2nd Draft
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Public Sector Corruption and Gender
Perceptions of Public Officials from Six Developing and Transition
Countries
Omer Gokcekus & Ranjana Mukherjee
Second Draft: June 2002
Abstract: Based on 3,927 responses from surveying public officials in six developing
and transition countries, this paper empirically shows that when the proportion of women
is very low, increasing that proportion reduces the severity of corruption and increases
the chances of its being reported. However, increasing women’s proportion of public
officials beyond a threshold value is counter-productive because that raises corruption
and lowers its chances of being reported.
1
I.
Introduction
Corruption undermines economic development and damages social stability (Grindle,
1997; World Bank, 2000a and 2000b). Concern about corruption has intensified in recent
years, and is accompanied by the effort to understand corruption. Bardhan, (1991),
Gupta, Davoodi, and Alonso-Terme (1998); Klitgaard (1998), Mauro (1997); Tanzi and
Davoodi (1997); and World Bank (2000) have focused on the economic, political, and
historical factors underlying the persistence of corruption, its patterns and size; and its
causes and consequences. Little is known about strategies that have been successful at
reducing corruption. Could the proportion of women employees in a public organization
be connected with the level of corruption in that organization? If women are underrepresented in public organizations’ employment, and if raising the percentage of women
is associated with reduced levels of corruption, then actively promoting women’s
employment could be part of the World Bank’s strategy to improve governance.
Possible connections between gender and corruption have not been adequately
investigated. The World Bank (2002, p. 9), while outlining a strategy for integrating
gender into its work, notes, “…a growing body of evidence suggests that gender equality
in rights and resources is associated with less corruption and better governance….” The
evidence cited in this World Bank report (Integrating Gender into the World Bank’s
Work: A Strategy for Action) is based upon two studies. Lambsdorff (1999) lists the same
two studies under corruption and gender in a detailed review of the available empirical
research on corruption. In the first study, Dollar, Fisman, and Gatti (1999), using
numerous behavioral studies, found women to be more trust-worthy and public-spirited
than men. They found, in a large cross-section of countries, the greater the representation
of women in parliament, the lower the level of corruption. In the second, Swamy, Knack,
Lee and Azfar (2001) used several independent data sets to show that corruption is less
severe where women comprise a larger share of labor force, and where women hold a
larger share of parliamentary seats.
2
The two studies provide preliminary evidence of a commonly held belief that increasing
women’s representation might reduce corruption in an organization and its environment.
The two previous papers found evidence of this in women’s representation in parliament
and in the labor force. The present paper examines whether this is applicable in public
sector organizations. Is corruption in public sector organizations connected with the
percentage of women employed in them? This investigation utilizes survey data from
World Bank funded surveys (see www1.worldbank.org/publicsector/civil
service/surveys.htm) of nearly 4 thousands public officials in 6 countries. It checks if
there is a statistically significant connection between the percentage of women in public
sector organizations on the one hand, and (i) severity of corruption, and (ii) its probability
of being reported –on the other. Officials’ responses to survey questions provide
necessary information for checking the empirical relationship between gender and
corruption at three different levels—across countries, within countries, and considering a
pool of public organizations regardless of country.
Results of the present investigation show that when public organizations have too few
women (less than one-third), increasing the proportion of females reduces the severity of
corruption. However, continuously increasing the proportion of females is counterproductive. After a certain threshold, further increasing the proportion of women
increases corruption and reduces the chances of its being reported.
The rest of this paper is organized into three main sections. Section one introduces the
data set, the concepts and the corresponding indices, and discusses the reliability of selfreported perceptions of public officials. Section two discusses the three levels of
analyses and presents the findings. Finally, section three contains concluding remarks,
and a discussion of the policy implications of these findings.
3
II.
Data Set and Indices
Before analyzing the relationship between women officials’ proportion in public
organizations, the severity of corruption and its probability of being reported, it is
necessary to explain how two appropriate corruption indices (severity, and reporting
probability) were constructed, and why these indices were considered reliable measures.
