The aim of this paper was to re-examine the relationship between the quality of public institutions and corruption. Estimations from generalized method of moments show that better public institutions (regulation, bureaucracy, political structures) are associated with lower levels of corruption.corruption, public institutions.

Gbewopo ATTILA

English

Research Papers in Economics

CERDI, Etudes et Documents, E 2008.13 
 
1 
 
 
 
 
 
 
Document de travail de la série 
Etudes et Documents 
E 2008.13 
 
Corruption and quality of public institutions: evidence from 
Generalized Method of Moment 
 
Gbewopo Attila
1 
University Clermont I, CERDI-CNRS 
 
 
June 2008 
 
                                                 
1  We  are  am  grateful  to  Jean-Louis  Combes  (CERDI,  University  of  Auvergne),  Gérard  Chambas 
(CERDI,  University  of  Auvergne),  Mathilde  Maurel  (University  of  Paris  I,  Pantheon-Sorbonne), 
Wladimir  Andreff  (University  of  Paris  I,  Pantheon-Sorbonne)  and  François  Roubaud  (DIAL,  IRD, 
Paris), Abdul Mijiyawa (CERDI, University of Auvergne)  for constructive comments and suggestions. 
The  usual  disclaimer  applies.  Please  address  correspondence  to  CERDI,  65  Boulevard  François 
Mitterrand 63000 Clermont Ferrand, France; e-mail: G.ATTILA@u-clermont1.fr . Tel: + 00 33 4 73 17 
74 22; Fax: + 00 33 4 73 17 74 28. 
 
 CERDI, Etudes et Documents, E 2008.13 
 
2 
 
 
 
 
Abstract 
 
The  aim  of  this  paper  was  to  re-examine  the  relationship  between  the  quality  of  public 
institutions and corruption. Estimations from generalized method of moments show that better 
public  institutions  (regulation,  bureaucracy,  political  structures)  are  associated  with  lower 
levels of corruption.  
 
 
 
 
 
Keywords: Corruption, public institutions. 
JEL Classification: D73, P48. CERDI, Etudes et Documents, E 2008.13 
 
3 
 
  1- Introduction 
Many  empirical  studies  examine  the  impact  of  a  specific  public  institution 
(bureaucratic, judicial or political) on corruption. Graeff and Mehlkop (2003) found that the 
relationship  between  economic  freedom  and  corruption  depends  on  a  country's  level  of 
development. Ledermann et al (2005) confirmed the importance of political institutions in 
curbing  corruption.  Seldadyo  and  de  Haan  (2005)  using  Extreme  Bound  Analysis  (EBA) 
concluded  that  institutional  variable  like  political  freedom  and  judicial  system  affect 
corruption. Using the EBA, Serra (2006) showed that corruption is lower where democratic 
institutions  have  been  preserved  for  a  long  continuous  period  but  higher  when  political 
instability is important. 
 
The present paper departs from many existing empirical studies of determinants of 
corruption on three main fronts. Firstly, it considers public institutions in a wide sense to 
include bureaucratic administrations and political structures as well as policies undertaken by 
public  authorities.  Estimates  based  on  the  same  sample  make  it  possible  to  compare  the 
impact of various aspects of public institutions.  
 
Secondly,  we  address  the  problem  of  endogeneity  of  the  variables  of  public 
institutions. Previous studies did not adequately account for the problem of simultaneity bias 
and endogeneity and hence the coefficients estimated were biased. Public institutions affect 
the level of corruption but conversely corruption shapes the quality of these institutions. In 
addition, the problem of endogeneity may result from errors of measurement of corruption 
and indicators of the quality of public institutions, which are subjective evaluations.  
 
  Thirdly, this paper addresses the issue of omitted variables by controlling for many 
other determinants of corruption. Lambsdorff and Cornelius (2000), using simple correlation 
coefficients, showed a positive relation between corruption and the uncertainty of regulation. 
Chowdhury (2004) used instrumental analysis when analyzing the impact of democracy and 
press  freedom  on  corruption  but  did  not  completely  control  for  other  determinants  of 
corruption (their table 2). The omission of variables such as social structures or economic 
factors may lead to inconsistent estimates.  CERDI, Etudes et Documents, E 2008.13 
 
4 
 
  In section 2, we outline the empirical approach and selected variables and in section 3 
present the main results. 
 
  2- The empirical approach and data 
  Estimations cover five periods (1996, 1998, 2000, 2002 and 2004) and a sample of 73 
countries.  Several  corruption  equations  are  estimated  with  right-side  variables  capturing 
public institutions and a set of control variables (economic development, social and historical 
variables).  
 
