Corruption in Developing...

Corruption in DevelopingCountries

Benjamin A. Olken1 and Rohini Pande2

1Department of Economics, Massachusetts Institute of Technology,

Cambridge, Massachusetts 02142; email: [email protected]

2Harvard Kennedy School of Government, Harvard University, Cambridge,

Massachusetts 02138; email: [email protected]

Annu. Rev. Econ. 2012. 4:479–509

First published online as a Review in Advance on

April 25, 2012

The Annual Review of Economics is online at

economics.annualreviews.org

This article’s doi:

10.1146/annurev-economics-080511-110917

Copyright © 2012 by Annual Reviews.

All rights reserved

JEL codes: H11, K42, O12

1941-1383/12/0904-0479$20.00

Keywords

corruption, development, graft, bribes

Abstract

Recent years have seen a remarkable expansion in economists’ ability

to measure corruption. This in turn has led to a new generation of

well-identified, microeconomic studies. We review the evidence on

corruption in developing countries in light of these recent advances,

focusing on three questions: how much corruption is there, what

are the efficiency consequences of corruption, and what determines

the level of corruption? We find robust evidence that corruption

responds to standard economic incentive theory but also that the

effects of anticorruption policies often attenuate as officials find alter-

nate strategies to pursue rents.

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1. INTRODUCTION

The past decade has seen a significant increase in the international policy community’s

interest in corruption. From 1998 to the present, 38 countries have ratified the OECD

(Organization for Economic Co-operation and Development) Anti-Bribery Convention. At

the end of 2005, the United Nations convention against corruption, the most comprehen-

sive corruption convention to date, entered into force. In 2007, the World Bank launched

its Strengthening World Bank Group Engagement on Governance and Anticorruption strat-

egy. In recent years, the US Department of Justice and the Securities and Exchange Commis-

sion have dramatically increased their enforcements under the Foreign Corrupt Practices

Act.1 At the same time, several international aid agencies, including the Millennium Chal-

lenge Corporation, have made aid disbursements to low-income countries conditional on

a country’s corruption record.

These initiatives reflect a growing academic and policy consensus that corruption is often

high in low-income countries and that it is costly. The growing policy activism that conditions

international assistance on corruption outcomes in turn reflects a belief that given the right

incentives, politicians, bureaucrats, and civil society in these countries can reduce corruption.

Evaluating these claims requires answers to three questions. The first, and arguably

most basic, question that underlies policy design is, how prevalent is corruption? Second,

what are the costs of corruption (i.e., is corruption actually harmful)? Finally, what fac-

tors influence the level of corrupt behavior? For example, is corrupt behavior responsive

to economic incentives and market forces, and in what ways? Are there other effective

approaches that can be brought to bear on corruption, such as technology, and how might

corrupt officials react to such changes?

In this article we review the literature on these three issues and in each case describe

both what we know and what we do not. We include a wide variety of types of corruption

in our analysis but primarily focus on bribes to government officials and theft of govern-

ment resources by public officials.2

In writing this review, several themes emerged. First, although there has been a revolu-

tion in the measurement of corruption over the past few years, estimated levels of corrup-

tion are remarkably heterogeneous, so there remains little consensus about its magnitude.

Second, corrupt behavior has significant adverse consequences for efficiency and equity

outcomes. Third, we find fairly robust evidence that corrupt behavior can be modeled in

line with a few general economic principles: Corrupt officials respond to monitoring and

punishments as one would expect from basic incentive theory, and standard market forces

influence the level of bribes. That said, the ability of corrupt officials to substitute to

alternate forms of corruption and to otherwise adapt to policy changes, either in the short

run or the long run, suggests that applications of these principles can be tricky in practice.

In the end we were left with two very different senses. On the one hand, there has been

a revolution in the measurement of corruption, and this has in turn led to a blossoming of

1In 2005 alone, the average number of new Department of Justice prosecutions exceeded fourfold the average for

the prior five years.

2Although many laws (such as the US Foreign Corrupt Practices Act) also define cases of payment to any third

party, in connection with or in furtherance of a contract, as corrupt practices, we exclude such cases from our

analysis. Our definition of corruption also excludes shirking by government employees (here, employees steal time

from the government, rather than money). A number of recent papers estimate the absenteeism of health workers

and school teachers. We refer interested readers to Chaudhury et al. (2006) and Banerjee et al. (2012) for compre-

hensive reviews of that topic.

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the academic literature on corruption. On the other hand, if we were asked by a politician

seeking to make his country eligible for Millennium Challenge aid or the head of an anti-

corruption agency what guidance the economic literature could give them about how to

tackle the problem, we realized that, beyond a few core economic principles, we had more

questions to pose than concrete answers.

Our review, especially the discussion of how to measure corruption, is related to recent

survey articles, prominent among which are Zitzewitz (2012) and Banerjee et al. (2012).

We complement these reviews by providing a summary of the different estimates of cor-

ruption magnitudes and identifying how anticorruption policies can be enriched by an

understanding of the role of incentives and market forces in influencing corrupt behavior.

The remainder of this article proceeds as follows. Section 2 begins by reviewing the

evidence to date on the magnitudes and efficiency costs of corruption. Section 3 begins by

laying out a simple theoretical framework for thinking about the determinants of corrup-

tion and then examines evidence on them. Section 4 examines how corruption adapts to

anticorruption policies. Section 5 concludes.

2. MAGNITUDES AND EFFICIENCY COSTS

Anecdotal and survey evidence suggests that corruption is rampant in the developing world

and is more prevalent in developing countries than in rich ones (for a summary of the

survey evidence, see Svensson 2005). Yet, as we show in Section 2.1, there are remarkably

few reliable estimates of the actual magnitude of corruption, and those that exist reveal a

high level of heterogeneity.

Just knowing the magnitude of corruption does not tell us how serious the problem

is. After all, it is at least theoretically possible that corruption represents a transfer from

one party (e.g., the government) to another party (e.g., bureaucrats), with little efficiency

cost. In fact, if bureaucrats’ official salaries were less than their market wage in expec-

tation of the corrupt rents they would obtain—and there is evidence that this is indeed

exactly what happens—there could be no net costs of corruption at all. In practice, how-

ever, the evidence we review in Section 2.2 suggests that the efficiency costs of corruption

can be quite severe, as corruption may raise the marginal tax rate of firms, decrease

business activity, raise the marginal costs of public funds, make certain government projects

economically unviable, and undo the government’s ability to correct externalities, leading to

inefficient outcomes.

2.1. Estimating the Magnitude of Corruption

2.1.1. Perceptions. Until very recently, most estimates of corruption were based on sur-

veys of perception. These perception surveys have the advantage of good coverage—it is

much easier to ask someone’s perceptions of corruption than to actually measure corrup-

tion directly. As such, they still form the basis of most cross-country corruption indices,

such as Transparency International’s Annual Corruption Perception Index and the World

Bank’s Control of Corruption Index.3 Perception-based measures were also used in some

3The latter incorporates a variety of different aspects of corruption, ranging from the frequency with which firms

make “additional payments to get things done,” to the effects of corruption on the business environment, to mea-

surements of “grand corruption” in the political arena.

www.annualreviews.org � Corruption in Developing Countries 481

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of the first empirical work in economics on corruption, such as Mauro’s (1995) cross-

country study of the relationship between corruption and growth.

The challenge with perception-based measures is that they may not measure corruption

accurately. To examine the reliability of villagers’ perceptions of the corruption level in a

local road building project, Olken (2009) obtains villager assessments of the likelihood of

corruption in the project. At the same time, he develops a much more detailed measure of

the amount of corruption that was actually present in the road project by comparing the

amount the village government spent on the road to the amount independent engineers

estimated the road would actually cost to build (for details, see Section 2.1.4). Although

villagers’ perceptions do reflect actual corruption in the road project, the correlation is

quite weak: Increasing the actual missing expenditures in the road project by 10% increases

the probability a villager reports any corruption in the road project by just 0.8%.

Moreover, villagers’ perceptions appear to be biased in two ways. First, villagers are

much better at detecting marked-up prices (i.e., overcharging for cement) than inflated

quantities (i.e., billing for 1,000 m3 of rocks but only delivering 800 m3). To the extent that

elected leaders care about villager perceptions, it is not surprising that most of the cor-

ruption occurs by inflating quantities. This may account for the relatively low correlation

between perceptions and actual corruption, as people must make an inference about the

aspects of corruption they cannot perceive—which end up being where the bulk of corrup-

tion is usually hidden. Second, Olken shows that individual characteristics, such as one’s

education, have much more power in predicting perceived corruption than actual corrup-

tion itself. If a perception survey has different compositions of respondents evaluating dif-

ferent projects (or countries), this could create systematic biases in the use of perception.

One response is to use expert surveys. Banerjee & Pande (2009) estimate political cor-

ruption among candidates for political office by surveying journalists who covered that elec-

tion and politicians who stood for election in neighboring jurisdictions. They then correlate

the reported outcomes (such as whether the candidate faced criminal charges) with actual

data on the same and find a high correlation. The constraint on such surveys, however,

remains researchers’ ability to identify the correct expert pool, and of course in other settings

it is possible that even experts’ perceptions may be biased.

These types of biases could create problems in macro-level perception indices as well.

For example, after the fall of Soeharto in 1998, many commentators perceived that cor-

ruption in Indonesia became worse. The commonly stated view was that many players

at both the local and the national level started demanding bribes, and their failure to

coordinate their bribe-taking behavior resulted in a higher total level of bribes. The wors-

ening perceptions of corruption was captured by the Transparency International index—

measured on a scale from zero (highly corrupt) to 10 (highly clean)—which fell from a

value of 2.0 in 1998 to 1.7 in 1999, and stayed at the same level in 2000. This may well

have been the case, but another explanation is that the fall of Soeharto’s dictatorship

resulted in a much freer press, which was newly able to report on allegations of corruption,

which it did. It is therefore possible that perceptions of corruption rose even though actual

corruption fell. For these types of reasons, economists have been moving to more direct

measures of corruption whenever possible.

2.1.2. Survey estimates of bribes. Perhaps the most direct way of measuring bribery is

through surveys of bribe payers. In most contexts, there is relatively little stigma associated

with paying bribes, so in many cases bribery can be measured using surveys of firms or

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households. One notable example is Svensson (2003), who surveys firms in Uganda and

examines how much they paid in bribes. On average, firms in the survey report bribe

payments of about USD 88 per worker, or approximately 8% of their total costs.

As this type of survey-based measure of bribes is the most easily replicable, it is one of

the only areas where consistent measurement is now being carried out across countries and

over time. One key data set is the International Crime Victims Survey from 49 countries, in

which individuals are asked whether any government official in that country has asked them

or expected them to pay a bribe for his services during the previous year. Using these data,

Mocan (2008), for example, finds that the income and education of the individual have posi-

tive impacts on the likelihood of being asked for a bribe in developing, but not developed,

countries. For firms, theWorld BankEnterprise Surveys4 have included comparable questions

about firms’ informal gifts or payments in obtaining water, electricity, telephone connec-

tion, operating and import licenses, and construction-related contracts; meeting with tax

officials; securing government contracts; and more generally “getting things done” for many

low- and middle-income economies. As this type of data becomes more available, we will

be able to produce more reliable estimates of bribery over time and across countries.

2.1.3. Estimates from direct observation. The best way to measure corruption is often

to observe it directly. Needless to say, this is difficult as officials rarely will let corrupt

behavior be observed. Nevertheless, there are several notable examples of the direct obser-

vation of corrupt activity. One such example is the case of Montesinos in Peru, docu-

mented by McMillan & Zoido (2004). Montesinos, who was secret-police chief under

President Alberto Fujimori in Peru, bribed judges, politicians, and the news media to

support the Fujimori regime. Remarkably, he kept detailed records, with signed contracts

from those he bribed and videotapes of them accepting the bribes, and these became public

after the fall of the Fujimori regime. McMillan & Zoido use them to estimate the cost of

bribing various types of government officials. On average, politicians received bribes

ranging from USD 3,000 to 50,000 per month, depending on whether the politician was

in the opposition party (higher) or Fujimori’s party (lower), with judges receiving bribes of

the same order of magnitude. The bribes to control the media were orders of magnitude

larger—as much as USD 1.5 million per month for one television station’s support.

Olken & Barron (2009) provide direct data on actual bribes in a more prosaic setting:

the bribes truck drivers pay to police on their routes to and from the Indonesian province of

Aceh. Over a nine-month period, enumerators accompanied truck drivers on their regular

routes, dressed as truck drivers’ assistants, and simply noted the amounts that truck drivers

paid each time they were stopped at a police checkpoint or weigh station. On over 300 trips,

they observed more than 6,000 illegal payments. Usually each payment was small, aver-

aging USD 0.50 to 1, sometimes in cash and sometimes in kind (such as a pack or two of

cigarettes). In total, the illegal payments represented 13% of the marginal cost of the trip.

By comparison, the salary of the truck driver was only 10% of the marginal cost of the trip.5

4The exact details on the number of countries and years for each type of survey are available at https://www.

enterprisesurveys.org.

5The authors also compared directly observed bribes to reported bribes from a survey of comparable trips and found

that reported bribes were about double the amount of actually observed bribes. One potential explanation is that

drivers have an incentive to overreport bribes in general because they are reimbursed by trucking firms on the basis

of the average amount of bribes they need to pay.


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Sequeira & Djankov (2010) use a similar methodology in Mozambique and South

Africa, shadowing clearing agents who process customs for cargo as it passes through the

ports. Specifically, they estimate the economic costs and distortions associated with cor-

ruption acts at two ports in Mozambique and South Africa by directly observing bribe

payments to port and border post officials for a random sample of 1,300 shipments. They

find that, on average, bribes represent 14% of the shipping costs for a standard container

passing through the port of Maputo, Mozambique, and 4% of the shipping costs for a

standard container passing through Durban, South Africa.

2.1.4. Graft estimation by subtraction. The most common method for estimating graft

(i.e., the theft of government funds) is what we term estimation by subtraction. In this

method, one obtains two measures of the same quantity: one measure before corruption

takes place and one measure after corruption takes place. The estimate of corruption is

the difference between the two measures.

One of the first estimates using this technique is the pioneering study by Reinikka &

Svensson (2004). Using what they term a public expenditure tracking survey (PETS), they

compare the amount of a special education block grant sent down from the central gov-

ernment in Uganda with the amount of the block grant received by schools. They estimate

a leakage rate of 87%. Once the results were publicized, a subsequent study found that the

leakage rate fell to less than 20%. An important question in such an approach is the quality

of record keeping: If schools have poor records, some of the money might not show up

on the books even though it may have been received. Studying the importance of record-

keeping quality in PETS is an important issue for the replicability of this technique. Sub-

sequent to this work, similar PETS studies have been carried out, largely by the World

Bank, in a variety of contexts (for a brief review, see Olken & Pande 2011).

Using a similar approach, Fisman & Wei (2004) measure tax evasion by comparing

Hong Kong’s reported exports and China’s reported imports of the same products. They

differentiate three different aspects of tax evasion: underreporting of unit value, underre-

porting of taxable quantities, and mislabeling of higher-taxed products as lower-taxed prod-

ucts. These calculations are then used to estimate the effect of tax rates in tax evasion. They

found that higher-taxed products were associated with a 40% higher median evasion rate.

Olken (2007) implements a related exercise in the case of rural road projects. He com-

pares the official amount spent on the road to an independent engineering estimate of what

the road actually cost to build, in which engineers dug core samples of the roads to estimate

materials quantities, did price surveys to estimate local prices, and interviewed villagers to

estimate actual wages paid. Importantly, because some amount of materials naturally

disappears during construction, Olken built several small test roads where he knew there

was no corruption so that he could calibrate the metric so it would show zero corruption

when, in fact, corruption was zero. Olken estimated that “missing expenditures”—the

difference between what the village claimed the road cost and what the engineers estimated

it actually cost—averaged approximately 24% of the total cost of the road.

An alternative approach is to compare administrative data to a generally administered

household survey. Olken (2006) uses this approach to estimate theft of rice from a program

that distributed subsidized rice in Indonesia. He estimates that, on average, at least 18% of

the rice cannot be accounted for, with greater amounts in ethnically heterogeneous and

sparsely populated areas. In a similar vein, Niehaus & Sukhtankar (2010) compare admin-

istrative and survey data to measure corruption as the gap between official and actual

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quantities, including over-reporting of days and underpayment of wages in the Indian

National Rural Employment Guarantee Act.

