CORRUPTION AND ELECTIONS: AN EMPIRICAL STUDY FOR A CROSS-SECTION OF COUNTRIES

CORRUPTION AND ELECTIONS: AN EMPIRICAL STUDYFOR A CROSS-SECTION OF COUNTRIES

STEFAN KRAUSE AND FABIO MENDEZ�

In this paper, we study whether voters are more likely to ‘‘vote out’’ acorrupt incumbent than to re-elect him. Specifically, we examine whetherthey retract their support from political candidates who they think arecorrupt by looking at changes in an index of corruption perceptionsbetween the current and the last elections. Our results suggest thatcorruption in public office is effectively punished by voters. Further-more, our findings support the idea that both the political system and thedemocratic experience are important determinants of the voters’ reactionand control of corruption; while voters in countries with parliamentarysystems or with relatively low levels of democracy react negatively to anincrease in corruption, no perceptible effect of this kind was found incountries with mature democracies, and the evidence is inconclusive inthe case of countries with presidential systems.

1. INTRODUCTION

WHETHER CORRUPT politicians are held accountable for their actions isimportant for preventing bad governance and for the functioning of demo-cratic societies. In general, greater political accountability is regarded asbeneficial, for it helps to narrow the gap between the citizens’ objectives andthe politicians’ choices (see e.g. Fackler and Lin, 1995; Ferejohn, 1986;Lederman et al., 2005; Persson et al., 1997; Wittman, 1989).

In modern democracies, citizens are able to vote against corrupt publicofficials and force them out of office. Yet, as discussed by Peters and Welch(1980) and Rundquist et al. (1977), there are several reasons why votersmight choose to re-elect a corrupt incumbent. For example, it is possible thatvoters may be willing to endure a corrupt representative in exchange forperiods of general economic prosperity. It is also possible that voters hold onto predetermined opinions about their politicians and disregard (or dis-count) common indications of corrupt behavior, or that voters are simplynot well informed about the incumbent’s actions. Alternatively, voters maysee corruption as a personal flaw and while they would not support a corruptcandidate, they would still be willing to vote for that candidate’s party.

�Corresponding author: Fabio Mendez, Department of Economics, Business Building Room402, University of Arkansas, Fayetteville, AR 72701, USA. E-mail: [email protected]. Stefankrause, Senior Economic Researcher, Banque de France. E-mail: [email protected]. The views expressed in this article are those of the authors, and do not necessarily reflectthose of either the Banque de France, or the Eurosystem.

r 2009 The Authors. Journal compilation r 2009 Blackwell Publishing Ltd.,9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA02148, USA. 179

ECONOMICS & POLITICS DOI: 10.1111/j.1468-0343.2008.00341.x

Volume 21 July 2009 No. 2

mailto:[email protected]




In this paper, we present empirical evidence from a cross-section ofcountries and study how changes in the perceived level of governmentcorruption affect the total amount of votes obtained by an incumbent. Morespecifically, we examine whether voters retract their support from politicalincumbents who they think are corrupt and whether voters are more likely to‘‘vote out’’ a corrupt politician than to re-elect him.

Similar studies analyze the effects of corruption charges on electoral re-sults using data for a single country. Peters and Welch (1980), for example,study the electoral impact of corruption charges on candidates in contest forthe U.S. House of Representatives. They estimate that candidates accused ofcorruption suffer a loss ranging between 6% and 11% of the expected vote.Similarly, Chang and Golden (2004) find that charges of corruption sig-nificantly decrease the re-election probability for Italian congressmen. Inturn, Fackler and Lin (1995) collect news stories and report a negativecorrelation between the amount of information about corruption and theelectoral support for the party in control of the presidency in the UnitedStates. Ferraz and Finan (2005) report similar results for the case of Brazil.

One difference between our paper and these previous studies is that we use across-sectional sample of countries, instead of looking at electoral results from asingle country alone. In particular, our data are obtained from 107 elections thattook place in 35 countries between 1995 and 2007. The sample includes electionsheld by 14 European countries, three North American countries, nine Centraland South American countries, six African countries, and three Asian countries.

By using a cross-sectional sample, we are able to test whether the elec-torate’s control of corruption is greater in societies with parliamentarysystems of representation than in societies with presidential systems. We arealso able to test whether the electorate’s control of corruption is greater incountries with a longer exposure to democratic traditions. Both of these testsare motivated by previous studies in the literature.

Lederman et al. (2005), for example, report that corruption is lower incountries with parliamentary systems, and also in countries where demo-cracy has gone uninterrupted for a number of years. Treisman (2000) alsoreports a negative correlation between long exposure to democracy and cor-ruption. A logical explanation for their findings is that citizens in countrieswith parliamentary systems and mature democratic traditions are more likelyto ‘‘vote out’’ corrupt incumbents.1 In this paper, we investigate whether suchan explanation is consistent with the evidence from electoral results.

Another important distinction between this paper and the previous lit-erature is that we use a measure of perceived corruption instead of accountsof actual corrupt acts. Hence, our measure of corruption does not neces-sarily reflect the behavior of the incumbent, but the voters’ perception of his

1Ferejohn (1986), for example, presents a theoretical model where the voters’ control on officeholders depends on the political regime assumed.

180 KRAUSE AND MENDEZ

r 2009 The AuthorsJournal compilation r 2009 Blackwell Publishing Ltd.

behavior. Noticeably, because it is the voters’ beliefs (regardless of theirveracity) that actually determine their vote, using corruption perceptionsas an explanatory variable of voting behavior is preferable to using theincumbent’s history of corruption charges.

When using the incumbent’s record of actual or alleged corruption, legit-imate concerns arise with regard to how effectively it can be used in a votingstudy. For example, one could question whether the information collected bythe researcher corresponds with that available to the voters, whether themedia informed accurately and effectively, or whether any of these records canactually change the voter’s opinion of the incumbent. When using perceptionmeasures directly, these types of concerns do not come up.

