrupt transactions were either stashed awayin foreign bank accounts or spent on luxury

consumption. Given the short life of many, butnot all, of Africas neo-patrimonial govern-ments, corruption takes tended to increase inanticipation of regime collapse (Szeftel, 2000, p.439). The effect on investment and growth of apolitical environment that encouraged chiefexecutives, high-ranking civil servants andordinary bureaucrats to loot state assets andheavily tax all productive activities was simplycatastrophic (Szeftel, 2000, p. 427). 15

This pattern of neo-patrimonial corruptactivities thrived in a wide range of political

economies in Africa. It took its most corrosiveform in the regions personal dictatorshipsasmanifested by Idi Amin in Uganda, Bokassa inthe Central African Empire, and Mobutu inZaire (Bratton & Van de Walle, 1994, p. 475).But neo-patrimonialism is also visible in theregions plebiscitary one party governmentstypified by president Eyadema in Togo andpresident Bongo in Gabon (Bratton & Van deWalle, 1994, p. 477). Africas military oligar-chies, 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-patri-monial politics (Bratton & Van de Walle, 1994,


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p. 480). So have the regions competitive oneparty states as in Zambia under Kaunda andthe Ivory Coast under Houphouet-Boigny(Bratton & Van de Walle, 1994, p. 483). Thereis also some evidence that corruption based on

a neo-patrimonial politics is not limited to sub-Saharan Africa. In at least one of the conti-nents Arab regimes, Morocco, corruptionrooted in neo-patrimonialism appears to havebeen essential to regime survival (Waterbury,1973). 16

Unlike Latin America and Africa, no singleunifying politics of corruption is visible in Asia.In three of this regions high growth economies,Hong Kong, Singapore and Malaysia, highgrowth and investment have gone hand in handwith relatively low levels of corruption

(SINGHKMALin Figure 1). For the rest of theEast Asian newly industrializing economies,including Japan, relatively high levels of cor-ruption have accompanied high growth andinvestment regimes (LEANICSin Figure 1). Ina number of other economies in this region,particularly in South Asia and the Philippines(SASIAP in Figure 1), relatively high levels ofcorruption appear to have been growth andinvestment reducing. It turns out that differ-ences in growth and corruption outcomes inAsia can be explained by differences in the

domestic politics of corruption. In Hong Kong,Singapore and Malaysia relatively strongautonomous states have worked very hard tolimit corruption. 17 Given the openness of theseeconomies to foreign trade and investment anddevelopment strategies rooted in linking theseeconomies to the West, it is not surprising thathigh growth and investment in these smalleconomies have been complemented by rela-tively low levels of corruption.

Elsewhere in Asia high levels of corruptionhave been combined with political economies

dominated by patronclient networks (Khan,1996, 2000). As Khan (1996, p. 691) arguesgovernments in Asia have historically relied onthese networks to implement their economicand political strategies. Their ability to do sohas been determined by the form that patronclient networks take. In patrimonial patronclient networks, the distribution of powerbetween government patrons and clients in civilsociety is tilted toward the state. Because statepatrons are strong relatively to their clients incivil society, polities driven by patrimonial

patronclient networks have sometimes beenable to allocate and protect new growthenhancing property rights. 18 But in political

economies, where patronclient networks aredominated by clients rather than by patrons,governments typically lack the power, relativeto their clients in civil society, to allocate andenforce existing or new property rights. 19 In

the former case, corruption can be growth and/or investment increasing, while in the lattercase, it typically reduces investment and/orslows growth.

