Advances in Measuring Corruption in the Field 1

Sandra SequeiraLondon School of Economics

February 2012

This chapter critically surveys recent advances in the methodology of measuringcorruption in the field. The issue of measurement is central in the corruptionliterature, and the choice of method can significantly influence our thinkingabout the determinants, the mechanics and the impact of corruption on theeconomy. We provide a conceptual categorization of different methods of mea-suring corruption ranging from surveys to direct observation of bribe paymentsin the field, while discussing the methodological and conceptual advantages anddisadvantages of each method. Finally, we highlight areas of complementarityacross methods and discuss avenues for future research.

I. Introduction

Corruption is still considered one of the most challenging obstacles to economic develop-

ment and growth. The World Bank estimates that over one trillion dollars are paid in bribes

worldwide and that 25% of African states GDP is lost to corruption each year (World Bank

Institute).

At the same time, there is a growing understanding of how corruption can distort busi-

ness activity, reduce investment, dampen the intended effect of policies and hinder the

functioning of institutions. The government of Indonesia estimates that lost forest revenue

due to corruption in the management of natural resources is costing the country up to US

$4 billion a year, or around five times the annual budget for the Indonesian department

of health (UNDP Report, 2008). The cost of corruption can also be high if it prevents

an efficient and equitable delivery of public services. According to Transparency Interna-

tional, corruption raises the price paid for connecting a household to a water network in

the developing world by as much as 30%. This is estimated to inflate the cost of achieving

the Millenium Development Goals on water and sanitation by more than US $48 billion, or

nearly half of the annual global aid outlays (Transparency International, Global Corrup-

tion Report 2008). In graft-addled public bureaucracies, it is estimated that over 50% of

allocated government funds do not reach clinics and hospitals (Transparency International,

2006 Global Corruption Report). As a result, corruption continues to figure prominently in

the policy and development agenda, conditioning international aid and driving governance

reform programmes worldwide. The World Bank alone has implemented more than 600

anti-corruption programmes since 1996.

Two decades of extraordinary developments in the breadth and depth of research on

corruption were triggered by this growing realization of the political, economic and social

costs it can impose, particularly on the poor, who are often least able to find ways to shield

themselves against corruption or to benefit from it directly. This research has sought to not

only measure the extent and prevalence of corruption, but also to understand its key deter-

minants and implications, motivated by the need to design more effective anti-corruption

policies.

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During this period, scholars have more or less converged on the overall definition of

corruption as the misuse of public resources and power for private gains (Klitgaard, 1968;

Shleifer and Vishny, 1993; Svensson, 2005) or more broadly, as the breaking of rules by

public officials, for private gain (Banerjee et al., 2011).

The primary challenge faced by scholars of corruption remains however one of measure-

ment. Without accurate and reliable measures, the extent and magnitude of corruption

cannot be properly identified, theories of corruption cannot be meaningfully tested against

the data to help us understand the fundamentals of how and why corruption emerges, and

effective anti-corruption strategies cannot be developed, tested and adapted to different

settings. Measuring corruption remains hard for a variety of reasons. At the most funda-

mental level, those who are involved in corruption are actively seeking to hide their behavior

for fear of punishment or shame. Corruption can also take many forms and involve many

different types of public officials, from port workers asking for bottles of whiskey to move

containers on the docks, to a doctor stealing medicine from a public clinic or shirking his

duties and not showing up for work. Identifying the full extent of different types of corrup-

tion will often require a deep understanding of the broader institutional, social, political

and cultural context in which the corrupt behavior is taking place. Given that the choice

of measurement strategy will ultimately help shape our thinking on the very dynamics of

corruption and on where to look for its impact, it should continue to be at the forefront of

the research agenda on corruption. The main challenge is to identify objective, replicable

and yet adaptive measures of corruption, capable of capturing new developments in corrupt

behavior as they emerge.

The last decade has witnessed an unprecedented revolution in the number of different

techniques that scholars have skilfully deployed to try to measure corruption. The pur-

pose of this chapter is to review these developments, providing a critical analysis of each

methods strengths and weaknesses. In the process, we offer suggestions on what we think

are the most important techniques that require further replication and development in the

future.2

The remainder of this article proceeds as follows. Section II begins by reviewing de-

2Interested readers should also see Banerjee et al. (2011), Olken and Pande (2011) and Zitzewitz (2011)for thorough reviews of current scholarship on corruption.

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velopments in indirect measures of corruption, ranging from perception-based indices to

statistical inference approaches, while section III discusses recent advancements in pur-

suing direct measures of corruption. Section IV concludes by suggesting areas for future

methodological advances that can help us glean more accurate and meaningful measures of

corruption.

II. The Challenge of Measuring Corruption

Earlier research on corruption was mostly theoretical, with theories on the systemic causes of

corruption such as the distribution of power between governments and private organizations

(Leff, 1964; Huntingdon, 1968; Tullock, 1971; Scott, 1972; Rose-Ackerman, 1978; Krueger,

1974; Bhagwati, 1982), jostling next to theories that emphasized the individual incentives

for bureaucrats to engage in corrupt behavior (Hirschman, 1970; Becker and Stigler, 1974;

Klitgaard, 1988). This literature identified administrative monopoly power, bureaucratic

discretion and lack of individual accountability as the main characteristics of corruptible

environments. A limited number of case studies were able to give life to some of these

concepts. Among these, Wade (1985) provided a vivid account of an entrenched network

of bribery in irrigation schemes in India, while Klitgaard (1988) described instances of

successful anti-corruption schemes in Asia and Tendler (1993) of successful governance

reform in Brazil. These case studies provided a first snapshot of how corruption could

emerge in very specific settings. They offered both reasons for concern, since corruption

could be deeply entrenched in complex institutional and organizational networks (Wade,

1985), and for hope, since carefully planned policy interventions and institutional reform

appeared to be able to successfully reduce it (Klitgaard, 1988; Tendler, 1993).

The case study methodology, while thorough and illuminating, was however unable

to tell us how pervasive and costly corruption would be in other settings, the different

types of corruption that can systematically emerge in the economy, the determinants of

incentive-compatible institutional and organizational reform for bureaucrats who are in

principal personally benefitting from the corrupt status quo, and whether these reforms

could succeed elsewhere.

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A. The Early Days: Measuring Perceptions of Corruption

The empirical research on corruption began to flourish in the 90s with the emergence of

new datasets of cross-country perception-based assessments of corruption. This was the

first attempt to identify consistent measures of a proxy for corrupt behavior, both across

time and countries.

