Hostname: page-component-745bb68f8f-lrblm Total loading time: 0 Render date: 2025-02-04T23:20:10.878Z Has data issue: false hasContentIssue false

Women’s Representation, Accountability and Corruption in Democracies

Published online by Cambridge University Press:  26 January 2017

Rights & Permissions [Opens in a new window]

Abstract

At the turn of the twenty-first century, an important pair of studies established that greater female representation in government is associated with lower levels of perceived corruption in that government. But recent research finds that this relationship is not universal and questions why it exists. This article presents a new theory explaining why women’s representation is only sometimes related to lower corruption levels and provides evidence in support of that theory. The study finds that the women’s representation–corruption link is strongest when the risk of corruption being detected and punished by voters is high – in other words, when officials can be held electorally accountable. Two primary mechanisms underlie this theory: prior evidence shows that (1) women are more risk-averse than men and (2) voters hold women to a higher standard at the polls. This suggests that gender differences in corrupt behavior are proportional to the strength of electoral accountability. Consequently, the hypotheses predict that the empirical relationship between greater women’s representation and lower perceived corruption will be strongest in democracies with high electoral accountability, specifically: (1) where corruption is not the norm, (2) where press freedom is respected, (3) in parliamentary systems and (4) under personalistic electoral rules. The article presents observational evidence that electoral accountability moderates the link between women’s representation and corruption in a time-series, cross-sectional dataset of seventy-six democratic-leaning countries.

Type
Articles
Copyright
© Cambridge University Press 2017 

Fifteen years ago, two important articles by Dollar, Fisman and Gatti and Swamy et al. established a curious observational link: greater representation of women in government is associated with lower levels of perceived corruptionFootnote 1 in that government.Footnote 2 The impact of these studies was substantial. In academia, the articles are extremely well cited and have inspired a still-growing literature.Footnote 3 In the policy world, the findings justified governments enthusiastically bringing women into political offices and bureaucratic positions, such as police forces and the civil service, as an anti-corruption measure.Footnote 4

In the years since the publication of these studies, two important challenges to this finding have emerged. First, research has found that the relationship between women’s representation and corruption is not universal – it holds in some countries but not others.Footnote 5 Esarey and Chirillo, for example, find that the relationship is specific to democracies; it does not hold in autocracies.Footnote 6 Secondly, scholars have criticized Dollar, Fisman and Gatti’s explanationFootnote 7 for the finding – that women are simply more honest and trustworthy and therefore less likely to be corrupt – and offered alternative explanations, such as that women have had less opportunity to engage in corruption because they are often excluded from power and patronageFootnote 8 or that networks of corrupt officials suppress women’s representation in government as a means of ensuring that outsiders do not penetrate these networks and disrupt the stream of benefits from corruption.Footnote 9 These challenges call into question our understanding of the relationship between women’s representation and corruption, as well as the basis for some public policies.

In this article, we ask: Why does the relationship between women’s representation and corruption vary across countries? We argue that women’s representation is linked to corruption through the moderating pathway of electoral accountability, which we define as voters’ ability to identify corrupt officials and punish them at the ballot box. Where electoral accountability is high, corruption is a risky behavior; where electoral accountability is low, corruption is less risky. We expect the strength of the relationship between women’s representation and perceived corruption to be proportional to the risk of being held accountable for corruption, with the strongest relationship in places where the risk of accountability is greatest. We offer two mechanisms to explain why accountability influences the women’s representation–corruption relationship. First, experimental and observational evidence indicates that women tend to be more risk averse than men (on average) when confronting identical situations. If women are more risk averse, they should be less likely to engage in corruption in high-accountability contexts because of the risks involved. Secondly, evidence suggests that voters hold female elected officials to a higher standard than men. If this is true, then the consequences for corruption disproportionately fall on women, which may deter them from participating in corruption when the risk of getting caught and punished is high. At the aggregate level, this translates into a strong relationship between women’s representation and corruption in political systems with high accountability and a weaker relationship in systems with low accountability.

This article studies countries with democratic-leaning institutions,Footnote 10 where the concept of electoral accountability for corruption is most relevant.Footnote 11 We expect that the observed relationship between women in government and perceived corruption should be strongest in democracies,Footnote 12 where institutions allow voters to hold government officials individually accountable for corruption by punishing them at the polls (and weakest where they do not). Specifically, there are four contexts in which we expect greater levels of women’s representation in the legislature to be more strongly associated with lower levels of perceived corruption: (1) where corruption is not an institutional norm, (2) where freedom of the press is respected, (3) in parliamentary rather than presidential systems and (4) under personalistic rather than party-centered electoral rules. As we explain below, each of these settings is associated with high levels of electoral accountability. We test these hypotheses empirically with a time-series, cross-sectional dataset of seventy-six democratic-leaning countries.Footnote 13 We present a set of bivariate correlations, multivariate statistical models and substantive marginal effects plots to show that all four hypotheses have strong empirical support, providing compelling new evidence that electoral accountability moderates the relationship between women’s representation and corruption.

The goals of this study are (a) to demonstrate that the empirical link between women’s representation in government and perceived corruption is sensitive to the strength of electoral accountability and (b) to articulate a theory that explains our finding and the pattern of past results. This article is an important contribution because it makes sense of a somewhat confusing pattern of findings and sets a theoretically driven agenda for future research, but it poses at least as many questions as it answers. Future research examining the micro-level mechanisms of differential risk aversion and differential treatment by voters and empirically studying the direction of causality would not be justified if we cannot establish the context sensitivity of the gender–corruption relationship. We return to a more detailed discussion of extensions of the theory and future empirical analyses that we think are suggested by our study in the conclusion.

A THEORY OF GENDER, CORRUPTION AND ACCOUNTABILITY

Why would electoral accountability produce a stronger relationship between women’s representation and reduced corruption? Our theory hinges on gender differences in how elected officials respond to the increased risk of engaging in corruption in governments with strong electoral accountability. The risk of being held accountable for corruption by voters is determined by two factors: the likelihood of corruption being detected and the severity of punishment upon detection.Footnote 14 Increases in the probability of detection and/or the severity of punishment make the prospect of corruption riskier. It is riskier for both women and men, but we argue that women are disproportionately more discouraged by the higher risk of engaging in corruption in high-accountability systemsFootnote 15 for two reasons. First, significant research shows that women are more risk averse than men, and if this is the case, then women will react more strongly to the greater risk associated with high-accountability systems. Secondly, research shows that voters perceive of and treat female representatives differently than male representatives, which could lead to women being more likely to be caught and more severely punished by voters than men. This risk increases in systems with higher electoral accountability. For both of these reasons, women should be disproportionately less likely to engage in corruption, and this gender difference should be larger in high-accountability systems than low-accountability systems.Footnote 16

Mechanism 1: Differential Risk Aversion

A recent review of the economic literature by Croson and Gneezy presents the following summary of the relationship between gender and risk taking:

The robust finding is that men are more risk prone than women. Previous surveys of economicsFootnote 17 and psychologyFootnote 18 report the same conclusions: women are more risk averse than men in the vast majority of environments and tasks.Footnote 19

Much of the evidence of women’s greater risk aversion in economics comes from laboratory experiments. Subjects in these experiments make a series of choices between lotteries offering a different combination of risks and rewards;Footnote 20 the lotteries are structured to determine a subject’s risk aversion.Footnote 21 The experimental findings are bolstered by observational research on differential risk taking in investment portfolios managed by men and women.Footnote 22 In psychology, evidence of gender differences in risk taking comes from a combination of survey experiments with hypothetical choices, self-reported risky behavior from surveys (for example, unsafe sex) and directly observed risky behaviors, such as dangerous traffic maneuvers monitored by researchers.Footnote 23

The explanation for women’s greater risk aversion is unclear. Based on recent evidence indicating that there is no gender difference in risk aversion in traditional societies,Footnote 24 we speculate that it results from the social, cultural and institutional environments in which women are socialized and operate. For the purpose of our research, the reason why women are, on average, more risk averse than men is less important than building from the empirically grounded assumption that they are, on average, and determining how and when that risk aversion translates into different behavior. Experimental research on gender and bribe taking lends insight into this question: it finds that women will only be less likely to take bribes than men when their behavior is being monitored and there is a chance of it being detected – in other words, when that bribe taking (that is, corruption) is risky.Footnote 25

If women are more averse to the risks presented by corruption than men, then women should be less likely than men to participate in corruption when it is risky. The risks of corruption come from the likelihood of corruption being detected and punished in systems with high levels of electoral accountability. Increases in the probability of detection or the severity of punishment for corruption will more strongly decrease women’s propensity to engage in corruption compared to men. This translates into an empirical expectation: the relationship between women in government and corruption gets stronger as corruption gets riskier.Footnote 26 This occurs because women respond more strongly than men to an increased possibility of getting caught and punished.

Mechanism 2: Differential Treatment by Gender

A second reason why the relationship between women’s representation and corruption may be moderated by the strength of accountability is that the mechanisms of accountability may be biased against women. That is, it is possible that women are proportionally more likely than men to be investigated and caught for engaging in corruption and more likely to be blamed and more harshly punished for corruption. This argument is rooted in recent research findings that women are perceived and treated differently while running for and holding office.

Research has found that voters evaluate male and female candidates through the filter of gender stereotypes.Footnote 27 Women have been perceived to be less likely to win elections than men,Footnote 28 even though research shows that women are as likely to win as men in settings with relatively gender equal cultures;Footnote 29 surveys suggest that many citizens still think that men make better political leaders than women.Footnote 30 Evidence of the importance of these stereotypes in evaluations of candidate choice is mixed,Footnote 31 but stereotypes about differences between male and female political leaders clearly exist. Research has also found that these gendered perceptions of elected officials translate into different behaviors by women in office. One line of research argues that because voters hold female candidates to a higher standard than their male counterparts, women are less likely to run for office.Footnote 32 Another suggests that women actually perform better than their male counterparts in direct response to gender stereotypes about women in politics.Footnote 33

If women in office are viewed differently than men and adapt their behavior accordingly, then it is logical that they may avoid a risky activity (like corruption) while in office. This could occur because they are more at risk of getting caught and/or because they are more at risk of being punished harshly. Their higher risk of being caught derives from the fact that they are more likely to be under a microscope while in political office. Recent research on female candidates for executive office and women serving as presidents and prime ministers reports that the novelty of women in politics leads the media and voters to pay extra close attention to women’s actions and behaviors.Footnote 34 A recent study of the US Senate finds that female voters are not blindly loyal to women in office simply because they are women but are, in fact, more likely to evaluate women in office more carefully based on the policies they promote while in office and hold them accountable.Footnote 35

Women’s higher probability of being punished for corruption results from the higher standard to which women are held. If women in office are stereotypically thought to be less corrupt than men, then they are likely to be more severely punished if they are accused of engaging in (or are perceived to be engaging in) corruption. Recent anecdotal evidence of female presidents (Laura Chinchilla in Costa Rica (2010–14) and Michelle Bachelet in Chile (2014 to present)) shows how quickly and severely their approval ratings have fallen in response to corruption scandals.

Summary

In sum, we argue that electoral accountability makes corruption risky, and therefore accountability should moderate the relationship between women’s representation and corruption for two reasons. First, women are more averse to the risks of engaging in corruption than men. Secondly, women may be more likely than men to be held accountable for corruption due to unequal treatment. If female legislators are less likely to engage in corruption than male legislators when accountability is high, then we should see this reflected in an aggregate relationship between women’s representation in legislatures/parliaments and corruption levels in a country. We expect a negative relationship between women’s representation and corruption when electoral accountability is strong, and this relationship will get weaker as electoral accountability gets weaker.Footnote 36

HYPOTHESES FOR ACCOUNTABILITY AND CORRUPTION

We identify four contexts in which voters should be able to hold elected representatives accountable for corruption – in other words, when they can more easily perceive corruption in government and punish corrupt officials at the polls – and, in turn, make corruption more risky: (1) when corruption is not a pervasive norm, (2) where press freedom is respected, (3) in parliamentary systems (as compared to presidential systems) and (4) when electoral rules establish direct and personalistic linkages between voters and elected legislators or members of parliament.Footnote 37 If our theory is correct, the empirical relationship between women’s representation in legislatures/parliaments and corruption should be statistically significant and negative in these settings of high accountability; the empirical relationship should be substantially smaller, and perhaps statistically insignificant, in low-accountability settings. In this section, we explain our reasoning for the link between our theory and these observable relationships.