When examining corruption through price manipulations, one can compare an official

price to the market price and use the difference as a measure of price manipulation. Hsieh &

Moretti (2006) do this for a famous case: corruption under the Iraqi Oil-for-Food program

administered by the United Nations. Specifically, they compare the price received by Iraq

for its oil to the going price for comparable oil on the world spot market and use a model

of the market for oil trading to infer what share of that underpricing was likely received

by Saddam Hussein’s regime. Although the total amount of corruption they estimate is

enormous—approximately USD 1.3 billion—it amounts to only approximately 2% of the

total volume of oil sold. Of course, not all price markups are corruption—they could simply

reflect incompetence or a lack of incentives in obtaining good prices for the government

(see, for instance, Bandiera et al. 2009).

2.1.5. Estimates from market inference. In some cases, one can use the theory of market

equilibrium, combined with data on market activity, to estimate the amount of corrup-

tion. In a pioneering study, Fisman (2001) applies this approach to estimate the value of

political connections to Indonesian President Soeharto. Specifically, he obtains an estimate

from a Jakarta consulting firm of how much each publicly traded firm was “connected” to

Soeharto, on a scale of zero to four. He then estimates how much each firm’s price moved

when Soeharto fell ill to estimate the stock market assessment of the value of those politi-

cal connections. If the efficient-markets hypothesis holds, then the change in stock market

value surrounding these events captures the value of the political connection to the firm.

Because investment bankers in Jakarta estimated that the total market would fall by 20%

if Soeharto died, he can calibrate these estimates to estimate the total “value” of the

connections to Soeharto. On net, for the most connected firms, he estimates that approxi-

mately 23% of their value resulted from Soeharto’s connections.

The Fisman market approach is replicable in any case in which one has data on firms’

connections to prominent politicians and when the politician experiences health shocks. For

example, Fisman et al. (2006) replicate the same approach for the United States, looking at

the value of connections to former US Vice President Dick Cheney, using shocks while he was

a candidate and while he was in office. In a marked contrast with the Soeharto paper, they

find that Cheney’s heart attacks had zero effect on the value of Cheney-connected stocks.

Faccio (2006) pursues a similar approach using a large sample of countries—she exam-

ines political connections to 20,202 publicly traded firms in 47 countries. For each of these

firms, she defines the firm as having a political connection if a board member or large

shareholder is a politician (e.g., member of parliament or minister). She focuses on cor-

porations in which a previous board member or large shareholder becomes a politician.

She finds that, on average, having a member of the board or large shareholder become

a politician is associated with a 2.29% increase in the company’s share value. Echoing the

contrast between Soeharto in Indonesia and Cheney in the United States, when she splits

the sample into countries with below- and above-average corruption levels (as measured by

the World Bank perceptions index), she finds that the impact comes entirely from high-

corruption countries: In above-median-corruption countries, having a board member or

large shareholder become a politician increases stock market value by 4.32%, but in

below-median-corruption countries, having a board member or large shareholder become

a politician has no impact on stock value.


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Another approach to measuring corruption uses equilibrium conditions in the labor

market. Specifically, one can use the fact that people in the public sector must, on the

margin, be indifferent between their public sector job and alternative jobs in the private

sector. If, controlling for their job opportunities, pay is lower in the public sector, the result

could simply reflect a compensating wage differential. But if pay in the public sector is

lower but consumption levels are the same, one could infer that the difference between

pay and consumption in the public sector relative to the same difference in the private

sector tells us something about how much those in the public sector are likely receiving in

the form of bribes. Gorodnichenko & Peter (2007) perform this exercise using a house-

hold survey in Ukraine. They find that, controlling for education, hours of work, job secu-

rity, fringe benefits, job satisfaction, and secondary employment, public sector workers

received 24%–32% less income than their private sector counterparts. Crucially, however,

they have the same level of consumption and assets, suggesting that a large part of the

gap must be made up in bribes. Aggregating across the economy, they estimate that the

total amount of the gap (and hence bribery) is between USD 460 million and 580 million, or

approximately 1% of GDP.

2.1.6. Other approaches. Although above we discuss the main approaches used in the

literature, this is not an exhaustive list. For instance, Ferraz & Finan (2008, 2011) and Brollo

et al. (2010) use official audits of municipal governments in Brazil to identify instances of

corruption. These audits were directly summarized and made available to the media. The

summary provided a short description of each irregularity in the municipality. The challenge

with audit data is that they represent a combination of both actual corruption and the

inability to hide it from auditors, so these data need to be used with care.

Asking whether, conditional on observables (which measure eligibility for public pro-

grams), public officials are more likely to benefit from publicly provided private transfers

gives another measure of corruption. Besley et al. (2012) show that controlling for asset-

based eligibility, holding political office increases the likelihood that a villager in India

has a Below Poverty Line card by 10%. A similar approach (and findings) is reported by

Olken (2007) and Niehaus et al. (2012).

2.1.7. So how much corruption is there, really? Table 1 presents the magnitude of corrup-

tion estimated from all the studies reviewed above, separated into estimates of graft (theft

of government funds) and estimates of bribes.6 The table shows the dramatic range. It also

shows that, although a number of credible estimates have emerged, in some sense there are

relatively few hard data when compared with other development indicators.

The magnitudes of corruption raise several important questions. First, a striking cor-

relation that comes up in a variety of data sets—from the perception indices, to Faccio’s

(2006) and Fisman’s (2001) studies of the value of political connections, to Sequeira &

Djankov’s (2010) comparison between ports in South Africa and Mozambique—is the

strong negative relationship between income and corruption: As best we can measure it,

richer countries appear less corrupt. The causality potentially runs in both directions. It is

easy to see how low corruption could cause countries to become rich if corruption hinders

6We include estimates of the value of political connections in the graft category, under the idea that the value of

those connections comes from the firm’s ability to appropriate rents from the government due their connections,

although one could easily categorize them separately instead.

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Table 1 Magnitudes of corruption

Paper Country Context

Strategy for

assessing corruption Corruption estimate

Corruption

estimate (%)

Estimates of bribery

Svensson (2003) Uganda Bribes firms paid Survey evidence Firms paid bribes of

USD 88 per worker

8% of costs

Olken &

Barron (2009)

Indonesia Bribes truck

drivers paid to

police on their

routes

Direct observation;

enumerators

accompanied truck

drivers on their

regular routes,

dressed as truck

drivers’ assistants,

and observed

illegal payments

Truck drivers paid

bribes averaging

USD 0.50 to

1 per payment

13% of cost

of a trip

McMillan &

Zoido (2004)

Peru Bribes the secret

police paid

to judges,

politicians,

and media to

support the

Fujimori regime

Direct observation;

after fall of Fujimori

regime, videotapes

and bribe receipts

became public

Politicians received

bribes of USD

3,000–50,000 per

month; media

received bribes

as much as

USD 1.5 million

per month for one

television station’s

support

N/A

Sequeira &

Djankov

(2010)

South Africa Bribes paid to

port and border

post officials

Direct observation;

enumerators

shadowed clearing

agents in ports to

collect information

on bribe payments

Bribes amounted to

14% and 4%,

respectively, of the

total shipping costs

for container

passing through

Mozambique

and South Africa

14% of

shipping

costs (Moz.)

Mozambique 4% of

shipping

costs

(S. Africa)

Estimates of graft

Reinikka &

Svensson

(2004)

Uganda Graft in public

spending of

educational

funds intended

to cover

schools’

nonwage

payments

Estimate by

subtraction; PETS

compared the

amount of grant

sent down from the

central government

to the amount

received by schools

Schools received on

average only 13%

of the grants

87% of funds

(Continued)


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Table 1 (Continued)


Strategy for


Corruption

estimate (%)

Estimates of graft

Olken (2007) Indonesia Graft in the

building of

rural roads

funded through

a national

government

program

Estimate by

subtraction; the

official amount

spent on the road

was compared to

an independent

engineering

estimate of what

the road actually

cost to build

“Missing

expenditures” (the

difference between

what the village

claimed the road

cost and what the

engineers estimated

it actually

cost) averaged

approximately 24%

of the total cost of

the road

24% of cost

of the road

Olken (2006) Indonesia Theft of rice

from a program

that distributed

subsidized rice

Estimate by

subtraction;

administrative data

were compared

to a generally

administered

household survey

At least 18% of the

program’s rice

disappeared before

reaching households

18% of

program

expenditures

Hsieh &

Moretti (2006)

Iraq Bribes from the

underpricing

of oil in Iraq’s

Oil-for-Food

program

Estimates by

subtraction; the

selling price of Iraqi

oil was compared

to the Oil-for-Food

program and the

author’s estimates

of the “market”

price of Iraqi oil

Iraq collected

USD 1.3 billion in

bribes from

underpricing oil,

or 2% of oil revenues

2% of oil

revenues

Khwaja &

Mian (2005)

Pakistan Politically

connected loans

Estimate from

market inference;

the additional

nonperformance rate

from politically

connected loans was

compared to that

from nonpolitically

connected loans

Politically connected

firms received

45% larger loans

from government

banks despite having

50% higher

default rates

0.3%–1.9%

of GDP

(Continued)

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Table 1 (Continued)


Strategy for


Corruption

estimate (%)

Estimates of graft

Niehaus &

Sukhtankar

(2010)

India Wages on the

National Rural

Employee

Guarantee

Scheme

Estimate by

subtraction; the

officially paid wages

were compared to

wages as reported

by a survey

INR 236 were stolen

per actual day paid,

where an actual day

paid is about INR 60

79% of labor

expenditures

Fisman (2001) Indonesia Value of political

connections to

President

Soeharto for

Indonesian

public firms

Estimate from market

inference; firm stock

price movement was

examined when

Soeharto fell ill,

given the strength

of its political

connections to

Soeharto

For the value of the

most connected

firms, 23% was

due to political

connections

23% of

firm value

Fisman et al.

(2006)

United

States

Value of personal

ties to Vice

President

Cheney for

US public firms


inference; firms’

stock price

movement was

analyzed in response

to the shock to

Cheney’s health,

given the strength

of connection

to Cheney

In all events studied,

there is zero effect

on the stock prices

of connected firms

0% of

firm value

Faccio (2006) Cross-

country

Value of political

connections

for firms across

sample of

47 countries


inference; stock price

movements of firms

were analyzed

around the time of

announcements that

officers or large

shareholders were

entering politics or

that politicians were

joining their boards

There is a 2.29%

increase in company

value when a

businessman enters

politics and a 4.32%

increase in stock

market value when

a board member or

large shareholder

becomes a politician

in countries where

corruption is above

the median

2.3%–4.3%

of company

value

(Continued)


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economic activity (Mauro 1995). However, the relationship in the other direction—that

richer countries become less corrupt—is less obvious. On the one hand, certain types of

income shocks, such as natural resource shocks, may lead to there being more rents to be

expropriated and more corruption. For example, Caselli & Michaels (2009) present the

case of oil revenues distributed to municipalities in Brazil, as a result of the large increase

in Brazil’s offshore oil production, and argue that this led to an increase in corruption.

There is, however, some evidence that these rents dissipate in the medium run, possibly

because voters become more aware of the total resources (Monteiro & Ferraz 2010). On

the other hand, more complex business relationships may lead to demand for better

government, and higher incomes may mean that countries have more resources to invest

in cleaning up corruption (Treisman 2000).

Second, even among countries at similar income levels, and even within countries,

there is marked heterogeneity in corruption levels, as shown in Table 1. Once one starts

Table 1 (Continued)


Strategy for


Corruption

estimate (%)

Estimates of graft

Gorodnichenko &

Peter (2007)

Ukraine Bribes received

by public sector

employees


inference; residual

wage differentials

between the public

and private sectors

were examined

(consumption levels

are the same in the

two groups, and

labor market

equilibrium implies

that employees are

indifferent between

working in the

public and

private sectors)

The aggregate amount

of bribery was

estimated to be

between USD

460 million and

580 million, or

approximately 1%

of the GDP

of Ukraine

1% of GDP

Ferraz &

Finan (2010)

Brazil Corruption in

municipal

government

Audit reports from

central government

auditors

Audits find an average

of BRL 327,000

diverted resources

per violation, or

8% of total amount

audited

8% of total

amount

audited

Besley et al.

(2012)

India Beneficiary

selection by

village council

Conditional on

eligibility, does

political office

predict beneficiary

status

Chief village councilor

is 10% more likely

to be a beneficiary

2% of

beneficiaries

selected

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examining why corruption emerges, it becomes clear that there is no reason to expect

magnitudes of corruption to be similar across settings.

Third, virtually all of these “hard” estimates of corruption may suffer from selection

bias in both directions. To the extent that measures of corruption depend on voluntary

disclosure (such as surveys of bribery or disclosing links to politicians sitting on corporate

boards), corruption may be understated, as places where corruption is most severe might

be less likely to disclose it. To the extent that researchers purposefully choose cases to

study, corruption may be overstated, as researchers may hone in on situations where they

expect to find corruption. Developing careful, rigorous metrics of corruption that are not

subject to these types of selection bias is an important area for future research.

2.2. Does Corruption Matter?

Although the previous section shows that corruption is substantial in magnitude—whether

in the form of bribes given to civil servants or graft from public expenditures—this does

not necessarily answer the question of whether corruption actually has a negative impact

on economic activity.

For example, Gorodnichenko & Peter (2007) show that, on average, public employees

in Ukraine have the same consumption levels as their private sector counterparts, even

though their salaries are 24%–32% lower. Corruption does not seem to be providing extra

income to these public employees, as what the government pays them is reduced exactly

to offset the amount they receive in bribes. In this case the economic efficiency losses

(or gains) from corruption depend on whether the deadweight loss imposed by the bribes

they collect is greater than (or smaller than) the equivalent deadweight loss from taxation

that would be needed to raise the revenue to pay the equivalent amount of money in

salaries were corruption eliminated. More generally, corruption could either have effi-

ciency costs or lead to efficiency gains.

This section lays out the evidence thus far on the ways in which corruption may have

aggregate efficiency costs: the costs imposed on firms, the costs imposed on government

activity, and the costs imposed through the government’s lack of ability to correct exter-

nalities. The endogenous nature of corruption makes finding credible instruments for

corruption at the macro level difficult. We therefore restrict attention to micro evidence.

2.2.1. Impact on firms. To estimate the efficiency cost of corruption on firm behavior,

ideally one must know several things. First, how does corruption change the effective

marginal tax rate faced by firms? To the extent that bribery is used to reduce tax liabilities

(e.g., bribing tax officials to reduce tax payments), the marginal bribe rate should be

below the official marginal tax rate, so corruption reduces effective tax rates. Conversely,

if bribes are charged for other types of government activities, this could increase the

effective marginal tax rate faced by firms. Second, conditional on knowing the effective

marginal tax rate after corruption, for a given effective marginal tax rate, are taxes affected

by corruption more distortionary than de jure taxes?

Svensson’s (2003) study of bribe-paying behavior in Uganda provides some clues that

although there is a positive relationship between bribes and firm profits, it is very flat.

Specifically, he estimates that each USD 1.00 in firm profits per employee leads to about

USD 0.004 in additional bribes paid, for a “marginal bribe rate” of 0.4% on profits. He also

finds that each USD 1.00 in capital stock per employee leads to an additional USD 0.004


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in additional bribes paid, representing an additional 0.4% marginal bribe rate on capital

stock. Note that these are marginal rates: The average level of bribes is substantially higher,

but bribes increase relatively weakly with profits and capital stock. If the only impact of

corruption was to impose a tax of 0.4% on profits and 0.4% on capital, one might expect

a modest impact of corruption on firm activity. By way of comparison, the marginal tax

rate on corporate profits for large corporations in the United States is 35%.

Svensson’s study establishes effective corruption tax rates but does not tell us the impact

of corruption on firms. There may be other ways in which corruption affects firm behavior

beyond the marginal tax rate. For example, many have argued that the uncertainty surrounding

corruption makes it more costly than an equivalently sized tax. Wei (2000) makes this argu-

ment looking at foreign direct investment and measuring uncertainty through perceptions-

based metrics. More recently, Malesky & Samphantharak (2008) use survey data to show that

changes in governors in Cambodia are associated with increases in uncertainty about corrup-

tion but with reductions in actual corruption levels and decreased firm-level investment.

In Section 2.1.3 we discuss Sequeira & Djankov (2010), who examine a different type

of distortion: changes in the firm’s production choices designed to avoid corruption. Their

estimates suggest that approximately 46% of South African firms located in regions where

overland costs to the port of Maputo are 57% lower go the long way around to Durban to

avoid higher bribe payments. This represents a real efficiency loss: Firms are willing to pay

higher (real) trucking costs to avoid having to pay bribes in Mozambique.