The most widely used perception-based indices include the Transparency Internationals

Annual Corruption Perception Index (CPI), a survey of experts and public opinion on cor-

rupt practices in over 150 countries, and the Bribe Payers Index, a survey of businessmen

and investors on the likelihood of having to pay a bribe in over 60 countries. The Inter-

national Country Risk Guide (ICRG) and the World Bank Governance Indicators produce

similar yearly measures of the quality of institutions in different countries, including percep-

tions of the extent to which public power is exercised for private gain (including both petty

and grand forms of corruption), as well as the degree of capture of the state by elites

and private interests.3 These surveys include, among other indicators, questions about the

financial honesty of politicians, the likelihood of firms having to pay bribes to access a

variety of public services, and about the number of elected leaders who are perceived to be

involved in corruption deals.4

The new data generated important macro-level estimates of the negative impact of per-

ceptions of corruption on growth and investment (Mauro, 1995; Knack and Keefer, 1995;

Kaufmann et al., 1999; Wei, 2000).5 Bolstered by these preliminary empirical results, the

theoretical literature of the 70s and 80s became instrumental in driving the policy push for

deregulation and privatization in the 90s and early 2000s, as a means to curtail state power

and individual bureaucratic discretion. However, the literature on corruption still lacked

the empirical evidence to justify most of the general policy action it expounded.

In fact, despite its widespread use, scholars soon began to worry about the accuracy

and explanatory power of this method of measuring corruption. From a conceptual point

of view, perception-based indices were criticized as an attempt to weld together too many

3See Kaufmann et al. (2008) for a more detailed review of the World Bank Governance Indicators.4See Svensson (2005) for a thorough comparison between the different perception-based indices.5For further examples of how these indices have been used in the literature see Fisman and Gatti (2002),

Treisman (2000), La Porta et al. (1999) and Rauch and Evans (2000).

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different types and shades of corruption under a handful of indicators, limiting the range

of questions that could be asked in the study of corruption, and providing limited support

for targeted evidence-based policy action (Rose-Ackerman, 1983). For one, different types

of corruption could be cost-increasing or cost-reducing for different types of private agents,

depending on whether they reflected instances of collusion with a public official for shared

gain, or coercion by the public official for extortionary purposes (Sequeira and Djankov,

2010). A narrowly defined question about the prevalence of corruption applied to very

different settings would not be able to capture any of these differences.

Perception-based indices also face several methodological challenges, namely unpre-

dictable sampling and reporting bias. International businessmen, long considered the ex-

perts and the most informed respondents to these surveys, may not be impartial or objective

evaluators of corruption in different countries. Sampling bias emerges if an international

firms exposure to, and therefore knowledge of, corruption in a given country is determined

by the proclivity of a particular business to engage in corrupt behavior in the first place,

and by the type of business activity it is involved in. If most international businessmen are

involved in the oil sector in Nigeria and this is perceived as being a particularly corrupt

sector, Nigeria is likely to rank higher in the corruption index than other countries with

higher variance in the distribution of corruption and international businessmen across sec-

tors.

A second type of bias stems from voluntary or involuntary misreporting of perceptions

of corruption. Perceptions may differ significantly from actual practices for a variety of rea-

sons. Severe mismeasurement or perhaps even self-fulfilling forms of corruption can emerge

if respondents fall prey to certain cognitive biases identified in the psychology literature

such as the bandwagon effect, under which perceptions of respondents are influenced by

the most commonly held perceptions of corruption in a given country, even if they are not

substantiated by the respondents actual experience. A second type of cognitive bias that

may emerge is driven by a halo effect, as international experts and businessmen may

expect poorer countries or more dysfunctional governments to also be more corrupt.

At a more practical level, the methodology and degree of completeness of these indices

varies both from country to country, and from year to year, rendering cross-sectional and

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longitudinal studies hard to interpret.

The actual evidence on the validity of perception-based indices is mixed. Fisman and

Miguel (2007) identify a positive correlation between being perceived as a corrupt country

according to the CPI index and actual corrupt practices, measured as the non-payment of

parking tickets by United Nations diplomats in New York City. Barr and Serra (2009) find

similar results in the context of a lab experiment. Olken (2009) on the other hand provides

suggestive evidence on the extent to which perceptions about corruption may differ from

actual corrupt practices. The author collects two measures of corruption in a road-building

project among 600 villages in Indonesia. The first measure is based on villagers perceptions

of corruption in their own village, while the second measure is based on an independent

comparison between reported funds used in road-building, and the actual funds spent. This

comparison revealed that increasing the actual missing expenditures in the road project by

10 per cent increased the probability of a villager reporting any corruption in the road

project by only 0.8 percent. Overall, perception biases appeared to be context-specific and

correlated with important respondent-level characteristics, a finding that was corroborated

by Donchev and Ujhelyi (2009).

If our goal is to understand the actual dynamics of corrupt behavior and the mecha-

nisms through which corruption affects the economy, then this research suggests that any

cross-country comparison based on perception-based indices, with different sets of respon-

dents and varying institutional contexts, is fraught with challenges.

Perception-based indices can however still play a role in furthering our understanding of

corruption. To ensure that perceptions are accurately measured, new attempts should be

made to design indicators that minimize sampling bias and misreporting, while increasing

the scope of corrupt practices they are able to capture. Future research could then focus

on two key areas: documenting the systematic ways in which perceptions differ from actual

corrupt behavior and identifying the circumstances under which perceptions themselves can

be an important driver of corrupt practices.

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B. Survey-based Measures of Corruption

The growing realization that perception indices could not explain the many shapes and

forms corruption could take prompted scholars to seek new ways to gather micro-level data

on corruption.

The first step was to re-design survey questions to elicit truthful reporting of actual

bribe payments and to apply these to a representative sample of agents in the economy.

As a result, new firm and household surveys began to emerge with standardized questions

on whether individuals or firms had actually engaged in corrupt behavior in specific, well-

defined instances, such as when obtaining a water contract or an electricity connection,

an import license or a government contract.6The World Bank Enterprise Surveys (WBES)

and the Business Enterprise Economic Surveys (BEES) collect the most widely used firm-

level survey data on corruption. The International Crime Victim Surveys (ICVS) covers

individuals in 49 countries on whether they were asked for a bribe in any interaction with

government officials.7

Svensson (2003) and Fisman and Svensson (2007) illustrate the importance of this

methodology. Using self-reported bribe payments by Ugandan firms captured by WBES,

the authors show that while corruption was pervasive in the country, its incidence varied by

firm characteristics. Understanding the full distribution of bribe payments across different

types of agents is critical to identify the distributional costs of corruption, and to begin to

devise targeted strategies to tackle it.

This type of survey data allowed for more specific and therefore meaningful longitudinal

and cross-sectional comparisons of corruption in different countries, based on a more repre-

sentative sample of respondents.8 While this was a clear improvement over the perception-

6These questions avoided putting the respondent on the spot but tried instead to contextualize his or heractions by asking questions like How frequently do you think corruption is part of the business culture inyour country of operation? (Soreide, 2004) or We have heard that police officers at road posts will oftenrequest informal payments to let truckers proceed. How much do you think a company like yours would beasked to pay throughout the year? (Sequeira and Djankov, 2010).