Corruption Norms

Although corruption occurs in countries all over the world, research has found that democracies are less corrupt, on average, than non-democracies.Footnote 38 But even within democracies, corruption is present in (and in some cases endemic to) the political system.Footnote 39 Countries where corrupt behaviors (such as bribery and graft) are ‘rooted in widely shared expectations among citizens and public officials’ and become a normal part of doing government business have strong corruption norms.Footnote 40 Measuring the presence of corruption norms is a challenge, but one proxy for it could be the (perceived) pervasiveness of corruption in politics and society.Footnote 41 Where corruption is endemic and pervasive, corruption norms develop because corruption becomes the accepted and expected way that politics is done. Corruption norms do not develop, however, where corruption is not pervasive.

We use the pervasiveness of corruption as a proxy for corruption norms and one of the institutions (albeit an informal institution) of electoral accountability. In countries with pervasive corruption, the risk of corruption being detected and punished (that is, accountability) must be low in order for corruption to flourish. By comparison, a country with less corruption has (ipso facto) demonstrated a tendency to remove or exclude corrupt persons from government. The pervasiveness of corruption can moderate the relationship between women’s representation and corruption because less pervasive corruption (stronger corruption norms) increases the risk of engaging in corruption.Footnote 42 Because women are more risk averse and aware of the differential treatment they may receive as officeholders, less pervasive corruption creates a stronger disincentive for women to engage in corruption than men. As a result, we expect a stronger link between women’s representation in government and corruption in countries with weaker corruption norms.Footnote 43

HYPOTHESIS 1: The relationship between female share of the legislature and corruption level will be more negative in states with low prior levels of corruption compared to states with high prior levels of corruption.

Some evidence supporting this hypothesis has already been presented in prior work. For example, ChaudhuriFootnote 44 reviews multiple experimental studies of the propensity to commit various corrupt behaviors (such as offering or accepting bribes).Footnote 45 He finds that there is substantial heterogeneity in female behavior across multiple experiments. In some experiments, women are less likely to offer a bribe than men, but in others women are statistically indistinguishable from men. He suggests that one of the key contextual factors may be the degree to which corruption is endemic to its political and economic culture: ‘evidence for greater incorruptibility on the part of women comes primarily from developed nations. We do not find strong differences in developing countries where the problem of corruption is far more endemic’.Footnote 46

Press Freedom

A second contextual factor that could affect the relationship between women’s representation and corruption in a democracy is the freedom of the press. The ability of citizens to identify corrupt officials is at least partly conditional on the ability of the media to investigate and report on allegations of corruption. Brazil’s now-infamous mensalão scandal, for example, came to light when several newspapers and news magazines produced a series of news stories alleging that the governing Worker’s Party (PT) was paying opposition legislators monthly salaries to support the governing party’s legislative agenda.Footnote 47 In the aftermath of the scandal, several deputies were forced from office, and the PT lost eight seats in the 2006 Chamber of Deputy elections – the first time since the transition to democracy in 1985 that it lost seats rather than gained them.

We argue that corruption is riskier in countries with a freer press compared to those where the government restricts press freedom because the risk of detection, and consequently punishment, is higher where journalists are free to investigate and expose corruption.Footnote 48 The greater risk of detection and punishment in countries with a free press should in turn lead women in office to be proportionally less likely to engage in corruption compared to men, resulting in a stronger relationship between female participation in government and corruption.

HYPOTHESIS 2: The relationship between female share of the legislature and corruption level will be more negative in countries with a free press than in those with an unfree press.

Parliamentary Governance

A third contextual factor influencing accountability for corruption in a democracy is the nature of the separation of powers. Research on the differences between parliamentary and presidential systems has long debated the strengths of each in terms of accountability. Scholars concerned about the fragility of democracy in presidential systems often argue that parliamentary systems are better for democracy because the fixed terms inherent to presidential systems make it impossible to bring an end to unpalatable governments in any way other than the breakdown of democracy.Footnote 49 The ability to call a vote of no confidence in parliamentary systems, in contrast, gives voters an opportunity to preserve democracy but turn over the government more quickly. Linz notes one of the key drawbacksFootnote 50 of the fixed terms of presidential systems: ‘It breaks the political process into discontinuous, rigidly demarcated periods, leaving no room for the continuous readjustments that events may demand’.Footnote 51 He later explicitly relates this to corruption, saying ‘parliamentary systems, precisely by virtue of their surface instability, often avoid deeper crises. A prime minister who becomes embroiled in scandal or loses the allegiance of his party or majority coalition and whose continuance in office might provoke grave turmoil can be much more easily removed than a corrupt or highly unpopular president’.Footnote 52

We build on Linz’s logic and argue that the absence of fixed terms in parliamentary systems should strengthen accountability for corruption. Indeed, there is already empirical evidence that parliamentary systems have lower levels of perceived corruption than presidential ones, although the causal pathway identified varies.Footnote 53 In parliamentary systems, the chief executive, cabinet and parliament’s terms in office are not fixed and elected officials constantly face the threat of being held to account by voters at any time. When a corruption scandal breaks, the absence of fixed terms for parliament, the threat of a vote of no confidence, and the fact that a no confidence vote not only causes the member of parliament (MP) to suffer defeat but can bring down the entire government mean that the punishment for an MP and a party is severe, and thus corruption is risky. In presidential systems, fixed terms mean that punishment may be delayed to the end of the term in office, giving elites time to rebuild their images prior to being held to account by voters, and the separation of powers means that actions in the legislature do not necessarily threaten the government itself. Thus, we argue that corruption is riskier in parliamentary systems. Because of women’s greater behavioral response to this risk (attributable to greater risk aversion and/or differential treatment by voters), the link between women’s representation and lower levels of corruption should be strongest in parliamentary systems.

HYPOTHESIS 3: The relationship between female share of the legislature and corruption level will be more negative in parliamentary systems when compared to presidential systems.

Personalism

Finally, we directly examine the strength of the link between elected representatives and voters – the degree of personalism produced by the electoral system. Existing research has produced mixed findings regarding the effects of electoral rules on corruption. Persson, Tabellini and TrebbiFootnote 54 and Kunicová and Rose-AckermanFootnote 55 link electoral rules to voters’ ability to monitor elected officials and find that stronger ties between constituents and individual elected representatives produce lower levels of corruption. In contrast, ChangFootnote 56 and Chang and GoldenFootnote 57 find that electoral systems that produce incentives to cultivate personal votes (measured as open-list proportional electoral systems with high district magnitudes) have higher levels of corruption, which they argue results from candidates having greater incentives to seek illegal funds for their campaigns in more personalistic systems. Attempting to mediate these divergent findings, Treisman found that the relationships between electoral rules and corruption were often indeterminate.Footnote 58

We argue that more personalistic rules should strengthen the effect of women’s representation on corruption. Personalistic electoral rules create tighter ties between voters and their elected representatives, while less personalistic rules emphasize the mediating role of parties in the voter–representative linkage.Footnote 59 The risk of being punished for corrupt behavior is therefore greater in personalistic systems because voters can individually identify their representative and hold them directly accountable. In less personalistic (more party-centric) systems, elites may be able to hide inside the party organization and deflect direct punishment at the polls. Voters may be willing to swallow one bad egg the party wants to defend if they are supportive of the party more generally. Parties may even collaborate to conceal the individual guilt of one member to preserve their collective electoral viability.

Because of the stronger electoral accountability created by personalistic systems, we claim that the individual risk of corrupt behavior is greater in these systems. Our theory predicts that this risk deters women in office from engaging in corruption more strongly than men, and as a result, the link between female representation in government and corruption is stronger than in party-centered systems.

HYPOTHESIS 4: The relationship between female share of the legislature and corruption level will be more negative in personalistic systems than in party-centric systems.

DATA AND VARIABLES

The dataset that we use is from Schwindt-Bayer and Tavits, and it contains measures of corruption perceptions, women’s representation in the legislature, accountability indicators and control variables for seventy-six democratic-leaning countries from 1990–2010;Footnote 60 summary statistics are reported in Table 1. The dataset includes all countries and years for which Freedom House’s average Civil Liberties and Political Rights scalesFootnote 61 was 5 or lower and Polity IV’s polity2 score was greater than 0 for twelve years or more.Footnote 62 The dataset also requires that, during this 12+ year period, countries have a consistent executive structure (presidential or parliamentary) and to not be missing all (or nearly all) data for any variable. These selection criteria have three main advantages: (1) they exclude countries that do not function according to the rules and norms of minimal democracy, (2) they include both semi-democracies and full democracies to allow generalization across degrees of democracy and (3) they allow sufficient time points and data availability to conduct a panel analysis.

Table 1 Dataset Summary Statistics

The dependent variable is the perceived level of corruption in countries as determined by three widely accepted country-level measures of corruption: Transparency International Corruption Perceptions Index (TI CPI), which measures ‘the abuse of public office for private gain’;Footnote 63 the World Bank Governance Indicators Control of Corruption measure (WBGI), which measures ‘the extent to which public power is exercised for private gain, including both petty and grand forms of corruption as well as “capture” of the state by elites and private interests’;Footnote 64 and the Political Risk Services’ International Country Risk Guide’s (ICRG) corruption risk measure, which measures ‘bribery […] excessive patronage, nepotism, job reservations, “favor-for-favors,” secret party funding, and suspiciously close ties between politics and business’.Footnote 65 Because corruption is notoriously difficult to assess, cross-national research often relies on corruption perceptions as a measure of underlying corruption; we believe these measures are advantageous because of their comprehensive nature and their wide availability over space and time.Footnote 66 All three measures are created from surveys and expert assessments of country-level corruption, and each measure has strengths and weaknesses.Footnote 67 By examining all three, we strengthen the robustness of our conclusions. The three measures correlate very highly with one another as well as with several alternative measures of corruption, which bolsters their validity.Footnote 68

We focus on the TI CPI (available from 1995–2010) in presenting our results, but our primary findings are similar regardless of whether we use the ICRG (available from 1990–2010) or the WBGI (available from 1996–2010, with biannual measurements between 1996 and 2002). The TI CPI measure is a scale of 0 to 10, the ICRG measure is a scale of 0 to 6Footnote 69 and the WBGI measure is a scale of −2.5 to 2.5. The original coding of all of these variables is such that higher numerical values indicate less perceived corruption (or more perceived government control of corruption). However, for ease of interpretation, we have recoded all three variables so that higher values equal more perceived corruption.Footnote 70

Our main independent variables are the percentage of the lower house of the legislature/parliamentFootnote 71 that is femaleFootnote 72 and four measures of accountability in the political system: (1) a one-year time lag of the dependent variable (specific to the corruption measure under analysis) to capture corruption norms in a country,Footnote 73 (2) the Freedom House’s Freedom of the Press measure, which we recode to range from −80 to 0 in order of increasing freedom,Footnote 74 (3) a dichotomous coding of whether a country’s form of government is presidential (coded as 1) or parliamentary (coded as 0)Footnote 75 and (4) a measure of the degree of personalism produced by a country’s parliamentary or legislative electoral system.Footnote 76 Personalism ranges from 1 to 13 in order of increasing levels of personalism. Each of these four measures of accountability is interacted with the percentage of women in the lower house of the parliament/legislature to allow the relationship between female participation in government and corruption to be conditional on the accountability variable.