Given that corruption could have both direct effects (through a change in the effective

marginal tax rate) and indirect effects (through uncertainty or other channels), it is neces-

sary to directly examine the net impact of corruption on firm decisions. Using the same

data set as Svensson (2003), Fisman & Svensson (2007) calculate bribes and tax payments

in Uganda as a function of total firm sales. They regress firm growth over a two-year

period on the bribe and tax rate, instrumenting for the bribe and tax rate with industry-

by-location averages. A 1-percentage-point increase in bribes reduces annual firm growth

by 3 percentage points. By comparison, a 1-percentage-point increase in taxes reduces annual

firm growth by 1 percentage point, so bribes have three times the negative impact of taxes

on firm performance. They interpret the findings as showing that the negative impacts of

bribes on firm activity are higher than the corresponding impacts of taxation—with sub-

stantially large magnitudes for both.7

2.2.2. Impact on government provision of goods and services. Corruption can have effi-

ciency consequences through impacts on government provisions of goods and services.

First, if it increases the cost of government goods and services, this could have an effect

similar to raising the price of these goods and services. The efficiency loss would arise if

projects that would be cost-effective at the true costs are no longer cost-effective once the

costs of corruption are included, and hence are not done. Second, corruption could create

additional efficiency costs through distortions. Corrupt officials usually cannot steal cash

directly, as that would be easily detected; instead, they need to go through a variety of more

convoluted procedures to extract rents. These convoluted procedures themselves may

7Although the level of this effect seems enormous, it is worth recalling that the bribe and tax rates are expressed

as fractions of sales, not profits. Because profits are much smaller than sales, the implied bribe and tax rates on

profits are much higher than those on sales, so the estimated impact of a 1-percentage-point increase in a tax on

profits would be substantially smaller than what they estimate.

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induce inefficiencies, which could potentially be larger than the direct cost of corruption

itself. We explore both these issues in turn.

Price effects. One way corruption may matter is if the theft of government resources increases

the cost of government activity, so that otherwise worthwhile government projects—such as

redistribution schemes or public works projects—become non-cost-effective. Olken (2006)

examines this possibility in the context of a large Indonesian antipoverty program that dis-

tributed subsidized rice to poor households. As described above, by comparing survey data

to administrative data, Olken estimates that at least 18% of the rice was lost from the

program. He also performs a welfare calculation of the benefits of the program, both as it

was implemented and using a counterfactual with the same targeting of beneficiaries but

without corruption. The estimates imply that the welfare losses from this “missing rice”

may have been large enough to offset the potential welfare gains from the redistributive

intent of the program, so that the program without corruption might have been cost-

effective but, in the presence of corruption, it likely was not.

In this particular case, the government implemented the program anyway, so in a sense

the efficiency costs from lost redistribution were not realized. An open question, however,

is whether governments endogenously adjust their composition of expenditures in response

to the higher prices imposed by corruption. We regard this question—of whether govern-

ments indeed optimize taking the price effects of corruption into account—as important

for future research.

Distortions. Because corrupt officials need to hide their activity, they may introduce two

types of distortions into the procurement of government activity. First, because corruption

is secret, the government may not anticipate the amounts lost to corruption (in some ways,

this is the countervailing force to the price effects discussed above). It may then effectively

underfund some activities relative to its preferences, once the losses due to corruption are

taken into account. Second, the need to keep corrupt activity secret could also introduce

distortions, as procurement officials may substitute the types of goods that make hiding

corruption easier. We discuss the evidence for both these types of corruption in turn.

The first type of efficiency impact is the effective underprovision of government activi-

ties, as the government does not fully anticipate the impact of the losses due to corruption.

As described above, Olken (2007, 2009) provides evidence for this type of efficiency loss

in studies of perceptions versus reality for rural roads in Indonesia. Because villagers are

better able to detect corruption when prices are marked up (for which there would only be

a price effect), village officials instead hide their corruption by deflating quantities; i.e.,

they claim to procure enough rock, sand, and gravel to make a road that is 20 cm thick

but instead build a road that is only 15 cm thick. As the roads they build are thinner than

official engineering guidelines, they will not last nearly as long and will need to be replaced

sooner. Although Olken was not able to directly detect this quicker rate of decay in the

time frame of his study, engineers estimate that the impact of the thinner-than-designed

roads on road life span is substantial enough to cause significant efficiency losses.

Ferraz et al. (2010) provide direct evidence of the efficiency costs. In Brazilian munici-

palities where corruption was detected in education, they show that students have test scores

that are 0.35 standard deviations lower than those municipalities without corruption, as

well as higher dropout and failure rates. Moreover, higher corruption translates into lower

quantities received: Teachers in corrupt municipalities are 10.7 percentage points less likely


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to receive pedagogical training and are less likely to have a computer or science lab. The

study does not discuss the composition of school budgets, so it is hard to know if what

the authors are picking up are price effects (there is less spending on schools because the

government anticipates corruption) or distortions from corruption. One challenge in the

study is that the level of corruption may be endogenous: Although the authors control for

other municipal characteristics, as well as corruption in other sectors and some indicators

for school management practices, the level of corruption could be correlated with unobserv-

able variables related to the quality of the school.

Another direct estimate of the efficiency costs due to distortion is the allocation of

capital from state banks. Khwaja & Mian (2005) show that politically connected firms,

defined as those with a politician on their boards, receive 45% larger loans from govern-

ment banks despite having a 50% higher default rate on these loans. Privately owned

banks, conversely, show no such political bias. According to estimates, and assuming

the default rates are equivalent to transfers from taxpayers, the deadweight loss due to

corrupt lending is between 0.15% and 0.30% of GDP. When the effect of the inefficient

investment of politically connected firms is considered, an additional 1.6% of GDP is

estimated to be lost each year due to preferential lending.

2.2.3. Impact on correcting externalities. A third way in which corruption may lead to

inefficiency is if it lessens the government’s ability to correct an externality. For example, if

someone can bribe a police officer or judge instead of paying an official fine, the marginal

cost of breaking the law is reduced from the official fine to the amount of the bribe. Even

worse, if the police officer extracts the same bribe regardless of whether the person has

broken the law, the marginal cost of breaking the law falls to zero, and the law ceases to

have a disincentive effect altogether.

Olken & Barron (2009) examine this possibility in the context of trucks stopping

at weigh stations in Aceh, Indonesia. Overweight trucks are a classic example of an exter-

nality: The benefits to a trucker from loading on additional weight are concave, whereas

the damage the truck does to the road rises to the fourth power with the truck’s weight.

They found that almost all trucks were substantially over the weight limits—and 42% of

trucks were more than 50% over the legal weight limit. The data suggest that corruption at

weight stations is the likely culprit. Whereas all trucks more than 5% over the legal weight

limit are supposed to be ticketed, immediately unload their excess cargo, and appear in

court to face a fine according to the law, in fact virtually none received an official ticket.

Instead, almost all paid a bribe. Although more overweight trucks did pay higher bribes,

this relationship was very flat, and even those trucks that were not overweight had to pay a

bribe. Corruption thus dramatically reduced the marginal cost of driving overweight, lead-

ing to more overweight trucks.

Bertrand et al. (2007) examine a similar question in the context of driver licenses in

India. They randomly allocated applicants for driver licenses into three groups. The first

group received a bonus if they obtained a driver’s license quickly, the second group received

free driving lessons, and the third group served as the comparison group. The findings

confirm an efficiency loss: Many people who were completely unable to drive were able to

obtain licenses by paying a fee to an agent—and, in fact, the fee charged by the agent was

unrelated to one’s ability to drive. This efficiency loss effect was greater among the group

that received the bonus for quickly obtaining a driving license because they faced a higher

incentive to bypass the official procedures. Conversely, those who were randomly allocated

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to the driver’s license training class and who were better drivers were able to obtain their

license with lower payments on average, mostly because they avoided using agents and

instead used the official channel.

Bertrand et al.’s (2007) and Olken& Barron’s (2009) studies have similar findings: In both

cases, those who are doing the activity the government wishes to discourage (getting a license

if they cannot drive or having a truck that is overweight) do pay a higher cost that those

who obey the laws. However, the marginal cost of breaking the law is much lower with cor-

ruption than it would be without corruption, so the net impact of corruption is to decrease

the marginal cost of breaking the law and thus to decrease the effectiveness of the law.

These studies raise an important question: Given that corruption exists, how should the

government structure the official laws so that the net of the corruption marginal cost

faced by citizens matches the government’s true objective function? Understanding how

corruption maps de jure marginal costs imposed by laws into de facto marginal bribe

payments (and hence the de facto marginal costs faced by individuals) is an important next

step in thinking about how to more effectively write laws in the presence of corruption.

2.2.4. Impact on individuals. A final question is how corruption affects individuals directly.

Hunt (2007) shows the negative distributional impact of corruption not by arguing that

poor people expend a higher proportion of their income on bribes, but by stating that

corruption can be an additional cost for the victims of misfortune—particularly crime

victims. The study relies on an individual survey in Peru to show that misfortune increases

victims’ demand for public services, raising bribery indirectly. However, the study also shows

that in many situations, crime victims bribe more than other users who are not victims.

2.2.5. Some concluding thoughts on efficiency. One common theme that has emerged

is that we know little about how governments respond endogenously to the presence of

corruption. For example, if there are higher or lower rates of corruption in certain types

of government spending, does the government reoptimize spending as theory would pre-

dict, and does this reoptimization mitigate the efficiency costs of corruption? Or given that

government rules to correct externalities are partially (but not completely) undone by

corruption, does the government set official fines higher than it really wants, knowing the

official fines will not be implemented exactly?

An issue on the flip side of this is the degree to which governments create regulations

to maximize opportunities for corruption. A classic example is red tape. We refer the

interested reader to Banerjee et al. (2012), who develop a theoretical framework for

understanding how red tape itself may be endogenously created as a way to maximize the

corrupt rents captured by bureaucrats, as suggested by Banerjee (1997), and review the

existing empirical literature. It is clear that understanding whether the red tape itself is

an endogenous response is another form of inefficiency that merits further study.

Similar issues apply to the costs of corruption for firms. Although Fisman & Svensson

(2007) suggest that bribes are more costly for firms than the equivalent amounts of taxes,

the tax rate could also be endogenous to the level of corruption. Gordon & Li (2009), for

example, suggest that the tax code of developing countries is endogenously shaped by the

presence of tax evasion, as governments reallocate tax systems toward those areas that

are less prone to corruption. However, whether marginal tax rates on firms are higher or

lower in corrupt countries, and therefore whether the net distortions that taxes imply for

firms are higher or lower in corrupt countries, is an open question for future research.


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3. WHAT DETERMINES CORRUPTION?

This section examines what we know about why corruption exists and, relatedly, what

can be done with it. To organize ideas, we provide a simple framework that models the

perspective of an individual bureaucrat, following the ideas of Becker & Stigler (1974).

This framework treats the gains from corruption (the bribe) as fixed and asks when

honesty will be preferable to dishonesty. We then examine what happens when the optimal

bribe is determined by the bureaucrat taking into account market forces, following the

ideas of Shleifer & Vishny (1993). The subsequent sections discuss the empirical evidence

along the dimensions suggested by the simple theoretical framework.

3.1. The Incentives Bureaucrats Face

Suppose that the bureaucrat receives a wage w from the government and, if fired, can

receive an outside option v. The bureaucrat can decide to be corrupt or honest. If corrupt,

he is detected with probability p, is fired, and receives outside option v. If he is undetected,

he receives his wage w plus the bribe b, less a dishonesty cost d. In equilibrium, he will be

corrupt if and only if w�v<1�p

p(b�d).

This framework suggests several avenues for reducing corruption. One could increase

the returns to staying on the job (w), or, equivalently in this context, one could decrease

the outside option (v) by increasing punishments. One could also increase the probability

of detection (p).

One implication is that if there is heterogeneity in d among potential bureaucrats, there

can be selection in which those who are most likely to be corrupt (those who have the

lowest dishonesty costs d) will self-select to be more likely to become bureaucrats. Suppose

that d in the population is distributed uniformly from zero to �d. If w�v>1�p

p(b), then

nobody will be corrupt, regardless of their level d, and there is no reason that the distribu-

tion of d among bureaucrats will be different than the distribution of d in the population.

If, however, the above inequality does not hold, then people with low d will have a

higher utility from becoming bureaucrats than those with high d, as they will be relatively

more efficient at corruption. Therefore, depending on how the government allocates

jobs, we might expect to have more low-d people among bureaucrats than in the popula-

tion. This implies that corruption may be harder to combat because a corrupt system may

attract bureaucrats who are more prone to corruption. It also implies that the effect of a

given anticorruption policy [i.e., a vector (w,p)] will depend on past levels of anticor-

ruption policies, as those past policies will influence the selection of bureaucrats.

The simple framework thus far has treated the amount of the bribe, b, as exogenous. In

practice, however, the bribe may be set by the bureaucrat to maximize his profits. Specifi-

cally, conditional on deciding to be corrupt, the bureaucrat will set his bribes to maximize

his profits, which are the number of bribes he receives multiplied by the price (i.e., qibi).8

The key insight of Shleifer & Vishny (1993) is that the optimal solution depends on what

other bureaucrats are doing and how they set prices. If a person needs permits from two

8To simplify the analysis, we assume that conditional on being caught, the probability of being caught does not

depend on the amount of the bribes or the quantity of bribes, although one could easily generalize the model to

include these effects.

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different bureaucrats to complete a transaction, and both set prices independently, then

each bureaucrat solves maxbi Q bi þ b�ið Þbi, taking the other bureaucrat’s bribe b�i as

given. In such a case, the total amount of the bribes (b1 þ b2) will be higher than if there

had only been a single bureaucrat, and the total quantity will be lower. Conversely, if a

consumer needs a single permit that can be obtained from either bureaucrat, they will

compete against each other and reduce the bribe beyond what a single, monopolistic

bureaucrat would charge. The key insight is that the bribes themselves may be a function

of the structure of the bureaucracy and that changing the nature of the organization may

have important implications for the level of corruption.

This framework, although stylized, highlights the important role that both the incentive

structure faced by individual bureaucrats (be it compensation, monitoring, selection, or

other incentives) and the bureaucratic organization may play in influencing the amount of

corrupt behavior. This section discusses the evidence to date on each of these factors in turn.

3.1.1. The bureaucrat’s decision problem: the role of compensation, selection, and other

incentives. We examine several aspects of the bureaucrat’s decision problem: the role of

compensation, monitoring and punishment, selection, and incentives.

Compensation. Despite the attention often given to civil service wages, there is relatively

little evidence on their impact. Several cross-country studies find that higher public wages

are associated with lower corruption, although these studies are essentially cross-sectional

in nature. For instance, in a cross section of 31 low-income countries, Van Rijckeghem &

Weder (2001) find that a doubling of government relative to manufacturing wages is asso-

ciated with only a 0.5-point reduction in the International Country Risk Guide’s corrup-

tion index measured on a scale from zero to six. Meanwhile, Rauch & Evans (2000) find

that the level of bureaucratic wages is significant in explaining only one of the five mea-

sures of bureaucratic performance, namely that a 1-standard-deviation increase in salary is

associated with an improvement of 0.5 standard deviations in the bureaucratic delay index

measured on a scale from one to four.

With regard to more micro evidence, Di Tella & Schargrodsky (2004) test the efficiency

wage idea by looking at a corruption crackdown in hospitals’ procurement departments in

Buenos Aires. They examine the impact of increasing the probability of detection and

examine heterogeneous impacts on the prices paid for basic inputs based on the level of

wages. Prices paid by hospitals for basic, homogeneous inputs decrease by 15% during

the first nine months of the crackdown, and the following period prices increase, but

remain 10% lower than those prevailing before the crackdown. During the first phase of

the crackdown, when audit intensity can be expected to be maximal, higher wages have no

effect on inducing lower input prices. Meanwhile, higher wages do have a negative effect in

the last phase of the crackdown, when audit intensity can be expected to take intermediate

values—the wage elasticity of input prices exceeds 0.2.

Niehaus & Sukhtankar (2010) examine the idea that the rents from keeping one’s job

can deter corruption today to preserve tomorrow’s opportunities. The rents they examine

come from corruption, not wages. They can identify the effect of future rents on the level of

corruption today because the program features two types of projects; some projects pay

fixed daily wages, whereas others pay piece rates. They examine how corruption in the two

types of projects varies with anticipated rent-extraction opportunities using an exogenous

increase in the wage rate for daily wage projects. Their results show an 80% reduction in


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the daily theft on piece-rate projects in the period following the wage increase. Hence,

when the opportunities for theft from daily wage projects increase, theft on piece-rate

projects goes down. In addition, they find reduced over-reporting of days worked on daily

wage projects in areas where the proportion of future daily wage projects is higher.

Monitoring and punishments. One would expect from the above framework that increased

monitoring would reduce corruption. In practice, however, the very individuals tasked

with monitoring and enforcing punishments may themselves be corruptible, so increasing

monitoring may simply increase transfers from low-level officials to auditors. Moreover,

just because people are audited does not necessarily mean that auditors will find enough

evidence to actually impose a punishment, even if corruption were taking place. Under-

standing the degree to which additional monitoring can reduce corrupt behavior is thus an

important area for empirical research.