The particular index of corruption perceptions used in this study is theCorruption Perceptions Index (CPI) from Transparency International (TI),which we describe in more detail in section 2. Ideally, for the purposes of thisstudy, the perceptions index used would include corruption perceptionsof local voters only. Instead, the surveys used by TI to construct the CPIinterview a mix of local resident and non-resident experts.

The Transparency International Annual Report states that ‘‘residents’viewpoints correlate well with those of non-resident experts,’’ but there is noseparate treatment for local perceptions and, to our knowledge, there is noother measure of corruption perceptions that report local opinions alone. Inthis regard, our standpoint is that the corruption perceptions reported by theCPI are likely to be highly correlated with the local voters’ perceptions.Nonetheless, we acknowledge that using the CPI as our independent variablemay introduce measurement errors. We discuss this issue further in section 4.

In what follows, we estimate a general voting function in which politicaland economic variables enter simultaneously as determinants of voting be-havior. The results of the paper regarding the effects of the economic vari-ables on the votes received by the incumbent are consistent with those ofprevious studies in the literature: higher output growth and lower inflationincrease the incumbent’s support (see Lewis-Beck and Stegmaier, 2000;Persson and Tabellini, 1999, for a discussion of these issues). In turn, withregard to the effects of changes in the level of perceived corruption on theelectoral support for the incumbent, we find that an increase in perceivedcorruption is positively associated with a loss of votes in the general sample.Thus, our results suggest that corruption in public office (or the perceptionthereof ) is effectively punished by voters at the same time that good eco-nomic conditions are rewarded.

Furthermore, our results support the idea that both the political systemand the democratic experience are important determinants of the voters’reaction and control of corruption. While our findings suggest that votersreact negatively to higher corruption levels in countries with parliamentarypolitical systems, in countries with presidential systems the evidence is lessconclusive. As for the democratic experience, we find that increased

181CORRUPTION AND ELECTIONS


corruption is punished only in countries with a relatively short exposure todemocracy, with no perceptible effect in mature democracies.

This paper complements the ample literature on economic voting, whichcan be traced back to Fair (1978, 1982), Kramer (1971), Stigler (1973), andother previous studies.2 The debate on how and whether economic factorsaffect voting is rich. Here, however, we turn to this literature only for ourpurpose of studying the effects of corruption on electoral results. The paperis also related to a smaller literature that studies the effects of the qualitativecharacteristics of the incumbent on the elections. Kulisheck and Mondak(1996) and McCurley and Mondak (1995), for example, examine how thequality and integrity of the incumbent affect an individual voter’s decisions.Kulisheck and Mondak (1996) report experimental results, whereasMcCurley and Mondak (1995) use individual-level data.

The remainder of the paper is organized as follows: section 2 provides adetailed description of the dataset used for this study. Section 3 discusses theeconometric specifications used. Section 4 shows the estimation results and,finally, section 5 concludes.

2. DATA DESCRIPTION

The data used in the empirical analysis include 35 countries and cover yearsbetween 1995 and 2007. For each electoral round, we collected data for thepolling results, and the political and economic conditions that characterizedit. We collected data from 107 elections held by 14 European countries, threeNorth American countries, nine Central and South American countries, sixAfrican countries, and three Asian countries. Out of our sample, 19 coun-tries have a parliamentary system and 16 have a presidential system. Tables1a and 1b show a descriptive summary of all variables of interest. All sourcesand variable definitions are described in detail in Appendix A.

An effort was made to obtain data from as many countries and electoralperiods as possible. As is common in voting studies with cross-sectional data,however, the sample size was limited by the number of countries that haveexperienced stable democratic and electoral processes within the time frameexamined. Others like Lewis-Beck and Mitchell (1990), Paldam (1991), andPowell andWhitten (1993), for example, used samples of 5, 17, and 19 countries,respectively. In our particular case, the sample size is also restricted by theavailability of corruption perception measures before 1995 (the CPI index wasfirst reported in 1995) and, since our analysis focuses on changes in electoralvotes, by the availability of at least two consecutive election periods per country.

Data on political parties and electoral results were obtained from threemain sources: the Dataset of Political Institutions (DPI) introduced by Becket al. (2001), the Political Dataset of the Americas managed by the Center

2See Kramer (1971) for a review of earlier studies on this matter.



TABLE1A

SUMMARYSTATISTIC

S–A

VERAGES

PERG

OVERNMENTPERIO

DFOREACHC

OUNTRY(C

OUNTRIE

SWIT

HAPARLIA

MENTARYSYSTEM)

Country

Dem

.

index

Votesfor

incumbent

(%)

Corruption

Perceptions

Index

GDP

growth

(%)

Consumer

price

inflation

(%)

Years

in

power

Party

ideology

Incumbent

seats

(%)

Fractionalization

(%)

