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Understanding corruption and firm responses in cross-national firm-level surveys

Abstract

The issue of corruption is important to politicians, citizens, and firms. Since the early 1990s, a large number of studies have sought to understand the causes and consequences of corruption employing firm-level survey data from various countries. While insightful, these analyses have largely ignored two important potential problems: nonresponse and potential false response by the firms. We argue that in politically repressive environments, firms use nonresponse and potential false response as self-protection mechanisms. Corruption is likely understated in such countries. We test our argument using the World Bank enterprise survey data of more than 44,000 firms in 72 countries for the period 2000–2005. We find that firms in countries with less press freedom are more likely to provide nonresponse and false response on the issue of corruption. Therefore ignoring these systematic biases in firms’ responses could result in serious underestimation of the severity of corruption in politically repressive countries. More important, these biases are a rich and underutilized source of information on the political constraints faced by the firms. Firm managers can better evaluate levels of corruption, not only by truthful answers to corruption questions, but also by nonresponses and false responses to such questions.

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Notes

  1. 1.

    For example, see the Journal of International Business Studies special issue on the topic (Rodriguez et al., 2006). Mocan (2008) examines individual-level corruption by utilizing the United Nations International Crime Victim Survey.

  2. 2.

    See, for example, Bardhan (1997), Gatti (2004), Gray and Kaufmann (1998), Kaufmann (1997), Mauro (1998), Tanzi (1998), Treisman (2000), and Wei (1999, 2000).

  3. 3.

    See Recanatini, Wallsten, and Xu (2000) for discussion of the early World Bank surveys. For examples of the firm-level data-based analyses, see Batra, Kaufmann, and Stone (2003), Clarke and Xu (2004), Escribano and Guasch (2005), Fisman and Gatti (2006), Gray, Hellman, and Ryterman (2004), Hellman et al. (2006), Hellman and Kaufmann (2004), Lee, Oh, and Eden (forthcoming), Svensson (2003), and World Bank (2005).

  4. 4.

    A few corruption studies triangulate between enterprise surveys, citizen surveys, and public officials surveys. See, for example, World Bank (2000).

  5. 5.

    As an exception, Svensson (2003) applies a selection model to the generation of firm nonresponses in a single-country survey, but does not find any significant selection effect.

  6. 6.

    A similar World Bank survey is the Business Environment and Enterprise Performance Survey.

  7. 7.

    Another general corruption question in the survey concerns the proportion of sales the firms reportedly have devoted to bribery. From both the legal and business perspectives, this question is highly problematic. As bribery is considered illegal in many countries, acknowledging the specific amount of bribery can easily be self-incriminating, causing the firm to be taken advantage of by the government or business competitors. It also reveals the firm's strategies to its potential business competitors. Finally, since bribery is also unethical, it is unrealistic and questionable to suggest that firm managers will truthfully admit and report their unethical behaviors. Other corruption-related questions in the PICS survey are narrowly targeted, concerning firm perceptions or their actual bribe payments for specific services (e.g., utility service, construction permit, import license, customs clearance). They lack the generalizability of the question we choose to analyze.

  8. 8.

    See Batra et al. (2003: 51) for the specific reference to China.

  9. 9.

    One may contend that these World Bank surveys typically have confidentiality agreements that protect the identity of the respondent from being revealed to the government. This type of protection may be limited when the World Bank survey team needs the collaboration of the relevant government bureaucracy to provide industry census data to generate the representative stratified sample. Also, there is often a data-sharing arrangement between the Bank and the national government. Hence it is quite plausible that an unconstrained autocratic government would be able to identity respondents.

  10. 10.

    It is important to note that we are not arguing that the lack of information causes corruption. See DiRienzo et al. (2007) for a theoretical argument and an empirical test linking information and communication technology to the level of corruption. Also see Freille, Haque, and Kneller (2007) for work on the relationship between press freedom and corruption, and Lee et al. (forthcoming) on the firm-level determinants of paying bribes.

  11. 11.

    While they often provide feedback (a public good) on the investment environment to government officials, World Bank staff, and other potential investors, the impact of each individual firm's response on the government policy reform is low, and the benefits of a resultant policy reform are diffused and dispersed among all firms, including those that do not participate in the survey.

  12. 12.