In his study of roads in Indonesia, Olken (2007) examines this question by conducting a

randomized experiment on auditing. Before villages began building road projects, some

villages were randomly selected for a high-audit-intensity group, where they faced an audit

by the government agency with 100% probability, as opposed to a 4% probability in the

control group. Olken finds substantial effects of the government audits, reducing corrup-

tion by 8 percentage points or approximately 30% from the baseline level. Interestingly,

the audits revealed substitution among alternative forms of corruption: Although audits

reduced missing expenditures, they increased nepotism (i.e., the hiring of family members

of the project leader or village officials to work on the project). One reason that the audits

did not reduce corruption to zero was that, even though audits found problems in 90%

of the villages they audited, the findings were typically administrative failures, such as

improper receipts or a failure to receive the required number of competitive bids, rather

than the direct evidence of corruption that would be needed for a criminal prosecution.

In other words, just because the probability of an audit was 100% does not imply that the

probability of punishment, conditional on the presence of corruption, was 100%. Never-

theless, on balance, the results demonstrate that the traditional economic approach to

fighting crime—increasing the expected cost of crime by increasing the probability of being

caught—can play an important role in reducing corruption, even in a highly corrupt

environment where those doing the monitoring are themselves potentially corruptible.

Another approach to providing monitoring—that does not involve a central auditor—is

grassroots monitoring, in which regular citizens are empowered to monitor their officials

to prevent corruption. Olken’s study also examines this by randomly allocating villages to

receive more intensive community monitoring. This was done through two interventions,

with different purposes. The first intervention involved inviting hundreds of villagers to

attend local accountability meetings, to reduce elite control over which community mem-

bers were involved in the monitoring. The second intervention involved distributing hun-

dreds of anonymous comment forms throughout the village, to allow community members

to voice concerns or complaints without fear of retaliation.

The invitations intervention reduced theft of materials, but only for theft of wages

(i.e., convincing villagers to work for free but billing the project for their work). One

reason may be that if theft of wages was detected, the benefits would go to the small

number of people who worked on the project and should have been paid; they there-

fore have a strong personal incentive to prevent this type of corruption. By contrast, the

benefits from detecting theft of materials would accrue to the village as a whole in the

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form of a better road, so the free-rider problem may be more severe. With regard to the

anonymous comment forms, they were successful only when they were distributed via

school children, not via the neighborhood government, as the neighborhood leaders

channeled the forms toward preferred people who were more likely to support the elite

in the project. One important thing to take away from is that for community participa-

tion to work, it is important to get the details right in terms of protecting people from

retaliation, limiting the free-rider problem, and preventing elite capture.

Increasing community participation can influence governance through multiple chan-

nels. The first, which is emphasized by Olken, is improvements in monitoring. A second

possible channel is improved information—leaders may learn more about villagers’ pref-

erences, and villagers in turn may learn more about outcomes. The second channel may

be particularly important when the outcomes being measured relate to service delivery,

not corruption.9

Ferraz & Finan (2008) examine the role of electoral sanctions. Randomized timing of

municipality audits allows them to examine the impact of audit timing on the probability

that the mayor is re-elected. Conditioning on the number of corruption violations found by

the auditors, those audited before the election were less likely to be re-elected than those who

were audited after the election. The finding suggests an important complementarity between

audits—which provide information about corruption—and electoral accountability.

Finally, electoral rules can also create mechanisms and incentives to increase political

accountability. In a follow-up paper, Ferraz & Finan (2011) compare corruption practices

for mayors audited at the same time but who differ in whether they are serving in a first

term (eligible for re-election) or a second term (ineligible for re-election). Using the share

of total federal resources transferred to municipalities associated with fraud in the public

procurement of goods and services, diversion of funds, and overinvoicing of goods and

services as a measure of corruption, they find that the share of stolen resources is, on aver-

age, 27% lower among mayors with re-election incentives than among mayors without

re-election incentives. Although this result suggests that a two-term period is more effec-

tive than a one-term period as an anticorruption policy, it does not mean that politicians

should be re-elected indefinitely. The absence of term limits by opening up the possibility

of long-term entrenchment may encourage politicians to develop long-term relationships

or policies that benefit them and their families. Term limits could also produce benefits

if, in the absence of the pressure of being re-elected, politicians have better incentives to

implement socially optimal policies with a long-term horizon.

Selection. Although the simple framework above suggests that the selection of who

chooses to become a bureaucrat is potentially important, there is relatively little evidence

on this point. Ferraz & Finan (2010) find that higher salaries attract better political can-

didates in Brazil, although the effects are relatively modest—a 20% increase in wages

leads only to a 0.2 increase in the average years of schooling and a 0.05 increase in the

9Bjorkman & Svensson (2010) examine a community monitoring intervention in Uganda, in which local NGOs

encouraged communities to be more involved in the state of health service provision. The intervention included

meetings to discuss baseline information on the status of health service delivery relative to other providers and the

government standard and encouraged community members to develop a plan identifying key problems and steps

the providers should take to improve health service provision. The intervention increased the quality and quantity

of primary health care provision; however, the design of the intervention suggests that the mechanisms could have

included better information flows and monitoring.


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number of terms of experience. Higher wages also improve the performance of a politi-

cian while in office. A 20% increase in wages leads to a 25% increase in the number of

bills submitted, however. The authors do not, however, examine impacts on corruption

per se. Evidence on the selection of politicians and the impact on corruption forms an

important area for future work.

Selection based on the propensity to be corrupt may lead to multiple equilibria in cor-

ruption. In particular, in a corrupt equilibrium, the people who have the highest propensity

to take advantage of corruption will disproportionately choose to become civil servants,

which could make fighting corruption in the future more difficult—i.e., the same policies

that effectively control corruption in a low-corruption country might not be enough to elimi-

nate corruption in a high-corruption country, and in fact the same set of incentives might be

consistent with both high- and low-corruption equilibria. Testing whether there are multiple

equilibria in corruption—for reasons of selection or for other reasons—is an important area

for future work.

Incentives. The framework outlined above is implicitly a model in which the only way

the principal can observe what the bureaucrat is doing is through monitoring. For many

government activities, however, there are direct indicators of agent behavior. This opens

the possibility of tying incentives more closely to performance either through direct finan-

cial awards or more complex incentive schemes through promotions, assignments, and

the like. However, performance indicators can be imperfect measures of the civil servants’

corrupt behavior: We want citations issued only for those drivers who actually break the

law, and not issued for those who do not; we want taxes collected when they are due, but

we do not want overzealous tax collectors collecting from those who do not owe. Hence,

in designing such incentive schemes, it is critical to deal with the so-called multitasking

problem (Holmstrom & Milgrom 1991) and ensure that the true goals of the principal are

achieved, not just the ones that are incentivized.

Evidence that directly links performance pay or other incentive schemes with corrup-

tion outcomes is largely lacking. Much of what we know comes from studies in the health

and education sector, in which incentives are conditioned either on worker absenteeism or

directly on health or education outcomes. The evidence on the effectiveness of incentive

schemes that condition on worker absenteeism is mixed—in situations in which mechanisms

to monitor performance are relatively tamper-free, performance-based pay can reduce absen-

teeism and, in the case of school teachers, improve test scores (Duflo et al. 2012). However,

if service providers can collude with their monitors and/or tamper with monitoring tools,

then such mechanisms may be undone in the medium run (Banerjee et al. 2008).

Similarly, evidence on the effect of performance pay for teachers is mixed. Muralidharan&

Sundararaman (2011) conduct a randomized evaluation of a teacher incentive program in

government-run rural primary schools in India. Teachers in treatment schools were eligible

to receive a bonus payment based on the improvement of the students’ average test scores.

Some schools were assigned to a group incentive treatment, in which teachers were paid a

group bonus based on improvements in the school-level average test score, whereas other

schools were assigned to an individual incentive treatment in which the teacher was paid an

individual bonus based on improvement in the average test scores of his students. They find

significant improvements in student test scores. However, although group and individual

incentive schools performed equally well in the first year of the program, average test

scores were 0.10 standard deviations higher in schools where teachers were given individual

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incentives relative to schools with group incentives by the end of second year of program.

In contrast, Glewwe et al. (2010) show that performance pay for teachers in Kenya led to

an improvement in outcomes only along the measures used to compute the formula that

determines pay.

Outside education and health, there is little evidence on how incentives change the

performance of bureaucrats. Kahn et al. (2001) use tax reform instituted by the Brazilian

government in 1989 to study the effect of performance-based wages for tax collectors, in

an economy with widespread tax evasions. The reform offered a bonus to tax officials based

on group and individual performance in finding and collecting taxes from tax evaders. They

find that the growth rate of fine collection exhibits a break in 1989 and estimate that fine

collections per inspection are 75% higher on average than what they would have been in

the absence of the program, with substantial heterogeneity across regions. The authors do

their best to provide evidence that the surge in tax collections post-1989 resulted from the

performance incentives provided by the tax reform, but because they do not have a control

group, the evidence is suggestive but not conclusive.

Taken together, the tentative conclusion of this evidence is that there is room for

incentives to succeed, but caution must be taken to design the incentives well and prevent

them from being undermined. It is striking that few studies directly examine the impact of

improved incentives on corruption outcomes.

3.1.2. The market for bribes: changing the structure of the bureaucracy to harness the forces

of competition. The previous section focuses on how a principal—i.e., the government—

can best monitor its agents—civil servants. In other settings, however, strategic interactions

between corrupt agents themselves become important, and depending on how the market is

structured, these kinds of strategic interactions can either raise or lower the bribe amounts.

If a person needs to bribe multiple corrupt officials to perform a given task, Shleifer &

Vishny (1993) argue that the “double-marginalization” problem can arise. Specifically,

if each agent does not fully internalize the effect of his bribes on other agents’ bribe

revenues, the total amount of bribes one would need to pay could be higher than if agents

had acted independently.

Olken & Barron (2009) use data on the bribes truck drivers pay to empirically test

the idea that market forces partially determine the level of corruption and specifically to

test for this type of double-marginalization. They exploit the fact that, during the period

studied, the number of checkpoints along one of the roads was reduced in accordance with

a peace agreement signed earlier in the year. They use this change in market structure to

estimate the elasticity of the average bribe paid with respect to the expected number of

checkpoints. They show that the average price paid at checkpoints increases when the

number of checkpoints declines, consistent with the double-marginalization idea. These

findings highlight the need to consider strategic interactions between corrupt agents them-

selves, in addition to interactions between principals and agents, in designing effective

anticorruption policy.

An implication of this view is that a policy reform that moves from having a large number

of independent agents to a single agent may reduce corruption and increase economic effi-

ciency. Bruhn (2008) uses the sequential implementation of a reform that simplified business

entry regulations across municipalities in Mexico to estimate the economic effects of such

reforms more convincingly than in cross-country data. Although the paper does not look at

the effects of the reform on corruption directly, the results show that simplified regulation


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improved efficiency. She finds that the reform increased the number of registered businesses

by 5%, which was accounted for by former wage earners opening businesses. Wage employ-

ment also increased by 2.2% as a result of the reform, whereas competition from new

entrants decreased the income of incumbent businesses by 3%. It is, however, not possible to

distinguish between less potential for corruption and increased convenience as the mecha-

nism underlying efficiency gains.

The flip side of strategic interactions between bureaucrats is that if bureaucrats are

competing against one another, this could reduce the bribes paid and lead to lower bribes

and more output. In a recent study, Burgess et al. (2011) explore this issue in the context

of deforestation in Indonesia. In particular, they explore a setting in which local district

forestry officials can allow logging beyond the legal logging quota in exchange for bribes.

The study shows that as the number of political jurisdictions increases, so that there are

more bureaucracies with the potential to facilitate illegal logging in a province, logging

rates increase and prices for wood fall, consistent with a model of Cournot competition

between bureaucrats.

Despite the potential for competition between bureaucrats to reduce bribes, other than

Burgess et al.’s (2011) study we know of no other evidence that examines how competition

between bureaucrats works in practice. In Burgess et al.’s study, competition occurs only

through the product market: Each district chooses how much wood to extract, and market

forces—a common demand curve—determine how much they receive in rents. In many

other settings, however, individual agents would be able to choose which bureaucrat to

work with to obtain a service, and the bureaucrats might compete on price. This type of

Bertrand competition could result in even larger impacts of competition than the type

of Cournot-style competition studied by Burgess et al. (2011). We regard further studies

examining competition between agents as a first-order question for future work.

It is important to note that competition leading to lower bribes is not necessarily

socially optimal. In particular, it depends on what the government is trying to accomplish

and whether the bribes are on top of, or instead of, official government fees. For example,

in the case of deforestation studied by Burgess et al. (2011), bribes were to allow more

logging than the government had deemed optimal (for example, for reasons of watershed

protection or biodiversity protection). Competition meant lower bribes and greater quan-

tities, which in this context meant more illegal logging, and hence greater social losses,

than had there been less competition. Conversely, in the case of the road checkpoints

studied by Olken & Barron (2009), traveling the road should have been free, so lower

bribes would have meant greater road travel and greater efficiency. Understanding the

welfare implications of these types of strategic interactions depends therefore on whether

higher or lower bribes would increase or decrease social efficiency, and we do not yet

know of an empirical example demonstrating how competition between bureaucrats could

lead to greater social efficiency.

3.2. Transparency

One of the key themes of the international anticorruption movement is the role of

transparency—so much so that the largest worldwide anticorruption nongovernmental

organization (NGO) is called Transparency International. But does transparency matter?

The basic idea about transparency is that by enabling information about govern-

ment actions, citizens can better monitor government officials and enforce greater electoral

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accountability. However, the effect of making information about politicians publicly avail-

able is a priori unclear. Although disclosure of information can increase political account-

ability, it can also undermine politicians’ privacy and thus potentially worsen the pool

of entrants.

Several pieces of evidence suggest a relationship between access to information about

politicians’ performance and both the political accountability and the quality of govern-

ment. In a cross-sectional, cross-country study, Djankov et al. (2010) study the relation-

ship between disclosure rules for information about parliament members and a number

of measures of government quality and corruption. Their main conclusion is that public

disclosure, but not internal disclosure to parliament, is associated with lower perceived cor-

ruption and better government. They further find that information about politicians’

assets, liabilities, income sources, and potential conflicts, as opposed to simply income

and wealth levels, is more consistently associated with better government. Because the

study is cross-sectional in nature, they cannot rule out reverse causality (i.e., higher-quality

governments adopt better transparency laws).

In a more micro example, Banerjee et al. (2012) study how public disclosures about

politicians’ performance and qualifications can influence electoral accountability in set-

tings characterized by weak institutions and a less educated population by conducting a

randomized experiment in Delhi, India. Using the Indian Right to Information Act and

candidates’ affidavits, they created report cards for 10 assembly jurisdictions during the

run-up to the 2008 election in Delhi. They then randomly provided slum dwellers with

pamphlets and free newspapers containing information on candidate qualifications and

legislator performance. The information increased voter turnout by 3.5 percentage points

and reduced the incidence of vote buying by 19 percentage points. The information cam-

paign seems to increase the quality of government: The vote share of the best-performing

incumbent increased by 7 percentage points in the treatment group relative to the controls.

A related example, discussed in the monitoring section (Section 2.1.6), is Ferraz &

Finan’s (2008) study in Brazil on how public dissemination of corruption scandals in local

governments had a negative effect on incumbents’ electoral performance. Importantly,

they find more pronounced impacts in areas where local radio stations were present to

broadcast the results of the audit reports. The probability of re-election for an incumbent

who committed two corruption violations in municipalities with pre-election audits was

7 percentage points lower than one who had zero violations and 11 percentage points lower

if radio stations were present in the municipality. One interpretation for the larger effect in

municipalities where local radios were present to divulge the information is that radios

provide an efficient way of transmitting information about local politics.

A second way that transparency may matter—and the way that many suggest it does—

is by providing citizens with information on what they are entitled to. Reinikka &

Svensson (2005) study how an information campaign to monitor local officials can reduce

corruption and increase educational outputs. They exploit a newspaper campaign in

Uganda aimed at reducing the capture of public funds by providing students’ parents with

information to monitor local officials’ use of an educational grant. Their empirical strategy

uses distance to the nearest newspaper outlet as an instrument of school exposure to

information and finds that an increase in information resulted in an increase in spending

reaching the schools and ultimately an increase in school enrollment and student learning.

An important caveat is that the distance to newspaper outlets may be nonrandomly

assigned, and it may also have other, direct impacts on educational performance.