The regional and country case literaturelinking corruption to investment and growth islargely consistent with the recent theoreticalliterature on corruption, investment andgrowth. In an influential essay, Shleifer andVishny (1993) argue that the impact of cor-ruption on growth depends on the industrialorganization of corruption networks. When

those networks are organized and managed bya strong centralized state, as in a monopolyindustry, corruption is likely to be less corro-sive to investment and growth than when it isorganized by numerous government officialsacting as independent monopolists. In fact,when the latter happens, bribes rise to infinityand growth and investment collapse (Shleifer &Vishny, 1993, p. 606). How might these differ-ences in the organization of corruption net-works account for what we see in the regionaland country case literature on corruption and

in Figure 1? Perhaps the large East Asian NICshigh-corruption high-investment and growthoutcomes reflect monopoly control of corrup-tion networks by strong overcentralized states,while South Asias and the Philippines high-corruption, low-investment, low-growth out-comes reflect control of corruption networks bycompeting monopolists in government. There issubstantial case study evidence (Bardhan, 1997,p. 1324; Hutchcroft, 1994; Johnson, 1987, 1999;Kang, 2002; Khan, 1996, 2000; Rock, 2002 andNotes 18 and 19) to support this conclusion.

By itself, however, differences in the indus-trial organization of corruption may not beentirely sufficient to explain all the differentpatterns observed in Figure 1. Olson (1993)suggests what else matters. His objective is toexplain why economic agents in any domain(country) might prefer a government of sta-tionary bandits to one of roving bandits. As he(1993, p. 568) says, rational (and successful)stationary bandits will monopolize theft (cor-ruption) in their domain while limiting whatthey steal because they know they will be able

to extract more in the long run if their subjectshave an incentive to invest and produce addi-tional income and wealth. The prospect of a


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future income stream from the monopolizationof theft may even encourage governments ofstationary bandits to provide the public goodsthat enable economic agents in stationarybandits domains to generate even higher

incomes and more wealth. Since roving banditshave short time horizons, they have fewincentives to limit theft and no incentives toprovide the public goods necessary to enticeresidents in their domains to invest and increasetheir incomes. Because of this, Olson suggeststhat investment and growth should be lower incountries governed by roving bandits. On theother hand, he asserts that if stationary banditsare committed to growth and development as away of maximizing their long-run corruptiontakes, investment and growth might be sub-

stantially higher in countries governed by sta-tionary bandits.

What this means is that the impact of cor-ruption on growth and investment depends onboth the industrial organization of corruptionand the time horizon of those who controlcorruption networks. Table 1 presents a two-by-two table of four possible growthinvest-mentcorruption outcomes based on differencesin the industrial organization of corruption andin time horizons of those who control corrup-tion networks. Governments (bandits) can

either be roving bandits with short time hori-zons or stationary bandits with long timehorizons. Corruption networks can either bemonopolized by a strong centralized state(bandit) or fragmented and controlled by asignificant number of independent monopolists(bandits). In all but one instance, exhibited by

stationary bandits with long time horizons,corruption should reduce investment and/orslow growth. This combination appears tocapture the essence of the role of corruption inEast Asias large developmental states. In these

states, relatively strong, stable and autonomouscentral governments have used their discre-tionary power to create, allocate and protectnew property rights (promotional privileges)for new groups in civil society (capitalists andentrepreneurs). These governments develop-mental orientation appears to have led them totake a long-run view of banditry (corruption).Because of this they have invested heavily inpublic goods and they exert near monopolycontrol over the corruption networks they cre-ated. This enables them to offer promotional

privileges in exchange for bribes and kickbacksthat they use to consolidate their politicalpower and enrich themselves.

In each of the other combinations in Table 1,corruption reduces investment and/or slowsgrowth. 20 When corruption networks arecontrolled by a significant number of rovingbandits who act as independent monopolists, asis typical in at least some of the countries insub-Saharan Africa, extremely weak states havebeen sustained by multiple patronclient net-works controlled by one or more ethnic groups

with extremely short time horizons. In thisworld, each independent monopolist within thestate extracts as much as they can as fast asthey can from both the state and the privatesector. Because those who control each cor-ruption network expect to be replaced in arelatively short period of time, there is little

Table 1. Corruption and growth regimes

Industrial organization of

corruption networks

Time horizon of government officials (bandits)

Short for roving bandits Long for stationary bandits

Strong centralized govern-

ments, at least for executives,

who exert monopoly control

over corruption networks

Business politicians in

hyper-presidential regimes in

Latin America (as in

Argentina, Brazil and Mexico)

East Asias 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 (+)

Weak and fragmented govern-

ments with multiple indepen-

dent monopolists controlling

corruption networks

Africas neo-patrimonial re-

gimes, 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 ())


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incentive to invest in public goods or developmutually beneficial relationships with anyone inthe private sector. Simple looting and plunderdominate decision-making.