No.of

elections

Austria

10.00

32.23

7.72

1.80

1.85

14.00

0.40

60.38

45.04

5

Belgium

10.00

15.25

6.64

2.04

1.70

10.50

1.00

58.66

78.26

3

Botswana

5.22

53.00

6.05

5.48

8.12

33.00

1.00

82.50

0.00

2

Canada

10.00

38.35

8.42

2.61

1.83

7.67

0.25

56.38

0.00

4

Denmark

10.00

32.67

8.13

1.70

2.14

4.67

0.50

44.57

36.84

4

Finland

10.00

24.40

7.80

3.15

1.28

5.33

0.50

66.88

67.25

4

Germany

10.00

38.12

6.20

1.28

1.47

9.00

0.50

51.01

32.69

4

Greece

7.16

42.43

6.72

3.43

3.87

9.00

0.00

53.15

0.00

3

Hungary

2.58

36.93

6.15

4.03

12.71

4.00

0.00

59.58

34.25

4

India

8.29

22.95

2.85

4.32

3.91

5.00

0.50

55.16

61.36

2

Japan

9.45

34.01

6.32

1.12

�0.04

6.67

0.75

54.12

16.25

4

TheNetherlands

10.00

25.37

8.86

1.81

2.26

5.33

0.50

59.33

61.16

4

Norw

ay

10.00

22.23

6.96

2.50

2.01

5.33

0.50

34.54

35.86

4

Portugal

4.98

39.78

7.20

1.65

3.09

5.33

0.50

50.07

6.98

4

Spain

4.65

41.38

5.44

2.69

2.85

6.00

0.67

52.00

12.47

3

Sweden

10.00

38.90

7.52

2.54

1.08

8.00

0.25

51.81

29.17

4

Switzerland

10.00

22.53

6.95

0.87

0.75

6.00

0.33

82.36

74.17

3

Turkey

7.13

14.08

3.65

1.55

69.18

3.50

0.33

50.81

56.13

3

United

Kingdom

10.00

39.95

6.10

2.42

2.54

6.00

0.33

63.19

0.00

3



TABLE1B

SUMMARYSTATISTIC

S–A

VERAGES

PERG

OVERNMENTPERIO

DFOREACHC

OUNTRY(C

OUNTRIE

SWIT

HAPRESID

ENTIA

LSYSTEM)

Country

Dem

.

index

Votesfor

incumbent

(%)

Corruption

Perceptions

Index

GDP

growth

(%)

Consumer

price

inflation

(%)

Years

in

power

Party

ideology

Incumbent

seats

(%)

Fractionalization

(%)

No.of

elections

Argentina

3.69

44.00

5.07

1.04

0.76

10.00

1.00

62.12

0.00

2

Brazil�

4.67

46.43

5.82

0.95

13.06

5.33

0.25

60.51

0.00

4

Chile

4.42

49.97

8.21

3.54

4.87

13.00

1.00

55.00

0.00

3

Colombia

6.58

57.63

6.90

2.31

6.11

4.00

0.50

10.00

0.00

2

CostaRica

10.00

31.90

6.64

2.45

11.08

6.00

0.67

40.35

0.00

3

ElSalvador

3.11

54.84

4.35

0.44

2.10

15.00

1.00

57.14

0.00

2

Ghana

1.13

50.90

3.55

2.68

21.76

4.00

0.50

52.00

0.00

2

Guatemala

2.87

33.51

5.65

0.17

6.78

4.00

0.50

55.75

0.00

2

Honduras

2.98

48.81

5.73

0.64

9.80

6.00

1.00

50.00

0.00

3

Kenya

0.91

35.60

2.06

�0.08

6.03

24.00

0.00

50.95

0.00

2

Malawi

1.24

44.15

3.45

�0.78

24.28

10.00

1.00

48.43

0.00

2

Mexico

1.55

41.03

6.22

1.39

13.46

15.50

0.33

42.18

0.00

3

Nigeria

1.96

62.30

1.75

0.11

11.34

4.00

0.50

61.25

0.00

2

Tanzania

0.40

75.95

2.70

4.79

3.66

9.00

0.00

91.04

0.00

2

United

States

10.00

49.06

6.39

2.25

2.35

6.00

0.33

50.52

0.00

3

Uruguay

6.31

26.57

3.75

0.20

15.85

7.50

0.67

91.12

0.00

3

Note:� M

ixed

system

withpresidentialelections.



for Latin American Studies at Georgetown University in collaboration withthe Organization of American States, and the Database for EuropeanPolitical Parties and Elections. Psephos Adam Carr’s election archive wasalso consulted.

Electoral systems were broadly classified as Parliamentary or Presidentialfollowing the DPI’s classification. For presidential systems, the incumbent’svotes correspond to the votes obtained by the party with which the in-cumbent president is associated. For parliamentary systems, the incumbent’svotes correspond to the votes obtained by the party with the largest presencewithin the government (see Anderson, 2000; Chappell and Goncalves Veiga,2000, for two papers that discuss how the clarity of political responsibility isrelevant in this context).

Notice that according to this definition, the incumbent party in a parlia-mentary system may well not constitute the party with the greatest amountof seats. In parliamentary systems, whenever a number of small partiescollude to form a coalition government, the party that obtains more seats isnot necessarily the one who is in charge of conducting policy (and istherefore blamed for good or bad performance). Thus, defining the incum-bent in this way has the advantage of assigning responsibility to the actualpolicy-maker.

For both systems, we recorded the percentage of the votes obtained by theincumbent as well as the percentage of votes obtained by that same party inthe previous elections (when it came to power). We also collected informa-tion on the percentage of parliamentary seats the incumbent’s party con-trolled at the time of the elections, and information on ideologicalidentification to create a dummy variable taking the value of 0 for left-oriented parties and 1 for right- or center-oriented parties. In addition, weuse a measure of the length of the electoral cycle (in number of monthsbetween elections) and the degree of fractionalization of the ruling govern-ment, as defined by the probability that two random draws from parliamentwould produce legislators from different parties (Beck et al., 2001).

To capture the exposure to democratic institutions, we classify countries as‘‘mature’’ or ‘‘new’’ democracies. In order to do so, we use annual measures forinstitutionalized democracy (DEMOC), available from the Polity IV datasetand developed by Marshall and Jaggers (2002). The DEMOC indicator isbased on an additive 11-point scale (0–10). We average these scores over theperiod 1949–2003 for each of the 35 countries in our sample and identify‘‘mature’’ democracies with countries for which the average value forDEMOCis equal to 10, and include Japan, for which the value equals 9.45. Similarly, weidentify ‘‘new’’ democracies with countries for which the average value ofDEMOC ranges between 0.40 (Tanzania) and 8.29 (India). There are 14countries classified as ‘‘mature’’ and 21 countries classified as ‘‘new.’’