  2.1- The econometric method 
  To  deal  with  the  problem  of  endogeneity,  we  used  the  Generalized  Method  of 
Moments (GMM), which is more efficient than the standard instrumental variables in the 
presence of heteroskedasticity (Baum et al, 2003).  
  We  parsimoniously  chose  as  instruments  the  political  rights  index  of  “Freedom 
House” and the democracy index of “Polity IV”. The political right variable ranks countries 
on  a  scale  of  1  (most  free)  to  7  (least  free).  The  democracy  index  describes  the  general 
openness of public institutions to political parties and ranges from 0 (low) to 10 (high).  
  While these variables may characterize democratic systems in general, we argue that 
they  are  exogenous.  First,  several  studies  found  no  significant  effect  of  democracy  on 
corruption (Paldam, 2002; Treisman, 2000; Rose-Akerman, 1999; Serra, 2006; Brunetti and 
Weder, 2003). Secondly, in order to validate these instruments, we performed the test of weak 
instruments  based  on  the  statistics  of  Cragg-Donald  (1993)  (see  Stock  and  Yogo,  2005; 
Staiger and Stock, 1997) and the over-identification test based on the J statistic of Hansen 
(1982).  
  Since time-varying variables of control may be potentially endogenous, we use their 
lagged values.  
 CERDI, Etudes et Documents, E 2008.13 
 
5 
 
  2.2- Measurement of corruption 
  Data  on  corruption  come  from  the  database  of  Kaufmann,  Kraay  and  Mastruzzi 
(KKM)  (2005).  We  rescaled  this  variable  from  0  (lowest  corruption)  to  10  (highest 
corruption). This index is a composite one and is therefore more reliable than any individual 
indicator.  The  KKM  data  include  continuous  variables,  and  so  allow  us  to  dispense  with 
multinomial model regressions.  
  2.3- Measuring the quality of public institutions 
We used six different indicators: 
1-  Quality  of  bureaucracy:  measures  the  important  changes  in  public  policies  or  the 
frequency of interruption in delivery of public services. 
2-  Effectiveness of government: includes the stability, predictability and effectiveness of 
governments’ actions.  
3-  Public  regulation:  measures  quantitative  regulations,  price  controls  and  other 
unjustified interventions in economic activities. 
4-  Influence  and  political  responsibilities:  includes  political  rights  and  civil  liberties, 
participation  in  electoral  process,  independence  of  medias,  accountability  and 
openness in public decisions. 
5-  Civil liberties: describes the general state of liberty in a country.  
6-  Efficiency of judicial system: includes the respect of law and order, the predictability 
and efficiency of the judicial system and enforcement of contracts. 
 
Each variable was rescaled so that lower values represent bad performance and higher 
values good performance.  
A main characteristic of the indicators of public institutions is the high correlation 
between them (simple correlation coefficient between 0.52 and 0.93) (table 1). 
Table 1: Correlations coefficients  
  REGUL  BUREAU  GOVEFF  VOICE  LAW  CIVIL 
             
REGUL             
BUREAU  0.6600**           
GOVEFF  0.8445**  0.7931**         
VOICE  0.5389**  0.5109**  0.4983**       
LAW  0.8314**  0.7907**  0.9352**  0.5225 **     
CIVIL  0.7130**  0.5039**  0.5843**  0.5283**  0.5891**   
OVERALL  0.9320**  0.7975**  0.9272**  0.7032**  0.9259**  0.7660** CERDI, Etudes et Documents, E 2008.13 
 