7For examples of studies using the ICVS data see Mocan (2008) and Hunt and Laszlo (2011).8A similar approach that is gaining currency in the policy world due to the rapid spread of cell phone

technology is based on mobile apps that allow citizens to report the payment of bribes in real time as theyinteract with different types of public officials. The Indian site www.ipaidbribe.org is one such example:at the time of writing, this site had already registered almost 15,000 reports of bribery incidents. Anotherexample is the site http://www.corruptiontracker.org/, which tracks self-reported bribe payments through-out the world in several domains of public services. This new method of measuring corruption is being

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based measurement of corruption from the earlier literature, survey data brought some

challenges of its own.

The accuracy and reliability of a survey-based measure of corruption is heavily depen-

dent on the quality and consistency of the wording of the questions posed to respondents.

Respondents from different countries and cultures may understand the same question in

completely different ways, particularly on something as elusive and ill-defined as corrup-

tion. What may be seen as a gift building towards a prosperous business relationship in

one country can be perceived as a blatant bribe in others. Several techniques have been

suggested to try to mitigate these problems and safeguard the comparability of the data

(eg. see King et al. (2011) for a description of the method of anchoring vignettes). Open-

ended questions, longer questions, and questions incorporating wording that implies that

the behavior is more or less common are techniques that have been shown to yield higher

reports of sensitive behaviors (Bradburn, 1983; Catania et al., 1990; Miller et al., 1990;

Schwarz et al., 1991).

A second type of challenge is the extent to which a respondent may purposefully mis-

report bribe payments. Fear or shame of exposure could easily lead respondents to under-

report bribes, while a strategic concern with influencing action on a particular corrupt

practice could lead them to over-report instances of corruption (Harrison and Hughes,

1997). The direction of this social desirability bias is hard to ascertain as it depends on

the particular interest of the respondent in either facilitating or preventing these practices.

This is in turn tied to whether the respondent is benefitting or not from corruption, and

to how detrimental or justified the respondent views his or her actions to be Ariely (2010);

Gino and Ariely (2010) . Moreover, survey interviews are a one off event and they are

too short for the enumerator to establish a relationship of trust with the respondent to en-

sure truthful reporting. Other limitations of survey data include imperfect recall of events

(Rose-Ackerman, 2006) and the fact that the questions currently asked in standard sur-

veys seldom allow for great detail on the micro-dynamics of corruption. The majority of

increasingly adopted to help concerned citizens monitor their governments and anonymously report bribes.This approach carries however important methodological concerns of selection bias of respondents, and ofthe possible manipulation or exaggeration of reports. In fact, countries with more registered instances ofcorruption may simply be countries with greater level of awareness and higher levels of citizen activism, notnecessarily higher levels of actual corruption.

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questions used in these surveys tend to be close-ended and few in number, leaving limited

scope for the detection of alternative forms of corruption researchers are not yet aware of.

Further research is also needed to correctly identify and account for any social desirability

bias or fear of public disclosure that may affect survey-based measures of corruption. In

fact, understanding the extent and determinants of this bias can even shed new light on

the motivations of those involved in corrupt activities.

An alternative method of measuring corruption is through official, government-led cor-

ruption audits. This measure was used in Ferraz and Finan (2008, 2011) to investigate

how disclosing results from municipal government level corruption audits affected electoral

outcomes in Brazil. While in this particular context the authors were less concerned with

the accuracy of their measure of corruption as long as it was deemed credible and accurate

by the electorate and by the politicians involved so as to affect their behavior, the main

challenge of using this type of measure is that the capacity of the government to detect

and quantify corruption may be altogether low, or, more importantly, it may vary across

regions and across agents involved in the bureaucratic chain. Moreover, once corrupt of-

ficials begin to understand the workings of a system that attempts to consistently detect

and measure corruption through systematic audits, they may adapt their behavior and find

ways to elude it. Finally, there may be political incentives to manipulate administrative

data so as to reward or punish at will (Banerjee et al., 2011; Camacho and Conover, 2009).

C. Minding Gaps in the Data

A recent but increasingly common approach to measuring corruption consists in identifying

gaps in primary or secondary data that suggest corrupt practices. We discuss three possi-

ble strategies under this approach: identifying a mismatch between two sources of official

administrative data; detecting discrepancies between administrative data and results from

an independent household or firm-survey; or generating two primary sources of data and

finding gaps that suggest hidden and illicit behavior.

The first example of comparing two official sources of administrative data can be found

in Reinikka and Svensson (2004)s attempt to measure corruption in transfers between the

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central government in Uganda and schools. The authors resort to a Public Expenditure

Tracking Survey (PETS) which allows them to see at what level of the bureaucracy funds

were captured, and how much of the originally allocated funds reached the lower levels

of the bureaucratic chain. The study finds significant leakage, in the order of 87% of the

total amount of funds transferred. More importantly, having micro data on these transfers

allowed the researchers to identify significant variation in corrupt behavior across schools,

providing valuable insights that led to the design of a more accurate bargaining model to

describe corruption in this particular setting.

This method was also employed in Fisman and Wei (2004) to measure corruption in

the form of tax evasion, by comparing reported exports to reported imports from sending

and receiving countries respectively. The intuition, first pioneered by Bhagwati (1964), was

that sending countries had no incentive to misreport prices or volumes whereas receiving

countries did. This methodology was replicated in Narciso and Javorcik (2008) comparing

the value of exports reported by Germany to the value of imports from Germany reported

by ten Eastern European countries. In both cases, the authors find that the gap is largest

for products with high tariffs, and smallest for products with high tariffs on closely related

products.9 The emergence of robust patterns in the data allay our concerns about the

possibility that the mismatch is driven by poor reporting capabilities in some countries

but not others. The level of detail in the data also allowed the researchers to identify the

different mechanisms of corrupt behavior at play: Fisman and Wei (2004) provide evidence

that product classification is the most prevalent form of tariff evasion while Narciso and

Javorcik (2008) provide evidence for price misrepresentation. Similarly, Fisman and Wei

(2009) detect corruption in the smuggling of cultural artefacts into the US by comparing

recorded imports to the US to reported exports from the rest of the world. The authors find

that this gap is largest for countries with lower scores in international corruption indices.

Another example of this method of measuring corruption by comparing data from of-

ficial sources can be found in Hsieh and Moretti (2006). The authors measure corruption

in the Iraqi Oil-For-Food program administered by the United Nations, as the difference

between world prices of oil and the price received by Saddam Husseins regime.

9Mishra et al. (2008) conduct a similar study for India and find that there are more missing importsduring periods of higher tariffs.

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This approach has been used not only to measure corruption and to detect interesting

patterns of corrupt behavior, but also to test for the impact of anti-corruption policies.