In turn, for measuring changes in corruption perceptions we use the CPIfrom TI. The CPI is a composite index that draws on 12 different polls from



nine independent institutions and scores countries on a scale from 0 to 10,with 0 indicating high levels of perceived corruption and 10 indicating lowlevels of perceived corruption. The CPI ‘‘draws on multiple expert opinionsurveys that poll perceptions on public sector corruption’’ and the corrup-tion of politicians (TI, press release 2006). As of 2006, the CPI has thegreatest scope of countries of any perception index available (163 countries),and has been used in multiple empirical studies (see e.g. Herzfeld and Weiss,2003; Persson et al., 2003).

For our purposes in this paper, we are interested in measuring whetherperceived corruption has increased during the incumbent’s tenure. Thus,we use yearly CPI values to calculate the change in CPI between the timethe incumbent took office and the time the elections take place. That is,we create the variable PCI (perceived corruption increase), which is definedas PCI¼ � (CPItþ e�CPIt), where subscript e represents the number ofyears between elections. A positive value for PCI corresponds to a perceivedincrease in corruption, while a negative value corresponds to a perceiveddecrease in corruption.

Finally, data for all the economic variables, namely GDP growth, infla-tion, and unemployment, were obtained from the World Bank’s WorldDevelopment Indicators database (2006). In the empirical section, we use theannual indices of each economic indicator averaged over the duration of theelectoral cycle in question.

3. MODEL SPECIFICATIONS

For the econometric specification, we adopt the standard voting functiondeveloped in the literature (see Lewis-Beck and Stegmaier, 2000; Paldam,1991; Powell and Whitten, 1993). The dependent variable is the gain in theshare of votes received by the incumbent party with respect to the previouselection, and the independent variables are selected from a list of economicand political factors. We modify this specification by introducing perceivedcorruption or changes thereof as explanatory variables.

We use measures of GDP growth and consumer price inflation as theeconomic factors in our set of explanatory variables. All of these measurescorrespond to the annual indices of each economic indicator, averaged overthe duration of the electoral cycle in question. Our choice of economic ex-planatory variables is comparable to that of Erickson (1989), Powell andWhitten (1993), Remmer (1991), and others. Our choice of economic ex-planatory variables, however, does not influence our main results regardingthe effects of corruption.3

3In some specifications, we also control for the behavior of unemployment. However, forsome countries and periods this information is not available, and so we do not report thoseresults in the paper. Our main findings remain unaltered, with unemployment entering theregressions with insignificant coefficients.



In turn, the political factors included as explanatory variables are: ameasure of absolute government support, a measure of the length of theincumbent’s tenure (in years), the ideological classification of the incumbent,the number of parliamentary seats controlled by the incumbent, and thedegree of fractionalization in the government. Below, we provide someintuition for why these controls are important. As we discuss in section 4,however, our results are robust to the inclusion of these variables.

We include the percentage of votes obtained by the incumbent in theprevious election in order to control for absolute government support. Asnoticed by Powell and Whitten (1993), ‘‘a loss of two percentage points maymean something different for a government that won 40% last time ascompared with a government that won 60% last time.’’ Thus, since differentparties have different electoral bases that remain stable over time, includingthis control variable is essential to the specification. We expect its coefficientto be negative as it is easier to lose an absolute percentage of the votes from alarger base.

In a similar fashion, we include a measure of the length of the incumbent’stenure (in years) in order to capture the depletion in government supportthat appears as the government ages and the initial popularity of thegovernment vanishes. Such loss of popularity has been previously docu-mented by authors like Goodhart and Bhansali (1970) and Paldam (1986).Since corruption may change as the end of the political tenure approaches,including the effects of the length in tenure may be relevant for ourestimation.

Finally, we also include a political ideology dummy and two variables thatcapture the cohesion of the government. Left- and right-leaning parties tendto have different preferences and approaches to economic policy, and votersmight take these historical trends into account when evaluating governmentperformance. Likewise, as explained by Lewis-Beck and Stegmaier (2000),the greater the perceived cohesion of the incumbent’s government, the morelikely voters are to charge the incumbent with the responsibility of recentpolicies and, thus, of any perceived corruption. The dummy variable takesa value of 1 for right- or center-oriented parties and a value of 0 for left-oriented parties. The variables used to capture government cohesion are thedegree of government fractionalization and the number of congressionalseats controlled by the incumbent at the time of the election.

For the purposes of this paper, however, the explanatory variables thatcapture most of the discussion are the PCI and the level of perceived cor-ruption at the time of the elections. In most of our estimations, we choose toinclude the perceived increase in government corruption (the PCI measureexplained before) as the explanatory variable. The logic behind our choice issimple: as with income growth and price inflation, we anticipate that votersevaluate the incumbent’s performance based on whether government cor-ruption improved during his tenure. We expect a decrease in perceived



government corruption to be valued positively by voters, and an increase inperceived government corruption to be valued negatively.

In addition, we sometimes estimate an alternative specification that usesthe level of perceived corruption at the time of the elections as the ex-planatory variable. Including the level of perceived corruption instead of thechange in perceived corruption seems more consequent with influentialmodels of political accountability such as those of Ferejohn (1986) andPersson et al. (1997). In these models, the voters monitor the incumbent’sperformance and decide to re-elect him if the perceived level of effort (in-terpreted as the opposite of rent extraction) is high enough.

Noticeably, however, while the models presented by Ferejohn (1986) andPersson et al. (1997) intend to explain the probability of re-election, thedependent variable in our study is the change in votes received by the in-cumbent (regardless of whether he wins re-election). Thus, although ourempirical specification is clearly related to those theoretical models, it doesnot provide an empirical test for their validity.