This is not the only way in which corruption

can reduce investment and slow growth. Cor-ruption networks, particularly the costly high-level corruption networks that predominate ina number of countries in Latin America, canalso be monopolized by business-politiciansturned presidents with short time horizons.These presidents, especially in Argentina, Bra-zil, and Mexico, have routinely demonstrated alack of interest in public investment, except tothe degree that it provides an additionalopportunity for corruption, and they haveroutinely used their presidential powers to

enrich themselves as quickly as possible. Saidanother way, these presidents (monopolists)have shown a predilection to behave as rovingbandits reducing investment and slowinggrowth. Finally, corruption networks can becontrolled by a significant number of indepen-dent monopolists in governments who tend tohave long time horizons. This condition existsin India, the Philippines, and in several regimesin sub-Saharan Africa, such as in Zambia underPresident Kaunda and Kenya under PresidentMoi. Governments in these conditions tend to

be weak and easily penetrated by their clients incivil society who routinely use their ties to theirpatrons in government to extract unproductivere-distributive rents. Sometimes those rents goto some in the emerging middle classes, par-ticularly when they are offered jobs in thepublic sector. Sometimes those rents go tocapitalists and landlords who use their ties totheir patrons in government to gain and keepprotection. In neither instance is corruptionlikely to exert a positive effect on investment orgrowth.

3. DATA AND EMPIRICAL TESTS

Empirical tests of hypotheses relating cor-ruption to investment and growth are moti-vated by the vast growth accounting literatureas well as by the need to test for the robustnessof regression coefficients of particular interest(Levine & Renelt, 1992). 21 Data constraints,particularly on corruption variables, led toestimation of four different sets of crosscountry

regressions for four different time periods198083, 198892, 198496 and 199496. Ineach instance, variables are calibrated as close

as possible to the time period covered by eachmeasure of corruption. This enables us to avoidthe pitfall evidenced in Mauro (1995, pp. 690,699 & 702703) of assuming that the averagelevel of corruption measured in one period

(198083) is the same as the average over amuch longer period (196085). 22 As the Polit-ical Risk Services (Political Risk Service, 2002)time series data on corruption during 198496shows, this assumption is a not a particularlygood one. 23

We made four adjustments to these basiccorruption variables. As is well known, each ofour corruption variables was originally scaledso that an increase in the measured variableindicated a decline in corruption. To beginwith, we simply re-scaled each corruption var-

iable so that an increase signifies an increase incorruption. To capture the impact of corrup-tion on investment and growth in developingcountries we created several new corruptionvariables. The first is a simple developingcountry corruption variable where, for exam-ple, for the Business International corruptionscore BILDC 0 if the country is a developedcountry andBILDC the countrys corruptionscore if the country is a developing country.This particular developing country corruptionvariable is constructed on a traditional neo-

classical rent-seeking hypothesis that increases(reductions) in corruption anywhere in thedeveloping world slow (increase) investmentand reduce (raise) growth.

Since the region and country case literaturesuggests that corruption is likely to be invest-ment and growth reducing everywhere in thedeveloping world except in the large East Asiannewly industrializing countries (NICs) we cre-ated two other developing country corruptionvariables. The first is an other developingcountry corruption variable. For this variable,

as in BIOLDC for the Business Internationalcorruption variable, BIOLDC 0 if a countryis a developed country or one of our large EastAsian newly industrializing economies and BI-OLDC the countrys corruption score if thecountry lies elsewhere in the developing world.Finally, we created a large East Asian NICcorruption variable. 24 For this variable, as inBILEANIC for the Business International cor-ruption variable,BILEANIC 0 if a country isa developed country, a developing countryoutside East Asia, or an East Asian non-NIC

developing country and BILEANIC thecountrys corruption score if the country isa large East Asian NIC. This process was


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repeated for each corruption variable in eachtime period. In all, this yielded 12 new devel-oping country corruption variables, three foreach corruption variable. 25

