Individual Attitudes Toward Corruption: Do Social Effects ... Individual Attitudes Toward Corruption:

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  • Individual Attitudes Toward Corruption:Do Social Effects Matter?

    Roberta GattiWorld Bank

    Stefano PaternostroWorld Bank

    Jamele RigoliniNYU and U. of Warwick

  • MOTIVATION (1/4)MOTIVATION (1/4)

    Cross-country analyses on corruption have shown that:

    Corruption and poor governance affect investment, growth and economic performance.(Mauro, 1995, Kaufman et al., 1999)

    Corruption affects the efficient allocation of resources and of public spending.(Krueger, 1974, Mauro, 1997)

  • MOTIVATION (2/4)MOTIVATION (2/4)

    Cross-country evidence suggests that better governance is associated with:

    Higher female participation in public life(Dollar et al., 2001)

    Higher freedom of press(Treisman, 2000)

    Higher fiscal decentralization(Fisman and Gatti, 2002)

    Higher degree of competition(Ades and di Tella, 1999)

  • MOTIVATION (3/4)MOTIVATION (3/4)

    Cross-country studies explain the macro-level correlates of corruption.

    But it is sometimes difficult to get rid of unobservables.

    Effective anti-corruption policies need to understand the micro-economics of corruption.

    Few studies, however, analyze the determinants of corruption at the individual level.

  • MOTIVATION (4/4)MOTIVATION (4/4)

    Exceptions:

    Using data at the individual level, Swamy, Knack, Lee, and Azfar(2001) find that women tend to be less corrupt.

    Svensson (2003) uses a survey of 176 Ugandan firms and finds that firms ability to pay and to relocate affects the payment of bribes.

    Ichino and Maggi (2000) analyze North-South shirking differentials within a large Italian bank. Shirking appears to be influenced by:

    Individual backgrounds.

    Group-interaction effects.

  • Two things:

    We investigate the determinants of corruption at the individual level using data from the World Values Survey (35 countries and more than 30,000 individuals).

    Although it is a potentially important angle, there are no empirical tests on the relevance of social effects in corruption:

    We investigate whether living in a region where on average corruption is more tolerated makes individuals more tolerant toward corruption.

    WHAT DO WE DO?WHAT DO WE DO?

  • WHAT ARE SOCIAL EFFECTS? (1/3)WHAT ARE SOCIAL EFFECTS? (1/3)

    Theoretical studies have stressed the relevance of peer effects in creating multiple corruption equilibria.(Cadot, 1987, Andvig and Moene, 1990, Tirole, 1996)

    Following Manski (1993), there are two types of social effects:

    Endogenous (or peer) effects.

    Exogenous effects that depend on the average distribution of characteristics in the reference area.

  • WHAT ARE SOCIAL EFFECTS? (2/3)WHAT ARE SOCIAL EFFECTS? (2/3)

    Everybodyis corrupt

    Everybodyhas incentivesto be corrupt

    Nobodyis corrupt

    Nobodyhas incentivesto be corrupt

    Bad Equilibrium Good Equilibrium

    Endogenous Social Effect

  • WHAT ARE SOCIAL EFFECTS? (3/3)WHAT ARE SOCIAL EFFECTS? (3/3)

    People have highmoral values

    I cannot be corruptregardless of my moral values

    Highly educatedpopulation

    It is more difficultto cheat

    I cannot be corruptregardless of my education

    Exogenous Social Effect

    With social effects, a Big Pushis necessary to combat corruption

  • Preview of Results:

    Women, employed, less wealthy, and older individuals claim to be more averse to corruption.

    The social environment has a strong influence on the individual attitudes towards corruption:

    if you move an individual to a more corrupt region, she becomes more corrupt.

    However, because of the reflection problem (Manski, 1993) we cannot separately identify endogenous and exogenous social effects.

    RESULTSRESULTS

  • DATA (1/2)DATA (1/2)

    The World Values Survey is a questionnaire covering personal characteristics and individual beliefs on politics, religion, and economics.

    Three waves: 1981-84; 1990-93; 1995-97.

    Wave III: 49 countries and 78,574 individuals interviewed.

    Not all questions are asked in all waves.

    Only 36 regions in 5 countries overlap between Wave II and Wave III.

  • DATASET (2/2)DATASET (2/2)

    Previous works using the WVS:

    Knack and Keefer (1997) build indices of social capital.

    Swamy et al. (2001) analyze the womens attitudes towards corruption.

    Guiso et al. (2002) look at the relationship between religion and socioeconomic attitudes.

  • CORRUPTION QUESTIONCORRUPTION QUESTION

    Someone accepting a bribe in the course of their duties is:

    8.1 5.0 2.4 3.7 1.3 1.0 1.0 0.5 1.5

    75.6

    0.0

    20.0

    40.0

    60.0

    80.0

    1 2 3 4 5 6 7 8 9 10

    Per

    cen

    tag

    e

    Never Justifiable Always Justifiable

  • LOW & MIDDLE INCOME VS. HIGH INCOME COUNTRIESLOW & MIDDLE INCOME VS. HIGH INCOME COUNTRIES

    Distribution of Answers

    85.4

    72.8

    0.0

    30.0

    60.0

    90.0

    1 2 3 4 5 6 7 8 9 10

    Value

    Per

    cen

    tag

    e

    High Income Countries (6300 Obs.)

    Low and Middle Income Countries (27400 Obs.)

    Never Justifiable Always Justifiable

  • 19951995--97 WVS WAVE97 WVS WAVE

    The 1995-97 WVS wave has 33,780 complete observations across 35 countries.

    Systematic missing observations:

    55% have secondary education.

    29% define themselves as high income.