The econometric specification can then be summarized by the followingequation:

Votesch ¼ aþ bCorruptionþ d~E þ g~Pþ e; ð1Þ

where Votesch is the absolute change in the percentage of the popular votecaptured by the incumbent in any election with respect to the previouselection; ~E is the vector of economic variables; ~P is the vector of politicalvariables; and Corruption enters the equation as either the PCI or the level ofcorruption at the time of the elections.

4. EMPIRICAL ANALYSIS AND RESULTS

Table 2 reports some interesting facts regarding the electoral results in oursample. As shown in this table, the loss of support experienced by the in-cumbent is much greater in those elections for which the perceived amountof corruption had increased than in those for which the perceived amount ofcorruption had decreased. For the total sample, the average loss of votesreceived by the incumbent (measured as the share of total votes) whenperceived corruption had increased was 7.1, compared with an average lossof only 1.2 when perceived corruption had decreased. Similar observationscan be made across all subsamples examined.

Interestingly, however, whether such a loss of votes is sufficient to defeatthe incumbent seems to depend on the political system. In countries with aparliamentary system, the incumbents were defeated 63% of the times whenthe perceived level of corruption had increased, and only 38% of the timeswhen the perceived level of corruption had decreased. A similar (but lessobvious) difference is observed in the mature and new democracies’ sub-samples, but for countries with presidential systems the trend is reversed.



Similarly, Table 3 presents some descriptive statistics regarding the level ofperceived corruption at the time of the elections and the change in corrup-tion perceptions between elections or PCI (measured in absolute value). Asshown, countries with parliamentary systems reported an average perceivedcorruption level of 7.51. This is more than three points higher than the 4.07reported in countries with presidential systems. In turn, mature democraciesreported an average perceived corruption level of 8.20, while new demo-cracies reported an average of 4.31.

In both cases, a simple test of differences in means suggests that the re-spective averages from both sample splits are significantly different (to the1% level in both cases). Thus, given that a higher number in the CPI indexindicates less corruption, the observations from our sample are consistentwith those of Lederman et al. (2005) and Treisman (2000). As mentionedbefore, these authors report that countries with presidential systems andshorter exposure to democracy tend to exhibit a higher degree of corruption.

In contrast, the average change in perceived levels of corruption betweenelections does not seem to vary across countries with different systems ofrepresentation or different exposure to democracy. For the total sample,

TABLE 2 CORRUPTION AND VOTING RESULTS

Parliamentary

system

Presidential

system

Mature

democracies

New

democracies

Average vote-share loss when

corruption increased �5.12 (5.44) 10.26 (12.38) 5.91 (8.62) 8.11 (9.38)

Average vote-share loss when

corruption decreased�0.82 (5.95) 2.51 (10.08) 1.96 (5.54) 0.22 (9.30)

Incumbent defeated when corruption

increased (frequency in %)

63 33 50 52

Incumbent defeated when corruption

decreased (frequency in %)

38 44 40 41

Note: �Standard deviations in parentheses.

TABLE 3 CORRUPTION PERCEPTIONS

Parliamentary

system�Presidential

system�Mature

democracies�New

democracies�

Average Corruption Perceptions

Index (CPI) at the time of the

elections

7.51 (1.88) 4.07 (1.78) 8.20 (1.38) 4.31 (1.62)

Average increase in corruption

perceptions (absolute value)

0.40 (0.45) 0.57 (0.54) 0.39 (0.38) 0.52 (0.58)

No. of countries 19 16 14 21

Note: �Standard deviations in parentheses.



the average change in corruption perceptions was 0.45, with a standarddeviation of 0.48, when measured in absolute values. The minimum PCIvalue was a negative 2.29 (Spanish elections of 2000) and the maximum PCIvalue was a positive 2.24 (Argentinean elections of 1999).

Before we turn to our empirical findings, it is important to acknowledgethat the CPI may be measured with error. Admittedly, we have no way ofverifying whether or not there exists a reporting bias when constructing theindex. As documented by Kaufmann and Kraay (2008), this is an issue thatapplies to governance indicators in general. For corruption indices in par-ticular, they argue that, whenever two indices measure the same concept oftransparency and corruption, their correlation can be interpreted as a meansof establishing the degree to which measurement error is present. Kaufmannet al. (2004) find that the estimates of corruption based on the TI CPI indexand their own Control of Corruption Indicator have a correlation above 0.9.While, as the authors clearly indicate, the similarity between these two in-dicators may be the outcome of ‘‘two offsetting biases in the TI methodol-ogy,’’ we can argue that the fact that these indices are statistically closelycomparable could signify that potential measurement errors would be of arelatively small magnitude.

The results of our econometric estimations4 are shown in Tables 4–7.Table 4 displays the results of estimating equation (1) using least-squaresestimation for the entire sample. Three alternative specifications are used inthis table: one with economic variables only, one with political variablesonly, and one with both political and economic variables. We estimate eachof these alternative specifications twice: first with the PCI as an explanatoryvariable, and then with the perceived level of corruption at the time of theelections as the explanatory variable.

The results of these estimations indicate that PCIs are associated withfewer votes for the incumbents. More specifically, a PCI of 1 point isassociated with a decrease in the incumbent’s share of total votes ofapproximately 3 percentage points. The estimated coefficients for the PCIshown in Table 4 range from � 3.04 to � 3.59 and they are statisticallysignificant at a 1% level across the different econometric specifications.

In general, one cannot tell whether PCIs alone will generate a loss of votesthat is substantial enough to defeat the incumbent, as the final result of theelections depends on many variables. Given these results, however, we thinkthere are at least two reasons to believe that PCIs play a determinant role indemocratic elections. First, although changes in perceived corruption arerarely dramatic (the average change in corruption perceptions in our sampleis 0.45), the loss of votes that is necessary for the incumbent to be defeated is

4Tables 4–7 report the number of observations used in the estimations. Because we use thechanges in electoral results as our dependent variable, the number of observations is smallerthan the number of elections covered by our sample.