We also include a set of common control variables for these kinds of corruption models:Footnote 77 the percentage of citizens who are Protestant;Footnote 78 democratic freedom, measured as the average political rights and civil liberties Freedom House scores inverted such that higher scores indicate greater freedom;Footnote 79 level of economic development, as measured by logged GDP per capita;Footnote 80 trade imbalance, measured as imports minus exports as a percentage of GDP;Footnote 81 and women’s economic rights, as measured in the Cingranelli-Richards Human Rights Dataset.Footnote 82 These measures block possible sources of spurious correlation attributable to cultural, socioeconomic and political explanations for variation in levels of corruption across countries and over time.

STATISTICAL METHODS

Our approach to analyzing and presenting our empirical evidence is straightforward: we consider each of our four accountability variables in turn. For each one, we first use a scatterplot to examine the pooled bivariate relationship between the TI CPI dependent variable and the percentage of women in government. To determine whether this relationship changes with the strength of electoral accountability for corruption, as would be consistent with Hypotheses 1–4, we split the data into high and low values on the accountability variable and construct separate scatterplots for each.

Secondly, we verify the findings of the bivariate plot by constructing a multivariate linear regression model.Footnote 83 We include a lagged dependent variable in all models because we believe that corruption is a path-dependent process, the presence of which is a function of its history; this variable also models temporal dependence in the data. We include year and geographical region dummiesFootnote 84 to account for additional temporal and spatial dependence in the data.

We plot the marginal effect of percentage women in the legislature on the dependent variable at different values of the accountability variable, as prescribed by Brambor, Clark and Golder,Footnote 85 to determine whether the relationship between perceived corruption and women in government is stronger when individual accountability for corruption is stronger (as indicated by Hypotheses 1–4).

Some variables (including the TI CPI and WBGI dependent variables, press freedom, personalism, trade imbalance, and women’s economic rights variables) have missing observations in our dataset.Footnote 86 Simply deleting the observations with partially missing data can lead to biased and inefficient estimates in cases where stochastic multiple imputation of the dataset would not.Footnote 87 Consequently, when we estimate our model, we use multiple imputation with chained equationsFootnote 88 as implemented in Stata 14.2Footnote 89 to perform regression including the partially missing cases while incorporating uncertainty about the unknown true values of the missing variables.

EVIDENCE: GENDER, ACCOUNTABILITY AND CORRUPTION

As described above, we have four hypotheses about how accountability should influence the relationship between women’s political representation and corruption. In this section, we show evidence associated with each hypothesis in turn.Footnote 90 Note that our statistical methods only look for a correlational relationship between women’s representation and corruption at different levels of accountability. A specific pattern of correlations is predicted by our theory (that women’s representation in government causes lower corruption only when electoral accountability is high) and we seek to match those predictions as evidence for our theory, but we cannot definitively determine a direction of causality.Footnote 91 We discuss empirical causal modeling strategies in the conclusion as suggestions for future research, but in this article our goal is simply to establish whether there is an empirical relationship between women’s representation and corruption that is conditional on electoral accountability and consistent with our theoretical predictions.

Hypothesis: Corruption Norms

Our first hypothesis is that the relationship between the female share of the legislature and the perceived corruption level should be stronger (more negative) in democracies with low prior levels of corruption compared to democracies with high prior levels of corruption. As Figure 1 indicates, we find evidence for this relationship in our data. The simple bivariate scatterplots with the linear prediction included show that the percentage of the legislature/parliament that is female is not associated with perceived corruption in countries with high levels of prior perceived corruption. Where prior perceived corruption levels are low, greater levels of women’s representation in the lower house of parliament are strongly associated with lower levels of perceived corruption.

Fig. 1 How does the past prevalence of corruption influence the relationship between gender and corruption? Note: the figure shows the relationship between the TI CPI and the percentage of women in the lower house for seventy-six democratic-leaning countries between the years 1996–2010; the top panel shows countries with prior TI CPI scores>5 and the bottom panel shows countries with TI CPI scores≤5. The difference between the slopes is 0.070, which is statistically significant (p<0.001).

Table 2 confirms this pattern in a multivariate regression using all three measures of corruption.Footnote 92 The interaction between the percentage of the legislature that is female and the lagged measure of corruption perceptions is positive and statistically significant in all three models.Footnote 93 Figure 2 presents the marginal effect of women’s representation on perceived corruption as the prior perceived corruption level increases based on the TI CPI results from Table 2; it indicates that a larger share of women in government is associated with a lower level of perceived corruption, but only when prior levels of perceived corruption are already low.Footnote 94 When prior perceived corruption levels range from 0 to about 4.5, increasing women’s representation correlates with less perceived corruption to a statistically significant degree. At a prior corruption score of 2, the present corruption score would be ≈0.02 lower for every one-percentage-point higher value of women in parliament. This indicates that a state with a 40 per cent share of women in the legislature would have a 0.80 point lower present TI corruption score compared to a state with no women in parliament; this is about 8 per cent of the maximum difference possible on this perceived corruption scale. The finding is consistent with our theoretical argument that the gender–corruption relationship is sensitive to electoral accountability. Interestingly, the model also indicates that there is a statistically significant and positive relationship between women’s participation in government and perceived corruption at the highest lagged values of perceived corruption (between ≈7.5 and 10 on the TI CPI scale); however, only about 9 per cent of our observations lie in this range.

Fig. 2 How does the relationship between gender and corruption differ by prior corruption? Note: the figure reports the marginal effect of the percentage of female members in the lower house of parliament on the TI CPI for different lagged values of the TI CPI score. Estimates are based on Model 1 reported in Table 2.

Table 2 How Does the Past Prevalence of Corruption Influence the Relationship Between Gender and Three Measures of Corruption?

Note: the table reports the output of ordinary least squares regression models using three dependent variables: (1) Transparency International Corruption Perception Index (TI CPI); (2) the International Country Risk Guide corruption rating (ICRG); and (3) the World Bank Governance Indicators Control of Corruption measure (WBGI). All three measures have been recoded so that higher values on each DV indicate more corruption. The data includes seventy-six democratic-leaning countries; the time dimension spans 1995–2010 for the TI CPI variable, 1996–2010 for the WBGI variable, and 1991–2010 for the ICRG variable. Year and region dummies are included in the models, though not reported in this table. Estimates are based on multiple imputation into fifty datasets using chained equations. R2 for the models are: (1) 0.919, (2) 0.931, (3) 0.867. t statistics in parentheses. *p<0.05, **p<0.01, ***p<0.001

Hypothesis 2: Press Freedom

We also find evidence that press freedom is associated with the relationship between women’s representation and corruption in a way that is consistent with our theory of electoral accountability. The bivariate scatterplot shown in Figure 3 shows no relationship between gender and corruption perceptions when press freedom is restricted, but a strong negative relationship in countries with high levels of press freedom. This is consistent with the idea that the greater risk of detection and punishment for corruption that is created by a free press disproportionately affects the behavior of women.

Fig. 3 How does press freedom influence the relationship between gender and corruption? Note: the figure shows the relationship between the TI CPI and the percentage of women in the lower house for seventy-six democratic-leaning countries between the years 1995–2010; the top panel shows countries with press freedom scores≤−30 and the bottom panel shows countries with press freedom scores>−30. The difference between the slopes is 0.110, which is statistically significant (p<0.001).

Table 3 shows that this finding is supported by the results of a multivariate regression: a statistically significant interaction effect exists between women’s representation in parliament and press freedom for all three measures of corruption. The relationship is most clearly seen in Figure 4, which illustrates the marginal effect of women’s parliamentary representation on corruption perceptions as press freedom increases based on the TI CPI results from Table 3.

Fig. 4 How does the relationship between gender and corruption differ by press freedom? Note: the figure reports the marginal effect of the percentage of female members in the lower house of parliament on the TI CPI for different values of the press freedom variable. Estimates are based on Model 1 reported in Table 3.

Table 3 How Does Press Freedom Influence the Relationship Between Gender and Three Measures of Corruption?

Note: the table reports the output of ordinary least squares regression models using three dependent variables: (1) the Transparency International Corruption Perceptions Index (TI CPI); (2) the International Country Risk Guide corruption rating (ICRG); and (3) the World Bank Governance Indicators Control of Corruption measure (WBGI). All three measures have been recoded so that higher values on each DV indicate more corruption. The data includes seventy-six democratic-leaning countries; the time dimension spans 1995–2010 for the TI CPI variable, 1996–2010 for the WBGI variable and 1991–2010 for the ICRG variable. Year and region dummies are included in the models, though not reported in this table. Estimates are based on multiple imputation into fifty datasets using chained equations. R2 for the models are: (1) 0.922, (2) 0.931, (3) 0.873. t statistics in parentheses. *p<0.05, **p<0.01, ***p<0.001

The estimated marginal effect of women’s representation on perceived corruption becomes negative and statistically significant when press freedom is in the top third of its range (about −25 to 0). When press freedom is at −10, the marginal effect of women in parliament is ≈ −0.02. Once again, this implies that countries with a 40 per cent female parliament are, on average, about 0.8 lower in the TI corruption perceptions measure compared to a country with no women in parliament. As Hypothesis 2 indicated, a larger share of women in parliament is associated with lower levels of corruption when the press is free, but not when the press is restricted.

Hypothesis 3: Parliamentary Governance

The relationship between women’s representation and corruption perceptions in our data is different across types of democratic government. In presidential systems, women’s representation in legislatures has no discernible relationship with perceived corruption, whereas in parliamentary systems, greater women’s representation correlates with considerably lower levels of perceived corruption. These divergent patterns are striking in the bivariate relationships depicted in Figure 5.

Fig. 5 How does separation of powers influence the relationship between gender and corruption? Note: the figure shows the relationship between the TI CPI and the percentage of women in the lower house for seventy-six democratic-leaning countries between the years 1995–2010; the top panel shows countries with presidential systems and the bottom panel shows countries with parliamentary systems. The difference between the slopes is 0.148, which is statistically significant (p<0.001).

As Table 4 shows, multivariate regression models support the bivariate findings: the interaction between the percentage of female legislators and the presidentialism dummy variable is statistically significant and positive in all three models. The marginal effect plot in Figure 6 shows the relationship between the percentage of the legislature/parliament that is female and corruption perceptions estimated in the TI CPI model in Table 4. While greater women’s representation has no statistically significant relationship with the level of perceived corruption in presidential systems, it has a strong and statistically significant negative relationship in parliamentary systems of ≈ −0.01 – about half the substantive magnitude of the relationships in the prior two contexts.

Fig. 6 How does the relationship between gender and corruption differ by government type? Note: the figure reports the marginal effect of the percentage of female members in the lower house of parliament on the TI CPI for parliamentary and presidential systems. Estimates are based on Model 1 reported in Table 4.

Table 4 How Does Separation of Powers (Accountability) Influence the Relationship Between Gender and Three Measures of Corruption?

Note: the table reports the output of ordinary least squares regression models using three dependent variables: (1) the Transparency International Corruption Perceptions Index (TI CPI); (2) the International Country Risk Guide corruption rating (ICRG); and (3) the World Bank Governance Indicators Control of Corruption measure (WBGI). All three measures have been recoded so that higher values on each DV indicate more corruption. The data includes seventy-six democratic-leaning countries; the time dimension spans 1995–2010 for the TI CPI variable, 1996–2010 for the WBGI variable and 1991–2010 for the ICRG variable. Year and region dummies are included in the models, though not reported in this table. Estimates are based on multiple imputation into fifty datasets using chained equations. R2 for the models are: (1) 0.919, (2) 0.931, (3) 0.868. t statistics in parentheses. *p<0.05, **p<0.01, ***p<0.001

This finding supports our theoretical argument that parliamentary systems present a greater individual risk for corruption due to the threat of swift sanctioning by voters, which creates a larger gender difference in corruption behavior. This difference becomes manifest in a stronger negative relationship between the perceived level of corruption and the share of women in the legislature in parliamentary systems compared to presidential systems.