6 
 
 
3- Empirical estimates 
  3.1- Main results 
The  results  from  the  GMM  are  given  in  table  3.  We  controlled  for  many  other 
determinants of corruption as already identified in the literature. The statistics of Hansen and 
Cragg-Donald (table 2) show the relevance and weak exogeneity of instrumental variables.  
Tableau 2: Corruption and quality of public institutions 
  (1)  (2)  (3)  (4)  (5)  (6)  (7) 
Quality of bureaucracy  -1.681***             
  (-7.16)             
Effectiveness of government    -2.069***           
    (-12.1)           
Quality of public regulation      -1.717***         
      (-8.30)         
Political responsibilities        -1.388***       
        (-6.72)       
Civil liberties          -0.987***     
          (-7.14)     
Efficiency of judicial system            -1.782***   
            (-13.6)   
Overall public performance              -1.309*** 
              (-11.6) 
Log of real GDP per capita  0.000172  -0.0120  0.0333  0.0175  -0.00115  -0.00582  -0.00191 
  (0.0057)  (-0.62)  (1.12)  (0.51)  (-0.041)  (-0.38)  (-0.096) 
Public expenditure/GDP  -0.0485**  -0.0118  -0.0391***  -0.0576**  -0.0611***  -0.0174*  -0.0461*** 
  (-2.58)  (-1.15)  (-2.65)  (-2.32)  (-3.06)  (-1.82)  (-3.77) 
Trade openness  0.000526  -0.000864  0.00210  0.00499**  0.00368**  0.00160*  0.00294*** 
  (0.27)  (-0.97)  (1.32)  (2.06)  (2.14)  (1.66)  (2.78) 
Fuel exports   -0.00306  -0.00342  -0.00856*  0.00814*  0.00510  0.00427**  0.000837 
  (-0.75)  (-1.38)  (-1.96)  (1.95)  (1.32)  (2.38)  (0.32) 
Mineral exports   -0.0307***  -0.000275  0.00377  0.0109  -0.00369  -0.00243  -0.000790 
  (-3.99)  (-0.067)  (0.65)  (1.11)  (-0.53)  (-0.67)  (-0.15) 
Latitude from equator   -0.388***  -0.0242  -0.394***  -0.383***  -0.425***  -0.0318  -0.303*** 
  (-3.84)  (-0.46)  (-5.01)  (-3.00)  (-4.19)  (-0.61)  (-4.73) 
Ethnic fractionalization  0.906  0.283  1.613***  1.747**  2.367***  0.181  1.167*** 
  (1.51)  (0.85)  (3.58)  (2.41)  (4.20)  (0.55)  (2.97) 
Religious fractionalization  -1.156**  0.0292  -1.327***  -1.182**  -1.115***  -0.253  -0.672*** 
  (-2.44)  (0.13)  (-4.19)  (-2.30)  (-3.18)  (-1.33)  (-2.77) 
Urbanization  0.00561  -0.000920  -0.00925*  -0.0179**  -0.0244***  -0.00945***  -0.0106** 
  (0.63)  (-0.21)  (-1.68)  (-2.40)  (-4.03)  (-3.05)  (-2.48) 
British legal origin  0.386  -0.131  -0.373  -0.633  8.247***  0.00752  -0.457** 
  (1.21)  (-0.88)  (-1.45)  (-1.64)  (16.8)  (0.041)  (-2.15) 
French legal origin  -0.435*  -0.0642  0.0422  -0.247  -0.888***  0.115  -0.138 
  (-1.96)  (-0.49)  (0.23)  (-0.84)  (-2.79)  (1.05)  (-0.89) 
Constant  8.947***  5.561***  5.277***  5.523***  -0.131  5.669***  5.883*** 
  (19.5)  (17.1)  (11.0)  (8.61)  (-0.54)  (19.6)  (18.0) 
Observations  223  235  235  225  235  235  225 
R-squared  0.71  0.91  0.79  0.50  0.63  0.92  0.86 
J statistics of Hansen  2.311  7.923  0.386  0.0741  2.141  3.056  0.00742 
(P-Value)  0.128  0.00488  0.535  0.785  0.143  0.0804  0.931 
F statistics of Cragg-Donald  21.09  23.10  40.24  32.40  529.3  34.13  94.06 
Robust t statistics in parentheses *, **, *** significant at 10%, 5% and 1% 
 
Estimations  show  that  all  the  variables  of  public  performance  are  significantly 
inversely related to corruption. Better public regulation of economic activity helps to reduce CERDI, Etudes et Documents, E 2008.13 
 
7 
 
corruption. Likewise, the better the quality of bureaucracy the lower the level of corruption. 
The effectiveness of public policies has an adverse and significant effect on corruption.  
 
With respect to political institution variables, estimations evidenced a negative and 
significant causal relationship between political responsibilities, civil liberties and efficiency 
of the judicial system.  
Another  important  result  is  that  each  public  institutions  variable  had  a  different 
reducing-impact  on  corruption.  The  variables  describing  the  quality  of  government 
bureaucracy seems to have a greater impact than that of political structures. A one standard-
deviation  of  government  effectiveness  (0.94)  contributes  toward  reducing  corruption  by  2 
points (=0.94*2.069) (on a scale ranging from 0 to 10). Increasing civil liberty to a level equal 
to a one standard-deviation only reduces corruption by less than 1 point: 0.81 points.  
 
  3.2- Robustness analysis 
  In addition to the six indicators, we calculated a composite index of overall public 
institution  performance  using  the  method  of  principal  components.  The  rationale  for 
aggregating is to obtain a better estimate of the impact of public institutions on corruption 
once the measurement errors in individual indexes are accounted for.  
  High  correlations  appear  between  this  variable  and  the  individual  institutional 
variables (see table 1). 
  The last  column of table 2  (7) shows a significant impact of this variable. A one 
standard-deviation change in overall public performance decreases corruption by 1.31 points, 
a decrease lower than the average impact of the quality of public administration (1.88) but 
roughly equal to the average impact of political characteristics (1.31).  
 
4- Conclusion 
  This study departs from previous empirical research and rigorously tests the causal 
relationship  between  the  quality  of  public  institutions  and  corruption  by  correcting  for 
endogeneity.  Estimations  show  that  that  better  public  institutions  (in  the  form  of  better CERDI, Etudes et Documents, E 2008.13 
 
8 
 
regulation, better bureaucracy, political responsibility, a greater degree of civil liberty and a 
more effective judicial system) are associated with lower levels of corruption.  
The results of this paper therefore support institutional reforms in developing countries 
that aim at improving the quality of public institutions.  
 
 
 
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Corruption and quality of public institutions: evidence from Generalized Method of Moment

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Corruption and quality of public institutions: evidence from Generalized Method of Moment

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