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A third way in which transparency could matter is by allowing citizens to signal interest

in a particular outcome. Peisakhin & Pinto (2010) examine this by conducting a random-

ized experiment to test whether freedom-of-information laws can improve access to basic

public goods that are otherwise attainable only through bribery. The experiment randomly

assigned individual applicants in India to one of three mechanisms used when requesting

public benefits and then tested the effect of these mechanisms on the time that elapsed

before the applicant received the benefit. In the first treatment group, applicants submitted

an information request under the Right to Information Act shortly after their applications.

The second group of applicants presented a letter of support from a local NGO with

their application. Finally, the third group of applicants paid a bribe to a local to obtain

the benefits. According to the results, 94% of those who paid bribes or sent an information

request received benefits over the course of one year, as opposed to 21% in the NGO and

control groups. Individuals in the group that paid bribes received benefits in a median of

82 days, 38 days less than those in the groups that filed an information request. The groups

that neither paid a bribe nor requested information obtained benefits only after 343 days.

The results suggest that requesting information under the freedom-of-information law is

a reasonable, although imperfect, substitute for bribing an official. In a follow-up study,

Peisakhin (2012) estimates the effect of the freedom-of-information law in the process of

voter registration and here finds that the information law is an effective, free, and legal

substitute to bribery for middle-class applicants.

3.3. Technology and Communications

Technological innovations can help make tools available that are hard for humans to

tamper with and that enhance communication. For many (although not all) corrupt activi-

ties, the corrupt agent needs to somehow evade the rules or procedures that the official

government bureaucracy has set up. Technology can help address this problem by ensuring

mechanically that certain procedures are followed (Duflo et al. 2012).

Technology can also have a substantial impact on corruption by facilitating communi-

cation, which can enable better monitoring. Yang (2008) explores how hiring foreign

inspectors to verify the tariff classification and the value of shipments before they leave

their origin country impacts import duty collections. The key mechanism to reduce cus-

toms fraud is the transmission of information from the foreign firm at the origin port to the

client government. The flow of information could not only improve the monitoring ability,

but also reduce the bargaining power of corrupt customs officials, which can reduce bribe

payments and custom clearance time. The results from the study provide evidence in favor of

this hypothesis, showing that preshipment import inspection programs increased import

duty collection by 15–30 percentage points in the first five years after implementation.

Relatedly, in many countries technology has played an important role in the design and

administration of the tax system. One key idea of tax enforcement is double-reporting, in

which the tax department compares two independent reports about tax performance and

investigates discrepancies. In the developed world, Kleven et al. (2010) analyze a random-

ized tax-enforcement experiment in Denmark and find that the tax evasion rate is very

small (0.3%) for income subject to double-reporting and much higher (37%) for self-

reported income. Relatedly, in Chile, Pomeranz (2010) finds that audits have a much larger

impact on the part of the VAT chain where there is not double-reporting, suggesting that

for the rest of the VAT chain, double-reporting played an important role in encouraging

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truth telling. Technology plays a key role here: In a manual system, actually doing the

matching from all the double-reported information would be challenging, but once the

system is automated it is much easier. Given the large number of countries in the process

of modernizing and computerizing their tax infrastructure, it should be possible to study

the impacts of this type of technology in the context of poorer countries where tax evasion

is usually higher.

A final area in which technology holds promise is in procurement. Throughout the world,

including in the developing world, governments have been moving to online procurement

systems. These systems can potentially reduce corruption by increasing access to information

(undermining bidding rings) and by making the procurement system more transparent.

Lewis-Faupel et al. (2011) examine the impact of electronic procurement for road projects

in India, taking advantage of a staggered rollout across Indian states. They find that

electronic procurement leads to higher-quality roads, as measured by independent central

government audits, although not to lower costs. The evidence suggests that the quality

improvement comes from higher-quality contractors being more likely to win contracts.

4. SOME CAVEATS: ADAPTATION IN THE SHORTANDMEDIUMRUN

Much of the evidence discussed above shows the short-run effects of anticorruption policies

and programs. But there is ample evidence to believe that the long-run impacts could be quite

different. For example, it could take corrupt officials time to learn how to manipulate a new

system, so the long-run effects of an anticorruption policy could be smaller than the short-

run effects. Alternatively, it could take time for a new group of civil servants to select into

the system, so an anticorruption policy could be more effective over time if it encourages

more low-corruption types to select into the civil service. Or officials might simply substitute

from one form of corruption to another.

In the short run, there are several examples of substitution from one type of corruption

to another. In Olken’s (2007) study, an increase in auditing of road expenditures led to

decreased missing expenditures from the project, but to more family members of project

officials being hired to build the roads. In Niehaus & Sukhtankar’s (2010) study, con-

versely, an increase in the wages of daily wage jobs (and hence in the ability to steal from

those workers) led to a reduction in theft of piece-rate jobs. Burgess et al. (2011) find that

when a district’s oil and gas revenues increase, providing an alternate source of rent extrac-

tion for local district officials, illegal logging falls. In all these cases, it appears that corrupt

officials have different avenues of corruption available to them and substitute among them

as the returns to one form of corruption get easier or harder. If an anticorruption policy

clamps down differentially on certain types of corruption (as almost all do), one needs to

take care that corrupt officials do not substitute to other forms of corruption with more

severe efficiency costs.

There are also several examples that suggest that the long-run effect of anticorruption

policies may be smaller than the short-run effect as officials adapt. One of the examples

mentioned above is Banerjee et al. (2008). In this study, an incentive program on nurse

attendance in India was found effective only during the first six months of the intervention,

when the program was correctly in place. Later, however, the system was undermined by

the local health administration, who took advantage of a loophole in the program design

and began allowing many more unexcused absences. By 18 months after the program had

started, the program was no longer able to improve nurse attendance.


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In the case of Brazil, Ramalho (2007) uses the 1992 impeachment of President Fernando

Collor to evaluate the impact and persistence of corruption on the market value of politically

connected companies. The results suggest that the market perceived the decrease in the

president’s probability of staying in power as affecting the value of politically connected com-

panies, but only temporarily. According to the results, family-connected companies had on

average daily abnormal returns that were 2–9 percentage points lower during bad event days,

with the effect reversing completely within one year. One interpretation is that over the course

of the year, these previously politically connected firms were able to form new connections.

In Colombia, Camacho & Conover (2009) study the manipulation of the poverty index

score as an eligibility requirement to gain access to social programs. In particular, people

were eligible for the program if their poverty index was below a given threshold. In the

first year of the program, there was no discontinuity in poverty index scores at the

threshold, but over the subsequent years, as the formula became better known, more and

more manipulation began to take place, resulting in a larger number of people with scores

just below the eligibility threshold. The results suggest that in total 3 million people had

their score changed, which accounts for approximately 40% of the beneficiaries.

A final example comes from Burgess et al. (2011). As noted above, when a district’s

oil and gas revenues increase, providing an alternate source of rent extraction for local

district officials, illegal logging falls. However, within three years, the effect reverses and

illegal logging returns to almost its previous level. Burgess et al. provide suggestive evi-

dence that the mechanism is a change in the political equilibrium—the higher oil and gas

rents change the nature of the governing coalition toward a type of coalition associated

with higher rent extraction. This new political coalition presumably extracts rents not just

from oil and gas, but also from the forest sector.

5. CONCLUDING THOUGHTS

Recent years have seen a dramatic rise in microempirical research on corruption in devel-

oping countries. A string of papers has shown how basic economic concepts can be applied

to corruption. Corrupt officials respond to incentives and the threat of punishment, even

in corrupt environments. Strategic interactions between corrupt officials affect the level of

corruption—bidding down bribes if they compete against one another, and increasing bribes

if multiple bribes are required and officials cannot coordinate with one another. Recent work

has also shown that corrupt officials are resilient: Over time, they adapt to changes in their

environments, in some cases offsetting anticorruption policies with new avenues for seeking

out rents.

Although these examples highlight cases in which adaptation took place over time, it is

also possible that in some situations the long-term impacts of anticorruption policies

exceed the short-run effects. One area where this is likely is the case of transparency reforms:

A higher likelihood of information disclosures may both incentivize politicians to perform

better and improve the incentives for high-talent individuals to enter politics.

It is also important to note that there is relatively little research on many of the main

anticorruption policy initiatives we observe in the world today. When aiming to fight

corruption domestically, many countries set up high-profile, independent anticorruption

agencies with prosecutorial powers. From the international perspective, there have been

major efforts at promoting transparency (such as the Extractive Industries Transparency

Initiative), and at limiting the ability of foreign companies to pay bribes (such as the OECD

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Anti-Bribery Convention and the US Foreign Corrupt Practices Act). Despite the recent

advances in research on corruption, we know relatively little about whether these types of

domestic and international policy initiatives are successful, and how potentially corrupt

agents respond to these types of policies.

Taken together, the existing and ongoing research on corruption in developing countries

suggests a large and promising research agenda. Researchers have identified several inno-

vative ways of measuring corruption, and economic theory offers us significant guidance

on how to design anticorruption policies. At the same time, the ability of individuals to

outguess those who seek to regulate them suggests an important need to collect data on

both the short- and long-run impacts of many different anticorruption policies in many

different contexts.

DISCLOSURE STATEMENT

The authors are not aware of any affiliations, memberships, funding, or financial holdings

that might be perceived as affecting the objectivity of this review.

ACKNOWLEDGMENTS

This article was originally written as part of the Abdul Latif Jameel Poverty Action Lab’s

Governance Initiative, which is funded by DFID, the Hewlett Foundation, and an anony-

mous donor. We gratefully acknowledge the outstanding assistance of Raluca Dragusanu

and Cristobal Marshall, as well as extensive conversations with Iqbal Dhaliwal. The views

expressed here are those of the authors and do not necessarily reflect the views of DFID,

the Hewlett Foundation, or any other third party.

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v

Annual Review of

Economics

Volume 4, 2012Contents

Paul Samuelson’s LegacyAvinash Dixit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Saving Money or Just Saving Lives? Improving the Productivity of US Health Care SpendingKatherine Baicker, Amitabh Chandra, and Jonathan S. Skinner . . . . . . . . 33

International Comparisons in Health Economics: Evidence from Aging StudiesJames Banks and James P. Smith . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

Rare Macroeconomic DisastersRobert J. Barro and José F. Ursúa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83

Endogenous Extreme Events and the Dual Role of PricesJon Danielsson, Hyun Song Shin, and Jean-Pierre Zigrand . . . . . . . . . . 111

The Distribution of Teacher Quality and Implications for PolicyEric A. Hanushek and Steven G. Rivkin . . . . . . . . . . . . . . . . . . . . . . . . 131

Economic Modeling and Analysis of Educational VouchersDennis Epple and Richard Romano . . . . . . . . . . . . . . . . . . . . . . . . . . . 159

Heterogeneity in Human Capital Investments: High School Curriculum, College Major, and CareersJoseph G. Altonji, Erica Blom, and Costas Meghir . . . . . . . . . . . . . . . . 185

Credit Constraints in EducationLance Lochner and Alexander Monge-Naranjo . . . . . . . . . . . . . . . . . . . 225

New Perspectives on Statistical Decisions Under AmbiguityJörg Stoye . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 257

The Empirics of Firm Heterogeneity and International Trade Andrew B. Bernard, J. Bradford Jensen, Stephen J. Redding, and Peter K. Schott . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 283

Natural Resource Wealth: The Challenge of Managing a WindfallFrederick van der Ploeg and Anthony J. Venables . . . . . . . . . . . . . . . . . 315

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The Economics and Politics of Women’s RightsMatthias Doepke, Michèle Tertilt, and Alessandra Voena . . . . . . . . . . . 339

Recent Developments in the Economics of Time UseMark Aguiar, Erik Hurst, and Loukas Karabarbounis . . . . . . . . . . . . . . 373

Life-Cycle Wage Growth and Heterogeneous Human CapitalCarl Sanders and Christopher Taber . . . . . . . . . . . . . . . . . . . . . . . . . . . 399

Behavioral Economics and Psychology of IncentivesEmir Kamenica . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 427

The Relationship Between Economic Preferences and Psychological Personality Measures Anke Becker, Thomas Deckers, Thomas Dohmen, Armin Falk, and Fabian Kosse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 453

Corruption in Developing CountriesBenjamin A. Olken and Rohini Pande . . . . . . . . . . . . . . . . . . . . . . . . . . 479

A Reduced-Form Approach to Behavioral Public FinanceSendhil Mullainathan, Joshua Schwartzstein, and William J. Congdon . . . . . 511

Recent Research on the Economics of PatentsBronwyn H. Hall and Dietmar Harhoff . . . . . . . . . . . . . . . . . . . . . . . . 541

Probability and Risk: Foundations and Economic Implications of Probability-Dependent Risk PreferencesHelga Fehr-Duda and Thomas Epper . . . . . . . . . . . . . . . . . . . . . . . . . . 567

The Theory of Clubs and Competitive CoalitionsMyrna Wooders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 595

The Promises and Pitfalls of Genoeconomics Daniel J. Benjamin, David Cesarini, Christopher F. Chabris, Edward L. Glaeser, David I. Laibson, Vilmundur Guðnason, Tamara B. Harris, Lenore J. Launer, Shaun Purcell, Albert Vernon Smith, Magnus Johannesson, Patrik K.E. Magnusson, Jonathan P. Beauchamp, Nicholas A. Christakis, Craig S. Atwood, Benjamin Hebert, Jeremy Freese, Robert M. Hauser, Taissa S. Hauser, Alexander Grankvist, Christina M. Hultman, and Paul Lichtenstein . . . . . . . . . . . . . . . . . . . . 627

Indexes

Cumulative Index of Contributing Authors, Volumes 1–4 . . . . . . . . . . . . . 663Cumulative Index of Chapter Titles, Volumes 1–4 . . . . . . . . . . . . . . . . . . . 665

Errata

An online log of corrections to Annual Review of Economicsarticles may be found at http://econ.annualreviews.org

vi Contents

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Journal of Economic Perspectives-Volume 19, Number 3-Summer 2005-Pages 19-42

Eight Questions about Corruption

Jakob Svensson

Some years ago I interviewed the chief executive officer of a successful Thai

manufacturing firm as part of a pilot survey project. While trying to figure out a good way to quantify the firm's experience with government regula-

tions and corruption in the foreign trade sector, the CEO exclaimed: "I hope to be reborn as a custom official." When a well-paid CEO wishes for ajob with low official

pay in the government sector, corruption is almost surely a problem! The most devastating forms of corruption include the diversion and outright

theft of funds for public programs and the damage caused by firms and individuals that pay bribes to avoid health and safety regulations intended to benefit the public. Examples abound. A conservative estimate is that the former President of Zaire, Mobutu Sese Seko, looted the treasury of some $5 billion-an amount equal to the

country's entire external debt at the time he was ousted in 1997. The funds

allegedly embezzled by the former presidents of Indonesia and Philippines, Mo- hamed Suharto and Ferdinand Marcos, are estimated to be two and seven times

higher (Transparency International, 2004). In the Goldenberg scam in Kenya in the early 1990s, the Goldenberg firm received as much as $1 billion from the

government as part of an export compensation scheme for fictitious exports of commodities of which Kenya either produced little (gold) or nothing at all (dia- monds) ("Public Inquiry into Kenya Gold Scam," 2003). An internal IMF report found that nearly $1 billion of oil revenues, or $77 per capita, vanished from

Angolan state coffers in 2001 alone (Pearce, 2002). This amount was about three times the value of the humanitarian aid received by Angola in 2001-in a country where three-quarters of the population survives on less than $1 a day and where one

* Jakob Svensson is Assistant Professor, Institute for International Economic Studies, Stock- holm University, Stockholm, Sweden. He is also Senior Economist, Development Research

Group, World Bank, Washington, D.C.; and Research Fellow, Center for Economic Policy Research, London, United Kingdom. His e-mail address is ('[email protected]).



20 Journal of Economic Perspectives

in three children dies before the age of five. In Turkey, the effect of the earthquake that took thousands of lives in 2004 would have been much less severe, according to the government of Turkey, if contractors had not been able to pay bribes to build homes with substandard materials (Kinzer, 1999). Extrapolating from firm and household survey data, the World Bank Institute estimates that total bribes in a year are about $1 trillion (Rose-Ackerman, 2004). While the margin of error in this estimate is large, anything even in that general magnitude ($1 trillion is about 3 percent of world GDP) would qualify as an enormous issue.

This paper will discuss eight frequently asked questions about public corruption: 1) What is corruption? 2) Which countries are the most corrupt? 3) What are the common characteristics of countries with high corruption? 4) What is the

magnitude of corruption? 5) Do higher wages for bureaucrats reduce corruption? 6) Can competition reduce corruption? 7) Why have there been so few (recent) successful attempts to fight corruption? 8) Does corruption adversely affect growth? These questions are not meant to be exhaustive, and readers interested in additional discussion might begin by turning to the reviews by Bardhan (1997) and Rose-Ackerman (1999).