Hypothesis 4: Personalism

Finally, we examine how the relationship between women’s representation and corruption is influenced by the personalism embedded in legislative or parliamentary electoral rules. We find that more personalistic rules are associated with a stronger negative relationship between the percentage of women in parliament and perceived corruption. Figure 7 shows the bivariate scatterplots and linear predictions for democratic-leaning countries with more party-centered (less personalistic) electoral rules compared to more personalistic electoral rules. Both figures show a negative relationship, but the effect is slightly steeper in democratic-leaning countries with more personalistic rules (and the difference between the slopes is statistically significant at p<0.001.

Fig. 7 How does personal accountability influence the relationship between gender and corruption? Note: the figure shows the simple bivariate relationship between the TI CPI and the percentage of women in the lower house for seventy-six democratic-leaning countries between the years 1995–2010; the top panel shows countries with personalism scores≤6, and the bottom panel shows countries with personalism scores>6. The difference between the slopes is 0.082, which is statistically significant (p<0.001).

Table 5 shows our multivariate statistical models with personalism interacted with the percentage of female legislators. The interaction terms are negative and statistically significant in all three models. Figure 8 shows the TI CPI model’s marginal effect for women in parliament on perceived corruption at varying levels of personalism. The effect is not statistically significant in the least personalistic systems (where the personalism score is less than about 2.5); this encompasses 33 per cent of the sample of country-years (that is, about two-thirds of the sample has more personalistic electoral rules). As personalism increases from 3 to 13, the effect of women’s representation on corruption perceptions is negative and statistically significant. At a personalism value of 13, the marginal effect of women in parliament is about −0.03; this means that a country with 40 per cent women in parliament is expected to have a corruption score 1.2 points lower than a country with no women in parliament. This supports our argument that electoral rules that produce a stronger accountability link between individual representatives and voters disproportionately deter women from engaging in corruption.

Fig. 8 How does the relationship between gender and corruption change as personalism changes? Note: the figure reports the marginal effect of the percentage of female members in the lower house of parliament on the TI CPI at different levels of personalism (Johnson and Wallack Reference Johnson and Wallack1997). Estimates are based on Model 1 reported in Table 5.

Table 5 How Does Personal Accountability Influence the Relationship Between Gender and Three Measures of Corruption?

Note: the table reports the output of ordinary least squares regressions using three dependent variables: (1) the Transparency International Corruption Perceptions Index (TI CPI); (2) the International Country Risk Guide corruption rating (ICRG); and (3) the World Bank Governance Indicators Control of Corruption measure (WBGI). All three measures have been recoded so that higher values on each DV indicate more corruption. The data includes seventy-six democratic-leaning countries in each model; the time dimension spans 1995–2010 for the TI CPI variable, 1996–2010 for the WBGI variable and 1991–2010 for the ICRG variable. Year and region dummies are included in the models, though not reported in this table. Estimates are based on multiple imputation into fifty datasets using chained equations. R2 for the models are: (1) 0.920, (2) 0.931, (3) 0.869. t statistics in parentheses. *p<0.05, **p<0.01, ***p<0.001

In sum, we observe that the relationship between the level of women’s representation and the perceived level of corruption is indeed conditional upon the strength of individual accountability to voters in the political system. This finding corresponds to the implications of our theoretical argument: accountability moderates the relationship between women’s representation and corruption through the mechanisms of greater risk aversion and/or higher standards of accountability for women.

CONCLUSION

Corruption is a political threat that all countries fight, with varying degrees of success. In some countries, corruption levels are low and instances of suspected corruption are quickly brought to justice. The recent convictions of former Illinois governor Rod Blagojevich and former New Orleans mayor Ray Nagin in the United States exemplify this. Corruption is a risky activity for political elites in these settings. In other countries, like Mexico and Venezuela, corruption levels are persistently high and individual cases of corruption rarely make headlines or produce negative consequences for those involved. Participating in corruption is therefore not particularly risky in these locales and may even be a way for elites to further their political careers. Previous studies have found that women’s representation in government is associated with lower levels of corruption, leading some to think that increasing women’s election to office will reduce corruption in countries. Yet this finding is not consistent across countries.

In this article, we asked: why are women’s representation and reduced corruption related in some countries but not others? We argued that greater women’s representation in parliaments and legislatures is more strongly associated with lower levels of corruption in countries with higher electoral accountability, that is, where voters can identify corrupt officials and punish them at the ballot box. We explained this conditional relationship with two theoretical mechanisms that relate the relationship between women’s representation and corruption to the risks of corruption – women’s greater risk aversion and the different ways in which voters treat them. We generated four institutional hypotheses about the rules and norms that influence electoral accountability and tested these hypotheses with data from seventy-six democratic-leaning countries around the world. We found consistent evidence that, where accountability is high, a strong negative relationship exists between women’s representation and perceived corruption levels. Where accountability is low, a much weaker relationship exists. Strong electoral accountability appears to be the mechanism by which higher levels of women’s representation relate to reduced corruption perceptions.

Identifying and providing empirical evidence that electoral accountability is the key moderating factor in the relationship between women’s representation and perceived corruption is an important new finding. It answers a puzzling question – why does the relationship only exist in some countries and not others – and provides a critical caution to policy makers who think bringing women into government can solve corruption problems. Increasing the proportion of women in government might reduce perceived corruption, but empirical evidence of an association between the two only exists in countries that already have high levels of electoral accountability. We find little reason to suspect that changing the proportion of women in government will change perceived corruption levels in countries with low electoral accountability.

Our empirical finding also highlights two areas for further research on the gender–corruption link. First, this article does not empirically establish the direction of causality in the relationship between women’s representation and corruption. Our theoretical argument is that having more women in legislatures and parliaments will reduce overall corruption levels because women are less likely to engage in corruption than men. Our empirics support a correlation between women in government and perceived corruption that is consistent with this theory, but they do not prove a direction of causality or establish that the relationship applies to directly observed (as opposed to perceived) corruption. Concordantly, other interpretations of our evidence are conceivable. For example, women could be more likely than men to avoid running for public office in high-corruption environments, but only when electoral accountability is high; this is a strategy of avoiding participation in corruption, and is therefore generally consistent with our theory that women avoid corruption in high-accountability contexts, but it has different causal implications.Footnote 95 In this alternative interpretation, increasing the number of women in office may not reduce corruption; it depends on how women who would not have ordinarily run for office behave once they are elected. Another possibility is that greater female representation in government changes how observers perceive the degree of state corruption, but not the real rate of corrupt practices, when electoral accountability is high. Our current study is not designed to empirically disentangle these and other possibilities, but rather to identify that accountability is an important contextual factor that must be considered in future work that is designed to do so.

Two strategies could be particularly useful to empirically estimate the causal effect of increased women’s representation on corruption. First, survey and laboratory experiments could be designed to investigate the degree to which people select themselves out of positions that involve corruption, or choose to accept these positions but resist corruption once there. Experiments could also focus on how and why voters hold politicians accountable for corruption, which would be particularly useful in helping us establish what causes voters to punish corruption (and what causes politicians to avoid it) at the micro level. As a bonus, experiments can allow a researcher to directly observe corrupt behaviors rather than the indirect perception of corruption. Secondly, instrumental variables techniques may allow us to directly measure the local average treatment effect of a program designed to increase female representation in government on corruption in that government.Footnote 96

A second important priority for future research is to distinguish between the two micro-level theoretical mechanisms – risk aversion and differential treatment – that we argued might explain why accountability moderates the relationship between women’s representation and corruption. Again, survey and laboratory experiments may help us separate these mechanisms and determine the extent to which each produces the greater responsiveness to electoral accountability that we see in observational data. Additionally, collecting panel data on individual voter attitudes and behavior toward women in government and corruption may give us traction on this question. As an added benefit, closer empirical examination of these theoretical mechanisms may also uncover other reasons why electoral accountability moderates the corruption and women’s representation relationship, some of which may be related to men’s responses to women’s increased levels of political participation.

This article takes an important first step towards understanding when women’s representation in government is associated with political corruption and why. While early work suggested that there is a clear and relatively simple link – namely, that more women in government means less corruption because women are intrinsically less corrupt – our findings support a subtler relationship that runs through electoral accountability. These findings matter for scholars hoping to better understand the causes and consequences of women’s political representation, and they have important implications for policy makers who think that increased women’s representation is a direct solution for endemic and pervasive corruption. Our findings support Goetz’s assertion that ‘To expect that women’s gender alone can act as a magic bullet to resolve a corruption problem that is much bigger than they are, that is systemic, is unrealistic to say the least. It reflects not just wishful but almost desperate thinking.’Footnote 97 At the same time, our findings suggest that countries considering the anti-corruption benefits of increasing gender parity in government should consider simultaneously implementing institutional reforms to catch and punish officials who are guilty of corruption. Women’s representation is much more likely to be associated with reduced corruption when accountability is high.

Footnotes

*

Department of Political Science, Rice University (email: justin@justinesarey.com); Department of Political Science, Rice University (email: schwindt@rice.edu). We would like to thank the participants and audiences at the numerous workshops and departmental colloquia where we presented this paper, including ‘Why is Gender Equality Good for Governance?’ at Freie Universitat, Berlin; the University of Tennessee; the University of Maryland; the Center for Women’s Leadership at Portland State University; the Quality of Government Institute at the University of Gothenburg; the European Conference on Politics and Gender in Uppsala, Sweden; and ITAM, Mexico City. We also thank Margit Tavits for sharing the data that she and Leslie Schwindt-Bayer collected. Data replication sets including logs, analysis scripts and data files are available at http://dataverse.harvard.edu/dataverse/BJPolS and online appendices are available at https://doi.org/doi:10.1017/S0007123416000478.

1 By corruption, we mean the appropriation of public authority for personal or private benefit. This definition includes the solicitation of bribes, embezzling public money and other forms of graft. Due to the difficulty of directly observing these usually hidden behaviors, we measure corruption using the perceptions of country experts and business professionals (among others). Our definition and measure is are consistent with those used in most empirical studies of country-level corruption; see the Data and Variables section for a more detailed discussion.

3 Alhassan-Alolo Reference Alhassan-Alolo2007; Barnes and Beaulieu Reference Barnes and Beaulieu2014; Esarey and Chirillo Reference Esarey and Chirillo2013; see, for example, Sung Reference Sung2003; Wangnerud Reference Wangnerud2012; Watson and Moreland Reference Watson and Moreland2014. According to Google Scholar, Dollar, Fisman, and Gatti’s (Reference Dollar, Fisman and Gatti2001) article has more than 379 citations and Swamy et al. (Reference Swamy, Knack, Lee and Azfar2001) has over 477 as of 22 September 2014.

4 Kahn Reference Kahn2013; Karim Reference Karim2011; McDermott Reference McDermott1999; Moore Reference Moore1999; Quinones Reference Quinones1999. Although Dollar, Fisman, and Gatti (Reference Dollar, Fisman and Gatti2001) focused only on women’s representation in parliament and corruption, Swamy et al. (Reference Swamy, Knack, Lee and Azfar2001) studied the effect of women’s parliamentary representation, their presence in senior bureaucratic posts and their labor force participation on corruption. The findings have been used to justify increasing women’s presence in many areas of government, not just parliaments and legislatures.

6 Esarey and Chirillo Reference Esarey and Chirillo2013.

7 Dollar, Fisman, and Gatti Reference Dollar, Fisman and Gatti2001, 423–4.

9 Bjarnegård Reference Bjarnegård2013; Goetz Reference Goetz2007; Grimes and Wängnerud Reference Grimes and Wängnerud2012; Johnson, Einarsdóttir, and Pétursdóttir Reference Johnson, Einarsdóttir and Pétursdóttir2013; Stockemer Reference Stockemer2011; Sundström and Wängnerud 2016.

10 For the purpose of defining the sample, we consider ‘democracy’ as part of a dichotomous conceptualization of regime type in which the two options are ‘democracy’ and ‘authoritarian or autocratic’. This means that we consider semi-democracies that lean democratic to be ‘democracies’ and those leaning autocratic to be ‘authoritarian’ (Cheibub 2006; Przeworski et al. Reference Przeworski, Alvarez, Cheibub and Limongi2000). Thus when we use the term ‘democracy’ in this article to describe countries in our sample, we are using a minimalist definition that includes both full and semi-democracies.