Following standard practice in growth

accounting (Barro, 1991; Levine & Renelt,1992; Mankiw, Romer, & Weil, 1992), depen-dent variables include the average investmentshare in real GDP in PPP$ and the average rateof growth of real GDP per capita in PPP$ overcertain time periods. As is typical of cross-country regression studies of corruption(Knack & Keefer, 1995; Li et al., 2000; Mauro,1995) initial regressions focus on the re-scaledredefined regional corruption variables on thedependent variables. To these simple regres-sions of corruption on investment and growth,

a standard basic list of regressors includinginitial income per capita in 1960 (GDPN60), theaverage population growth rate (POPG), andthe secondary school enrollment ratio in 1960(SEC60) is added. 26 To these base regressionequations, robustness tests are carried out byadding a small list of other variables generallyagreed to affect crosscountry differences ininvestment to GDP ratios and growth rates inreal GDP per capita. These other variablesinclude the share of exports plus imports ortrade in GDP, TRDY/GDP, the share of

government consumption in GDP, GOVCY/GDP, price distortions in the investmentdeflator, PPIDEV60, in 1960, and ethno-lin-guistic fractionalization, ETHNIC. 27 All vari-able definitions and their sources appear in theAppendix.

Results of estimation 28 for each of the alldeveloping country corruption variables,BILDC, TILDC, IRLDCand WBLDC appearin Table 2. 29 Several important results standout.

First, two of the four all developing coun-

try corruption variables, BILDCand TILDC,are not statistically significant in either theinvestment or the growth equation. In two outof four instances, these variables have thewrong sign. On the other hand, IRLDChas theexpected sign ()) and is robust for the invest-ment equation, but not for the growth equa-tion, while WBLDC has the expected sign ())and is robust for both the investment andgrowth equations. These findings, particularlyfor IRLDC and WBLDC, provide whatappears to be modest support for the neoclas-

sical rent-seeking literature, which hypothesizesthat corruption reduces investment and/orslows growth.

But when Chow F breakpoint tests for largeand small countries are applied to the robust-ness test equations in Table 2, they reveal sta-tistically significant structural breaks ininvestment equations for TILDC, IRLDC and

WBLDC and structural breaks in growthequations forBILDCand WBLDC. Moreover,when the robustness test equations are re-esti-mated for large and small countries for IRLDCand WBLDC (Table 3), empirical results aresubstantially different. To begin with, none ofthe large country all developing countrycorruption variables are statistically significantand in two out of four cases, those corruptionvariables have the wrong sign (+). On the otherhand, the all developing country corruptionvariables for small countries are statistically

significant with the expected sign ()

) androbust for the investment equation for IRLDCand they are statistically significant with theexpected sign ()) and robust for the investmentand growth equations for WBLDC. This find-ing offers powerful support for the hypothesisthat corruption is more damaging to invest-ment and growth in small developing countriesthan it is in large developing countries. Byitself, this may explain why development-oriented governments in small developingcountries that adopt strong anti-corruption

programs such as Singapore, Hong Kong,Malaysia, Botswana and Chile tend to growfaster than those with more corruption.

Replacing the all developing country cor-ruption variables, such as BILDC, with theother developing country corruption vari-ables, such as BIOLDC, and the large EastAsian newly industrializing economies cor-ruption variables, such as BILEANIC, yieldsother interesting results (Table 4). Severaldeserve mention. To begin with, the otherdeveloping countries corruption variables,

BIOLDC, TIOLDC, IROLDCand WBOLDCare statistically significant with the expectedsign ()) in three out of four investment equa-tions and in one of the growth equations (forWBOLDC). At the same time, the large EastAsian NIC corruption variables, BILEANIC,TILEANIC, IRLEANIC and WBLEANIC,always have the expected sign (+) and arealways statistically significant in the growthequations, but none are statistically significantin the investment equations. One additionalfinding, pointed out by an anonymous

reviewer, deserves mention. As is well known,Kaufmann et al. (1999, p. 9) use an unobservedcomponents model to generate the World


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Table 2. OLS robustness test regression equations for all developing country corruption variablesBILDC, TILD