TABLE4

DEPENDENTV

ARIA

BLE:C

HANGE

INV

OTES

OFIN

CUMBENT

(POOLEDR

EGRESSIO

N:ENTIR

ESAMPLE)

Economic

variablesonly�

Politicalvariablesonly�

Economic

and

politicalvariables�

Perceived

CorruptionIncrease

(PCI)

�3.21(0.00)

�3.59(0.00)

�3.04(0.00)

Corruptionlevel

0.06(0.89)

0.61(0.23)

�0.08(0.85)

GDPgrowth

2.29(0.00)

2.41(0.00)

2.25(0.00)

2.41(0.00)

Inflation

�0.12(0.00)

�0.12(0.02)

�0.12(0.00)

�0.13(0.02)

Votesincumbent(previouselection)

�0.03(0.67)

�0.05(0.53)

0.01(0.22)

0.22(0.19)

0.14(0.32)

0.11(0.44)

Years

inpower

�0.04(0.76)

�0.10(0.43)

�0.12(0.31)

�0.19(0.11)

Partyideology

�1.9

(0.3)

�1.53(0.46)

�0.04(0.97)

�0.41(0.81)

Incumbentseats

�0.05(0.52)

�0.03(0.69)

�0.03(0.65)

�0.02(0.79)

Fractionalization

0.10(0.11)

0.10(0.13)

0.08(0.17)

0.08(0.14)

R2

0.27

0.21

0.14

0.09

0.31

0.25

F-statistic

13.01

7.89

3.12

1.10

6.58

4.45

Number

ofobservations

72

72

72

72

72

72

Note:� p

-Values

computedusingrobust

standard

errors

are

inparentheses.



also small, depending on how competitive the elections are. The medianvalue of the incumbent’s loss of votes for all elections was only � 1.5 forAfrican countries, � 2.79 for North American countries, � 2.86 for Eur-opean countries, and 7.1 for Central and South American countries.

TABLE 5 DEPENDENT VARIABLE: CHANGE IN VOTES OF INCUMBENT

(POOLED REGRESSION: PARLIAMENTARY VS. PRESIDENTIAL SYSTEMS)

Parliamentary system� Presidential system�

Economic

variables All variables

Economic


Perceived Corruption

Increase (PCI)

� 2.72 (0.00) � 3.10 (0.00) � 3.84 (0.02) � 4.18 (0.08)

GDP growth 2.08 (0.00) 1.9 (0.00) 2.04 (0.26) 2.08 (0.31)

Inflation � 0.14 (0.00) � 0.15 (0.00) � 0.09 (0.73) � 0.08 (0.74)

Votes incumbent

(previous election)

� 0.16 (0.02) � 0.30 (0.06) 0.38 (0.25) 0.39 (0.29)

Years in power 0.08 (0.58) � 0.11 (0.79)

Party ideology � 1.28 (0.41) 2.16 (0.7)

Incumbent seats 0.007 (0.90) � 0.02 (0.84)

Fractionalization � 0.04 (0.43)

R2 0.41 0.43 0.24 0.26

F-statistic 8.40 4.03 5.96 4.35

Number of observations 48 48 24 24

Note: �p-Values computed from robust standard errors are in parentheses.


(POOLED REGRESSION: ‘‘MATURE’’ VS. ‘‘NEW’’ DEMOCRACIES)

Mature democracies� New democracies�

Economic


Economic



Increase (PCI)

� 0.76 (0.57) � 0.519 (0.77) � 3.33 (0.00) � 3.14 (0.01)

GDP growth 1.01 (0.23) 1.00 (0.33) 3.00 (0.00) 3.12 (0.00)

Inflation � 1.92 (0.06) � 1.84 (0.08) � 0.06 (0.19) � 0.07 (0.2)

Votes incumbent

(previous election)

� 0.04 (0.60) � 0.03 (0.87) 0.08 (0.4) 0.10 (0.57)

Years in power � 0.06 (0.79) � 0.22 (0.27)

Party ideology � 0.10 (0.97) 0.28 (0.92)

Incumbent seats 0.06 (0.53) � 0.10 (0.23)

Fractionalization 0.002 (0.97) � 0.004 (0.96)

R2 0.39 0.40 0.44 0.50

F-statistic 1.33 0.95 20.24 14.38

Number of observations 38 38 34 34




Second, it is likely that the results presented in Table 4 underestimate theimpact of PCIs on the electoral votes. Several papers have shown how anincrease in perceived corruption can be detrimental for investment andsubsequently growth (see e.g. Mauro, 1995; Mendez and Sepulveda, 2006).Thus, when an increase in perceived corruption occurs, it is likely to cause anadditional loss of votes through its effect on the prevailing economic con-ditions. Such indirect effects are not captured by our estimations.

When the alternative specification was used instead and the level of cor-ruption at the time of the elections was included as the explanatory variable,the estimated coefficient was never statistically different from zero. The levelof perceived corruption at the time of the elections alone is not a goodindication of the voters’ evaluation of an incumbent’s performance. Thus,compatible with our initial intuition, the results presented in Table 4 suggestthat voters increase (or decrease) their support of an incumbent based onwhether their perceived level of government corruption has improved,without regard to the existing level of perceived corruption at the time ofthe elections. In what follows, we continue to use the change PCI as ourindependent variable.