Responses of 3,927 officials from 90 organizations were utilized to construct corruption
indices.1
Table 1 Data Set Summary
Number of
Number of public
organizations
officials surveyed
surveyed
1 Argentina 370
5
2 Bolivia
692
16
3 Bulgaria 1,089
23
4 Guyana 464
15
5 Indonesia 640
15
6 Moldova 672
16
Total
3,927
90
Country
Number of
women in the
sample
155
201
741
278
166
296
1,837
Percentage of
women
42%
29%
68%
60%
26%
44%
47%
During each of the six country surveys, officials were first asked to assess the severity of
corruption in their organizations as follows:
Some consider that one of the main problems affecting the performance of the
Government and its structures is corruption. How important is this problem in
your organization?
1) Very important
2) Relatively important
3) Of little importance
4) Not important at all
Officials were next asked about the chances of reporting corruption:
In general, how often are cases of corruption reported to proper authorities?
1
Public officials surveys were administered in 16 countries. For the purpose of this investigation, only six
countries were selected because they each contained almost identically worded questions probing the same
issue. Sample distribution in all surveys closely followed actual distribution of officials (level, type of
organization), and random stratified sampling was commonly employed.
4
1) Always
2) Frequently
3) Sometimes
4) Never
Officials’ responses to these corruption-probing questions were on closed-ended but
varying descriptive scales—depending on the exact questions asked. For instance,
Moldavian officials being asked about the severity of corruption were asked to choose
among four responses ‘very important,’ ‘relatively important,’ ‘of little importance,’ and
‘not important at all’. Argentinean officials, on the other hand, were asked to choose
among three choices whether corruption was a ‘significant problem,’ ‘somewhat of a
problem,’ or ‘not much of a problem.’ Similar minor variations appeared in questions
about reporting cases of corruption. Moldavian officials were asked to choose between
‘always,’ ‘frequently,’ ‘sometimes,’ ‘never’. In Bulgaria, the available responses to
whether corruption is reported were ‘yes’ or ‘no’.
To measure all surveyed organizations’ corruption indices on the same scale, officials’
descriptive responses were converted to a numerical scale of 0 to 10,where 0 = good i.e.
no corruption, and 10 = bad, i.e. highly corrupt. The following formulas were used to
convert the different scales to a common scale: For questions with four response choices:
1 = very important, 2 = relatively important, 3 = of little importance, and 4 = not
important at all, CORRUPTION INDEX organization-i = 40/3 – 10/3 (Average response
organization-i).
For questions with three responses 1 = significant problem, 2 = somewhat of a
problem, or 3 = not much of a problem, CORRUPTION INDEX organization-i = 15 – 5
(Average response organization-i)
Table 2 below summarizes surveyed officials’ perceptions of the level of corruption and
its probability of being reported.
5
Table 2 Officials’ perceptions of severity and reporting of corruption
Country
Percentage of officials who reported
Percentage of officials who reported
that corruption is a serious /
that corruption is not reported
important problem
All officials Female
Male
All officials Female
20%
28%
75%
44%
Male
1
2
3
4
Argentina
Bolivia
Bulgaria
Guyana
62%
88%
50%
32%
61%
87%
53%
34%
63%
88%
41%
28%
18%
31%
73%
44%
5
Indonesia
93%
93%
93%
The survey administered to Indonesian
officials did not ask whether cases of
corruption are reported to proper authorities
6
Moldova
73%
76%
69%
18%
17%
16%
35%
70%
44%
18%
Reliability of using officials’ perceptions to measure corruption
Table 2 above shows that women do not systematically under or over-estimate
corruption. The biggest perception difference (12%) among genders was in Bulgaria.
However, according to two-sided t-tests, these differences are not statistically significant
even at a 0.10 level.