Dependent variable I/Y I/Y I/Y I/Y GDPNG GDPNG

Equation 1 2 3 4 5 6

C 17.52 24.17 21.64 18.26 0.06 4.90

GDPN60 7.95E)

05(0.22)a

)0.0004

()0.80))

0.0005()1.06)

)0.0001

()0.49))

0.0001()1.02)

)0.0002

()1.68)

POPG )0.99

()0.94)

)1.96

()1.42)

)0.82

()0.72)

)1.68

()1.19)

)0.65

()0.98)

)0.91

()1.73)

SEC60 0.09

(1.38)

0.06

(0.78)

0.13

(2.24)0.10

(1.77)0.04

(1.94)0.01

(0.61)

TRDY 0.08

(8.10)0.05

(2.70)0.05

(3.01)0.03

(2.13)0.02

(3.95)0.01

(2.44)

GOVCY )0.19

()1.50)

)0.03

()0.19)

)0.20

()1.34)

)0.09

()1.11)

)0.05

()0.95)

)0.11

()1.37)

PPID60 )0.06

(2.80))0.01

()2.21))0.01

()2.62))0.01

()2.02))0.002

()0.21)

0.002

(0.84)

ETHNIC )

2.87(0.98) )

4.82()1.23) )

2.75()1.06) )

4.62()1.76) )

0.35()0.17) )

2.76()1.59)

BILDC )0.03

()0.06)

0.21

(0.77)

TILDC )0.62

()0.85)

0.15

(0.60)

IRLDC )2.05

(2.58)

WBLDC )3.77

()2.42)

Chow F 0.49 2.61 6.11 5.21 2.56 1.79

R2

0.62 0.48 0.54 0.49 0.14 0.28

N 58 47 79 90 58 47

a Numbers in parentheses are t values. Estimation is with Whites heteroskedasticity-consistent standard errors. The Chow statistic.* Significant at the 0.10 level.** Significant at the 0.05 level.*** Significant at the 0.01 level.

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Table 3. OLS robustness test corruption regression equations for small and large developing countries with IRIS (IRLDC),corruption variables, 199496a

Dependent variable I/Y I/Y GDPNG GDPNG I/Y I/Y


C 6.58 33.10 3.51 0.82 7.94 27.76

GDPN60 0.0002

(0.58)

)0.0008

()1.51)

)0.0001

()0.98)

)0.0005

()1.83)0.0005

(1.68))0.0006

()1.10)

POPG 1.30

(1.15)

)5.59

()2.52))0.69

()1.42)

)2.04

()2.74)1.00

(0.85)

)8.03

()3.52)

SEC60 0.16

(2.17)0.08

(0.99)

0.01

(0.36)

0.07

(1.93)0.10

(1.76)0.12

(1.50)

TRDY 0.07

(3.76)0.16

(3.45)0.01

(4.19)0.04

(3.31)0.03

(2.64)0.17

(4.39)

GOVCY )0.04

()

0.24)

)0.60

()

1.60)

)0.07

()

0.97)

0.07

(0.67)

)0.01

()

0.18)

)0.52

()

1.68)PPIDEV60 )0.009

()1.85))0.01

()0.85)

0.002

(0.96)

)0.02

()1.61)

)0.008

()1.84))0.03

()1.31)

ETHNIC )1.74

()0.63)

)1.60

()0.35)

)2.00

()1.40)

0.25

(0.17)

)5.50

()1.93)0.09

(0.01)

IRLDC )1.49

()2.06))1.47

()0.93)

0.07

(0.33)

0.75

(1.32)

WBLDC )4.22

()3.09)1.36

(0.40)

R2

0.74 0.63 0.26 0.49 0.67 0.59

POP POP < 20 POP> 20 POP< 20 POP> 20 POP< 20 POP> 2

N 50 29 50 29 59 31

a Numbers in parentheses are tvalues. Estimation is with Whites heteroskedasticity-consistent standard errors.* Significant at the 0.10 level.** Significant at the 0.05 level.*** Significant at the 0.01 level.