12 Esarey and Chirillo Reference Esarey and Chirillo2013.

13 Schwindt-Bayer and Tavits Reference Schwindt-Bayer and Tavits2016.

14 We present the probability of detection and the severity of punishment as co-equal contributors to the strength of accountability. Our article does not intend to distinguish when women’s propensity to engage in corruption results from a threat of detection versus when it results from punishment. We more simply argue that women’s reduced engagement in corruption could result from one, the other or both.

15 Our theory is agnostic about whether men will be less likely to engage in corruption when it becomes riskier; we only predict that women will have a stronger response to the risk of corruption than men. Consequently, it would be consistent with our theory if men did not react at all to an increased risk of corruption, but it would also be consistent if men reduced their participation in corruption in response to increased risk but that women reduced their participation even more.

16 Note that ‘low’ accountability does not mean ‘no’ accountability. In systems with no electoral accountability, we would expect no differential risk for women and men, and thus no relationship between women’s representation and corruption levels. In systems with low accountability, however, some risk may occur, theoretically producing a small relationship between women’s representation and corruption. Our concern is not so much whether there is a relationship in low-accountability systems, but whether this relationship is significantly smaller than in high-accountability systems.

17 Eckel and Grossman Reference Eckel and Grossman2008.

18 Byrnes, Miller, and Schafer Reference Byrnes, Miller and Schafer1999.

19 Croson and Gneezy Reference Croson and Gneezy2009, 449.

20 Croson and Gneezy Reference Croson and Gneezy2009, 450, Table 1.

21 Holt and Laury Reference Holt and Laury2002.

22 Bernasek and Shwiff Reference Bernasek and Shwiff2001; Sundén and Surette Reference Sundén and Surette1998; Watson and McNaughton Reference Watson and McNaughton2007.

23 Byrnes, Miller, and Schafer Reference Byrnes, Miller and Schafer1999, 370.

24 Gneezy, Leonard, and List Reference Gneezy, Leonard and List2009; Henrich and McElreath Reference Henrich and McElreath2002.

25 Armantier and Boly Reference Armantier and Boly2011; Schulze and Frank Reference Schulze and Frank2003.

26 As explained in Footnotes 15 and 16, our theory makes no empirical prediction about the relationship between women in government and corruption when electoral accountability is low or about how men will respond to a greater risk of corruption.

28 Dowling and Miller Reference Dowling and Miller2015; Fox and Lawless Reference Lawless2004.

29 Schwindt-Bayer, Malecki, and Crisp Reference Schwindt-Bayer, Malecki and Crisp2010; Seltzer, Newman, and Leighton Reference Seltzer, Newman and Leighton1997.

30 Inglehart and Norris Reference Inglehart and Norris2003; Morgan and Buice Reference Morgan and Buice2013.

32 Fox and Lawless Reference Lawless2004; Lawless and Fox Reference Lawless and Fox2005.

33 Anzia and Berry Reference Anzia and Berry2011.

36 Another way to test this theory empirically would be to directly measure the extent to which elected officials will engage (or not) in corrupt activities. Convincing elected officials to participate in an experiment on corruption or even trying to survey them about their corrupt behavior or potential willingness to engage in corrupt behavior is challenging because of social desirability bias (among other reasons). Additionally, what is driving our study is not so much empirically evaluating the behavior of individual legislators, but trying to explain why an aggregate relationship between women’s representation and corruption varies across settings. Thus we think it is appropriate under these circumstances to test the aggregate country-level implications of our theory (which also has individual-level implications).

37 An anonymous reviewer suggested two other possible contexts in which electoral accountability is higher: (a) in countries with stronger democratic institutions (see Esarey and Chirillo (Reference Esarey and Chirillo2013) for relevant theoretical arguments along this line), as measured by Polity IV’s polity2 score (Marshall, Gurr, and Jaggers Reference Marshall, Gurr and Jaggers2014), and in countries that lack electoral quotas for gender and therefore women are not guaranteed seats in parliament (Childs and Krook Reference Childs and Krook2012; for related theory and evidence, see Franceschet and Piscopo Reference Franceschet and Piscopo2008). Although we do not describe these contexts in detail in our article, we did empirically test each hypothesis and confirmed that the relationship between women in government and corruption is stronger in the presence of stronger democracy and in the absence of electoral gender quotas; see Appendix Table S6 for details.

40 Helmke and Levitsky Reference Helmke and Levitsky2004.

41 Fisman and Miguel Reference Fisman and Miguel2007.

42 We recognize that this argument appears tautological: if corruption norms were the only way in which accountability operated in democracies, then citizens would never be able to hold elected officials accountable in settings of high accountability. Similarly, the only time they could hold elected officials accountable would be when corruption is already low. However, we know that other mechanisms of accountability exist – we discuss three others in this article – and as a result, corruption norms are rarely operating in isolation from other forces for accountability. We do think that high levels of corruption make it difficult to hold elites accountable, and moving from a high-corruption to a low-corruption environment via accountability will be a slow process. But norms change, albeit slowly, and the presence of other institutions that increase electoral accountability can help destroy the norms of corruption present in various countries. The critical distinction is between (a) existing levels of corruption and (b) the degree to which corruption responds to changes in women in government as a function of that level: the lower the level of corruption, the more responsive that corruption will be to the proportion of women in government. Our operationalization reflects that distinction.

43 In the terminology of Esarey and Demeritt (2014), we hypothesize that the relationship between women in government and corruption is state dependent: it grows stronger as corruption levels fall.

44 Chaudhuri Reference Chaudhuri2012, 40, Table 6.

45 See also Alhassan-Alolo Reference Alhassan-Alolo2007.

46 Chaudhuri Reference Chaudhuri2012, 41–2.

47 The Economist 2013.

48 Adserà, Boix, and Payne Reference Adserà, Boix and Payne2003; Lederman, Loayza, and Soares Reference Lederman, Loayza and Soares2005; Treisman Reference Treisman2007.

50 Defenders of presidentialism have pointed out some of the strengths of accountability in presidential systems: for example, voters have the opportunity to hold the executive and legislature independently accountable for government (Hellwig and Samuels Reference Hellwig and Samuels2008; Mainwaring and Shugart Reference Mainwaring and Shugart1997; Persson, Roland, and Tabellini Reference Persson, Roland and Tabellini1997; Samuels and Shugart Reference Samuels and Shugart2003; Shugart and Carey Reference Shugart and Carey1992). However, this also means that voters may have a more difficult time assigning blame due to the separation of powers inherent in presidential systems (Samuels and Shugart Reference Samuels and Shugart2003; Shugart and Carey Reference Shugart and Carey1992); each branch of government can blame the other. In this article, we cannot empirically distinguish corruption in the executive branch from corruption in the legislative branch, making it impossible to test this angle of the accountability argument.

51 Linz Reference Linz1990, 54.

52 Linz Reference Linz1990, 64.

53 Gerring and Thacker Reference Gerring and Thacker2004; Lederman, Loayza, and Soares Reference Lederman, Loayza and Soares2005; Treisman Reference Treisman2007; but see Persson and Tabellini Reference Persson and Tabellini2002.

54 Persson, Tabellini, and Trebbi Reference Persson, Tabellini and Trebbi2003.

55 Kunicová and Rose-Ackerman Reference Kunicová and Rose-Ackerman2005.

57 Chang and Golden Reference Chang and Golden2007.

59 Cain, Ferejohn, and Fiorina Reference Cain, Ferejohn and Fiorina1990; Carey and Shugart Reference Carey and Shugart1995.

60 Replication files are available at http://dataverse.harvard.edu/dataverse/BJPolS. For more information on the Schwindt-Bayer and Tavits dataset, see Chapter 3 of Schwindt-Bayer and Tavits (Reference Schwindt-Bayer and Tavits2016).

61 Freedom House 2014.

62 Polity2 is the most commonly used measure of electoral democracy. It ranges from −10 (highly autocratic) to +10 (highly democratic). The measure is an aggregation of scores on various components that measure electoral participation and contestation in a country; these scores are assigned by expert coders. These components are: competitiveness of executive recruitment, openness of executive recruitment, executive constraints, the regulation of political participation and the competitiveness of participation (Marshall, Gurr, and Jaggers Reference Marshall, Gurr and Jaggers2014).

63 Transparency International 2011, 2.

64 Kaufmann, Kraay, and Mastruzzi Reference Kaufmann, Kraay and Mastruzzi2010, 4.

65 Political Risk Services Group 2012. The ICRG measures the risk that corruption presents to foreign business and investment (Political Risk Services Group 2012, 5–6). This means that the ICRG index does not just capture raw levels of corruption, but the degree to which the state’s institutions convert this corruption into a threat to businesses (e.g., by threatening the stability of a government). A country’s democratic accountability and tolerance of corruption might therefore influence the ICRG rating because states with greater accountability or less tolerance might be more likely to experience political turmoil as a result of corruption scandals (Lambsdorff Reference Lambsdorff2006, 82–3).

66 The use of perception-based corruption measures has been hotly debated in recent years (Donchev and Ujhelyi Reference Donchev and Ujhelyi2014; Provost Reference Provost2013). The primary concern is that the subjective perception of corruption is not necessarily identical with its reality. However, alternative ‘objective’ measures of corruption are also subject to criticism: ‘since corruption is clandestine, it is virtually impossible to come up with precise objective measures of it. … There should be no presumption that objective data is necessarily more informative than reports from experts, citizens, or firms on the ground – irrespective of their extent of perception or subjectivity’ (Kaufmann, Kraay, and Mastruzzi Reference Kaufmann, Kraay and Mastruzzi2007, 4). For example, consider two ‘objective’ alternatives: contract-intensive money (CIM) and the Global Corruption Barometer (GCB) survey measure of bribes paid to legal and judiciary institutions. Although not dependent on subjective perceptions or available for many countries and time periods, CIM does not solely measure corruption. Specifically, CIM is ‘the ratio of non-currency money to the total money supply’ (Clague et al. Reference Clague, Keefer, Knack and Olson1999, 188), as compiled by Mark Souva (Johnson, Souva, and Smith Reference Johnson, Souva and Smith2013), and therefore is a measure of citizens’ willingness to hold non-cash monetary assets. It is designed to measure ‘the enforceability of contracts and the security of property rights’ (p. 185) including ‘not only the risk of government expropriation of financial assets (for example, through bank nationalization), but the expropriation through arbitrary regulation or outright confiscation of any type of fixed asset’ (p. 203). Freedom from corruption constitutes only one aspect of secure property rights. The GCB legal/judicial bribery variable is more narrowly defined than any comprehensive definition of corruption would imply: it is the proportion of respondents in a country-year indicating that someone in their household paid a bribe to the legal/judicial system (Teorell et al. Reference Teorell, Charron, Samanni, Holmberg and Rothstein2015 codebook, 254; Transparency International 2015). While bribery of these officials is one aspect of corruption, corruption can take many other forms and involve many other government and non-government officials. Additionally, this measure is available for a relatively limited number of countries and time periods compared to the TI CPI, WBGI and ICRG.

68 WBGI and TI CPI correlate at r=0.98; ICRG correlates with WBGI at r=0.87 and with TI CPI at r=0.86. In Appendix Figure S1, we show strong associations between TI CPI and the two ‘objective’ measures noted in the preceding footnote, CIM and GCB Legal/Judicial Bribery.

69 ICRG data were monthly up through mid-2009. In those cases, we use the twelve-month average score.

70 The TI CPI measure is recoded by 10 minus the original value of the dependent variable. The ICRG measure is recoded by 6 minus the original value of the dependent variable. The WBGI measure is recoded by 2.6 minus the original value of the dependent variable.

71 We believe that focusing on women in the legislature in this analysis is appropriate because our accountability measures are focused on accountability to voters.