Officials’ subjective assessments based upon their perceptions of corruption were utilized
in the present investigation to estimate public organization’s severity and reporting of
corruption. Perceptions are hard to measure and easy to challenge. Therefore, even before
checking the relation between gender and corruption in public organizations, the
reliability of using officials’ perceptions of corruption were checked against another
estimate of corruption that is not based on perceptions. Transparency International’s (TI)
Corruption Perception Indices (CPI) are composite, based upon assessments of business
people and risk analysts, utilize 14 different data sources from seven different
institutions, and omit countries where fewer than three reliable sources of data are
available (Lambsdorff 2001, p.232-233.). Transparency International’s 2001 Corruption
Perception Indices were available for all surveyed countries in the present sample except
Guyana. TI’s widely acceptable 2001 CPIs were compared against each of the present
study’s surveyed organizations’ corruption index. The comparison showed that public
6
organizations’ corruption as calculated in the present investigation from officials’ survey
responses is almost perfectly correlated with Transparency International’s estimate
(Figure 1). The estimated correlation coefficient is 0.99, which is statistically significant
at a 0.01 level, according to a two-sided t-test. Transparency International found overall
corruption to be high in Indonesia and Bolivia, and low in Bulgaria. Officials in Bolivian
and Indonesian public organizations have rated severity of corruption in their
organizations as very high; while officials in Bulgaria estimated their own organizations’
corruption as less severe.
Percentage of officials that reported corruption to be a
significant problem
Figure 1 Public officials perceptions of corruption versus TI-2001 Corruption
Perception Indices
100%
y = 1.30 -0.20x
R2 = 0.97
Indonesia
90%
Bolivia
80%
Moldova
70%
Argentina
60%
Bulgaria
50%
40%
1
2
3
4
Transparency International's 2001 Corruption Perceptions Index
(10 = very little corrution, 0 = highly corrupt)
III.
Main Findings
The association between gender and corruption in public sector organizations was
assessed, using three different bases of analyses to avoid possible biases. The connection
between gender and corruption (severity and reporting probability) was checked: first,
7
across the six sampled countries; next, within each surveyed public sector; and finally,
within a common pool of public organizations regardless of country. At each level of
analysis, appropriate statistical tests were performed to determine the statistical
significance of the associations.
A. Cross-country Connections
Figure 2 presents the relationship between public officials’ estimate of corruption in the
public sector and the percentage of female officials employed in sampled organizations in
six countries. It shows that, in general, public sector corruption declines with rising
percentage of female employees. Among the sampled public sectors, Bolivia and
Indonesia had a comparatively small percentage of females, and high corruption.
Figure 2 Association of corruption severity with percentage of females employed in public
sector, r= 0.9
Percentage of officials who reported that
corruption is a significant problem
100%
Indonesia
Bolivia
75%
Moldova
Argentina
50%
Bulgaria
Guyana
25%
25%
50%
Percentage of female officials in public sector
Bulgaria and Guyana had a large percentage of females, and less severe corruption.
However, increasing females’ percentage beyond 60% proves counter-productive by
raising the severity of corruption.
75%
8
At cross-country level, the next relationship examined was that between the percentage of
female officials employed in the public sector and percentage of (all) officials reporting
that corruption is not reported. Figure 3 below presents the relationship between
corruption -reporting indicator and percentage of female officials in the public sector in
five countries. (As mentioned earlier in Table 2, the survey in Indonesia did not ask
officials about reporting corruption.) When the percentage of females is low (less than
one-third), increasing the percentage of females generally raises the likelihood of
corruption reporting. However, raising the percentage of females beyond 40% reduces
the likelihood of corruption being reported.
Figure 3 Association of reporting corruption with gender in public sector organizations, r=0.78
Percentage of officials who reported that
corruption is not reported
100%
75%
Bulgaria
50%
Guyana
Bolivia
25%
Moldova
Argentina
0%
25%
50%
75%
Percentage of female officials in public sector
Taken together, cross country empirical analysis suggests that having too few or too
many women is associated with an increase of the severity of corruption and a drop in
reporting.
9
B. Within-country Findings
Aggregate country pictures could be considered unreliable because they consider
averages of corruption indices of all surveyed public sector organizations in the country,
and each of those organizations could have widely varying levels of corruption and
proportions of female employees. Focusing on averages without taking standard
deviations into consideration might be misleading. Therefore, it is a useful exercise to
check whether, within each country, corruption of public sector organizations is
associated with the percentage of female officials employed in the organization.
To do this, surveyed organizations in each country were divided into two groups, HIGH
and LOW, depending on whether the percentage of female officials employed in that
organization were high or low. The classification of HIGH or LOW was not absolute, but
relative to the average of surveyed public organizations’ employment for that country.
