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Causes of Corruption: A Survey of Cross-Country Analyses and Extended Results

Abstract

We survey and assess the empirical literature on the sources of corruption. Thanks to the improved availability of data, we are able to produce a comprehensive cross-country econometric model to test well-established and more recent hypotheses jointly. We do not find that the common law system, or a past as a British colony predicts corruption. Our results support cultural theories on the causes of corruption, and suggest that a medium-long exposure to uninterrupted democracy is associated with lower corruption levels, while political turnover tends to raise corruption. The results also suggest that the diffusion of newspapers helps to lower corruption levels.

JEL classification

  • D72
  • H11
  • H50
  • K42
  • O17

Keywords

  • Corruption
  • Culture
  • Ethnolinguistic fractionalization
  • Democracy
  • Political turnover

This chapter is a slightly revised version of Pellegrini and Gerlagh (2008).

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Fig. 3.1

Notes

  1. 1.

    On the ELF scandal see The Washington Post, Wednesday, February 9, 2000; Page A21.

  2. 2.

    http://archives.cnn.com/2001/WORLD/europe/10/10/chirac.court/.

  3. 3.

    http://www.businessweek.com/magazine/content/01_48/b3759151.htm.

  4. 4.

    Corruption Blackens Nordic Region’s Lily-White Image, Agence France Presse, December 4, 2003.

  5. 5.

    http://www.transparency.org/pressreleases_archive/2005/faq_tsunami.html#faqti1.

  6. 6.

    See http://info.worldbank.org/governance/wbes/.

  7. 7.

    This relatively recent paper has been already cited in 231 other works according to ISI Web of Science (checked on the 14th August, 2010).

  8. 8.

    Treisman (2000) selected exactly 46 years because his source of data on democracy was available from 1950 to 1995.

  9. 9.

    Lambsdorff (1999) provides a comprehensive survey of earlier empirical results.

  10. 10.

    Specifically, when we compare our study to Treisman’s, we find that our sample is larger than 100 countries in most regressions, while Treisman’s sample size is between 44 and 64 countries in the majority of regressions.

  11. 11.

    The same point is valid also for the rest of the econometric analyses in this study. In Chap. 4 in particular, the difference between corruption and the transmission channels could be described as corruption being the underlying determinant and the transmission channels being the proximate variables influencing economic growth.

  12. 12.

    Macaulay was in India working for the Supreme Council of India and later became a member of the British Parliament.

  13. 13.

    Further distinctions could be made between different groups within these religions. For example, Sunni and other forms of Islam could be differentiated to verify whether they have a different impact on corruption.

  14. 14.

    President Fox has been accused of using illegal funds to finance his campaign, see http://news.bbc.co.uk/hi/spanish/latin_america/newsid_2802000/2802161.stm.

  15. 15.

    On the tape-scandals, involving the most important aides of Lopez Obrador, see http://news.bbc.co.uk/hi/spanish/latin_america/newsid_3531000/3531475.stm.

  16. 16.

    On the scandal involving the young leader of the Partido Verde Ecologista, see http://www.esmas.com/noticierostelevisa/mexico/345598.html.

  17. 17.

    We note that the effect of democracy on corruption could also work on a longer time frame; in this case the benefits of democratic changes in Mexico will be reaped in the future. Indeed, in the analysis below we find that exposure to democracy for a long period of time is associated with corruption levels, while contemporary democracy is not.

  18. 18.

    For an overview of complexities and the evolution in social sciences of the definition of corruption see Williams (1999).

  19. 19.

    One example of the special features that very small countries have is the more limited extent of ethnolinguistic fractionalization and the fact that they tend to be more open to trade (e.g. Knack and Azfar 2003). Since small countries are included in corruption surveys only when they are more interesting for investors, the over-representation of small countries with good investment climate and low corruption levels could easily introduce in the sample a spurious correlation between corruption, openness (negative) and ethnolinguistic fractionalization (positive).

  20. 20.

    Depending on the regression, the number of observations that drop out ranges between 16 and zero.