72 Inter-Parliamentary Union 2012.

73 Our results are robust to using a two- or three-year lag instead of a one-year lag in this model; see Appendix Table S3 for details.

74 Freedom House assesses freedom of the press in all countries every year. Their measure assesses freedom in print, broadcast and internet media by creating a sub-score for each media type of the following ways in which media freedom can be restricted: laws and regulations that influence media content, political pressures and controls on media content, economic influences over media content and repressive actions (www.freedomhouse.org). These are aggregated into a scale that runs from 0 to 100 (in order of decreasing freedom). No country in the dataset had levels higher than 80 because it excludes non-democracies, where press freedom is likely to be most restricted.

75 The dataset authors coded semi-presidential systems as presidential or parliamentary depending on the powers of the president. Specifically, premier-presidential systems were coded as parliamentary systems in which the president has no power to dissolve the cabinet (only the assembly can) and president-parliamentary systems as presidential where the president has the power to dissolve the cabinet alongside the assembly (Elgie Reference Elgie2011; Samuels and Shugart Reference Samuels and Shugart2010).

76 Johnson and Wallack Reference Johnson and Wallack1997. Johnson and Wallack’s personalism score has become a common measure of how strongly certain configurations of electoral rules incentivize personalistic rather than party-centered behavior among candidates and elected representatives. They use Carey and Shugart’s (Reference Carey and Shugart1995) schema for coding electoral systems according to the extent to which the ballot structure allows voters to disturb party lists, how votes are pooled across a ballot and the type of vote a voter places. Configurations of scores are then ranked by how much personalism they create, and the electoral system of a country is classified accordingly.

78 CIA World Factbook 2013.

79 Freedom House 2014.

80 World Bank 2013.

81 World Bank 2013.

82 Cingranelli and Richards Reference Cingranelli and Richards2010.

83 Random effects variants of these models are substantively no different from standard ordinary least squares regressions; the random effects explain no appreciable portion of variance when added. Fixed-effects (FE) models and system GMM dynamic panel data models produce weaker and inconsistent findings, albeit with some qualitative similarities to our main results (see Appendix Tables S4 and S5). We argue that the models we present are more credible; consider the comparison with FE models. First, FE models are inefficient in the presence of short panels thanks to an incidental parameters problem (Hsiao Reference Hsiao2003, 48–9; Neyman and Scott Reference Neyman and Scott1948); in our dataset, even the dependent variable with the greatest availability (the ICRG) has just ≈20 observations per panel. Secondly, FE models are inefficient for estimating the effect of slow-moving independent variables, and all of our main variables are very slow moving within panels; fixed effects alone explain 83 per cent of the variance in press freedom, 99 per cent of the variance in presidentialism and 86 per cent of the variance in personalism. Thirdly, from a theoretical perspective, we do not believe in (or wish to model) persistent country-level variation in corruption net of the path-dependent history of corruption being captured by the lagged dependent variable and the other institutional influences being captured by our control variables. For example, corruption in the United States was widespread in the latter nineteenth century but comparatively low by the end of the twentieth century; a fixed effect presumes that this characteristic is essentially permanent. Finally, FE models are known to be biased in short panels in the presence of lagged dependent variables (Judson and Owen Reference Judson and Owen1999; Nickell Reference Nickell1981), and the lagged dependent variable is a theoretically relevant variable for the analysis. Dynamic panel data models address only this last problem: models with a lagged dependent variable are consistent in short panels when the number of panels is large (Roodman Reference Roodman2006). But a new problem is created in its place: dynamic panel data models are not supported after multiple imputation (using mi estimate) in Stata 14.2, and thus any problems inherent to the missing data problem reappear. Additionally, we have a relatively small number of panels to support an argument of consistency. We do not have confidence that this model is compatible with an interaction between the percentage of women in the legislature and a lag of the dependent variable, and so do not estimate this model.

84 The regions are Sub-Saharan Africa, South Asia, East Asia, South East Asia, Pacific Islands/Oceania, Middle East/North Africa, Latin America, Caribbean and non-Iberic America, Eastern Europe/Soviet Union and Western Europe.

85 Brambor, Clark, and Golder Reference Brambor, Clark and Golder2006.

86 For the ICRG dependent variable, our main regression models use datasets that have 1.3 per cent (lag DV and presidentialism models), 1.7 per cent (personalism model) or 13.2 per cent (press freedom model) of cases with missing observations. For the TI CPI dependent variable, our main regression models use datasets that have ≈18.7 per cent of cases with missing observations. For the WBGI dependent variable, our main regression models use datasets that have ≈25.7 per cent of cases with missing observations.

87 van Buuren Reference van Buuren2012, 3–23.

88 Multiple imputation by chained equations (MICE) generates multiple imputation datasets by (1) eliminating any observations with missing values for all variables; (2) substituting random values for missing values in any remaining observations; (3) imputing the values of a missing variable X i using model predictions from a GLM model of all the other variables X i on the (non-missing) values of X i , where the model includes observations with imputed values of X i where X i is non-missing; (4) repeating step 3 for all values of i=1...k in sequence for the k independent variables; (5) repeating steps 3–4 a large number of times to refine the predicted missing values; and finally (6) repeating steps 2–5 with new initial values M times to generate M imputation datasets. The resulting datasets are analyzed and the results combined using the method of Rubin (Reference Rubin1996). See Royston and White (Reference Royston and White2011) for more details of the implementation of MICE in Stata.

89 Royston and White Reference Royston and White2011.

90 As described in Footnote 37, and at the suggestion of an anonymous reviewer, we also find evidence that the negative relationship between women in government and perceived corruption is stronger in the presence of stronger democratic institutions (as measured by the Polity score) and in the absence of electoral gender quotas; these are both environments where electoral accountability may be stronger. See Appendix Table S6 for the results.

91 As an initial effort to establish some credible evidence for a causal effect of women’s representation on corruption, we estimate a two-stage least squares (2SLS) version of our TI CPI model in Tables 3, 4 and 5 by using two-period lags of the key independent variables (including interaction terms) as instruments; this identification strategy is suggested by Reed (Reference Reed2015). The results are shown in Appendix Table S2. The substantive findings from this model are similar to those from our OLS models, although the relationship between women’s representation and corruption becomes statistically insignificant in the presidentialism instrumental variable (IV)/2SLS model; this change might be due to efficiency loss because we can no longer use multiple imputation for the IV/2SLS model.

92 The TI CPI time series passes the Augmented Dickey-Fuller and Phillips-Perron unit root tests with p<0.01 using the inverse χ2 transformation, which indicates that the series is stationary and the state-dependence model can be used (Esarey and DeMeritt Reference Esarey and DeMeritt2014, 74–6).

93 When the lagged dependent variable is interacted with the percentage of women in the legislature, a state-dependent dynamic model is created (Esarey and DeMeritt Reference Esarey and DeMeritt2014). In a state-dependent system, the effect of an independent variable on the dependent variable depends on the prior level of the dependent variable. Methodological study of this model has indicated that, regardless of the number of panels, a longer time series is helpful in order to ensure accurate inference from this model; T=20 is a rule of thumb for a minimum (Esarey and DeMeritt Reference Esarey and DeMeritt2014, 76). Thus, while we report model results for the TI CPI model (with T=15) in Figure 2, we note that the result for the ICRG measure (with T=20) is substantively similar.

94 At the suggestion of an anonymous reviewer, we conducted a robustness check for all our hypothesis tests using the TI CPI dependent variable and adding two additional control variables: years since women’s suffrage was granted without restrictions (Inter-Parliamentary Union n.d.) and official development assistance from the Organisation for Economic Co-operation and Development recorded in replication data for Lebovic and Voeten (Reference Lebovic and Voeten2009). The results, which are substantively similar to those presented in the main body of the article, are shown in Appendix Table S1.

95 Note that this argument is quite different than saying that networks of corrupt officials collude to suppress female participation in government (which often involves newcomers to governance) as a part of ensuring and increasing the benefits that they derive from corrupt governance; this alternative argument has been made by others in the literature who believe that corruption suppresses women’s participation in government (Bjarnegård Reference Bjarnegård2013; Goetz Reference Goetz2007; Grimes and Wängnerud Reference Grimes and Wängnerud2012; Johnson, Einarsdóttir, and Pétursdóttir Reference Johnson, Einarsdóttir and Pétursdóttir2013; Stockemer Reference Stockemer2011; Sundström and Wängnerud 2016). It is conceivable that corrupt officials exert more effort to suppress female participation in high-accountability environments, where women are less likely to co-operate with corruption. Yet heightened accountability to voters for corruption would presumably make it easier for women to gain office in spite of corruption, as prior research argues that many women come to participate in politics through social movements that (among other activities) work against corruption and serve as the basis for independent political networks (Rodríguez Reference Rodríguez2003). Corruption fighting can even become a signature issue for female candidates (Goetz Reference Goetz2002, 566).

96 See Appendix Table S2 for an initial instrumental variable model that uses two-period lagged values of the independent variables as instruments; future research would presumably offer instruments for electoral accountability that do not depend on assumptions about dynamics.