Next, each public sector’s average percentage of females was calculated. Organizations
with the percentage of females at least one standard deviation above the country’s
average were included in HIGH group; similarly, organizations with percentage of
females at least one standard deviation below the country’s average were included in
LOW group. Both groups’ index of corruption severity and corruption reporting were
calculated.
Figure 4 shows that in four of the six sampled public sectors—Argentina, Bulgaria,
Guyana, and Indonesia, organizations with lower-than-average females had higher
corruption than organizations with higher-than-average proportion of females. These
differences are statistically significant at a 0.01 level in Guyana; at a 0.12 percent level in
Argentina; 0.14 level in Bulgaria; and at a 0.27 level in Indonesia. Gender had the
biggest impact on public sector corruption in Argentina and Guyana—2.19 and 2.07
standard deviations respectively. On the other hand, in Bolivia and Moldova, corruption
difference according to females’ percentage is small and not statistically significant.
Testing within-country differences between LOW and HIGH groups in these five
countries showed that the corruption severity difference is a statistically significant one at
a 0.12 level.
10
Severity of corruption (in standard deviations from the
national average)
Figure 4 Severity of corruption in public organizations with higher or lower
than average female officials
2
1.5
1.36
0.80
1
0.59
0.53
0.61
0.5
0.14
0
Argentina
Bolivia
Bulgaria
Guyana
Indonesia
Moldova
-0.5
-0.45
-1
-0.83
-0.49
-0.67
-0.87
-1.5
-1.54
-2
LOW
HIGH
Figure 5 below shows that in Bolivia (with the second-smallest percentage of female
officials in the sample, 29%), the chances of reporting corruption were higher in HIGH
public organizations. In the remaining sampled public sectors that already had more than
40% women officials – i.e. Argentina (42%), Moldova (44%), Guyana (60%) and
Bulgaria (68%), the chances of reporting corruption were lower in the HIGH group of
organizations.
11
Figure 5 Association of chances of reporting corruption with gender in public
organizations
Chances of reporting corruption (in standard deviations from the
national average)
1.2
1.05
1
0.85
0.8
0.6
0.38
0.4
0.25
0.23
0.2
-0.02
0
-0.2
Argentina
Bolivia
Bulgaria
Guyana
Moldova
-0.29
-0.4
-0.37
-0.6
-0.57
-0.57
-0.8
LOW
HIGH
Taken together, within country findings are that in Bolivia (29% women) and Moldova
(42% women), raising the proportion of women improves the severity of corruption. The
chances of corruption reporting improved with higher percentage of women only in
Bolivia that had less than 30% female officials.
C. Common pool of organizations regardless of country
To eliminate cultural or any other country-specific bias, the 90 surveyed public sector
organizations from the six countries were first placed in a common pool, and next divided
into four quartiles according to the percentage of female officials employed. The bottom
quartile i.e. the 22 public organizations with fewest females were labeled as LOWEST;
and the top quartile i.e. the 22 organizations with the highest percentage of female
officials were labeled as HIGHEST.
12
Figures 6 presents the average corruption and reporting corruption scores for LOWEST
and HIGHEST groups. For the LOWEST and HIGHEST groups, the average
standardized corruption scores were 0.18 and -0.39 respectively. The difference in
corruption severity is 0.57 standard deviation.
Corruption severity (in standard
deviations from the national average)
Figure 6 Organizations with the highest and lowest percentage of women had the lowest and
highest corruption severity
0.3
0.2
0.18
0.1
0
-0.1
LOWEST
HIGHEST
-0.2
-0.3
-0.4
-0.39
-0.5
Organizations in the highest and lowest quartiles
13
On the other hand, the average standardized reporting-corruption scores are 0.49 and -.25
for the LOWEST and HIGHEST agencies, respectively (Figure 7). The difference is a
Figure 7 Organizations with the highest and lowest percentage of women had the highest and
lowest chances of corruption being reported
Chances of corruption reporting (in
standard deviations from the national
average)
0.6
0.49
0.5
0.4
0.3
0.2
0.1
0
-0.1
LOWEST
HIGHEST
-0.2
-0.3
-0.25
Organizations in the highest and lowest quartiles
0.74 standard deviation, and as is summarized in Table 3, the corruption difference
between LOWEST and HIGHEST groups is statistically significant at a 0.01 level. Table
3 summarizes that the corruption difference between LOWEST and HIGHEST groups of
organizations is statistically significant at a .06 level
Table 3 Pair-Wise t-test for Differences in Means of Level of Corruption and Reporting
Corruption
Grouping
LOW
HIGH
│t-values│
Level of Corruption
1.71
Within-country
0.32
-0.46
(0.12)
1.87
Pooled-organization
0.18
-0.39
(0.06)
Reporting Corruption
Within-country
0.37
-0.19
Pooled-organization
0.49
-0.25
Two-tailed tests, assuming equal variances, (p-values in parentheses).