  21. 21.

    The standard deviation is exactly equal to 1 in the complete sample, but because of missing data it changes slightly in each sample.

  22. 22.

    Our results hold also for ordinary least squares estimations, but as expected weighted least squares produce more “precise” estimates (i.e. slightly higher t statistics).

  23. 23.

    Being a former-British colony should affect the degree of corruption because of the lasting effect British occupation has on the organization of the civil service. The UK has that same civil service organization and this is the reason for including the UK together with its former colonies in the dummy. Furthermore, we find the dummy to be statistically insignificant and excluding the UK would further strengthen this result.

  24. 24.

    For a thorough comparison of the corruption perception index from Transparency International and the one from the World Bank, see Kaufmann et al. (2005).

  25. 25.

    Our dataset includes former British colonies such as Myanmar and Sudan, which rank among the countries where corruption is perceived to be the highest in the world. Data on these countries has only recently become available.

  26. 26.

    The list of countries, in our dataset, that experienced British control, but did not adopt the British legal system are: Egypt, Iraq, Jordan, Kuwait, Myanmar, Mauritius, and Oman. Countries, included in the dataset, that adopted the British legal system without being colonies are: United Arab Emirates, Liberia, Namibia, Saudi Arabia, Somalia, and Thailand.

  27. 27.

    We also computed the variance inflator factors, for both variables, which were well below the conventional level of 10.

  28. 28.

    The income variable refers to 2001.

  29. 29.

    Indeed, for natural resources there is a large literature on the “resource curse” and the “Dutch disease”, which have shown the detrimental effect that natural resources have on economic growth (Stevens 2003).

  30. 30.

    On the direction of causality between institutions and income there is a large and growing empirical literature. Most of the authors seem to agree that causality runs from institutions to income , rather than the other way around (e.g. Rodrik et al. 2004; Acemoglu et al. 2001). For an example of an econometric study finding the opposite direction in the causality between growth and institutions, see Chong and Calderon (2000).

  31. 31.

    A good instrumental variable must be highly correlated with the variable to be instrumented and should not have additional explanatory power.

  32. 32.

    The only exception is contemporary democracy that becomes significant. In the analysis below, we prefer to use and discuss the measure of medium-term persistence of democracy , because it is significant even with the inclusion of income .

  33. 33.

    A note of caution is needed when we analyze the results with the instrumental variable, because theories that link geographical factors to institutions and through them to income levels have been developed (Hall and Jones 1999; Acemoglu et al. 2001). If these theories are correct, latitude could be used as an instrumental variable for corruption as well, and the interpretation of the 2-stage results would become problematic. For our own dataset, we checked whether latitude could be used as an instrument for corruption in a regression on income and found indications that latitude would not be a valid instrument, because it retained explanatory power when added to corruption in the regression.

  34. 34.

    Unfortunately, our proxy for decentralization is available just for a small sample of countries. Once more statistics on government finance, uniform across countries, are available a more reliable empirical test of the link between decentralization and corruption will be possible.

  35. 35.

    To be sure, we also included, as a proxy of the size of the country, the natural logarithm of the population (as in Fisman and Gatti 2002), to account for the fact that countries with different size may have different “natural” centralization levels. Conforming with previous literature, we did not find the variable to be significant or to affect the coefficient of the decentralization variable.

  36. 36.

    In the United States of Mexico, central government spending exceeds the States and the local governments spending together by more than three times. While the Mexican constitution is of federal nature, political power is centralized in the country’s capital. “For most of the seven decades of rule by the Institutional Revolutionary Party (PRI), Mexico was a highly centralized one-party polity. State governors, and even many mayors, were named by the president and answered to him, even if they were duly elected, by fraud if need be”, see “Mexico’s truncated moves towards real federalism”, March 27th 2003, From The Economist print edition.

  37. 37.

    We set the cut off point at the level of seven on a 0–10 scale of democracy in the Polity IV variable.

  38. 38.