With respect to the role of economic performance, we find that higherGDP growth rates are associated with increases in votes for the incumbent,while higher inflation is correlated with a decrease in voters’ support. Bothcoefficients are significant at the 1% level in all specifications. Our findingsare consistent with previous studies that have reported a connection betweenthese economic variables and both the popularity of the government and thevotes obtained by the incumbent (see e.g. Paldam, 1991; Powell andWhitten,1993; Remmer, 1991).5


(COUNTRY-SPECIFIC RANDOM EFFECTS REGRESSION)

Parliamentary

system�Presidential

system�Mature

democracies�New

democracies�


Increase (PCI)

� 2.87 (� 0.01) � 3.69 (0.24) � 0.82 (0.66) � 3.19 (0.06)

GDP growth 1.84 (0.00) 2.85 (0.09) 0.96 (0.33) 2.98 (0.00)

Inflation � 0.11 (0.02) � 0.12 (0.71) � 1.96 (0.00) � 0.09 (0.29)

R2 0.36 0.18 0.39 0.43

Wald w2 24.46 (0.00) 4.44 (0.22) 21.98 (0.00) 22.93 (0.00)

No. of observations 48 24 38 34


5See Lewis-Beck and Stegmaier (2000) for additional evidence in the case of U.S. elections;Nordhaus et al. (1989) for evidence on inflation and unemployment performance; and Abramsand Butkiewicz (1995) for an analysis of how state-level economic conditions have incidence onpresidential elections.



In turn, with regard to the role of political factors, we do not observe areduction in the incumbent party’s support base, as discussed by Powell andWhitten (1993), or a weardown effect, as identified by Paldam (1991). Nei-ther the votes obtained in the previous elections by the incumbent nor thelength of their tenure seem to have a significant outcome on the change invoters’ support, albeit they do enter the regression with the expected negativecoefficients. A potential explanation for this discrepancy with the findings ofPaldam (1991) and Powell and Whitten (1993) is that, while their studiescover elections in industrialized countries, our sample also takes intoaccount elections in emerging markets and transition economies.

In Tables 5 and 6, we examine whether differences in the political systemcan be used to predict the strength with which voters penalize corruption.For this purpose, the sample was divided into smaller subsamples. In Table5, the sample is divided between countries with parliamentary systems ofrepresentation and countries with presidential systems. In Table 6, thesample is divided between new and mature democracies. As before, eachtable presents the results of estimating two alternative specifications: the firstincludes only economic variables (GDP growth and inflation) as explanatoryvariables, while the second incorporates political variables as well.

As shown in Table 5, splitting the sample between countries with parlia-mentary and presidential systems does not seem to alter the results we ob-tained when considering the entire sample: a PCI, lower GDP growth, andhigher inflation are all significantly correlated with a loss of votes by theincumbent. These results are robust to controlling for political variables. Asin the case of the entire sample, the political control variables do not appearwith significant coefficients; the only exception is the percentage of votes theincumbent received in the previous election, which enters the regression witha negative sign for countries with parliamentary systems. Thus, for thissubsample we do observe a reduction in support due to a larger base, con-sistent with the findings of Powell and Whitten (1993) that use a samplecomposed mainly of countries with parliamentary systems.

As a robustness check, in Table 7 we allow for country-specific randomeffects, in order to verify whether the results are driven by changes withineach country.6 For countries with parliamentary systems, a PCI is sig-nificantly associated with a loss of votes (at the 1% level), as reported in thefirst column of Table 7. In turn, for the subsample of countries with pres-idential systems, we find that the coefficient on the PCI becomes non-significant (second column, Table 7).

In this regard, it is possible that extreme values for inflation in somecountries with presidential systems may be responsible for a lack of precision

6Given that for several countries in our sample we only have two elections (and, as a result,only one observation of PCI), we opted to perform country-specific random effects instead offixed effects, to avoid the further loss of degrees of freedom.



in the estimates. Thus, in order to account for such a possibility, we re-estimated the regressions in Table 7 using a transformed rate of inflationgiven by TRI¼ p/(pþ 1). The results remained almost identical.7 This leadsus to note that the evidence of punishment by voters in presidential systemsas a result of a higher degree of corruption is less conclusive.

In Table 6, we perform our second sample split based on exposure todemocratic institutions and report the results. Interestingly enough, voters incountries that have had stable democracies since the post-war do not seem topunish the incumbent party when they perceive an increase in corruption,whereas voters in relatively ‘‘new’’ democracies do significantly punish thegoverning party when they perceive an increase in corruption. These resultsare robust to controlling for the inclusion of political variables, as shown incolumns (2) and (4) of Table 6, and to allowing for country-specific randomeffects, as shown in the last two columns of Table 7.

Thus, our results are in line with those of Remmer (1991, 1993). In herstudies of the new Latin American democracies of the 1980s, Remmer re-ports that competitive elections help enhance the capacity of political leadersto address outstanding problems of macroeconomics management. She alsoreports that the ‘‘relationship between economic conditions and electoralinstability is mediated by party system structure rather than democraticage.’’

In short, our results suggest that while the empirical observation thatcorruption is lower in countries with parliamentary systems can be explainedby the greater control that voters exert in those countries (and their dislike ofcorruption), the empirical observation that corruption is lower in countrieswith older democratic traditions cannot be explained in the same way. Thus,the question of how the length and stability of a democratic system affects itslevel of corruption remains unanswered.

5. CONCLUSIONS AND IMPLICATIONS

We present empirical evidence from a cross-section of countries regardinghow changes in the perceived level of government corruption affect the totalamount of votes obtained by an incumbent. Our results suggest that anincrease in perceived corruption is effectively punished by voters in thegeneral election. For the entire sample, this result is significant and robust toalternative specifications of the voting functions.

Our findings provide strong evidence that voters react negatively to anincrease in corruption in countries with parliamentary systems, but theevidence is less conclusive for countries with presidential systems of rep-resentation. In turn, our results indicate that while an increase in perceivedcorruption is punished in countries with a relatively short exposure to

7Results are available from the authors on request.



democracy, it is not a significant determinant of electoral results in maturedemocracies. This may be due to the fact that in relatively ‘‘newer’’democracies, where voter turnout during elections is, on average, higherthan in established democracies, the electorate becomes more vigilant of theincumbent’s actions, creating a larger margin for punishment or reward atthe time of the elections.