97 Goetz Reference Goetz2007, 102.

References

Adserà, Alícia, Boix, Carles, and Payne, Mark. 2003. Are You Being Served? Political Accountability and Quality of Government. Journal of Law, Economics, and Organization 19:445490.CrossRefGoogle Scholar
Alatas, Vivi, Cameron, Lisa, Chaudhuri, Ananish, Erkal, Nisvan, and Gangadharan, Lata. 2009. Gender, Culture, and Corruption: Insights from an Experimental Analysis. Southern Economic Journal 75:663680.CrossRefGoogle Scholar
Alhassan-Alolo, Namawu. 2007. Gender and Corruption: Testing the New Consensus. Public Administration and Development 27 (3):227237.Google Scholar
Anzia, Sarah F., and Berry, Christopher R.. 2011. The Jackie (and Jill) Robinson Effect: Why Do Congresswomen Outperform Congressmen? American Journal of Political Science 55:478493.CrossRefGoogle Scholar
Armantier, Olivier, and Boly, Amadou. 2011. A Controlled Field Experiment on Corruption. European Economic Review 55:10721082.Google Scholar
Barnes, Tiffany D., and Beaulieu, Emily. 2014. Gender Stereotypes and Corruption: How Candidates Affect Perceptions of Election Fraud. Politics & Gender 10:365391.CrossRefGoogle Scholar
Bauer, Gretchen, and Tremblay, Manon. 2011. Women in Executive Power: A Global Overview, 1st Edition. New York: Routledge.CrossRefGoogle Scholar
Bernasek, Alexandra, and Shwiff, Stephanie. 2001. Gender, Risk, and Retirement. Journal of Economic Issues 35:345356.CrossRefGoogle Scholar
Bjarnegård, Elin. 2013. Gender, Informal Institutions and Political Recruitment: Explaining Male Dominance in Parliamentary Representation. Basingstoke, UK: Palgrave Macmillan.CrossRefGoogle Scholar
Brambor, Thomas, Clark, William Roberts, and Golder, Matt. 2006. Understanding Interaction Models: Improving Empirical Analyses. Political Analysis 14:6382.Google Scholar
Branisa, Boris, and Ziegler, Maria. 2011. Reexamining the Link Between Gender and Corruption: The Role of Social Institutions. Proceedings of the German Development Economics Conference, Berlin. Verein für Socialpolitik, Research Committee Development Economics. Available from http://ideas.repec.org/p/zbw/gdec11/15.html, accessed 19 November 2014.Google Scholar
Byrnes, James P., Miller, David C., and Schafer, William D.. 1999. Gender Differences in Risk-Taking: A Meta-Analysis. Psychological Bulletin 125:367383.Google Scholar
Cain, Bruce, Ferejohn, John, and Fiorina, Morris. 1990. The Personal Vote: Constituency Service and Electoral Independence. Cambridge, MA: Harvard University Press.Google Scholar
Carey, John M., and Shugart, Matthew Soberg. 1995. Incentives to Cultivate a Personal Vote: A Rank Ordering of Electoral Formulas. Electoral Studies 14:417439.Google Scholar
Central Intelligence Agency (CIA). 2013. CIA World Factbook. Available from https://www.cia.gov/library/publications/the-world-factbook/index.html, accessed 22 June 2016.Google Scholar
Chang, Eric C. C. 2005. Electoral Incentives for Political Corruption Under Open-List Proportional Representation. Journal of Politics 67:716730.CrossRefGoogle Scholar
Chang, Eric C. C., and Golden, Miriam A.. 2007. Electoral Systems, District Magnitude and Corruption. British Journal of Political Science 37:115137.CrossRefGoogle Scholar
Chaudhuri, Ananish. 2012. Gender and Corruption: A Survey of the Experimental Evidence. In New Advances in Experimental Research on Corruption , edited by Danila Serra and Leonard Wantchekon, 1349. Bingley, UK: Emerald.Google Scholar
Childs, Sarah, and Krook, Mona Lena. 2012. Labels and Mandates in the United Kingdom. In The Impact of Gender Quotas, edited by Susan Franceschet, Mona Lena Krook and Jennifer M. Piscopo, 89102. Oxford: Oxford University Press.Google Scholar
Cingranelli, David, and Richards, David. 2010. The Cingranelli-Richards (CIRI) Human Rights Dataset. Available from http://www.humanrightsdata.com, accessed 22 June 2016.Google Scholar
Clague, Christopher, Keefer, Philip, Knack, Stephen, and Olson, Mancur. 1999. Contract-Intensive Money: Contract Enforcement, Property Rights, and Economic Performance. Journal of Economic Growth 4:185211.CrossRefGoogle Scholar
Croson, Rachel, and Gneezy, Uri. 2009. Gender Differences in Preferences. Journal of Economic Literature 47:448474.Google Scholar
Dolan, Kathleen. 2010. The Impact of Gender Stereotyped Evaluations on Support for Women Candidates. Political Behavior 32:6988.Google Scholar
Dolan, Kathleen. 2014. Gender Stereotypes, Candidate Evaluations, and Voting for Women Candidates What Really Matters? Political Research Quarterly 67:96107.CrossRefGoogle Scholar
Dollar, David, Fisman, Raymond, and Gatti, Roberta. 2001. Are Women Really the ‘Fairer’ Sex? Corruption and Women in Government. Journal of Economic Behavior & Organization 46:423429.Google Scholar
Donchev, Dilyan, and Ujhelyi, Gergely. 2014. What Do Corruption Indices Measure? Economics & Politics 26:309331.Google Scholar
Dowling, Conor M., and Miller, Michael G.. 2015. Can Information Alter Perceptions About Women’s Chances of Winning Office? Evidence from a Panel Study. Politics & Gender 11:5588.CrossRefGoogle Scholar
Eckel, Catherine C., and Grossman, Philip J.. 2008. Men, Women, and Risk Aversion: Experimental Evidence. In Handbook of Experimental Economic Results, Vol. 1, edited by Charles Plott and Vernon Smith, 10611073. New York: Elsevier.Google Scholar
Economist, The . 2013. What is Brazil’s ‘Mensalão’? The Economist, 18 November. Available from http://www.economist.com/blogs/economist-explains/2013/11/economist-explains-14, accessed 5 April 2014.Google Scholar
Elgie, Robert. 2011. Semi-Presidentialism: Sub-Types and Democratic Performance. New York and Oxford: Oxford University Press.Google Scholar
Esarey, Justin, and Chirillo, Gina. 2013. ‘Fairer Sex’ or Purity Myth? Corruption, Gender, and Institutional Context. Politics and Gender 9:390413.Google Scholar
Esarey, Justin, and DeMeritt, Jacqueline H. R.. 2014. Defining and Modeling State-Dependent Dynamic Systems. Political Analysis 22:6185.Google Scholar
Fisman, Raymond, and Miguel, Edward. 2007. Corruption, Norms, and Legal Enforcement: Evidence from Diplomatic Parking Tickets. Journal of Political Economy 115:10201048.Google Scholar
Fox, Richard L., and Lawless, Jennifer L.. 2004. Entering the Arena? Gender and the Decision to Run for Office. American Journal of Political Science 48:264280.Google Scholar
Franceschet, Susan, and Piscopo, Jennifer M.. 2008. Gender Quotas and Women’s Substantive Representation: Lessons from Argentina. Politics & Gender 4:393425.Google Scholar
Freedom House. 2014. Freedom in the World. Available from http://www.freedomhouse.org/report/freedom-world/freedom-world-2014, accessed 4 February 2014.Google Scholar
Gerring, John, and Thacker, Strom C.. 2004. Political Institutions and Corruption: The Role of Unitarism and Parliamentarism. British Journal of Political Science 34:295330.Google Scholar
Gneezy, Uri, Leonard, Kenneth L., and List, John A.. 2009. Gender Differences in Competition: Evidence from a Matrilineal and a Patriarchal Society. Econometrica 77:16371664.Google Scholar
Goetz, Anne Marie. 2002. No Shortcuts to Power: Constraints on Women’s Political Effectiveness in Uganda. The Journal of Modern African Studies 40:549575.CrossRefGoogle Scholar
Goetz, Anne Marie. 2007. Political Cleaners: Women as the New Anti-Corruption. Development and Change 38:87105.CrossRefGoogle Scholar
Grimes, Marcia, and Wängnerud, Lena. 2012. Good Government in Mexico: The Relevance of the Gender Perspective. QoG Working Paper Series. Gothenburg: University of Gothenburg. Available from http://www.qog.pol.gu.se/digitalAssets/1384/1384935_2012_11_grimes_w--ngnerud.pdf, accessed 25 October 2016.Google Scholar
Hellwig, Timothy, and Samuels, David. 2008. Electoral Accountability and the Variety of Democratic Regimes. British Journal of Political Science 38 (1):6590.CrossRefGoogle Scholar
Helmke, Gretchen, and Levitsky, Steven. 2004. Informal Institutions and Comparative Politics: A Research Agenda. Perspectives on Politics 2:725740.Google Scholar
Henrich, Joseph, and McElreath, Richard. 2002. Are Peasants Risk-Averse Decision Makers? Current Anthropology 43 (1):172181.Google Scholar
Holt, Charles A., and Laury, Susan K.. 2002. Risk Aversion and Incentive Effects. The American Economic Review 92:16441655.CrossRefGoogle Scholar
Hsiao, Cheng. 2003. Analysis of Panel Data. New York and Cambridge: Cambridge University Press.Google Scholar
Inglehart, Ronald, and Norris, Pippa. 2003. Rising Tide: Gender Equality and Cultural Change Around the World. New York and Cambridge: Cambridge University Press.Google Scholar
Inter-Parliamentary Union. 2012. Women in Parliaments: World and Regional Averages. Available from http://www.ipu.org/wmn-e/world.htm, accessed 11 July 2012.Google Scholar
Inter-Parliamentary Union. n.d. Women’s Suffrage. Available from http://www.ipu.org/wmn-e/suffrage.htm, accessed 2 January 2016.Google Scholar
Johnson, Janet Elise, Einarsdóttir, Þorgerður, and Pétursdóttir, Gyða Margrét. 2013. A Feminist Theory of Corruption: Lessons from Iceland. Politics & Gender 9:174206.CrossRefGoogle Scholar
Johnson, Jesse C., Souva, Mark, and Smith, Dale L.. 2013. Market-Protecting Institutions and the World Trade Organization’s Ability to Promote Trade. International Studies Quarterly 57:410417.Google Scholar
Johnson, Joel W., and Wallack, Jessica S.. 1997. Electoral Systems and the Personal Vote. Harvard Dataverse Network. Available from http://hdl.handle.net/1902.1/17901 V1, accessed 22 June 2016.Google Scholar
Jones, Philip Edward. 2014. Does the Descriptive Representation of Gender Influence Accountability for Substantive Representation? Politics & Gender 10:175199.Google Scholar
Judson, Ruth A., and Owen, Ann L.. 1999. Estimating Dynamic Panel Data Models: A Guide for Macroeconomists. Economics Letters 65:915.Google Scholar
Kahn, Carrie. 2013. Mexican State’s Anti-Corruption Plan: Hire Female Traffic Cops. NPR.org. Available from http://www.npr.org/2013/09/28/226903227/mexican-state-s-anti-corruption-plan-hire-women-traffic-cops, accessed 23 April 2014.Google Scholar
Karim, Sabrina. 2011. Madame Officer. Americas Quarterly, 5. Available from http://www.americasquarterly.org/node/2802/, accessed 20 July 2012.Google Scholar
Kaufmann, Daniel, Kraay, Aart, and Mastruzzi, Massimo. 2007. Measuring Corruption: Myths and Realities. Available from https://wdronline.worldbank.com/handle/10986/9576, accessed 19 December 2015.Google Scholar
Kaufmann, Daniel, Kraay, Aart, and Mastruzzi, Massimo. 2010. The Worldwide Governance Indicators: Methodology and Analytical Issues. Policy Research Working Paper No. 5430. Washington, DC: World Bank. Available from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1682130, accessed 25 October 2016.Google Scholar
Knack, Stephen. 2007. Measuring Corruption: A Critique of Indicators in Eastern Europe and Central Asia. Journal of Public Policy 27:255291.Google Scholar
Kolstad, Ivar, and Wiig, Arne. 2011. Does Democracy Reduce Corruption? Working Paper No. 4. Bergen, Norway: Chr. Michelsen Institute. Available from https://www.cmi.no/publications/file/4315-does-democracy-reduce-corruption.pdf, accessed 25 October 2016.Google Scholar
Kunicová, Jana. 2006. Democratic Institutions and Corruption: Incentives and Constraints in Politics. In International Handbook on the Economics of Corruption, edited by Susan Rose-Ackerman, 140160. Northampton, MA: Edward Elgar.Google Scholar
Kunicová, Jana, and Rose-Ackerman, Susan. 2005. Electoral Rules and Constitutional Structures as Constraints on Corruption. British Journal of Political Science 35:573606.Google Scholar
Lambsdorff, Johann Graf. 2006. Measuring Corruption – The Validity and Precision of Subjective Indicators (CPI). In Measuring Corruption, edited by Charles J. G. Sampford, Arthur Shacklock, Carmel Connors, and Fredrik Galtung, 8199. Burlington, VT: Ashgate Publishing, Ltd.Google Scholar
Lawless, Jennifer L. 2004. Women, War, and Winning Elections: Gender Stereotyping in the Post-September 11th Era. Political Research Quarterly 57:479490.Google Scholar
Lawless, Jennifer L., and Fox, Richard L.. 2005. It Takes a Candidate: Why Women Don’t Run for Office. New York: Cambridge University Press.Google Scholar
Lebovic, James H., and Voeten, Erik. 2009. The Cost of Shame: International Organizations and Foreign Aid in the Punishing of Human Rights Violators. Journal of Peace Research 46:7997.Google Scholar
Lederman, Daniel, Loayza, Norman V., and Soares, Rodrigo R.. 2005. Accountability and Corruption: Political Institutions Matter. Economics & Politics 17:135.Google Scholar
Linz, Juan J. 1990. The Perils of Presidentialism. Journal of Democracy 1:5169.Google Scholar
Linz, Juan J. 1994. Presidential or Parliamentary: Does It Make a Difference?. In The Failure of Presidential Democracy, Vol. 1, edited by Juan J. Linz and Arturo Valenzuela, 390. Baltimore, MD: Johns Hopkins University Press.Google Scholar
Mainwaring, Scott, and Shugart, Matthew Sobert. 1997. Juan Linz, Presidentialism, and Democracy: A Critical Appraisal. Comparative Politics 29:449472.CrossRefGoogle Scholar
Marshall, Monty, Gurr, Ted Robert, and Jaggers, Keith. 2014. Polity IV Project Political Regime Characteristics and Transitions, 1800–2013: Dataset Users’ Manual. Available from http://www.systemicpeace.org/inscr/p4manualv2013.pdf, accessed 9 November 2014.Google Scholar
McDermott, Jeremy. 1999. International: Women Police Ride In On A Ticket of Honesty. The Daily Telegraph, 31 July 31, 17.Google Scholar
Mishra, Ajit. 2006. Persistence of Corruption: Some Theoretical Perspectives. World Development 34:349358.Google Scholar
Moore, Molly. 1999. Mexico City’s Stop Sign to Bribery; To Halt Corruption, Women Traffic Cops Replace Men. The Washington Post, 31 July, A15.Google Scholar
Morgan, Jana, and Buice, Melissa. 2013. Latin American Attitudes Toward Women in Politics: The Influence of Elite Cues, Female Advancement, and Individual Characteristics. American Political Science Review 107:644662.Google Scholar
Murray, Rainbow. 2010. Cracking the Highest Glass Ceiling: A Global Comparison of Women’s Campaigns for Executive Office, 1st Edition. Santa Barbara, CA: Praeger.CrossRefGoogle Scholar
Neyman, Jerzy, and Scott, Elizabeth L.. 1948. Consistent Estimates Based on Partially Consistent Observations. Econometrica: Journal of the Econometric Society 16 (1):132.Google Scholar
Nickell, Stephen. 1981. Biases in Dynamic Models with Fixed Effects. Econometrica: Journal of the Econometric Society 49 (6):14171426.Google Scholar
Paul, David, and Smith, Jessi L.. 2008. Subtle Sexism? Examining Vote Preferences When Women Run Against Men for the Presidency. Journal of Women, Politics & Policy 29:451476.CrossRefGoogle Scholar
Persson, Torsten, Roland, Gerard, and Tabellini, Guido. 1997. Separation of Powers and Political Accountability. Quarterly Journal of Economics 112:11631202.Google Scholar
Persson, Torsten, and Tabellini, Guido. 2002. Political Economics: Explaining Economic Policy. Cambridge, MA: MIT Press.Google Scholar
Persson, Torsten, Tabellini, Guido, and Trebbi, Francesco. 2003. Electoral Rules and Corruption. Journal of the European Economic Association 1:958989.CrossRefGoogle Scholar
Political Risk Services Group. 2012. ICRG Methodology. Available from http://www.prsgroup.com/ICRG_Methodology.aspx, accessed 11 July 2012.Google Scholar
Provost, Claire. 2013. Is Transparency International’s Measure of Corruption Still Valid? The Guardian, 3 December.Google Scholar
Przeworski, Adam, Alvarez, Michael E., Cheibub, Jose Antonio, and Limongi, Fernando. 2000. Democracy and Development: Political Regimes and Material Well-Being in the World, 1950–1990. In Political Science and the Public Interest, edited by Edward D. Mansfield and Richard Sisson. Columbus: Ohio State University Press.Google Scholar
Quinones, Sam. 1999. Stop! Ms, December, 24.Google Scholar
Reed, William Robert. 2015. On the Practice of Lagging Variables to Avoid Simultaneity. Oxford Bulletin of Economics and Statistics 77:897905.Google Scholar
Rodríguez, Victoria E. 2003. Women in Contemporary Mexican Politics. Austin: University of Texas Press.Google Scholar
Roodman, David. 2006. How to Do xtabond2: An Introduction to ‘Difference’ and ‘System’ GMM in Stata. The Stata Journal 9:86136.Google Scholar
Rose-Ackerman, Susan. 1999. Corruption and Government: Causes, Consequences, and Reform. New York: Cambridge University Press.Google Scholar
Royston, Patrick, and White, Ian R.. 2011. Multiple Imputation by Chained Equations (MICE): Implementation in Stata. Journal of Statistical Software 45:120.Google Scholar
Rubin, Donald B. 1996. Multiple Imputation After 18+ Years. Journal of the American Statistical Association 91:473489.Google Scholar
Samuels, David, and Shugart, Matthew. 2003. Presidentialism, Elections and Representation. Journal of Theoretical Politics 15:3360.CrossRefGoogle Scholar
Samuels, David, and Shugart, Matthew. 2010. Presidents, Parties, and Prime Ministers: How the Separation of Powers Affects Party Organization and Behavior. New York and Cambridge: Cambridge University Press.Google Scholar
Schulze, Günther G., and Frank, Björn. 2003. Deterrence Versus Intrinsic Motivation: Experimental Evidence on the Determinants of Corruptibility. Economics of Governance 4:143160.Google Scholar
Schwindt-Bayer, Leslie. 2010. Political Power and Women’s Representation in Latin America. New York: Oxford University Press.Google Scholar
Schwindt-Bayer, Leslie, and Tavits, Margit. 2016. Clarity of Responsibility, Accountability and Corruption. New York: Cambridge University Press.Google Scholar
Schwindt-Bayer, Leslie A., Malecki, Michael, and Crisp, Brian F.. 2010. Candidate Gender and Electoral Success in Single Transferable Vote Systems. British Journal of Political Science 40:693709.Google Scholar
Seltzer, Richard A., Newman, Jody, and Leighton, Melissa Voorhees. 1997. Sex as a Political Variable: Women as Candidates and Voters in U.S. Elections. Boulder, CO: Lynne Rienner Publishers.CrossRefGoogle Scholar
Shugart, Matthew, and Carey, John M.. 1992. Presidents and Assemblies Constitutional Design and Electoral Dynamics. Cambridge and New York: Cambridge University Press.Google Scholar
Stockemer, Daniel. 2011. Women’s Parliamentary Representation in Africa: The Impact of Democracy and Corruption on the Number of Female Deputies in National Parliaments. Political Studies 59:693712.Google Scholar
Sundén, Annika E., and Surette, Brian J.. 1998. Gender Differences in the Allocation of Assets in Retirement Savings Plans. The American Economic Review 88:207211.Google Scholar
Sundström, Aksel, and Wängnerud, Lena. 2016. Corruption as an Obstacle to Women’s Political Representation Evidence from Local Councils in 18 European Countries. Party Politics 22 (3):354369.Google Scholar
Sung, Hung-En. 2003. Fairer Sex or Fairer System? Gender and Corruption Revisited. Social Forces 82:703723.Google Scholar
Swamy, Anand, Knack, Stephen, Lee, Young, and Azfar, Omar. 2001. Gender and Corruption. Journal of Development Economics 64:2555.Google Scholar
Tavits, Margit. 2007. Clarity of Responsibility and Corruption. American Journal of Political Science 51:218229.Google Scholar
Teorell, Jan, Charron, Nicholas, Samanni, Marcus, Holmberg, Sören, and Rothstein, Bo. 2015. The Quality of Government Dataset, Version Jan 15. University of Gothenburg: The Quality of Government Institute. Available from http://www.qog.pol.gu.se.Google Scholar
Transparency International. 2011. Methodological Brief. Available from http://www.transparencykazakhstan.org/UserFiles/file/CPI_2009_methodology_eng.pdf, accessed 11 July 2012.Google Scholar
Transparency International. 2015. Research – GCB – Overview. Available from http://www.transparency.org/research/gcb/overview, accessed 15 December 2015.Google Scholar
Treisman, Daniel. 2000. The Causes of Corruption: A Cross-National Study. Journal of Public Economics 76:399457.CrossRefGoogle Scholar
Treisman, Daniel. 2007. What Have We Learned About the Causes of Corruption from Ten Years of Cross-National Empirical Research? Annual Review of Political Science 10:211244.Google Scholar
Tripp, Aili. 2001. Women’s Movements and Challenges to Neopatrimonial Rule: Preliminary Observations from Africa. Development and Change 32:3354.Google Scholar
van Buuren, Stef. 2012. Flexible Imputation of Missing Data. Boca Raton, FL: Chapman and Hall/CRC.Google Scholar
Wangnerud, Lena. 2012. Why Women Are Less Corrupt than Men. In Good Government: The Relevance of Political Science, edited by Sören Holmberg and Bo Rothstein, 230250. Northampton, MA: Edward Elgar.Google Scholar
Watson, David, and Moreland, Amy. 2014. Perceptions of Corruption and the Dynamics of Women’s Representation. Politics & Gender 10:392412.Google Scholar
Watson, John, and McNaughton, Mark. 2007. Gender Differences in Risk Aversion and Expected Retirement Benefits. Financial Analysts Journal 63:5262.Google Scholar
World Bank. 2013. World Development Indicators. Available from http://data.worldbank.org/data-catalog/world-development-indicators, accessed 4 February 2014.Google Scholar
Figure 0