Taking advantage of a quasi-experiment resulting from the introduction of more stringent

monitoring over corrupt practices in the procurement of medication in the hospitals of

Buenos Aires in Argentina, Tella and Schargrodsky (2004) find that reported prices and

quantity of medication distributed decreased by 12.3% and 9.7% respectively during peri-

ods of more intense monitoring.

An alternative approach is to compare administrative data to an independently con-

ducted audit study, or a household or firm survey, as exemplified by Olken (2007). The

author compares reported expenditures on road-building in over 600 villages in Indonesia

to an independent engineering audit that determined how much was actually spent on each

road. The audit consisted of engineers digging out portions of the road to identify the ma-

terials used. Enumerators conducted price surveys in local markets to estimate the actual

prices of the materials used, and surveyed villagers to obtain estimates of local wages. This

allowed the author to measure the gap between declared official expenditures and a more

accurate measure of what was actually spent. The findings were startling: the difference

between what the village claimed to have spent on the road and what the engineers esti-

mated had actually been spent averaged about 24% of the total cost of the road.

Similarly, Olken (2006) measures corruption by comparing official government data to

an independent household survey, by estimating the extent of theft from a programme that

distributed subsidized rice in Indonesia. The author compares official data on rice dis-

tribution, to household-level information on the actual consumption of rice. Niehaus and

Sukhtankar (2011) adopt a similar methodology by measuring corruption as the gap be-

tween official and actual quantities of days and wages paid under the Indian National Rural

Employment Guarantee Act. Actual data is collected through an independent survey of the

days effectively worked and the payment effectively received. The authors find corruption

in the form of both the over-reporting of days and the under-payment of wages. Similarly,

Atanassova et al. (2009) collected data on prices paid and quantities received from the

public distribution system in India and compare them to the official prices of those same

commodities to detect instances of graft.

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While this method is now widely adopted in a variety of settings10, the fact that a

mismatch between reported and received transfers can be attributed to corruption is based

on the untested assumption of consistent and high-quality bookkeeping throughout the bu-

reaucratic setup of a given country. Bureaucratic inefficiencies or unexpected reallocations

of funds across budgetary categories could however give rise to similar patterns in the data,

leading us to mistakenly attribute the potential mismatch to corrupt behavior alone. To

substantiate this assumption, authors often try to find a source of exogenous variation in

incentives for corrupt behavior, which they can show to be correlated with variations in the

intensity of the mismatch. The challenge remains one of identifying a variation that affects

the outcome of interest but not the potential confounds.

Fisman and Wang (2011) provide an interesting example of this approach applied to

uncovering underpricing in state asset sales in China. Because managers of state compa-

nies do not personally bear the cost of selling shares at a discount, the lack of oversight

creates potential for buyers to bribe insiders to underprice sales. The authors construct a

database of negotiated state transfers complemented by firm-level information from pub-

lic sources, yielding a sample of 2,121 deals involving 649 firms. To measure corruption

they exploit two characteristics of the Chinese transfer market. First, holdings of Chinese

state companies are split between private shares (resulting from partial privatization in

the early 1990s) and a substantial amount of government shares. Unlike private shares,

however, government shares are non-tradable, with transfer sums determined through ne-

gotiation and then subject to regulatory approval. Since private and governmental shares

are comparable apart from the different trading procedures, any difference between the ne-

gotiated transfer price and the average stock price is likely to reflect underpricing. Second,

the authors also assume that sellers of underpriced government shares often deliberately

misstate their status as a private company in order to avoid close regulatory scrutiny and

detection. While the original ownership status of these disguised firms can be traced,

most of the regulatory bodies turned a blind eye, providing a channel for eluding oversight.

The authors then proceed to construct an indicator for disguised firms by systematically

checking the original ownership of each private seller via public firm listings and databases.

10For a review see Olken and Pande (2011)

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The main empirical goal is to identify a correlation between the extent of underpricing and

subsequent firm performance with the disguised firm dummy. The findings suggest that

sales by disguised sellers - i.e. firms misrepresenting their state of ownership to elude

regulatory scrutiny - are discounted 5-10% points more than sales by other owners, with

sale sizes significantly smaller (arguably also to prevent detection).

In a similar vein, Coviello and Gagliarducci (2010) study how a politicians tenure in

office may increase the chances of collusive corruption in public procurement auctions by

Italian municipalities. The authors exploit a change in the electoral law that introduced

two term limits that would immediately affect some, but not all mayors. The study finds

that an increase in a mayors tenure in office was associated with arguably worse pro-

curement outcomes in the form of fewer bidders per auction, a lower winning rebate, a

higher probability that the winner was local and that the same firm was awarded repeated

auctions. Sukhtankar (2011) measures corruption as the gap between reported sugar cane

crushed at Indian sugar mills and sugar actually produced. He finds that this gap is more

pronounced in election years, particularly for mills controlled by politicians who are con-

testing an election. This correlation suggests that politicians divert resources in election

years from the mills to financing their campaigns.

Tella and Franceschelli (2009) investigate whether coverage of governmental corruption

is negatively correlated with the amount of governmental transfers paid for advertisement

in newspapers. The authors measure corruption coverage by the total space in the front

page of a newspaper per month that is devoted to reporting corruption scandals involving

the government, and also collect data on governmental transfers for advertisement to news-

papers. Their preferred measure of corruption is the estimated coefficient when regressing

front page coverage of corruption on government-paid advertisement. In this case, a nega-

tive association suggests that these transfers are part of a corrupt relationship between the

government and the media.

Khwaja and Mian (2005) also find evidence of corruption by identifying a correlation

between politically connected firms in Pakistan and access to credit. The authors find that

politically connected firms receive loans that are 45% larger and have 50% higher default

rates. More importantly, this preferential treatment is entirely driven by loans from govern-

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ment banks, with private banks appearing to be free from any political bias in the allocation

of loans. The authors provide further evidence that corruption may be the mechanism at

play when they show that firms connected to the winning party or to the winning politician

receive more loans - a 10% point increase in the number of votes a politician obtains is

associated with a 7% increase in the amount borrowed by a connected firm.

Similarly, Faccio (2006) looks at a cross-section of 47 countries to estimate the impact

on stock values of companies having a politician join the firm as a board member or a large

shareholder. Evidence of the suggested mechanism of corruption is obtained by comparing

the strength of this relationship in countries with high and low levels of corruption, as

measured by standard perception based indices of corruption. The main finding is that this

relationship only holds in countries with above median corruption, lending further support

to the assumption that political connections may indeed be associated with corrupt prac-

tices.