    WVS is world representative for averages, but regression estimates are potentially biased.

    We do not use sampling weights.

    Results are surprisingly robust.

  • SOCIAL EFFECTSOCIAL EFFECT

    Regression specification (Manski, 1993):

    z i : Individual Characteristics

    x i : Reference Group of Individual i

    yi = + z i +

    Social Effect

    Peer Effect

    Ey xi +Exogenous Effect

    Ez x i +i

  • IDENTIFICATIONIDENTIFICATION

    Taking expectations the following holds:

    However, the following also holds:

    Ey z, x = + z + Ey x + Ez x

    Ey z, x = 1 + z + Ez x +1

    Ey x = 1 + Ez x +

    1

  • Randomized experiments:

    Katz et al. (2001) use the Moving to Opportunity experiment in Boston to analyze household improvements.

    Sacerdote (2001) uses the random assignment of roommates in Dartmouth to look at peer effects in student outcomes.

    Identification of the reference group by more than one characteristic:

    Bertrand et al. (2000) examine the role of social networks in welfare participation and characterize the network with two indices: language and neighborhood.

    HOW TO DEAL WITH UNOBSERVABLES?HOW TO DEAL WITH UNOBSERVABLES?

  • REGRESSION SPECIFICATIONSREGRESSION SPECIFICATIONS

    BRIBEi = Country / Region + z i + i

    BRIBEi = Country + z i + RBRIBEi + i

    BRIBEit = C,t1 + R2 + zit + RBRIBEi,t + it

  • VARIABLES DESCRIPTION (1/2)VARIABLES DESCRIPTION (1/2)

    Variable DescriptionMean 1995

    St. Dev. 1995

    Mean High Income

    Mean Low & Middle Income

    Dummy

    BRIBE 1.76 1.78 1.44 1.84 No

    RBRIBE Regional average of BRIBE 1.79 0.65 1.51 1.85 No

    SEX Women=1 0.54 0.50 0.55 0.53 Yes

    SECONDARY Has secondary education 0.55 0.50 0.49 0.57 Yes

    TERTIARY Has tertiary education 0.20 0.40 0.21 0.20 Yes

    MIDDLEINC Defines himself as middle income 0.35 0.48 0.35 0.34 Yes

    HIGHINC Defines himself as high income 0.29 0.46 0.41 0.27 Yes

    MIDDLETOWN Lives in a town with 10.000-100.000 inhabitants

    0.26 0.44 0.35 0.23 Yes

    BIGTOWN Lives in a town with more than 100.000 inhabitants

    0.39 0.49 0.29 0.41 Yes

    YOUNG 18-24 years old 0.07 0.25 0.02 0.08 Yes

    MIDOLD 45-64 years old 0.33 0.47 0.37 0.32 Yes

    OLD More than 64 years old 0.12 0.33 0.20 0.11 Yes

    FAMIMP Gives importance to the family 0.90 0.31 0.91 0.89 Yes

    MARRIED Married 0.75 0.44 0.73 0.75 Yes

    CHILDREN Number of children 2.26 1.42 2.39 2.23 No

  • VARIABLES DESCRIPTION (2/2)VARIABLES DESCRIPTION (2/2)

    Variable DescriptionMean 1995

    St. Dev. 1995

    Mean High Income

    Mean Low & Middle Income Dummy

    CHURCH Goes to church at least once a week 0.20 0.40 0.22 0.20 Yes

    CATHOLIC Catholic 0.23 0.42 0.36 0.21 Yes

    PROTESTANT Protestant 0.09 0.28 0.36 0.02 Yes

    ORTHODOX Orthodox 0.24 0.43 0.01 0.30 Yes

    MUSLIM Muslim 0.06 0.24 0.00 0.08 Yes

    JEW Jew 0.02 0.13 0.01 0.02 Yes

    OTHERREL Other religion 0.16 0.37 0.06 0.19 Yes

    RIGHT Defines himself politically from the right 0.16 0.36 0.11 0.17 Yes

    CENTER Defines himself politically from the center 0.46 0.50 0.60 0.43 Yes

    FULLTIME Works fulltime 0.37 0.48 0.37 0.37 Yes

    UNEMP Unemployed 0.07 0.26 0.06 0.07 Yes

  • BASIC REGRESSION RESULTS (1/2)BASIC REGRESSION RESULTS (1/2)

    Dep. Var.: BRIBE (I) (II) (III)

    RBRIBE 0.855 ***20.59

    SEX -0.071 ** -0.086 *** -0.089 ***(2.11) (2.85) (3.03)

    SECONDARY 0.059 * 0.046 0.046(1.77) (1.47) (1.50)

    TERTIARY -0.036 -0.027 -0.024(0.59) (0.52) (0.46)

    MIDDLEINC 0.086 ** 0.053 0.067(2.05) (1.28) (1.56)

    HIGHINC 0.174 *** 0.127 *** 0.147 ***(3.03) (2.68) (2.90)

    MIDDLETOWN 0.046 0.045 0.044(0.89) (0.97) (1.00)

    BIGTOWN 0.062 0.031 0.007(1.13) (0.54) (0.14)

    Obs. 33780 33780 33780Nations 35 35 35Regions 278 278 278Dummy National Regional National

    Dep. Var.: BRIBE (I) (II) (III)

    YOUNG 0.259 *** 0.261 *** 0.265 ***(2.80) (2.76) (2.77)

    MIDOLD -0.164 *** -0.194 *** -0.190 ***(5.30) (6.00) (6.20)

    OLD -0.221 *** -0.271 *** -0.264 ***(4.13) (5.10) (5.22)

    FAMIMP -0.287 *** -0.299 *** -0.302 ***