What is Corruption?

A common definition of public corruption is the misuse of public office for

private gain. Misuse, of course, typically involves applying a legal standard. Corrup- tion defined this way would capture, for example, the sale of government property by government officials, kickbacks in public procurement, bribery and embezzle- ment of government funds.

Corruption is an outcome-a reflection of a country's legal, economic, cul- tural and political institutions. Corruption can be a response to either beneficial or harmful rules. For example, corruption appears in response to benevolent rules when individuals pay bribes to avoid penalties for harmful conduct or when

monitoring of rules is incomplete-as in the case of theft. Conversely, corruption can also arise because bad policies or inefficient institutions are put in place to collect bribes from individuals seeking to get around them (Djankov, LaPorta,

Lopez-de-Silanes and Shleifer, 2003). A number of parallels have been proposed for thinking about corruption.

Although each of these parallels can be illuminating in certain ways, none of them

capture the phenomena perfectly. As one parallel, corruption is often thought of as like a tax or a fee. Bribes, like

taxes, create a wedge between the actual and privately appropriated marginal product of capital. However, along with the obvious point that bribes bring no

money to government coffers, bribes differ from taxes in other ways. Bribes involve higher transaction costs than taxes, because of the uncertainty and secrecy that

necessarily accompany bribe payments (Shleifer and Vishny, 1993). Corrupt contracts are not enforceable in courts. An official may renege on an agreement with



Jakob Svensson 21

the bribe-payer or demand another bribe for the same service (Boycko, Shleifer and Vishny, 1995).

Bribing also has parallels to lobbying in the form of campaign contributions or influence buying through other means, but again, they are not perfect substitutes

(Harstad and Svensson, 2004). Consider a situation in which a country has enacted tariffs or licence requirements for imports that affect all firms in a sector. A firm can avoid paying the tariff or buying a licence by bribing a custom official. Alternatively, firms in the sector may collectively lobby the government to provide the license for free or to remove the tariff. One difference between bribery and lobbying in this case is that a change in the trade regime through lobbying affects all firms in the

sector, as well as future entrants. However, the return to bribing is typically firm

specific, although potential externalities may arise both for other firms and consumers. A second difference is that a change in the trade regime through lobbying tends to be more permanent, because there is some cost to re-enacting the original law, while a bureaucrat cannot credibly commit not to ask for bribes in the future. A third difference is that decisions about government rule making involve officials

weighing the benefits of income from lobbying against the cost to the government of a rule change, while decisions about bribes are made by individual public officials who consider their private costs and benefits. Finally, unlike bribing, where firms weight the private benefit and cost of the action, lobbying involves joint actions with associated collective action problems. The question why firms choose to lobby or bribe, and the consequences of this choice, is analyzed in Harstad and Svensson (2004).

Corruption, or more precisely bribes, is not the same as rent-seeking, although the terms are often interchanged. Rent seeking is the socially costly pursuit of rents, often created by governmental interventions in the economy (Tollison, 1997), while bribes are technically a transfer.

No definition of corruption is completely clear-cut. The emphasis in this paper is on public corruption, but corruption can also take the form of collusion between firms or misuse of corporate assets that imposes costs on consumers and investors. Some activities will hover on a legal borderline: for example, legal payments that involve lobbying, campaign contributions or gifts can seem quite close to illegal payments that constitute bribery, or legal offers of postretirement jobs in private sector firms to officials and politicians assigned to regulate these same firms can seem quite close to illegal kickbacks.

Which Countries are the Most Corrupt?

Measuring corruption across countries is a difficult task, both due to the secretive nature of corruption and the variety of forms it takes. However, since

corruption reflects an underlying institutional framework, different forms of cor-

ruption are likely to be correlated. The past decade has seen an exponential growth in cross-country studies on

corruption. Three types of corruption measures have been exploited in the




literature. The first type, used initially by Knack and Keefer (1995) and Mauro

(1995), is based on indicators of corruption assembled by private risk-assessment firms. Of these, the corruption indicator published in the International Country Risk Guide has become the most popular, due to better coverage across time and countries. According to its creators, the International Country Risk Guide's cor-

ruption indicator captures the likelihood that high government officials will demand special payments and the extent to which illegal payments are expected throughout government tiers.'

The second set of variables is averages of ratings reported by a number of

perception-based sources. Among policymakers, the Corruption Perception Index

produced by Transparency International is the most widely disseminated. The source of this index varies from year to year, but the data released in October 2004 is based on 18 rankings from 12 institutions.2 According to Transparency Interna- tional, the essential conditions for inclusion are that a source must provide an ordinal measurement, or ranking, of nations and that the data must measure the overall extent of corruption and not the expected impact. For this reason, the

corruption indicator published in the International Country Risk Guide is not included because, according to Transparency International, it does not determine a country's level of corruption, but the political risk involved in corruption. These two issues can differ considerably, depending on, for example, whether public tolerance toward corruption is high or low.

Kaufmann, Kraay and Mastruzzi (2003) derive a complementary measure, Control of Corruption, drawn from a large set of data sources. They have a broader definition of corruption and include most cross-country indices reporting ranking of countries on some aspect of corruption. They also use a different strategy than

Transparency International to aggregate the corruption indicators. In the end, definitions and aggregation choice seem to matter only marginally.3 The simple correlation between Control of Corruption (from 2002) and the Corruption Per-

ceptions Index (from 2003) is 0.97 and the correlation between Control of Cor-

ruption or the Corruption Perceptions and the corruption scores from the Inter- national Country Risk Guide (from 2001) is 0.75. The main difference between the three indicators is which countries and years are covered.4

1 The data are produced by Political Risk Services-a private firm providing risk assessments across countries, (http://www.prsgroup.com/countrydata/countrydata.html). According to Political Risk Ser- vices, over 80 percent of the world's largest global companies (as ranked by Fortune magazine) use its data and information to make business and investment decisions. The current data are costly, although older versions are available on the web.

2 The Corruption Perception Index is produced by the University of Passau in Germany and by Transparency International. Data for 2004 and previous years back to 1996 are available for free at (http://www.transparency.org/surveys/index.html#cpi). SThe Control of Corruption Index is available from the World Bank at (http://info.worldbank.org/

governance/kkz2002/tables.asp). 4 The aggregation procedures used by both Kaufmann, Kraay and Mastruzzi (2003) and Transparency International presume that the measurement errors associated with each subindicator are independent across sources. This assumption allows them also to report measures of the precision or reliability of the estimates. In reality, the measurement errors are likely to be highly correlated, because the producers



Eight Questions about Corruption 23

The subjective corruption measures discussed above are ordinal indices, al-

though researchers have typically treated them as cardinal measures. At a mini-

mum, this limitation should be kept in mind when interpreting changes in the indices across time and countries. At least two cross-country data sets on corruption provide cardinal measures of corruption, although few papers in the economic literature on corruption have utilized them. Both of them are based on survey data. The EBRD-World Bank Business Environment and Enterprise Performance Survey compiles the experiences of more than 10,000 firm managers in 1999 and 2002. Firm managers were asked to estimate the share of annual sales "firms like yours" typically pay in unofficial payments to public officials.5 Unfortunately, these data are only available for 26 transition countries.

The International Crime Victim Surveys (ICVS), since 2003 under the responsibility of the United Nations Office on Drugs and Crime, focus on individuals rather than firms. The surveys are designed to produce comparable data on crime and victimization across countries, using a combination of computer-assisted tele-

phone interviewing techniques in developed countries and face-to-face surveys in

developing countries. In most developing countries, the survey data refer to the

experience of urban households, since the surveys are only implemented in the

capital (or largest) cities. With respect to corruption, respondents were asked if

government officials asked, or expected the respondent, to pay bribes for their service during the last year. These data can be used to derive the incidence of bribes across countries. To date, over 140 surveys in four waves (1989, 1992, 1996/1997, 2000/2001) have been done in over 70 different countries, although the latest round includes fewer than 50 countries.6 Incidence of bribes is highly correlated with the subjective measures (simple correlation lies between 0.57 and 0.67), but the best predictor of the share of households that need to pay bribes is actually GDP

per capita.7 One obvious advantage with the EBRD-World Bank Business Environment and

Enterprise Performance Survey and the International Crime Victim Surveys is that

they provide hard evidence on corruption. However, collecting reliable data on

corruption through traditional survey techniques is problematic. Respondents may choose to misreport or not report at all for many reasons. To the extent that these measurement error problems are not systematically related to country characteristics, however, this may be less of a concern when studying variations in corruption across countries.

A disadvantage is that the hard evidence is only available for a smaller sample

of the different indices read the same reports and most likely gauge each other's evaluations. If the independence assumption is relaxed, the gain from aggregating a number of different reports is less clear. Moreover, the estimates would be less precisely estimated than the stated estimates suggest. 5 The data are available for free at (http://www.ebrd.com/pubs/econ/beeps/main.htm). 6 The data are available for free at (http://www.unicri.it/icvs/data/index.htm). 7 In regressions using the incidence of bribes as the dependent variable and GDP per capita (in logarithms) and the subjective corruption indices (each entered one at the time) as the independent variables, the coefficient on GDP per capita is highly significant while the corruption indicators are insignificantly different from zero.




of countries. Moreover, the International Crime Victim Surveys only provide information on the incidence of corruption from a household perspective. The incidence and level of corruption are not necessarily highly correlated and may very well be driven by different factors. Clearly, they can also have differential impacts on economic and social outcomes. The subjective indices, on the other hand, are

mainly constructed for the private sector, and particularly for foreign investors.

Thus, they primarily measure corruption related to doing business-but corruption may take other forms as well.

Table 1 lists the 10 percent of countries that have the worst rankings for

corruption according to the four measures with broad regional coverage: the Control of Corruption index, the Corruption Perceptions Index, the corruption score produced by the International Country Risk Guide and the Incidence of Bribes from the International Crime Victim Surveys. Note that not all countries are ranked and that country coverage differs. For example, the Control of Corruption index includes many more countries. All three measures are rescaled such that a

higher value implies higher corruption.

What are the Common Characteristics of Countries with High Corruption?

Looking at the lists of most corrupt countries in Table 1 offers some hints about what characterizes countries with high corruption. All of the countries with the highest levels of corruption are developing or transition countries. Strikingly, many are governed, or have recently been governed, by socialist governments. With few exceptions, the most corrupt countries have low income levels. Of the countries

assigned an openness score by Sachs and Warner (1995), all of the most corrupt economies are considered closed economies, except Indonesia.s

How do these intuitive connections about the common features of countries with high levels of corruption compare with more systematic research? Theories about the determinants of corruption emphasize the role of economic and structural policies and also the role of institutions. These theories are best viewed as

complementary; after all, the choice of economic and structural policies is one channel through which institutions influence corruption. The literature is summarized in Acemoglu, Johnson and Robinson (2004), La Porta, Lopez-de-Silanes, Shleifer and Vishny (1999) and Djankov, Glaeser, La Porta, Lopez-de-Silanes and Shleifer (2003).

The institutional theories can be decomposed into two broad groups. The first set

8 The Sachs and Warner (1995) measure of openness considered an economy to be "closed" if it met any of five criteria: 1) average tariff rates above 40 percent; 2) nontariff barriers that cover more than 40 percent of all imports; 3) a socialist economic system; 4) a state monopoly of major exports; and 5) the black market premium exceeded 20 percent during the 1970s or the 1980s. Note that by construction, all socialist economies are defined as closed economies. Rodrigues and Rodrik (2000) argue that the Sachs-Warner indicator serves as a proxy for a wide range of policy and institutional differences, not only differences in openness to trade.



Jakob Svensson 25

Table 1 The Most Corrupt Countries

(the bottom 10 percent most corrupt countries from each data set)

Country CC Country CPI Country ICRG Country ICVS

Equatorial 1.9c,',v Bangladesh 8.7v Zimbabwe 5.8v Albania 0.75 Guinea Nigeria 8.6 China 5v Uganda 0.36

Haiti 1.7v Haiti 8.5v Gabon 5cv Mozambique 0.31

Iraq 1.4v Myanmar 8.4v Indonesia 5v Nigeria 0.30

Congo, Dem. 1.4c,v Paraguay 8.4v Iraq 5v Lithuania 0.24

Rep. Angola 8.2v Lebanon 5v

Myanmar 1.4v Azerbaijan 8.2 Myanmar 5v

Afghanistan 1.4c,',v Cameroon 8.2v Niger 5cv Nigeria 1.4 Georgia 8.2' Nigeria 5 Laos 1.3c,i,v Tajikistan 8.2i' Russia 5

Paraguay 1.2v Indonesia 8.2v Sudan 5v

Turkmenistan 1.2c'',v Kenya 8.1v Somalia 5cv Somalia 1.2cv Cote 7.9v Congo, 5cv Korea. North 1.2c,v d'Ivoire Dem. Rep. Zimbabwe 1.2v Kyrgyzstan 7.91'v Serbia and 5v Indonesia 1.2v Libya 7.9v Montenegro Angola 1.1v Papua New 7.9v Haiti 4.8v

Bangladesh 1.1v Guinea Papua New 4.8v Cameroon 1.1v Guinea

Niger 1.1c,v Sudan 1.1v

Azerbaijan 1.1

Tajikistan 1.1i'v Sample size 195 133 140 44

Notes: CC is the Control of Corruption Index for 2002 from Kaufmann, Kraay and Mastruzzi (2003). The index takes values between -2.5 to 2.5, with a higher score indicating higher corruption (rescaled). CPI is the Corruption Perception Index for 2003 from Transparency International. The index takes values between 0 to 10, with a higher score indicating higher corruption (rescaled). ICRG is the International

Country Risk Guide's corruption indicator for 2001 (average over 12 months). The index takes values between 0 to 6, with a higher score indicating higher corruption (rescaled). ICVS is the incidence of bribes in 2000 (share of households responding they need or are expected to pay bribes in 2000) from the International Crime Victim Surveys. c indicates that the country is not included in the Corruption Perception Index ranking. Sindicates that the country is not included in the ICRG ranking. v indicates that the country is not included in the ICVS survey.

of theories argues that institutional quality (and thus corruption) is shaped by economic factors. In short, institutions develop in response to a county's income level and differential needs (Lipset, 1960; Demsetz, 1967). A related view--the human capital theory--argues that growth in human capital and income cause institutional development (Lipset, 1960; Glaeser, La Porta, Lopez-de-Silanes and Shleifer, 2004). For

example, education and human capital is needed for courts and other formal institutions to operate efficiently, and government abuses are more likely to go unnoticed and unchallenged when the electorate is not literate. These theories suggest looking at

per capita income and education as causes of corruption. The second set of institutional theories stress the role of institutions more directly.




These theories often emphasize that institutions are persistent and inherited. Along these lines, Acemoglu, Johnson and Robinson (2001) argue that in former colonies, the institutions were set for the benefit of the colonizer and only when Europeans settled in large numbers did this also result in institutions aimed at benefiting residents of the colony. The disease environment in the colonies, in turn, explains why Euro-

peans settled or not. Thus, according to Acemoglu, Johnson and Robinson, corruption should be more widespread in colonies with an inhospitable environment.

Alternatively, La Porta, Lopez-de-Silanes, Shleifer and Vishny (1998, 1999) stress the identity of the colonizer and specifically the legal system transplanted from the colonizer to the colonies. In their view, French and Socialist legal origin countries (as opposed to former English colonies) regulate more, and regulation leads to corruption.

Yet another way in which historical traditions and colonization might affect the extent of corruption is through the influence of religion (Treisman, 2000). For

example, the institutions of the Protestant church, which arose in part as an opposition to state-sponsored religion, may be more inclined to monitor abuses by state officials. Landes (1998) also argues that the spread of education and learning was, and potentially is, slower in Catholic and Muslim countries. Thus, politicians and public officials

might be challenged less in Catholic and Muslim countries than in Protestant countries.

Economic and political institutions, in the view of the second set of theories, influence the extent of corruption, especially in the ways that they restrict market and political competition. Variables that capture restriction in the marketplace include openness to external competition from imports (Ades and Di Tella, 1999) and the extent of regulation of entry of start-up firms (Djankov, La Porta, Lopez- de-Silanes and Shleifer, 2002). On the political side, a free press provides greater information than a government-controlled press to voters on government and

public sector misbehavior, including corruption (Besley and Burgess, 2001; Bru- netti and Weder, 2001). More generally, the right to re-elect politicians can provide incentives for the incumbent to reduce rent seeking and corruption. The form of

political institutions-parliamentary versus presidential and proportional versus

majoritarian-can also affect the level of corruption as it influences the incentives of politicians and voters' ability to hold politicians accountable for abuse of power (as recently reviewed in this journal by Persson and Tabellini, 2004).