While these studies illustrate the remarkable creativity of their authors in obtaining

estimates of the magnitude and extent of corruption in a variety of complex settings, this

methodology still faces several challenges. Given that these are indirect measures of cor-

ruption and that authors are seldom able to identify an adequate comparison group and

an exogenous source of variation that induces changes in the incentives to engage in cor-

rupt behavior, concern with omitted variable bias and reverse causality are hard to dispel

entirely. For instance, it is possible that the underpricing of state sales studied in Fisman

and Wang (2011) is driven by other reasons than corruption such as liquidity discounts.

The direction and nature of corrupt dealings is also difficult to ascertain in many of these

cases. In Tella and Franceschelli (2009), it is hard to completely eliminate the possibil-

ity of reverse causality as governments may punish newspapers that report scandals by

withdrawing funds, but newspapers can also hold up the government until they receive a

bribe. These studies often require very careful and detailed collection of quantitative and

qualitative data to be able to convincingly tell a causal story, and to provide a meaningful

measure of corruption that can explain the mechanisms through which it is taking place.

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D. Measuring Corruption through Market and Statistical Inference

An emerging subfield labeled forensic economics is concerned with uncovering hidden

and harmful behavior through a rigorous application of economic theory, and a creative

search for secondary data. To uncover corruption in a wide range of contexts, authors have

compared official data to predictions from price-theoretic models and market equilibrium

conditions, in order to identify patterns of statistical anomalies that may suggest illicit

behavior.

Fisman (2001) best exemplifies this methodology in an event study that estimated the

value of firms political connections. The author begins by estimating the level of each

Indonesian companys political connectivity to President Suharto during his time in office,

and then measures how the prices of each firms stocks moved every time there was a rumor

about Suhartos imminent death. The underlying assumption was that if in equilibrium

stock prices reflect perfect information on the overall value of the firm, then the change

in stock market values, ceteris paribus, could only be attributed to a fall in the value of

the firms political connection. Based on baseline estimates of the impact Suhartos death

would have on the performance of the market (a 20% fall), the author estimates that at

least 23% of each firms value was due to the Suharto connection. Fisman et al. (2006)

apply the same methodology to estimate the value of firms political connections to former

US vice-president Richard Cheney during the Bush Administration, but this time to find

that this value was close to zero.

Gorodnichenko and Peter (2007) start from first principles on labor market equilibrium

conditions to identify corruption in public services. The authors conduct a household sur-

vey in Ukraine to test the hypothesis that a difference in pay between the public and the

private sector should lead to similar differences in consumption patterns of public and pri-

vate employees. The actual data revealed instead almost identical consumption patterns,

despite the significant wage differential of almost 24-32%. This discrepancy was attributed

to corrupt behavior by public workers.

Alternatively, several studies began to look for outliers or anomalous statistical patterns

in the data that suggested figures were being manipulated to cover illicit behavior. An ex-

15

ample of this type of approach can be found in Jacob and Levitt (2003), which detects

teachers manipulation of test scores. The authors first develop an algorithm for detecting

teacher cheating that combines information on unexpected test score fluctuations and sus-

picious patterns of answers for students in a classroom. A pattern was considered to be

suspicious if there were unexpected test score fluctuations for students from year to year,

or suspicious answer patterns within a class such as blocks of identical answers or a high

degree of correlation between answers. Using data from the Chicago Public School System,

they then find that serious cases of teacher or administrator cheating on standardized tests

occur in a minimum of 4-5 percent of elementary school classrooms annually.

Duggan and Levitt (2002) adopt a similar approach to measure the extent of corrup-

tion in Sumo wrestling, in the form of collusion and match fixing. The authors exploit a

non-linearity in the payoff function of sumo wrestlers: sumo wrestlers need to secure at

least 8 wins in order to rise up in the rankings. As the marginal return to winning the

8th match is much higher than winning - for example -12 matches (since the sumo wrestler

is already guaranteed to rise in rank), the opportunity emerges for a wrestler who has al-

ready secured his ascent to collude with one who has not, letting the opponent win the 8th

game. Evidence of corrupt behavior is then measured as the deviation between the actual

number of wins in over 64,000 sumo matches and what would have been predicted by the

binomial distribution, which assumes that match outcomes are independently and equally

distributed for seventh and eighth wins. The authors find that wrestlers on the margin to

securing 8 wins are significantly more likely to win the game. Conversely, wrestlers whose

opponents are on the margin of securing 8 wins are significantly less likely to win the game.

Wolfers (2006) employs a similar methodology to measure corruption in gambling, in

the form of point-shaving in basketball matches. In the National Collegiate Athletic As-

sociation (NCAA) matches, bids are won based on a gamble on the winning margin, not

just the actual win. Players therefore care about winning the game while gamblers care

about covering the spread. These asymmetric incentives create opportunities for corruption

in gambling to emerge in the form of point-shaving, the practice of shaving the winning

margin below the point spread. Players and teams can be bribed in exchange of avoiding

to cover the spread. The efficient market hypothesis would assume that the probability of

16

a team beating the spread is unpredictable. The author draws upon data on the outcomes

of 44,120 games obtained from online betting markets, to compare the actual distribution

of winning margins to what a normal distribution would predict. The fact that too few

strong favorites win the game and cover the spread, relative to what would be expected

if covering the spread followed a normal distribution, is interpreted as evidence of point-

shaving.

Camacho and Conover (2009) study corruption looking at the manipulation of a house-

hold level poverty index in Colombia that determined eligibility for a range of social pro-

grams. Evidence of manipulation is determined by the sharp discontinuity in the density

of the poverty index distribution exactly at the eligibility threshold. The authors confirm

this manipulation by showing that an increased number of census interviews required to

determine the poverty index took place right before mayoral elections, and that in more

competitive elections, cheating in the form of frequent and widespread manipulation, was

more pervasive. They find that a relatively high proportion of individuals had very similar

answers to the survey in a given month, and that from those, 97% had scores below the

eligibility threshold.

Finally, a model-based approach to measuring corruption can be found in Oliva (2008),

who combines a non-parametric test with a structural model to test for corruption in smog-

check vehicle testing. First, the author identifies anomalous patterns in pass/fail sequences

at smog check vehicle centers, given predicted fair probabilities of passing the test in a

model with honest behavior. The author estimates a mapping from car attributes into

fair probabilities of passing the test based on data from centers assumed to show limited

evidence of cheating. The mapping is then used to predict the fair probability of passing for

the rest of the car fleet. Finally, the author estimates a structural model of car owner testing

decisions that allows for both re-testing and cheating. A maximum likelihood estimation

of the model yields estimates for both the prevalence of cheating and the equilibrium bribe

in the cheating market.