Table 1 Dataset Summary Statistics

Figure 1

Fig. 1 How does the past prevalence of corruption influence the relationship between gender and corruption?Note: the figure shows the relationship between the TI CPI and the percentage of women in the lower house for seventy-six democratic-leaning countries between the years 1996–2010; the top panel shows countries with prior TI CPI scores>5 and the bottom panel shows countries with TI CPI scores≤5. The difference between the slopes is 0.070, which is statistically significant (p<0.001).

Figure 2

Fig. 2 How does the relationship between gender and corruption differ by prior corruption?Note: the figure reports the marginal effect of the percentage of female members in the lower house of parliament on the TI CPI for different lagged values of the TI CPI score. Estimates are based on Model 1 reported in Table 2.

Figure 3

Table 2 How Does the Past Prevalence of Corruption Influence the Relationship Between Gender and Three Measures of Corruption?

Figure 4

Fig. 3 How does press freedom influence the relationship between gender and corruption? Note: the figure shows the relationship between the TI CPI and the percentage of women in the lower house for seventy-six democratic-leaning countries between the years 1995–2010; the top panel shows countries with press freedom scores≤−30 and the bottom panel shows countries with press freedom scores>−30. The difference between the slopes is 0.110, which is statistically significant (p<0.001).

Figure 5

Fig. 4 How does the relationship between gender and corruption differ by press freedom? Note: the figure reports the marginal effect of the percentage of female members in the lower house of parliament on the TI CPI for different values of the press freedom variable. Estimates are based on Model 1 reported in Table 3.

Figure 6

Table 3 How Does Press Freedom Influence the Relationship Between Gender and Three Measures of Corruption?

Figure 7

Fig. 5 How does separation of powers influence the relationship between gender and corruption? Note: the figure shows the relationship between the TI CPI and the percentage of women in the lower house for seventy-six democratic-leaning countries between the years 1995–2010; the top panel shows countries with presidential systems and the bottom panel shows countries with parliamentary systems. The difference between the slopes is 0.148, which is statistically significant (p<0.001).

Figure 8

Fig. 6 How does the relationship between gender and corruption differ by government type? Note: the figure reports the marginal effect of the percentage of female members in the lower house of parliament on the TI CPI for parliamentary and presidential systems. Estimates are based on Model 1 reported in Table 4.

Figure 9

Table 4 How Does Separation of Powers (Accountability) Influence the Relationship Between Gender and Three Measures of Corruption?

Figure 10

Fig. 7 How does personal accountability influence the relationship between gender and corruption? Note: the figure shows the simple bivariate relationship between the TI CPI and the percentage of women in the lower house for seventy-six democratic-leaning countries between the years 1995–2010; the top panel shows countries with personalism scores≤6, and the bottom panel shows countries with personalism scores>6. The difference between the slopes is 0.082, which is statistically significant (p<0.001).

Figure 11

Fig. 8 How does the relationship between gender and corruption change as personalism changes? Note: the figure reports the marginal effect of the percentage of female members in the lower house of parliament on the TI CPI at different levels of personalism (Johnson and Wallack 1997). Estimates are based on Model 1 reported in Table 5.

Figure 12

Table 5 How Does Personal Accountability Influence the Relationship Between Gender and Three Measures of Corruption?

Supplementary material: Link

Esarey and Schwindt-Bayer Dataset

Link
Supplementary material: PDF

Esarey and Schwindt-Bayer supplementary material

Tables S1-S6 and Figure S1

Download Esarey and Schwindt-Bayer supplementary material(PDF)
PDF 171.3 KB