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Table 4. OLS robustness test regression equations on other developing country and east asian NIC corr

Dependent variable I/Y I/Y I/Y I/Y GDPNG GDPN


C 18.42 22.47 16.57 17.97 0.90 5.13

GDPN60 0.0001

(0.35)

)0.0001

()0.26)

)0.0001

()0.34)

)0.0001

()0.44)

)0.0001

()0.91)

)0.000

()1.20

POPG )

0.04()0.04)

)0.35

()0.28)0.40

(0.41))

1.42()1.04)

)0.02

()0.04))

0.28()0.50

SEC60 0.09

(1.36)

0.03

(0.48)

0.12

(2.25)0.11

(1.85)0.03

(1.98))0.004

()0.21

TRDY 0.08

(7.73)0.05

(3.09)0.05

(3.38)0.03

(2.06)0.02

(3.56)0.01

(2.23)

GOVCY )0.24

()1.92))0.07

()0.48)

)0.15

(1.07)

)0.09

()1.13)

)0.08

()1.56)

)0.14

()1.65

PPIDEV60 )0.04

()2.09))0.01

()2.37))0.01

()2.35))0.01

(2.03)0.009

(0.93)

0.002

(0.75)

ETHNIC )3.91

()1.41)

)5.22

()1.59)

)3.71

()1.58)

)4.82

()1.84))1.01

(0.27)

)2.83

()1.72)

BIOLDC )

0.65()1.23)

)0.22

()0.81)

BILEANIC 0.66

(1.24)

0.63

(2.59)

TIOLDC )1.18

()2.40))0.12

()0.51

TILEANIC 0.88

(1.17)

0.52

(2.12)

IROLDC )2.08

(2.90)

IRLEANIC 2.38

(1.52)

WBOLDC )

4.32()2.95)

WBLEANIC 1.47

(0.19)

R2

0.66 0.69 0.68 0.49 0.28 0.47

N 58 47 79 90 58 47

a Numbers in parentheses are tvalues. Estimation is with Whites heteroskedasticity-consistent standard errors.* Significant at the 0.10 level. ** Significant at the 0.05 level. *** Significant at the 0.01 level.

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Banks aggregated measure of corruption.They also demonstrate that this aggregatedmeasure, which is created by aggregating dataon all available measures of corruption, is amore accurate (precise) indicator of corrup-

tion than any single measure of corruption.Because of this, the regression results using thisvariable should be more robust (standarderrors should be smaller and t values higher)than for each of the other corruption variables.Examination of Tables 24 shows this to be thecase and this can be taken as one more signthat our findings, though at odds with theBanks view that corruption always slowsgrowth and/or reduces investment, are partic-ularly robust.

4. CONCLUSIONS

Taken together, these empirical results pro-vide substantial statistical support for our twocentral hypotheses. To begin with, they suggestthat corruption is likely to be much moredamaging to investment and growth in small asopposed to large developing countries. Theyalso demonstrate that corruption tends toslow growth and/or investment in most devel-oping countries but increase growth in the large

East Asian newly industrialized economies.What are the implications of these results forpolicy-makers? Several deserve mention.Although we found some evidence to supportthe conclusions reached in other crosscountryregression studies of the impact of corruptionon growth and investment, our findings aremore ambiguous and nuanced. By itself, thisshould caution those committed to reducing oeradicating corruption as it suggests that effortsto reduce corruption may not always yieldthe expected economic outcomes. Demonstra-

tion that corruption is more damaging toinvestment and growth in small developingcountries than in large ones is importantbecause it tentatively suggests that the inter-national institutions, regional developmentbanks and bilateral aid donors might havemore to gain by focusing their anti-corruptionprograms on small developing countries. 30 Italso suggests why it may be so hard to reformcorrupt governance structures in large devel-oping countries.