These studies offer a promising way ahead to better detect corruption in a variety

of settings, but also to better understand the micro-dynamics and the overall impact of

corruption in the economy. In contrast to the previous measures that rely solely on iden-

17

tifying gaps in the data, in this case authors start from first principles with a model of

non-corrupt behavior and draw specific theoretical predictions on how the data may reflect

deviations from this model. This method is particularly well-suited to understanding the

micro-dynamics of corrupt behavior and to directly test important theories of corruption in

the data. The challenge of applying this methodology is that since the corruption measure

is often indirect, the authors have to go to great lengths to rule out alternative explanations

such as whether sumo wrestlers or baseball players increase their effort at the margin; and

to argue that their results do not hinge on particular distributional assumptions, on the

characteristics of the statistical test employed, or on the features of their structural model.

Event studies like the ones employed in Fisman (2001) and Fisman and Wang (2011), also

require that the timing of events studied is well-understood and exogenous to pre-existing

levels of corruption.

III. Direct Observation of Bribe Payments

In recent decades, scholars have shown great ingenuity in developing new techniques to

glean more accurate, adequate and meaningful measures of corruption. While tremendous

progress has been made, several challenges still remain. Perception-based measures of cor-

ruption are vulnerable to sampling and reporting bias, survey-based measures struggle to

elicit truthful reporting of bribes, gaps in administrative data may be driven by dysfunc-

tional government bookkeeping and an approach based on market or statistical inference

may struggle to isolate which part of the detected deviation from equilibrium conditions

can be attributed to corruption, and which part cannot Banerjee et al. (2011).

A. Documented Measures of Corruption

Bearing in mind the limitations of indirect measures of corruption Tran (2010) and Tran

and Cole (2011), suggest a more direct method of measurement by gathering data on docu-

mented bribe payments from internal records of firms. The authors complement this bribe

data with extensive qualitative interviews with CEOs to reach a clearer understanding of

the motivation for the payments they observe. The authors provide suggestive evidence of

18

how government contracts are often inflated both to hide bribes and to evade corporate

income tax.

The reasoning behind this method is that larger and more sophisticated firms tend to

carefully record bribe payments as part of their normal tracking of expenditures, especially

since bribes are often paid at different stages of the procurement process, while contracts are

being negotiated and implemented. Specifying the timeline and amount of bribe payments

also has the advantage of providing firms with some guidance on how much to inflate other

expenses, to avoid paying income taxes on bribe payments since these cannot be deducted.

Researchers were able to access these data under conditions of non-disclosure of the identity

of either the payers or the payees of the bribes.

The advantage of relying on documented bribes is that data quality is likely to be high

and it may allow the researchers to correctly identify who is involved in the deals, at what

time, and for what reason. When matched to overall procurement data such as information

on the quality and competitiveness of alternative bids for each tender, it can provide a

clearer snapshot of both the magnitude and the determinants of corruption, relative to any

of the other indirect measures.

There are however three main challenges with implementing this method. The first con-

straint is one of scale and generalizability. Only the most corrupt firms or those operating

in more corrupt sectors are likely to keep track of bribes paid, giving us a biased indicator

of the level of corruption in the economy. Second, it is difficult to replicate this method at

a larger scale across time and firms, given the challenge of convincing several companies to

share their records consistently with the researchers. This may lead to significant sampling

bias.

More importantly, there may be substantial variation in how firms record bribe pay-

ments and how they cover them up in different accounting categories. These patterns may

not be fully understood by the researcher. In a departure of the evidence in Tran (2010),

Cai et al. (2011) suggests that firms record bribes under an accounting category of enter-

tainment and travel costs using fake or inflated receipts. The authors then have to resort to

restrictive techniques of structural modelling to isolate real from corruption-related records

under this category.

19

In yet other settings, private agents may actually not know they are paying bribes. If

the structure of the market is such that firms have to resort to intermediaries, as exem-

plified by the market for obtaining drivers licenses in Bertrand et al. (2007) or shipping

goods across international borders as described in Sequeira and Djankov (2010), then those

receiving the service may not be able to accurately distinguish between what was paid as

a bribe and what was paid to reward the service provided by the intermediary. This is

reinforced by the fact that intermediaries tend to have opaque pricing systems and private

agents may have limited information and knowledge on the actual price of the services

the intermediaries are paying for. Exploring this method therefore requires paying careful

attention to the possibility of measurement error and sampling bias.

The method of looking inside the firm to understand how and to whom bribe payments

are systematically paid is still in its infancy. Despite the challenges of replicability and gen-

eralizability, it offers great promise to generate important hypotheses on how corruption

affects the cost structure and consequently the production function of the firm.

A similar approach of using documented bribe payments is used by McMillan and Zoido

(2004) in a study of the extent and magnitude of bribe payments during Perus President

Alberto Fujimoris regime. Montesinos, the Presidents secret police-chief, bribed judges,

politicians and the news media in return for political support. He also kept records, with

signed contracts from those he bribed, and even videotapes of the act of paying a bribe.

The data became available after the fall of the Fujimori regime. While illuminating and rich

in detail, the rarity of this type of data may limit the use of this method more broadly in

the future. Unless it can be matched to secondary data, it also limits the range of questions

that can be explored on either the determinants or on the efficiency and distributional costs

of this type of corruption on the economy.

B. Observing Corruption in the Field

To overcome some of the limitations of previously discussed approaches, scholars have be-

gun to reach deeper into the black box of corruption to try to directly observe agents as

they engage in the act of paying a bribe.

Chaudhury et al. (2006) apply this method of direct observation to measure the extent

20

to which public officials such as teachers and health care providers shirk from their official

duties, by not showing up to work while earning a government salary. Their measure of

shirking is based on three surprise visits to 3,700 randomly-selected schools in 20 Indian

states. The authors conclude that teacher-absenteeism was on average 25%, which meant

that on a normal day, a quarter of all primary school teachers were absent from school

throughout India.

Bertrand et al. (2007) adopt an experimental design to measure corruption in obtaining

drivers licenses in India and to identify which rules could be broken through bribes. The

authors randomly allocate applicants to one of three groups: a bonus group (which received

a bonus for obtaining a license quickly), a lesson group (offered free driving lessons) and

a comparison group. When given a financial incentive to obtain a drivers license faster,

applicants were able to do so at the cost of not learning how to drive. This was taken

as evidence that corruption was more than just a transfer from citizens to bureaucrats,

but that it actually allowed private agents to circumvent what in principle were viewed as

socially optimal rules. The experimental design and the richness of the dataset enabled the

authors to not only gauge the magnitude and extent of corruption, but also to directly test

whether corruption rendered public service delivery more responsive to citizens needs, and

if so, at what social cost.

Olken and Barron (2009) directly observe bribes paid by truck drivers to police and

military officers at road-posts and weighting stations along two main roads in Indonesia.