    We also checked whether the interaction term between contemporary democracy and newspapers circulation would be significant, controlling whether a widespread press circulation together with a democratic regime would have a special effect on corruption levels. In our regressions the interaction term was not significant.

  39. 39.

    Treisman employed a variable that simply stated the number of government leaders changes in each year.

  40. 40.

    A better proxy would be the ratio of civil servants pay to service or manufacturing salaries (that are not influenced by the share of population employed in the agricultural sector). Van Rijckeghem and Weder (2001) use the ratio of government wages to manufacturing wages and find it to be a significant determinant of corruption levels. Their data sample, though, is limited to 31 countries and data limitations do not allow us to follow their data.

  41. 41.

    The estimates if Transparency International’s margins of error have been shown to be unduly large (Kaufmann et al. 2005) and we preferred the ordinary least squares, as a regression technique, rather than the weighted least squares technique.

  42. 42.

    The sample size ranges between 98 and 67 countries.

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Correspondence to Lorenzo Pellegrini .

Appendix

Appendix

Table 3.2 Descriptive statistics

Corruption is the Perceived Corruption Index 2004, from the World Bank. It is an aggregate indicator combing information—from a number of sources—measuring the incidence of corruption. The sources include surveys of experts, investors, and citizens’ opinion polls (see Kaufmann et al. 2005) and the data are available at http://www.worldbank.org/wbi/governance/data.html. For robustness checks the Corruption Perception Index from Transparency International was used (available at http://www.icgg.org/). Data on corruption have been rescaled throughout the book so that an increase in the index has the intuitive meaning of increase in corruption.

Protestants is the share of Protestants in the population (see La Porta et al. 1999).

Ethnolinguistic fractionalization is an average of five different indexes—based on linguistic groups—measuring the probability that two randomly selected individuals in the population would belong to the different groups and the percentage of population that does not speak the most common/official language (see La Porta et al. 1999).

Fuels and minerals equals to the share of fuels and minerals on exports, averaged over 1993–2002 (from the World Development Indicators, 2004).

Income is the natural logarithm of GDP per capita in 2001 (from the World Development Indicators, 2004).

Decentralization is the expenses of state and local government divided by the central government averaged over 1993–2002 (from the “Government Finance Statistics 2004” of the International Monetary Fund).

Contemporary Democracy is the average of the institutional democracy score for the years 1994–2003 from the Polity IV dataset (the “polity” variable in the original dataset). Democracy is measured along three lines: the first is the influence of citizens in the choice of leaders and policies, the second is the existence of constraints on the exercise of power by the executive, and the third is the guarantee of civil liberties to all citizens with respect to their daily lives and to political participation. The score is obtained as a weighted sum of the components and the scores are given by experts. The original indicator has been rescaled to a 0–1 scale (see http://www.cidcm.umd.edu/inscr/polity/).

Newspapers Circulation is daily newspapers circulation for ten people (from the World Development Indicators 2004).

Imports is a measure of the openness of the economy and equals to the share of imports over GDP, averaged over 1993–2002 (from the World Development Indicators, 2004).

Government Intervention is an index for 2004 of the influence of government on the economy based on government consumption as a percentage of the economy, government ownership of businesses and industries, the share of government revenues from state-owned enterprises, and government ownership of property and economic output produced by the government (from The Index of Economic Freedom 2005).

Political Turnover is the percentage of veto players in the political system that changed every year, averaged for 1991–2000 (see the Database of Political Institutions 2000 of the World Bank, Clarke et al. 1999).

Government Wage is the average government wage as a multiple of GDP per capita (see Schiavo-Campo 1998).

British Colony is the dummy variable for countries that have been under British control (from Treisman 2000 augmented with information from Flags of the World Website http://flagspot.net/flags/gb-colon.html).

Common Law is the dummy variable for countries that adopted the common law system in their commercial code (see La Porta et al. 1999).

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Pellegrini, L. (2011). Causes of Corruption: A Survey of Cross-Country Analyses and Extended Results. In: Corruption, Development and the Environment. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-0599-9_3

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