Thus, while the empirical observation that corruption is lower in countrieswith parliamentary systems can be explained by the greater control thatvoters exert in those countries (and their dislike of corruption), the empiricalobservation that corruption is lower in countries with older democratictraditions cannot be explained in that manner.

APPENDIX A: THE ELECTORAL RESULTS FOR INCUMBENTS (ERI) DATABASE

The ERI database is available for download at http://comp.uark.edu/� fmendez/Research.html

A.1 Sources of Information

1. Dataset of Political Institutions (DPI) introduced by Beck et al. (2001).2. Political Dataset of the Americas (PDA). Managed by the Center for

Latin American Studies at Georgetown University and the Organiza-tion of American States.

3. The database for European Political Parties and Elections (EPPE).‘‘Parties and Elections in Europe’’ includes a database about parlia-mentary elections in the European countries since 1945 and additionalinformation about the political parties and the acting political leaders.The private website (http://www.parties-and-elections.de) was estab-lished by Wolfram Nordsieck in 1997.

4. Psephos Adam Carr’s election, available at http://psephos.adam-carr.net/

5. The World Bank’s World Development Indicators.

The countries with a presidential system included in the sample are: Argen-tina, Brazil, Chile, Colombia, Costa Rica, El Salvador, Ghana, Guatemala,Honduras, Kenya, Malawi, Mexico, Nigeria, Tanzania, Uruguay, and theUnited States. The countries with a parliamentary system included in thesample are: Austria, Belgium, Botswana, Canada, Denmark, Finland,Germany, Greece, Hungary, India, Japan, the Netherlands, Norway, Por-tugal, Spain, Sweden, Switzerland, Turkey, and the United Kingdom.

Data on electoral dates (used to compute the length of the incumbent’stenure), party ideology, votes received by incumbent, incumbent’s seats incongress, and fractionalization of the governing coalition were obtainedmainly from the DPI, the PDA, and the EPPE databases. They were alsopartly completed through direct inquiries to individual government sources.



http://comp.uark.edu/~fmendez/data





http://www.parties-and-elections.de

http://www.parties-and-elections.de

http://psephos.adam-carr.net/

http://psephos.adam-carr.net/

Data on GDP growth, inflation, and unemployment were obtained from theWorld Bank’s World Development Indicators (WDI) (2006).

A.2 Variable Definition and Methodology

Note: Each data point corresponds to one democratically held election.

cname Country name.id Country identification number.syst Dummy variable. syst¼ 0 for countries with presidential systems;

syst¼ 2 for countries with parliamentary systems; syst¼ 1 forcountries with a mixed presidential system. This classificationmatches the one provided in the DPI.

eyear Year when general elections took place. For countries with pres-idential systems, eyear contains those years when executiveelections were held (starting from 1984). For countries withparliamentary systems, eyear contains those years when legisla-tive elections were held (starting from 1984). This informationwas obtained from either the DPI, the EDSA, the EPD, or acombination of these. The three sources of data usually agree onthe dates, but small corrections are sometimes required.

emonth Month of the year when elections took place.peyr Year when the previous general elections took place.pemonth Month of the year when previous elections took place.cycle Number of months spanning between elections. This number is

presented in years, so that a 4.25, for example, represents fouryears and three months.

growth Average annual growth rate of GDP per capita between the yearin which the incumbent took office and the year of the elections.This variable is constructed using the ‘‘GDP per capita growth(annual %),’’ from the WDI.

infl Average annual change in consumer prices between the year inwhich the incumbent took office and the year of the elections.This variable is constructed using the ‘‘Inflation, consumer prices(annual %),’’ from the WDI.

unempl Average annual rate of unemployment between the year in whichthe incumbent took office and the year of the elections. Thisvariable is constructed using the ‘‘Unemployment, total (% oftotal labor force),’’ from the WDI.

vinc Percentage of valid votes received by the incumbent party. Forcountries with syst¼ 0, this number corresponds to the votesreceived by the party that holds the executive office. For coun-tries with syst¼ 2, this number corresponds to the votes receivedby the largest party in government.



vincp Percentage of valid votes received by the incumbent party in theprevious election (which resulted in this party gaining control ofthe executive or, in the case of syst¼ 2, that resulted in this partybecoming the largest party in government).

vchg Decrease in voters’ support: vchg¼ vincp� vinc.yp Number of years that the incumbent party has been in power.

For countries with syst¼ 0, this number corresponds to thenumber of years for which the incumbent party has held theexecutive office. For countries with syst¼ 2, this number corre-sponds to the number of years for which the incumbent party hasbeen the largest party in government.

ideoinc Dummy variable representing the political ideology of the in-cumbent party. For left-wing parties we assign a value of 0, whilefor right-wing parties we assign a value of 1.

seats Number of government seats in parliament (at the time of theelections) divided by total seats. This corresponds to the variable‘‘majority’’ in the DPI dataset for both parliamentary and pres-idential systems.

govfrac This variable corresponds to the government fractionalizationmeasure of the DPI dataset. By definition, this variable has avalue of zero for governments in presidential systems.

cpi This is the Corruption Perception Index (CPI) corresponding tothe electoral year or say at the time the incumbent competes foroffice. The CPI was obtained directly from Transparency Inter-national (2006).

pci Increase in corruption perceptions measured by the change in theCPI index: PCI¼ � (CPItþ e�CPIt).

ACKNOWLEDGMENTS

We would like to thank seminar participants at the 2008 Public ChoiceSociety meeting and the 2008 PEARLE seminar in Rennes for valuablecomments and suggestions. We would also like to thank two anonymousreferees for their input.

STEFAN KRAUSE FABIO MENDEZ

Emory University University of Arkansas

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Documents

CORRUPTION AND ELECTIONS: AN EMPIRICAL STUDY FOR A CROSS-SECTION OF COUNTRIES