During 9 months, enumerators/observers shadowed truck drivers as they made over 6,000

payments to police on their route to and from the Indonesian province of Aceh. Truck

drivers made payments to avoid harassment at checkpoints along the roads, to avoid fines

for driving overweight, and to buy protection from criminal organizations or from the po-

lice. Enumerators observed whether payments were made in cash or in kind, and found

that bribe payments represented about 13 percent of the marginal cost of the trip. This

rich dataset allowed the authors to go beyond just measuring the magnitude of corruption

to directly test the extent to which standard pricing theories from industrial organization

were consistent with actual patterns of bribe payments. The authors exploit an exogenous

variation in the market structure of bribe payments caused by the government-led with-

21

drawal of over 30,000 police and military officials who were manning the checkpoints where

bribe extraction occurred. This withdrawal affected only one of the provinces under study

and because it was driven by the signing of a recent peace agreement, it was also plausibly

exogenous to existing patterns of bribes. The authors find that bureaucrats behave very

much like firms as they adopt sophisticated price discrimination strategies to set bribes and

they adjust their behavior in response to changes in market structure.

The strategy of having observers shadow bribe payers raises however an additional set

of concerns. It is possible that the presence of the observer affects the frequency, type

or magnitude of the bribe payments observed. While under observation, private agents

or public officials may reduce the extent of their illicit behavior or find new ways to hide

it. We are then faced with the Heinseberg indeterminacy principle, when agents change

their behavior because they are being studied in such a way that it becomes impossible

to measure simultaneously the phenomenon under study and the effect of the observation.

It is also very difficult to predict the direction of any Hawthorne or experimenter demand

effects.11 It is possible that participants want to please the researchers by over-reporting

corruption or that they change their behavior to pay fewer bribes following cues from the

researchers that this is what constitutes appropriate behavior.

Sequeira and Djankov (2010) measure bribe payments at ports and border posts in

two competing transport corridors in South Africa and Mozambique, with the goal of un-

derstanding the impact of corruption on firm behavior. The authors work directly with

well-established clearing agents who, by law, every importing firm has to resort to in order

to clear imports through international borders. Given the illicit nature of the bribe pay-

ments, the sample size was restricted to eight clearing agents so as to ensure discretion in

the data collection and to maximize the accuracy of the data. Each clearing agent worked

with an average of 20 to 25 clients. The authors began by conducting an informal survey

in the shipping industry to help stratify an official listing of these agents by their reputa-

tion for corruption and the length of establishment of their business. A random sample

of clearing agents was then selected from within each stratum to participate in the data

collection. This recruitment of the clearing agents was a long and carefully planned process.

11See Zwane et al. (2011).

22

It required several months of engagement, so that the agents would fully understand how

the data would and would not be used. In all instances, researchers satisfied the clearing

agents participation constraint by ensuring that no data would be collected on their clients

apart from general indicators of size and frequency of shipments, and in some cases, that

the data would be handed over in anonymized spreadsheets to avoid the possibility of at-

tribution.

Clearing agents tracked a random sample of 1,300 shipments, going through the ports of

Maputo in Mozambique, Durban in South Africa and the border post between South Africa

and Mozambique. They recorded detailed information on the characteristics of the cargo

and provided information on the primary recipients of bribes, the bribe amounts requested

and the reason for the bribe, ranging from the need to jump a long queue of trucks to

get into the port, to evading tariffs or missing important clearance documentation. The

findings were striking: bribe payments represented an increase of up to 14% of the marginal

cost of a shipment at the most corrupt port, and a monthly salary increase of up to 600%

for the average customs official.

Once the authors were able to estimate expected bribes per shipment based on cargo

and client characteristics, they then identified a set of firms that were equidistant to both

ports, and, given the product they were shipping, estimated how much each firm would pay

in bribes at either port. The authors also noted whether corruption was cost-increasing

(coercive) or cost-reducing (collusive) for each firm, at each port. The main findings were

that firms adjusted the organization of production in response to the different types of cor-

ruption they faced at each port. Coercive corruption led firms to go the long way around

to avoid the most corrupt port (more than doubling their transport costs in the process),

but collusive corruption, mostly in the form of tariff evasion, was associated with a higher

demand for port services given that corruption decreased the relative cost of imported in-

puts. The advantage of this methodology is that it provided an extremely rich dataset

that allowed the researchers to fully understand the extent, the magnitude and the reasons

for bribe payments along a chain of different bureaucratic procedures. It also provided

important insights into how corruption can introduce actual distortions in the economy by

having a real impact on different margins of firm behavior.

23

Sequeira (2011) applies the same methodology to investigate how corrupt practices re-

spond to organizational changes in opportunities for bribe extraction. The author exploits

an exogenous variation in tariff schedules that reduced opportunities for the extraction of

bribes at a specific stage of the clearance process (the payment of tariffs) to observe any

substitution or income effects that could displace corruption into other stages of the deliv-

ery of the public service. The study found that while the reduction in opportunities for the

most profitable method of bribe extraction - tariff evasion - was associated with an overall

decrease in the probability of bribe payments occurring, this was partially offset by the

displacement of corruption into other more extortionary, more coercive and less efficient

methods of bribe extraction. The setup and level of detail of the dataset enabled the author

to measure the magnitude of corruption, the patterns of bribe payments across different

types of shippers, shipments and bureaucrats, as well as the impact of policy changes that

affect just one method of bribe extraction in a long chain of procedures that constitute the

delivery of the public good.

The primary concern with relying on private agents to document bribes is the fact that

they may not have an incentive to truthfully report either the amount, the frequency or to

whom the bribe is paid to, for fear of punishment or shame. While these concerns cannot be

fully dismissed,Sequeira and Djankov (2010) find that the distribution of the correlates of

bribes across shipments and bribe recipients was very similar for all participating clearing

agents, the majority of whom were not aware of each other before or during the study,

and would therefore have limited opportunities to collude in fixing the data. Moreover,

the authors made clear from the onset that the main focus of the study was on measur-

ing the total costs of importing goods into each country, including all formal and informal

payments. Equal emphasis was therefore placed on collecting information on the charac-

teristics of the cargo and the tariff amounts due, as on the pattern of bribe payments. This

particular setup was also unique in the sense that there was limited stigma attached to the

payment of bribes to port or border officials, and clearing agents would perceive a bribe as

a payment made on behalf of their clients. As mere intermediaries, they felt limited moral

responsibility for their actions.

To directly test for Hawthorne effects, Sequeira (2011) conducts an experiment by ran-

24

domly assigning clearing agents to sequences of monitored and non-monitored data collec-

tion. The monitored sequences were conducted by locally-hired observers, who observed all

legal and illegal payments made to port and border officials. The observers had experience

in the shipping industry, and were therefore familiar with all clearance procedures. To avoid

any suspicion, they were also similar in age and appearance to any other clerk who normally

assists clearing agents in their interactions with port officials. The experiment yielded in-

teresting insights: shadowed clearing agents revealed a lower probability of paying a bribe

and reported lower bribe amounts on average, even when controlling for the characteris-

tics of the cargo, the client firm and clearing agent fixed affects. The general sense of the

observers who participated in the experiment was that their presence had indeed changed

the nature of the interactions between the clearing agent and the public official, inhibiting

certain illicit transactions. An extensive literature in psychology also shows that private

methods of interviewing yield higher reports of sensitive behavior. In particular, there is

growing evidence that self-administered questionnaires increase the willingness of respon-

dents to report sensitive behavior in a variety of settings (Bradburn and Sudman, 1979;

Groves, 1989; Waterton and Duffy, 1984; Weinrott and Saylor, 1991; Turner et al., 1983).