What is the empirical evidence on these various hypotheses? Figure 1 plots the

relationship between corruption, proxied by the indicator with the largest country coverage (Control of Corruption), and GDP per capita (in logarithms), and draws the line implied by the estimated regression of corruption on GDP per capita. The

graph illustrates two facts. First, richer countries have lower corruption. Second, corruption varies greatly across countries, even controlling for income. Some of the countries far away from the regression line-and thus the most and least corrupt for a given level of development-are highlighted in the graph. For example, Argentina, Russia and Venezuela are ranked as relatively corrupt given their level of income. Countries in sub-Saharan Africa are typically aligned close to the




Figure 1

Corruption and Income

4.39 Eq uatoral Guinea Haiti

o Turkmenistan 0 I1rtl ay

S Vzakstan Venenuela

0- eo ~Ru0ia Argeptina 0 Gabon

Hthj c ( OT0

C Eni rea 0o C M idagascar 0 C\ audtania o 0 0 O , - 0 0 0e

0 0 000

0 0 0

0

Bhatan e

00

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New Zalanawel Sisngpore .11 Finund

II

309.81 35144.2

Real GDP per capita 1995

Note: The graph depicts the regression line of corruption (CC 2002) on real GDP per capita (in logarithms) 1995.

regression line, which shows that their perceived corruption is close to the expected level given their per capita GDP.

The strong relationship between income and corruption is consistent with the theories of corruption that argue that institutional quality is shaped by economic factors. However, it is a weak test of these theories, since economic development not only may create a demand for good government and institutional change, but

may also be a function of the quality of institutions. Moreover, the huge variation around the regression line suggests that these theories are at best incomplete.

What can account for this variation? To explore this, I carried out a series of

regressions where the dependent variable is corruption, proxied with the three

subjective measures of corruption described earlier. The explanatory variables in each regression include initial GDP per capita and initial human capital (both measured in 1970) as control variables. I then add a series of country characteris-

tics, one at a time, and test if the coefficient is significantly different from zero. These partial correlations, of course, do not identify causal effects. Even so, the correlations are interesting because they reveal something about common characteristics of corrupt countries, adjusting for initial income and human capital.

What are the results? Table 2 shows that corrupt countries have significantly lower levels of human capital stock, proxied by years of schooling of the total

population aged over 25. This relationship holds independent of what measure of

corruption is used.




Table 2

Corruption and Country Characteristics: Human Capital

Corruption ICRG ICRG IVSC Control of Perception Corruption Corruption Incidence Corruption Index Score Score of Bribes

Dep. variable (2002) (2003) (1982-01) (2001) (2000)

Real GDP per capita (log) -0.60*** -1.38*** -0.87*** -0.73*** -0.03** (.123) (.33) (.20) (.19) (.01)

Years of schooling (log) -0.62*** -1.53*** -0.53** -0.51** -0.06* (.18) (.52) (.27) (.28) (.03)

Sample size 91 79 83 83 26

Notes: Control of Corruption Index for 2002 from Kaufmann, Kraay and Mastruzzi (2003). The index takes values between -2.5 to 2.5, with a higher score indicating higher corruption (rescaled). Corruption Perception Index for 2003 from Transparency International. The index takes values between 0 to 10, with a higher score indicating higher corruption (rescaled). ICRG is the International Country Risk Guide's corruption indicator for 2001 (average over 12 months). The index takes values between 0 to 6, with a higher score indicating higher corruption (rescaled). ICVS is the incidence of bribes in 2000 (share of households

responding they need or are expected to pay bribes in 2000) from the International Crime Victim Surveys. Real GDP per capita in 1970 is from the Penn World Tables. Years of schooling of the total population aged over 25 in 1970 is from Barro and Lee (2000). Robust standard errors in parenthesis. *** statistically significant at 1 percent level. ** statistically significant at 5 percent level. * statistically significant at 10 percent level.

Corrupt countries do have some significantly different policy characteristics. Table 3 shows the regression results from a measure of openness to external competition from imports (imports of goods and services as percent of GDP). Table 4 shows the regression based on the extent of regulation of entry of start-up firms (time it takes to obtain legal status to operate a firm). Table 5 shows

regression results based on freedom of the press (a subjective score from Freedom House). The findings are robust across data sets, although the openness proxy is

insignificant in some regressions. Corrupt countries are less open and regulate both entry to the market and the press more. Replacing freedom of media with a broader measure of political freedom (like the broader Gastil index also produced by Freedom House) yields qualitatively similar results.9

Using the incidence of bribes from the International Crime Victim Survey as

9 I also carried out parallel regressions using a variety of other explanatory variables that provided less robust results. Tables showing these regression results are in an appendix attached to the on-line version of this paper at the journal's website, (http://www.e-jep.org). A short summary of the results is that when settler mortality is included in this sort of regression (which is used as a proxy variable for whether it was attractive for Europeans to settle in a certain area), it cannot account for why some countries, given current levels of physical and human capital, are more corrupt than others. Countries with a French legal system or a socialist legal system tend to have more corruption, although the connection is not statistically significant in all data sets. The proportion of the population identified as Catholic is positively correlated with several corruption indicators; however, correlations between the proportion of the population that is Muslim and measures of corruption are not statistically significant. The religious and legal variables lose significance in a multiple regression with the policy variables as additional controls.



Jakob Svensson 29

Table 3

Corruption and Country Characteristics: Openness

Corruption ICRG ICRG IVSC Control of Perception Corruption Corruption Incidence

Corruption Index Score Score of Bribes Dep. variable (2002) (2003) (1982-01) (2001) (2000)

Real GDP per capita (log) -0.67*** - 1.43*** -0.90*** -0.71*** -0.06*** (.12) (.32) (.21) (.20) (.01)

Years of schooling (log) -0.51*** - 1.36*** -0.47* -0.53* (.18) (.50) (.27) (.28)

Imports/GDP -0.01** -0.03*** -0.00 -0.01 -0.00 (.00) (.01) (.00) (.00) (.00)

Sample size 89 77 83 81 44

Notes: For details on sources of data, see Table 2. Imports/GDP is imports of goods and services as

percentage of GDP (average from 1980-2000) from World Development Indicators (2004). *** statistically significant at 1 percent level. ** statistically significant at 5 percent level. * statistically significant at 10 percent level.

Table 4

Corruption and Country Characteristics: Regulation of Entry


Corruption Index Score Score of Bribes

Dep. variable (2002) (2003) (1982-01) (2001) (2000)

Real GDP per capita (log) -0.70*** -1.65*** -0.79*** -0.74*** -0.05*** (.17) (.37) (.24) (.22) (.01)

Years of schooling (log) -0.18 0.12 -0.17 -0.03 (.31) (.61) (.40) (.34)

No. of business days to 0.33*** 0.98*** 0.27*** 0.34*** 0.01 obtain legal status (log) (.09) (.20) (.10) (.10) (.01)

Sample size 61 60 61 61 35

Notes: For details on sources of data, see Table 2. Number of business days to obtain legal status is the time it takes to obtain legal status to operate a firm, in business days (a week has five business days and a month has 22) from Djankov, La Porta, Lopez de Silanes and Shleifer (2002). *** statistically significant at 1 percent level. ** statistically significant at 5 percent level. * statistically significant at 10 percent level.

the dependent variable, rather than one of the subjective measures of corruption, drastically reduces the sample size, as shown in the final column of the tables. Somewhat surprisingly, only GDP per capita, the proxy for initial human capital stock, and regulation of the press remain significantly correlated with corruption.

These associations suggest some general conclusions. First, corruption is

closely related to GDP per capita and to human capital. These correlations are consistent with the economic and human capital theories of institutional development, but the correlations could also be driven by reverse causality or omitted




Table 5

Corruption and Country Characteristics: Freedom of Media


Corruption Index Score Score of Bribes Dep. variable (2002) (2003) (1982-01) (2001) (2000)

Real GDP per capita (log) -0.55*** -1.29*** -0.81*** -0.68*** -0.06*** (.11) (.31) (.20) (.19) (.01)

Years of schooling (log) -0.65*** -0.97* -0.18 -0.22 (.12) (.59) (.28) (.36)

Freedom of media index -0.05** -0.10* -0.06** -0.05* -0.01** (.02) (.06) (.03) (.03) (.00)

Sample size 91 79 83 83 44

Notes: For details on sources of data, see Table 2. Freedom of media index is the average score of the four criteria "Laws and regulations that influence media content," "Political pressures and controls on media content," "Economic influences over media content," "Repressive actions" for print and broadcast media, average over 1994-2001, from the Freedom House.

variables. Second, for a given level of income, the extent of corruption still varies

greatly. The cross-country evidence suggests that this variation can partly be accounted for by the degree of market and political competition.

What is the Magnitude of Corruption?

The rankings of countries as more or less corrupt are based on subjective judgments and as such cannot be used to quantify the magnitude of corruption. Thus, until recently, the magnitude of corruption had to be assessed using anecdotal or case-study evidence.10 However, the past few years has seen a small but

growing body of research on identifying and quantifying corrupt behavior.11 There is some firm-survey evidence on the magnitude of corruption. Svensson

(2003) presents survey data from Ugandan firms. Although the survey was adjusted in several ways to encourage managers to report graft payments truthfully, some

misreporting surely remains in the sample. Nonetheless, the results provide a

gloomy picture of entrepreneurship in one of the fastest growing countries in sub-Saharan Africa in the last 10-15 years. Over 80 percent of Ugandan firms

reported needing to pay bribes. Avoiding graft comes at a cost, since the 20 percent

10 As an example in this journal, see McMillan and Zoido (2004). They use recorded bribe transactions of and by Peru's former secret-police chief Montesinos and find that Montesinos paid television-channel owners 100 times in bribes what he paid judges and politicians. Using a revealed preference argument, they conclude that news media, consistent with the cross-country evidence discussed above, are the

strongest check on the government's power. "

Again, the focus of this paper is on public corruption. There is a related literature on private corruption or collusion (for instance, McAfee, 1992; Porter and Zona, 1993; Duggan and Levitt, 2002). There is also a related literature on the value of political connectedness (for instance, Fisman, 2001; Khwaja and Mian, 2004).




of firms reporting that they had not paid had also chosen to minimize contacts with the public sector. Of the graft-paying firms, graft, on average, corresponds to

roughly 8 percent of total costs.

Corruption is also widespread in public procurement and service delivery programs. In another study in Uganda, Reinikka and Svensson (2004a) examine a

public education program that offered a per-student grant to cover nonwage expenditures in primary schools. To estimate the magnitude of corruption, or diversion of funds, they compared the flows disbursed from the central government to the school districts with survey data from 250 schools on the actual receipts of cash and in-kind school material. Over the period 1991-1995, schools received only 13 percent of central government spending on the program. Most schools received

nothing, and the evidence suggests that the bulk of the grants was captured by local

government officials and politicians. Subsequent studies have indicated that the situation is similar in other sub-Saharan African countries (Reinikka and Svensson, 2004a). Olken (2003, 2004), using a similar methodology, finds that 29 percent of funds allocated to a road building project and 18 percent of subsidized rice in a

large antipoverty program in Indonesia were stolen. Price comparisons can be another fruitful method to infer the magnitude of

corruption. Di Tella and Schargrodsky (2003) compare prices paid for basic

homogeneous inputs at public hospitals in the city of Buenos Aires. They show that

prices paid fell by 15 percent during the first nine months of a crackdown on

corruption in 1996-1997, providing a lower bound of corruption in procurement in Buenos Aires hospitals in the late 1990s. Hsieh and Moretti (2005) estimate the extent of underpricing of Iraqi oil during the United Nations Oil for Food Program by comparing the gap between the official selling price and various estimates of the market price of Iraqi oil during and prior to the program. They argue that

underpricing was a way for the Iraq regime to obtain illegal kickbacks from oil

buyers and estimate that Iraq collected $1 to $4 billion in bribes from 1997 to 2001, or about 2-10 percent of the total amount spent under the auspices of the

program. The literature on quantifying and identifying corruption is still at its infancy.

The existing contributions are scattered and often context specific. Still, the literature conveys that corruption can be quantified in a variety of ways. As more studies and data points become available, one should also be able to say something convincingly about aggregate corruption. As of now, the studies discussed above

suggest a huge variation in corruption, ranging from a few percent in the Oil for

Food Program that affected Iraq to 80 percent in the primary education program in Uganda. When comparing numbers, it is important to keep in mind that most studies do not claim to capture all corruption within the program or sectors. For

example, the hospital procurement study in Argentina estimates the extent of corruption affected by an increase in monitoring, and Hsieh and Moretti (2005) note that there likely were other irregularities in the Oil for Food Program that allowed Iraq to siphon funds from the program.

How do these micro findings on the magnitude of corruption relate to the macro literature on the institutional determinants of corruption? Here the




evidence is even more limited. For example, in the study discussed above, Reinikka and Svensson (2004) estimate the extent of corruption in a national school grant program and argue that economic development, here conceptualized as the com-

munity's ability to organize and exercise voice, affects the local government's incentives for corrupt actions. This hypothesis is confirmed in the data: schools in better-off communities, controlling for other community and school-specific fixed effects, experience a significantly lower degree of corruption, and the size of the effect is economically important.

Di Tella and Schargrodsky (2003) and Svensson (2003) also relate quantitative measures of corruption to policy. In a cross-section of Ugandan firms, Svensson finds that the incidence of corruption is highly correlated with the extent to which rules and regulations give public officials the bargaining rights to extort bribe

payments from firms. The level of reported graft payment, on the other hand, is driven by firm-specific factors, suggesting that corrupt officials condition their bribe requests on the firm's ability to pay bribes. An implication of this finding is that research on corruption should focus not only on the macro question of how institutional frameworks affect corruption but also on the micro question of how

corruption varies across a given institutional framework.

Do Higher Wages for Bureaucrats Reduce Corruption?

Aid donors and international organizations routinely recommend fighting corruption by paying higher wages to public servants. As a historical example of this

policy, Sweden, which ranks among the least corrupt countries on all current

cross-country rankings, was considered as one of the most corrupt countries in

Europe in the seventeenth and eighteenth centuries. Increased remuneration of civil servants combined with deregulation have been put forward as important explanations for the emergence of an honest and competent public administration in Sweden in the late nineteenth century (Lindbeck, 1975).

The analytical underpinning to the policy recommendation to increase public sector wages stems from a seminal paper by Becker and Stigler (1974), who show that by paying the official a wage above the official's opportunity wage, one can

ensure, under certain conditions, that the official will behave honestly. However, when the bribe level is not fixed and third-party enforcement does not exist, the theoretical relationship becomes ambiguous. For example, if the official and

bribe-giver bargain over the bribe, a higher wage strengthens the official's bargaining power as it raises the expected cost of being corrupt and thus leads to higher bribes (Mookherjee and Png, 1995).

The systematic evidence on the relationship between pay and corruption is

ambiguous. In cross-country studies, Rauch and Evans (2000) and Treisman (2000) find no robust evidence that higher wages deter corruption, while Van Rijckeghem and Weder (2001) find that it does. These cross-country studies, however, are

fraught with problems. Measuring the extent of corruption using rankings is

problematic. It is difficult to tell whether higher wages are a function of low



Jakob Svensson 33

corruption or vice versa. In addition, these studies have aggregate data on wages, so that the data on corruption and the data on wages may refer to different groups of individuals.

Di Tella and Schargrodsky (2003) avoid most of these problems in their study of how a crackdown on corruption in Buenos Aires affected the procurement policies of public hospitals. They divide the 19 months of data into three distinct

periods: a period with low, high and intermediate audit intensity from the city government. Linking the wage premium-the difference between the procurement officer's wage and an estimated opportunity wage-to the price paid for a set of homogeneous hospital inputs, they conclude that higher wages have a negative and quantitatively important effect on procurement prices, but only when audit

intensity takes intermediate levels. These results are not indisputable; in particular, there is some concern that variation in the wage premium is driven primarily by variation in the determinants of the opportunity wage-and these determinants

may have a direct bearing on the incentives for corrupt behaviour. Still, the findings provide fairly convincing evidence that paying higher wages can deter corruption under certain circumstances.

Should countries facing a high level of corruption react with a policy of higher wages for bureaucrats? Many poor developing countries with widespread corruption probably lack the third-party enforcement assumed in Becker and Stigler (1974) or the outside audits examined in Di Tella and Schargrodsky (2003). Yet the effectiveness of anticorruption wage policies hinges on the existence of an honest third party that can monitor the agent. Similarly, Besley and McLaren (1993) show that paying high wages maximizes tax revenues only when the share of dishonest

employees available to the government is high and the monitoring apparatus is effective.