Demonstration that corruption tends to be

growth-enhancing in the large East Asian newlyindustrializing countries where governmentswith long time horizons have centralized cor-

ruption networks with their big business part-ners is equally important. On the one hand, itprovides solid empirical support to a regionaland country case literature that explains theEast Asian paradoxthe combination of high

corruption and high growth seen in Figure 1in terms of stable and mutually beneficialexchanges of promotional privileges for bribesand kickbacks. On the other hand, it suggeststhat there is more than one way to provideinvestors in market economies with the pro-tection of property rights they need to get themto innovate and invest than is suggested by thecurrent discussion of governance and corrup-tion. 31 This should undermine at least some ofthe hubris evident in assumptions about theuniversality of a neoliberal governance para-

digm.As our results also show, however, govern-

ments in the rest of the developing world havenot been very successful at using corruptionnetworks to enhance investment and growth. Ifwe are right, this may well be because all toooften governments elsewhere in the developingworld have failed either to exercise monopolycontrol over corruption networks or to behaveas stationary bandits committed to develop-ment. There are several other reasons why ourresults should not leave one too sanguine about

corruption in general or East Asias corruptioncum growth regimes. To begin with, the cor-ruptioncum growth regimes in Southeast Asia,particularly in Indonesia, Malaysia and Thai-land, appear to have supported primitiveaccumulation and/or technological learning insimple labor-intensive industries, rather thantechnological learning in skill-intensive indus-tries as in Japan, South Korea and Taiwan. 32

Because governments in these economies areweaker and less autonomous from the orga-nized business groups they helped to create, it is

not clear that Southeast Asias softer develop-mental states can use their corrupt ties tobusiness to generate the high-speed technolog-ical learning in skills intensive industries visiblein Northeast Asia. If they cannot, their cor-ruptioncum growth regimes may prove, in thelong run, to be more of an inhibitor to ratherthan an incubator for further growth. Second,there is some evidence that the sustained cor-ruption between political elites and big businessin East Asia undermined the political legiti-macy of the regions developmental states. 33

Since no government can rule for long withoutsubstantial political legitimacy, this loss oflegitimacy is particularly worrisome. Equally


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worrisome is the carrying over of a legacy ofcorruption into the regions nascent democra-cies following democratic transitions. This hasthe potential to substantially alter the industrialorganization of corruption by replacing

monopoly control of corruption networksextant in the ancien regimes with more decen-

tralized corruption networks fraught with theproblems associated with corruption networksdominated by multiple independent monopo-lists. Such a change could very well presage ashift from growth and investment enhancing

corruption to growth and investment retardingcorruption. 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 Banks anti-corruption activities can be

accessed at http://www1.worldbank.org /publicsector/

igrs.htm and http://www.worldbank.org/wbi.governance.

The Asian Development Banks anti-corruption activi-

ties can be accessed at http://www1.oecd.org/daf/Asia-

com/ and USAIDs anti-corruption activities can be

found at http://www.usaid.gov/democracy/anticorrup-

tion/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 popula-

tions 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 GDPNG1.688)

0.569 BIC whereGDPNG 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 3:19) significant at the 0.01 level with the expected

sign ()) and R2 0:13. The simple regression equation

for large countries is GDPNG 1.388 ) 0.0327 BIC

where BIC is statistically insignificant (t 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 fromforeign 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. 157171) and

Botswana (Holm, 2000) addressed corruption rather

early in their development.

9. During 198496, 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 smallcountries 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 withSingapore and Hong Kong (SINGHKMAL) because it

is a relatively small country with relatively low corrup-

tion scores (Lim & Stern, 2002, p. 5). The Philippines is

combined with South Asia (SASIAP) because its client

dominated patronclient networks (Hutchcroft,

1994Hutchcroft, 2000, p. 218) are similar to those in

South Asia (Khan, 1996, pp. 691695). Countries in the

large East Asian newly industrializing economies (LEA-

NICS) category include China, Indonesia, South Korea,

Thailand and Japan. China (Wedeman, 2002b), Indo-

nesia (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


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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 insti-

tutional 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. 4547).

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. 7778).

16. While there is some evidence of recent change in

Morocco (Economist, 1998, pp. 5860), there is also

substantial evidence of continuing and serious problems

with corruption (Transparency International, 2003, pp.

204207).

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.