The intuition is that agents feel more at ease and more comfortable with gathering the

data themselves, without being directly observed in their interactions with public officials

Sequeira (2011). Understanding the nature, extent and implications of these Hawthorne

effects in different settings remains an important topic for future research.

A critical logistical constraint associated with this method of direct observation is that

it may require a long and at times difficult process of securing consent from a network of

actors in the field. The ease with which this can be done will vary from context to context,

and remain highly dependent on the levels of trust and openness that can be established

between researchers and subjects. Subjects may feel embarrassed to truthful report their

behavior or be concerned with the possible legal repercussions from disclosing sensitive in-

formation so surveying procedures that are able to take these motives into account in the

design and administration of the survey are more likely to succeed.

Despite these challenges, obtaining transaction-level data of bribe payments for a rep-

resentative sample of agents offers great promise to enable scholars to test more specific

25

theories of the micro-dynamics of corrupt behavior, and to better identify the distribution

of costs and benefits it may bring to the different players involved in bribery deals. Ob-

serving the entire chain of public service delivery also holds great promise for identifying

behavioral responses to policy changes, which may result in a displacement of corruption

across different methods of bribe extraction. Different methods of bribe extraction can

ultimately determine the overall costs corruption imposes on the economy.

IV. Measuring Corruption: an Agenda for Future Research

A. What we have learned

Corruption has for a long time been one of the most sensitive and elusive research topics

in social sciences. Despite the challenges, scholars have made major strides in developing

innovative and increasingly precise measures of corruption in recent decades. New meth-

ods have emerged, reflecting advances in experimental and quasi-experimental econometric

techniques, but also important changes in the way corruption itself is understood.

Earlier studies viewed corruption primarily as a barrier to trade, investment and growth.

The emergence of cross-country data on perceptions of corruption triggered an extensive

empirical literature, which substantiated some of these theoretical predictions. Perception-

based measures of corruption were however limited in their ability to explain the micro-

determinants of corruption or the full set of mechanisms through which corruption could

affect the economy. They were also unable to explain important within country variation

in the incidence of corruption across different public services or to differentiate between

different types of corruption (eg high level vs petty corruption, coercive vs collusive) and

the range of behavioral responses it can induce. The empirical literature was plagued with

difficult issues of causal identification, and as a result represented a poor basis for the design

of effective anti-corruption policies.

When corruption began to be understood as a broader development challenge, perception-

based data became ill-suited to answer most of the important questions that emerged.

Corruption was now viewed as an obstacle to the efficient and equitable delivery of public

services and as an impediment to the proper functioning of a broad set of institutions. The

26

analysis of the determinants and implications of corruption required a much richer and

more detailed set of measures of corrupt behavior than what was available.

A vibrant new strand in the empirical literature emerged based on the premise that

corruption is in fact more measurable than is often assumed, and that creative methods of

inquiry could help us peer into the actual black-box of corrupt behavior. Scholars made

significant inroads into measuring corruption through a crafty combination of direct and

indirect methods including self-reported survey data of both households and firms, detect-

ing gaps between official and survey data, or identifying statistical anomalies in secondary

data that suggested illicit behavior.

More recently, a transaction-based approach to corruption has led researchers to delve

deep into the complex environment of a particular bureaucratic process in order to under-

stand how corruption emerges, and the implications it may have for the different agents

involved in corrupt deals. The intuition is that an improved understanding of the micro-

dynamics of corrupt behavior and of the broader institutional and organizational setup in

which it takes place can then provide a more solid basis for policy action.

These extraordinary advances in the measurement of corruption have brought clarity,

meaning and direction to research on corruption. They have allowed us to begin to test

different theories of corruption, to better understand the institutional and organizational

setup that frames corrupt behavior, to measure the impact of corruption and to identify

the behavioral responses it may induce.

B. What we need to learn

Despite significant overall progress, challenges still remain. There are three main areas of

methodological development in the measurement of corruption that we see as being central

to pushing the empirical literature further.

The first big challenge is to better understand the relationship between direct, indirect

and perception-based measures of corruption, and to identify the different set of biases

and measurement error each method may carry. It is important to identify under which

circumstances each measure is likely to yield a more accurate reading of the magnitude and

shape of corruption.

27

The second big challenge is to identify sources of exogenous variation in institutional

setups and organizational rules, within or across countries, and develop appropriate mea-

sures that allow for a better understanding of the relationship between institutional context

and patterns of corrupt behavior. Conceivably, even field experiments could be designed

to test behavioral responses of corruption to changes in different types of rules, which may

affect some individuals or firms but not others. Researchers should also be sensitive to the

possibility that corruption can generate asymmetric responses among different agents (in-

dividuals or firms), and that this broader set of behavioral responses will have implications

for the overall efficiency costs and distributional implications of corruption. Understanding

the whole range, distribution and intensity of behavioral responses to different types of

corruption will certainly continue to figure prominently in the corruption research agenda.

Third, researchers should look more systematically at the conditions under which direct

methods of measuring corruption can be scaled up to allow for a more accurate estimation

of the determinants and consequences of corruption across different contexts.

Our discussion of the relative advantages and disadvantages of each method of mea-

suring corruption reveals that no single method alone is devoid of conceptual or logistical

challenges. The choice of method should ultimately be guided by a careful analysis of the

implicit conceptual and logistical trade offs. Perception-based indices or survey-based data

may be more suitable for identifying macro level correlates and trends in corruption across

countries, whereas methods involving direct observation of bribes may be more suited to

identifying the different types of corruption that can emerge in a given economy and its

distributional impact across agents. Market and statistical inference methods together

with measures based on gaps in administrative data are particularly suited to unveiling

the extent of corruption and illicit behavior in particular settings but are less capable of

suggesting specific means to eliminate such corruption. Their advantage lies in being the

cheapest and least cumbersome method relative to primary surveys or direct observation.

The most promising way forward however may perhaps lie in adopting a multiangular

approach, bridging macro and micro data on corruption and triangulating through an iter-

ative process between different direct and indirect methods of measuring corruption. This

triangulation can be guided by the comparative advantage of each method in any particular

28

setting, but also in some instances, constitute an important process of cross-validation of a

particular method.

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IntroductionThe Challenge of Measuring CorruptionThe Early Days: Measuring Perceptions of CorruptionSurvey-based Measures of CorruptionMinding G