Thus, wage incentives can reduce bribery, but only under certain conditions. This strategy requires a well-functioning enforcement apparatus; the bribe being offered (or demanded) must not be a function of the official's wage; and the cost of paying higher wages must not be too high. In many poor developing countries where corruption is institutionalized, these requirements appear unlikely to hold.

Can Competition Reduce Corruption?

Another common approach to control corruption is to increase competition among firms. One argument is that as firms' profits are driven down by competitive pressure, there are no excess profits from which to pay bribes (Ades and Di Tella, 1999). In reality, however, the connections between competition, profits and

corruption are complex and not always analytically clear. For example, Bliss and Di Tella (1997) construct a model where public officials

have the power to extract rents from firms. In the model, corruption does not need

any pre-existing rents or imperfect competition, since the excess profits from which to pay bribes may be created by the official by inducing exit. The level of graft demanded per firm depends on the likelihood that firms in the market are more




or less likely to exit due to a marginal increase in graft demand, not on the number of firms in the market or the degree of "natural" competition.

What then can account for the positive relationship between corruption and

regulation of markets discussed above? One plausible mechanism has to do with bureaucratic powers. Government regulations that raise barriers to entry are often enacted because they give public officials the power to demand and collect bribes

(De Soto, 1989; Shleifer and Vishny, 1993). Thus, deregulation may reduce cor-

ruption not so much by increasing competition, but by reducing the extent to which public officials have the power to extract bribes.

At least in theory, increased competition at the level of the official receiving the bribes may also reduce corruption (Rose-Ackerman, 1978). When officials

dispense a government-produced good, such as a passport, the existence of a

competing official to reapply to in case of being asked for a bribe will bid down the

equilibrium amount of corruption (Shleifer and Vishny, 1993). However, there is as yet no convincing empirical evidence that competition among officials actually reduces corruption. Moreover, the mechanism will only work if the multiple officials can individually produce the good. If multiple officials must sign off on the

good, each with the power to stop a project, extremely high bribe levels may result. In public service delivery, competition may not necessarily lead to lower

corruption.12 Consider a parent in Uganda, faced with the diversion of public funds from schools. Such parents have two choices: voice and exit (Hirschman, 1970). That is, they can either voice a complaint with some formal or informal authority, or they can send their children to some other school (or have them drop out of school altogether). But if parents react to public corruption through exit and by sending their children to competing schools, the likelihood of voice as the response to corruption is reduced-and corrupt local officials may be able to extract an even

greater share of the school's entitlements. A variety of evidence suggests that increased competition, due to deregulation and simplifications of rules and laws, is

negatively correlated with corruption. But it can be a difficult task to strike the right balance between enacting and designing beneficial rules and laws to constrain

private misconduct while also limiting the possibilities that such laws open the door for public corruption (Djankov, Glaeser, La Porta, Lopez-de-Silanes and Shleifer, 2003).

Why Have There Been So Few (Recent) Successful Attempts To Fight Corruption?

Most anticorruption programs rely on legal and financial institutions-

judiciary, police and financial auditors-to enforce and strengthen accountability in the public sector. The tacit assumption is that more and better enforcement of

12 There is a large literature on school competition in developed countries focusing on other implications of competition. As a starting point, see Hoxby (2003) or the exchange between Ladd (2002) and Neal (2002) in this journal.




rules and regulations will reduce corruption. However, in many poor countries, the

legal and financial institutions are weak and often corrupt themselves. In such a

setting, providing more resources to enforcement institutions may not be the right solution to the problem of corruption. An illustrative example is given in Hay and Shleifer (1998). When the elite units of the Russian police obtained more advanced

guns to combat crime, they simply sold these guns to the mafia at higher prices than the previous, less powerful, weapons could fetch.

To date, little evidence exists that devoting additional resources to the existing legal and financial government monitoring institutions will reduce corruption. Hong Kong and Singapore are the most cited exceptions. In both countries, the reduction in corruption went hand in hand with the establishment and strengthening of an independent anticorruption agency with widespread powers. For

example, in Hong Kong, the Independent Commission Against Corruption created

legal precedents such as "guilty until proven innocent" (Klitgaard, 1988; UNDP, 1997). However, the same types of anticorruption agencies have in many other countries been used as an instrument of repression against political opponents, not to fight corruption. Why then did they work in Hong Kong and Singapore? In those

countries, several reforms were implemented simultaneously with the strengthening of the enforcement agencies. For example, in Singapore, civil servants' pay relative the private sector increased substantially; public officials were routinely rotated to make it harder for corrupt official to develop strong ties to certain

clients; rewards were given to those who refused bribes and turned in the client; and importantly, rules and procedures were simplified and often published, permits and approvals were scrapped, and fees (including import duties) were lowered or removed. In both Hong Kong and Singapore, the top political leadership was committed to fighting corruption. In many developing countries, this commitment cannot be taken for granted.

Alternative approaches to fighting corruption exist. One method is to replace public with private enforcement of public laws through lawsuits, at least for a time

(Hay and Shleifer, 1998). But litigation, just as deregulation, has its limitations. Another complementary approach turns to citizen enforcement, by providing easy public access to information on the workings of public programs. This information enables citizens to demand certain standards, to monitor service quality and to

challenge abuses by officials. Some data suggests that improving citizen access to information and giving

citizens a greater right to action can reduce corruption. As discussed above, in the

mid-1990s, a survey revealed that primary schools in Uganda received only a small

fraction of the funds allocated to them by the central government. As this evidence became known, the central government began to publish newspaper accounts of

monthly transfers of the capitation grants to districts, so that school staff and

parents could monitor local officials. Reinikka and Svensson (2004b) find that the

newspaper campaign brought a large improvement. In 2001, schools received an

average of 80 percent of their annual entitlements. How can one estimate the causal effects of improved access to public infor-

mation? Reinikka and Svensson (2004b) employ a two-step procedure. First, they




use a simple test administered to head teachers to measure knowledge of the

program. Second, they measure the distance to the nearest newspaper outlet from the school. They find that head teachers in schools closer to a newspaper outlet know more about the rules governing the grant program and the timing of release of funds by the central government. Using distance as an instrument, they show that the more informed schools experienced a dramatic reduction in the share of funds

captured by corruption. Importantly, prior to the newspaper campaign, proximity to a newspaper outlet and changes in capture were uncorrelated.

The success of the newspaper campaign happened in a particular context. The

program was a simple entitlement program, which made monitoring easier, and

parents and school staff in Uganda had institutions already in place to handle collective decisionmaking. But in general, citizen enforcement or grass-root mon-

itoring are subject to possibly large free-riding problems (Olken, 2004). At the same

time, grass-root monitoring initiatives are becoming increasingly popular in many places. Examples include participatory budgeting in Porto Allegre, Brazil; citizen

report cards in Bangalore, India; and right to information on public works and

public hearings, or jan sunwais, in Rajasthan, India. Although there is no robust scientific evidence yet on the impact of these initiatives, the preliminary evidence

suggests that corruption has been dramatically reduced. Yet another strategy to fight corruption is delegation, or hiring integrity, from

the private sector. In the past two decades, over 50 developing countries have hired

private (international) firms to conduct preshipment inspection of imports and in few cases also handed over the responsibility for collecting customs duties (Yang, 2005). Preshipment inspection can reduce customs corruption in various ways: for

example, it improves the monitoring ability of higher-level enforcers, and it gen- erates independent information on the contents of a shipment that could increase the importer's bargaining power vis-a-vis a corrupt customs officer. Yang finds that

preshipment programs are associated with increases in the growth rate of import duties of 6 to 8 percentage points annually. The preshipment programs are

accompanied by an increase in imports (possibly due to reductions in importers' bribe payments) and a decline in measures of misreporting in customs.

Does Corruption Adversely Affect Growth?

Corruption could conceivably have a positive effect on economic growth. The

proponents of "efficient corruption" claim that bribery may allow firms to get things done in an economy plagued by bureaucratic hold-ups and bad, rigid laws (Leff, 1964; Huntington, 1968). A system built on bribery for allocating licenses and government contracts may lead to an outcome in which the most efficient firms will be able to afford to pay the highest bribes (Lui, 1985). However, these arguments typically take the distortions circumvented by the corrupt actions as given. In most cases, distortions and corruption are caused by, or are symptoms of, the same set of underlying factors. As Myrdal (1968) pointed out, corrupt officials may not



Jakob Svensson 37

circumvent distortions, but instead actually cause greater administrative delays to attract more bribes.

In most theories that link corruption to slower economic growth, the corrupt action by itself does not impose the largest social cost. Instead, the primary social losses of corruption come from propping up of inefficient firms and the allocation of talent, technology and capital away from their socially most productive uses

(Murphy, Shleifer and Vishny, 1991, 1993). When profits or potential profits are taken away from firms through corruption, entrepreneurs choose not to start firms or to expand less rapidly. Entrepreneurs may also choose to shift part or all of their

savings toward the informal sector, or to organize production in a way that the need or demand for public services is minimized. Moreover, if entrepreneurs expect they will be forced to bargain over bribes in the future, they have incentives to adopt inefficient "fly-by-night" technologies of production with an inefficiently high degree of reversibility, which allows them to react more flexibly to future demands from corrupt officials-and more credibly threaten to shut down operations (Choi and Thum, 1998; Svensson, 2003).

Corruption also affects the allocation of entrepreneurial skills. When corruption is widespread and institutionalized, some firms may devote resources to

obtaining valuable licenses and preferential market access, while others focus on

improving productivity (Murphy, Shleifer and Vishny, 1991). In the extreme, it may be financially more rewarding for an entrepreneur to leave the private sector

altogether and instead become a corrupt public official. What does the evidence say? The micro and case study evidence tend to

support to the theoretical predictions laid out above, but the macro evidence is inconclusive.

Bates (1981), for example, shows that in many sub-Saharan African countries, peasant farmers avoided corruption by taking refuge in subsistence production, with a consequent subsequent decline in productivity and living standards. Many formal sector firms, on the other hand, specialized in securing special advantages that they were unable to secure by competing in the marketplace. De Soto (1989) documents similar effects in Peru, where high start-up costs due to regulatory constraints and corruption forced entrepreneurs to establish new firms under-

ground and on a smaller scale. Does corruption affect firms' choice of technology and the allocation of talent?

Exploiting firm-level capital stock data on reported resale and replacement values, Svensson (2003) provides evidence suggesting that the amount of bribes a firm

needs to pay is negatively correlated with the degree of reversibility of the capital stock-a result consistent with the "fly-by-night" hypothesis discussed above. Fis-

man's (2001) findings on political connectedness in Indonesia suggest that some firms do specialize in corruption and rent seeking as means of growth and Khwaja and Mian's (2004) results on borrowing and default rates of politically connected firms in Pakistan suggest that one of the reasons politicians start firms, or join existing ones, is that it enables them to capture public resources through corruption.

Specialization in corruption also occurs in the public sector. Wade's (1982)




vivid account of corruption in the canal irrigation department in a south Indian state describes how some irrigation engineers raise vast amounts in bribes from the distribution of water and contracts, and redistribute part to superior officers and

politicians. The system of corruption is institutionalized, and there is even a second-hand market for posts that provide the holder an opportunity to extract bribes. Thus, politicians and senior officers are able to obtain for themselves part of the engineers' income from corruption by auctioning available posts. Moreover, those specializing in corruption-and thereby able to earn many times their annual official income though bribes-will be able to outbid other contenders less able or less inclined to exploit their official powers to extract bribes. In this example, competition results in higher corruption.

Micro studies on corruption have also yielded insights about the long-run cost of corruption. Reinikka and Svensson (2005), building on the Ugandan newspaper campaign study by Reinikka and Svensson (2004b), find that the reduction in

corruption caused by the information campaign had a significant and economically large effect on school enrollment and academic achievement. To the extent that human capital accumulation drives long-run growth, the results suggest an important mechanism through which corruption can hurt growth. Social service delivery in developing countries is often plagued by corruption of a variety of forms- bribes are charged for services to be provided and public funds are embezzled. Corrup- tion is therefore a leading candidate to explain why the impact of public spending on growth and social welfare has been so disappointingly low in many countries.

Some suggestive evidence also exists on the relationship between corruption and growth at the firm level. Fisman and Svensson (2001) use firm-survey data on the estimated bribe payments of Ugandan firms to study the relationship between

bribery payments, taxes and firm growth over the period 1995-1997. Using industry-location averages to circumvent the potential problem of endogeneity, they find that both the rate of taxation and bribery are negatively correlated with firm growth. For the full data set, a one percentage point increase in the bribery rate is associated with a reduction in firm growth of three percentage points, an effect that is about three times greater than that of taxation.

What about the macro evidence? Mauro (1995) is the first attempt to study the

relationship between corruption and growth in a large cross-section of countries.

Contrary to what is sometimes claimed, Mauro does not find robust evidence of a link between corruption and growth, although a broader measure of bureaucratic

efficiency is correlated with investment and growth. In Table 6, I updated Mauro's

calculations. I ran regressions with economic growth (over the period 1980-2000) as dependent variable and corruption (the International Country Risk Guide's

corruption indicator averaged over 1982-2000), initial GDP per capita and human capital as the explanatory variables. The estimated coefficient on corruption in this regression is negative-that is, less corruption is correlated with higher growth- but it is not significantly different from zero. I then added broad range of explanatory variables that have been suggested in the growth literature, but the coefficient on corruption remained insignificantly correlated with growth. Exploiting the panel dimension; that is, using five-year averages for corruption and growth and




Table 6 Growth and Corruption

Growth Growth

(1980-2000) (1980-2000)

Dep. variable Ordinary least squares Fixed effects

Real GDP per capita (log) -0.82* -6.50*** (.47) (1.03)

Years of schooling (log) 1.86*** 6.63***

(.66) (1.36) Corruption -0.33 0.11

(.24) (.24) Countries 85 86 Observations 85 335

Notes: For details on sources of data, see Table 2. Growth is growth in real GDP per capita over the period 1980-2000 in specification (1) and growth in real GDP per capita over the periods 1981-1985, 1986-1990, 1991-1995, 1996-2000 in specification (2). Real GDP per capita and

years of schooling are measured at the start of the sample period (in 1980 for specification (1) and in 1980, 85, 90, 95 for specification (2)). Corruption is the International Country Risk Guide's corruption indicator, average for 1982-2000 in specification (1) and average over 1982-1985, 1986-1990, 1991-1995, 1996-2000 in specification (2).

country-specific fixed effects to control for time-invariant country characteristics, also yields insignificant results.13

This finding seems to lead to a puzzle. Most of the theoretical literature as well as case study and micro evidence suggest that corruption severely retards development. However, to the extent we can measure corruption in a cross-country setting, it does not affect growth. The puzzle may arise from econometric problems involved in

estimating the effects of corruption on growth using cross-country data. For example, the difficulties of measuring corruption may include omitted variables, like the extent of market regulation, and reverse causality, like whether modernization and rapid growth may increase corruption, as Huntington (1968) argued. Another plausible explanation for the mismatch between the micro and macro evidence is that corruption takes many forms, and there is no reason to believe that all types of corruption are

equally harmful for growth. Existing data, however, are by and large too coarse to examine different types of corruption in a cross-section of countries.

Conclusion

In this paper, I posed eight questions about corruption. The answers are often not clear-cut, and there are many issues about corruption we simply know too little about. As the study of corruption evolves, three areas are of particular importance.

13 Using the two other subjective corruption indicators yields, in some specifications, a statistically significant negative effect of corruption on growth. However, these indicators are measured at the end of the sample period, thus making it even more difficult to draw causal interpretations from corruption to growth.




First and most urgently, scant evidence exists on how to combat corruption. Because traditional approaches to improve governance have produced rather

disappointing results, experimentation and evaluation of new tools to enhance

accountability should be at the forefront of research on corruption. Second, the differential effect of corruption is an important area for research.

For example, China has been able to grow fast while being ranked among the most

corrupt countries. Is corruption less harmful in China? Or would China have grown even faster if corruption was lower? These types of questions have received some

attention, but more work along what context and type of corruption matters is

likely to be fruitful.

Finally, the link between the macro literature on how institutions provide a more-or-less fertile breeding ground for corruption and the micro literature on how much corruption actually occurs in specific contexts is weak. As more forms of

corruption and techniques to quantify them at the micro level are developed, it should be possible to reduce this mismatch between macro and micro evidence on

corruption.

m I am grateful for comments and suggestions by Nicola Gennaioli, Assar Lindbeck, Torsten Persson and David Str6mberg, as well as editors James Hines, Andrei Shleifer, Timothy Taylor and Michael Waldman. The views expressed here do not represent the official opinion of the World Bank.

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