5657). Part of that commitment included building an

exceptionally clean (anti-corrupt) government (Lee,

2000, pp. 157171). The British colonial government of

Hong Kong committed to more or less laissez faire

economic policies has a similarly strong history of anti-corruption (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. 82114;

Khan, 1996, p. 86). The foreign investors who have

driven much of Malaysias industrial development mir-

acle 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 monitor-

ing 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 regimeand 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 govern-

ment 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 privi-

leges in exchange for bribes and kickbacks. Khan (2000,

1996, 2002), Rock (1995, 1999, 2000, 2002) and Woo-

Cummings (1999, p. 16) contend that this mutuallybeneficial exchange of promotional privileges for bribes

is characteristic of investment and growth enhancing

corruption in South Korea, Indonesia, Thailand and

Japan. Wedeman (2002b, pp. 172178) argues that such

a mutually beneficial exchange of privileges and protec-

tion for bribes and kickbacks characterizes the relation-

ship 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-seekingactivities 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 theirunproductive re-distributive rents simply by expending

resources on lobbying politicians and bribing bureau-

crats. 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 classificationof countries and regions into one of the four cells in

Table 1 is meant to be illustrative rather than definitive.


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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 196085 and the average

rate of growth of real GDP per capita during 196085 on

bureaucratic inefficiency and corruption indices aver-

aged over 198083.

23. For example, Bangladeshs corruption score on

the IRIS corruption variable fell by 33% during 198993,

Brazils increased by 50% during 199196, and Chinas

increased by 50% during 199496 (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 econ-

omies 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 regres-

sion results with and without Japan as a large EastAsian NIC, it should be noted that regression find-

ings are not sensitive to the inclusion/exclusion of Japan.

25. These variables areBILDC,BIOLDCand BILEA-

NICSfor the Business International corruption variable;

TILDC,TIOLDCandTILEANICfor 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 equa-

tion.

27. The Business International (BI) corruption regres-

sions are for a sample of 58 developed and developing

countries in 198083. The Transparency International

corruption regressions are for a sample of 47 developed

and developing countries in 198892. The IRIS corrup-tion regressions are for a sample of 79 developing and

developed countries in 198486. The World Bank

corruption regressions are for a sample of 90 developed

and developing countries in 199496. 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 oftenincluded 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 fraction-

alization 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 hypoth-

esis 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. 157172) 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-corruptionprograms emphasizes what might best be called Anglo-

American governance structures and Anglo-America

rule of law. But as Rodrik (2002, pp. 45) 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 promotethe credible enforcement of contracts have indeed

existed in many of these East Asian countries. (These)


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. . .authors argue that rents and corruption have been

essential to the credible enforcement of contracts. . .

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.

33. For discussion of this in Indonesia see Schwarz

(1999, pp. 159161).

34. Kang (2002, pp. 158171) suggests that this has

happened in Korea, Rock (2000, pp. 197199) sees this

as a problem in Thailand and Dick (2001, p. 13)discusses this problem in Indonesia following the fall of

Suharto.

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APPENDIX A. BASE VARIABLES AND SOURCES

Variable name Definition and source

GDPNG Average real GDP per capita growth rate in PPP$ 1996 from PennWorld Tables (PWT6.0)

GDPN60 Real GDP per capita in 1960 PPP$ 1996 from PWT6.0I/Y Average ratio of gross domestic investment to GDP from PWT6.0POPG Average rate of population growth from PWT6.0PPIDEV60 Deviation of purchasing power parity value of the investment deflator

from its sample mean in 1960 from PWT6.0SEC60 Secondary school enrollment ratio for 1960 from World Bank (2000)TRDY Average share of trade in GDP from World Bank (2000)GOVCY Average share of government consumption expenditures in GDP from

World Bank (2000)BI Business International corruption index for 198083 from Mauro

(1995, pp. 708710)TI Transparency International corruption index for 198892 from Internet

Center for Corruption Research at http://www.gwdg.de/~uwvw/histor.htm

WB World Bank corruption index for 199798 from Kaufmannet al. (1999)IRIS IRIS/Political Risk Service (PRS) corruption index for 198496 from

Political Risk Service (2002)ETHNIC Ethno-linguistic fractionalization, a measure of ethnic diversity from

La Porta, Lopez-de-Silanes, Shleifer, and Vishny (1999, Appendix B)


Documents

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