    It is important to note that firms that find these disincentives to be so large will be unlikely to answer any question at all. And these firms are typically replaced in surveys by those that are willing to respond to at least some questions. To the extent that the inclusion of politically sensitive questions deters firm participation in autocratic countries, we should expect to see higher replacement rates in them than in democracies. But this implication cannot be tested, because the replacement data are not available.

  13. 13.

    The Freedom House also provides a categorical press freedom variable with three categories: Free, Partially Free, and Not Free. Using this variable, we code a press freedom dummy variable, with 1 indicating no press freedom and 0 otherwise. Statistical results based on this press freedom dummy are consistent with those based on the continuous measure. These results, not reported because of space constraints, are available upon request.

  14. 14.

    OLS regressions produce similar results.

  15. 15.

    The calculation employs the computed marginal effect of press freedom on the actual dependent variable in Tobit, which is 0.11. OLS estimates lead to smaller standard errors, but a very similar substantive impact. A move from the lowest level of press freedom to the highest level leads to a 7.8% increase in the response rate.

  16. 16.

    This is a continuous aggregate measure of corruption, ranging from −2.5 (lowest level of corruption) to 2.5 (highest level of corruption). Data are available at www.govindicators.org.

  17. 17.

    This includes cases where the response to the corruption question is recorded as 3 (major) or 4 (very severe) in the data.

  18. 18.

    Since our dependent variable is no longer censored, we use OLS instead of Tobit for estimation.

  19. 19.

    These results are robust for the dichotomous measure of press freedom, which are not reported here for the sake of space.

  20. 20.

    We present the raw country-level data in the Appendix. We also examined the robustness of our results for both nonresponse and potential false response at the country level, using the robust regression procedure rreg in Stata. This iteratively reweighted least-squares estimator first runs the OLS regression, finds the values of Cook's D (an outlier diagnostic), drops any observation if its Cook's D value is greater than 1, and then iteratively performs regression using case weights from absolute residuals until the maximum change in weight from one iteration to the next drops below tolerance. In essence, this estimator drops the most influential observations and then down-weights cases with large absolute residuals. Our results for press freedom based on this robust regression estimator remain unchanged (results available from the authors).

  21. 21.

    Alternative measures of corruption, such as expert surveys and the Kaufmann et al. measure, may also confront the same problems. As noted earlier, though, we have reasons to believe that the Kaufmann et al. measure is closer to the true level of corruption than that reflected by the firm-level survey data.

  22. 22.

    Assuming that the per capita GNI variable allows us to control for the information access effect identified by DiRienzo et al. (2007), our statistical evidence relates directly to our argument.

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Acknowledgements

Equal authorship is implied. The authors thank Lorraine Eden, Witold Henisz, Aart Kraay, Andrew Stone, Vincent Palmade, Matt Gabel, Layna Mosley, Eddy Malesky, Tom Kenyon, the anonymous referees, the participants at the Political Risk in Emerging Markets Conference, Washington University, at St Louis, March 2007, and the Midwest Political Science Association Conference, Chicago, April 2007, for their comments. Greg Allen, Daehee Bak, Ekrem Karakoc, and Sam Snideman provided research assistance. David Stewart helped the authors with their numerous queries related to the surveys. Nathan Jensen's research was funded by the Weidenbaum Center on the Economy, Government, and Public Policy at Washington University. The views expressed in this paper are solely those of the authors, and they do not necessarily represent the views of the World Bank, its Board of Directors, or the countries they represent. The authors are responsible for all the errors.

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Correspondence to Nathan M Jensen.

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Accepted by Witold Henisz, Area Editor, 2 November 2009. This paper has been with the authors for three revisions.

APPENDIX

APPENDIX

See Tables A1, A2, A3, A4, A5 and A6.

Table a1 Summary statistics
Table a2 Correlation matrix: Country-level analysis
Table a3 Correlation matrix: Firm-level analysis 1
Table a4 Correlation matrix: Firm-level analysis 2
Table a5 Impact of political freedom on nonresponses at country and firm levels
Table a6 Impact of political freedom on potential false responses at country and firm levels

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Jensen, N., Li, Q. & Rahman, A. Understanding corruption and firm responses in cross-national firm-level surveys. J Int Bus Stud 41, 1481–1504 (2010). https://doi.org/10.1057/jibs.2010.8

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Keywords

  • corruption
  • nonresponse
  • false response
  • political freedom
  • firm-level surveys