1.77
(0.11)
2.63
(0.01)
14
To control the effect of country specific variables’ and organizational functions’ effect on
corruption, a regression analysis was conducted. Dummy variables were created for
transition economies (two out of six in our sample of countries) and policy implementing
agencies (the most common type of organization surveyed). The table below presents the
estimation results.
Table 4 The OLS regression estimates
Intercept
Transition
POI
R-female
(R-female)2
R2
# of observations
Coefficients
7.776
-0.802
1.731
-9.139
11.682
Standard Error
1.067
0.569
0.522
5.014
5.557
t Stat
7.288
-1.408
3.316
-1.823
2.102
0.149
89
Transition countries had a relatively lower level of corruption than other countries in our
sample; and policy implementing organizations had a higher level of corruption than
organizations with other functions. Even controlling for these factors, increasing the
percentage of females up to 40% level reduces the level of corruption, and increasing
females beyond this level (of 40%) raises the severity of corruption. In other words,
having too few or too many women is associated with an increase of the severity of
corruption.
15
Concluding Remarks
Empirical analysis provided evidence
Table 4. Proportion of women in work force
% of women in % of women at
Country Name
labor force ministerial level
Argentina
32
8
Bolivia
38
6
Bulgaria
48
NA
Guyana
34
NA
Indonesia
40
3
Moldova
49
0
Source: World Development Indices, 2001
that there is a statistically significant
relationship between corruption and
gender. Across countries, within
public organizations in a particular
country, or considering public
organizations irrespective of country,
higher percentage of female
employees is connected with lower
corruption in public organizations and increases the probability of corruption instances
being reported. Statistics in Table 4 indicate that countries with a low proportion of
women in the work force (Argentina, Guyana, Bolivia and Indonesia) may benefit from
raising the proportion of women.
It could also be argued that a very low percentage of women in public sector employment
is the result of the tendency for clientilistic, traditional systems to exclude certain groups.
Equally, causality could in fact the other way round, in that corruption causes imbalanced
Figure 8 Severity of corruption
Figure 9 Chances of reporting corruption
1.20
Percentage of officials who reported significant
corruption
1.20
1.00
0.80
0.80
0.60
0.60
0.40
0.40
0.20
0.20
0.00
0.00
0%
10% 20%
30% 40% 50% 60% 70% 80%
-0.20
0% 10% 20% 30% 40% 50% 60% 70% 80%
-0.20
-0.40
-0.40
-0.60
-0.60
-0.80
Percentage ogf officials who reported that
corruption would not be reported
1.00
Percentage of females in public
organizations
-0.80
-1.00
Percentage of females in public
organizations
16
representation of men and women in the public sector.
The findings of this investigation have led to the simplistic recommendation that
continuously increasing the percentage of females in public sector organizations can
reduce corruption until if all employees were women, corruption would be eliminated.
However, empirical evidence, as is summarized in Figures 8 and 9, suggests a point of
flexion. Increasing the percentage of females beyond a certain point (around 45%)
reduces the likelihood of its being reported, and increasing females beyond 70% again
raises the severity of corruption. For the Bank’s work in client countries that have a low
percentage of women in the public sector, actively promoting women’s recruitment to
raise that percentage to about 40 may help reduce corruption. On the other hand, in
countries with more than 50% women employees in the public sector, actively promoting
the recruitment of men may help reduce corruption.
17
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