Abstract
Recent studies have found reticent managers are less likely to report corruption than are non-reticent managers. We confirm this using new data from Bangladesh and Sri Lanka. We find reticence greatly affects estimates of corruption for measures based on both direct and indirect questions. We also find reticence affects response rates. Surprisingly, reticent managers were less likely to refuse to answer questions on corruption than non-reticent managers, possibly because reticent managers believe that refusing to answer seems like a tacit admission of guilt. Throughout the analysis, we control for the potential endogeneity of the reticence measure.
Similar content being viewed by others
Notes
The data generated from the Sri Lanka survey and the questionnaire are available from the World Bank on the World Bank’s Enterprise Survey website (http://www.enterprisesurveys.org).
Classifications were based on ISIC rev 3.1.
This document is available for registered users of World Bank Enterprise Survey data on the Enterprise Survey webpage (http://www.enterprisesurveys.org)
Transparency International assigns scores on perceptions of public sector corruption ranging from 0 to 100, with 0 representing highly corrupt and 100 representing very clean.
Clarke (2011a) shows managers who answer the question as a percentage of sales report paying far higher bribes than do managers who answer the question in local currency. He also shows this is true even after controlling for other things that might affect bribe payments.
The other four are electricity, access to finance, access to land, and political instability.
Managers who answered ‘do not know’ to whether they had met with or been inspected by tax officials were also asked the indirect question.
In addition, it was asked only to managers who said tax inspectors had not inspected their firm, further suggesting it is not asking about the manager’s own experiences.
In practice, most studies assume managers answer question like this with their own experience in mind. See, for example, Clarke and Xu (2004, p. 2077), Johnson et al. (2000, p. 504), Johnson et al. (2002, pp. 1337–1338) and Svensson (2003, pp. 212–213).
Consistent with this, Clarke (2012b) shows managers in Afghanistan who do not bid on government contracts are more likely to say corruption is a serious problem when bidding on government contracts than managers who do bid. Clarke (2012b) argues the most reasonable explanation is firms excluded from bidding due to corruption are more concerned about corruption than firms that bid.
For the ‘any bribes’ question, although they cannot answer ‘yes’ or ‘no’, we will treat a positive amount as a ‘yes’ and zero as a ‘no’ in the discussion.
The same, or a similar, approach has been used in Clarke (2011b, 2012a), Clausen et al. (2010), Friesenbichler et al. (2014) and Jensen and Rahman (2011). Azfar and Murrell (2009) and Clausen et al. (2010) provide greater detail on the methodology.
See Fox and Tracy (1986) for a general discussion or Recanatini et al. (2000) for a discussion directly linked to the Enterprise Surveys. A related technique is list randomization where survey respondents are asked to report how many sensitive statements in a given list are true. Karlan and Zinman (2012) used list randomization in a study looking at loan use by microenterprises.
Lensvelt-Mulders et al. (2005) suggest that random response questions reduce underreporting.
Edgell et al. (1982), for example, found significant underreporting of sensitive behaviors when they used a version of the forced response methodology. They used a random number generator to generate random numbers. On some questions, however, the random number generator was not random and instead always forced the respondents to say yes. Despite this, about one-quarter of respondents answered some questions ‘no’.
The expected distribution assuming 30% have done each behavior is calculated assuming the probability an individual does each act is independent of the probability that they will do the other acts.
We do not have any information on the educational attainment of the respondent (unless the respondent is also the top manager).
Several studies have shown that corruption is greater when the burden of regulation is heavier (Djankov et al., 2002; Safavian et al., 2001).
We would like to thank an anonymous referee for this observation.
The one difference is that in the model for tax inspections - not inspected, the significance level falls to about 12%.
In particular, the linear probability model can be applied with continuous, binary or categorical variables (Lewbel et al., 2012). The linear probability model is also more robust to heteroskedasticity. Because the error terms in the linear probability are heteroskedastic by construction, we use robust standard errors. Although robust standard errors are less efficient than using weighted least squares, they allow for more general heteroskedasticity.
References
Azfar, O and Murrell, P . 2009: Identifying reticent respondents: Assessing the quality of survey data on corruption and values. Economic Development and Cultural Change 57 (2): 387–411.
Bound, J, Jaeger, DA and Baker, RM . 1995: Problems with instrumental variables when the correlation between the instruments and the endogenous explanatory variable is weak. Journal of the American Statistical Association 90 (430): 443–450.
Clarke, GRG . 2011a: How petty is petty corruption? Evidence from firm surveys in Africa. World Development 39 (7): 1122–1132.
Clarke, GRG . 2011b: Lying about firm performance: Evidence from a firm survey in Nigeria. Texas A&M International University: Laredo, TX.
Clarke, GRG . 2012a: Do reticent managers lie during firm surveys? Texas A&M International University: Laredo, TX.
Clarke, GRG . 2012b: What do managers mean when they say ‘firms like theirs’ pay bribes? International Journal of Economics and Finance 4 (10): 147–160.
Clarke, GRG and Xu, LC . 2004: Privatization, competition and corruption: How characteristics of bribe takers and payers affect bribes to utilities. Journal of Public Economics 88 (9–10): 2067–2097.
Clausen, B, Kraay, A and Murrell, P . 2010: Does respondent reticence affect the results of corruption surveys? Evidence from the World Bank Enterprise Survey for Nigeria. Policy Research Working Paper No. 5415. World Bank: Washington DC.
Coutts, E and Jann, B . 2011: Sensitive questions in online surveys: Experimental results for the randomized response technique (RRT) and the unmatched count technique (UCT). Sociological Methods and Research 40 (1): 169–193.
Dillman, DA, Smith, JD and Christian, LM . 2008: Internet, mail and mixed-mode surveys: The tailored design method. John Wiley and Sons: Hoboken, NJ.
Djankov, S, La Porta, R, Lopez-de-Silanes, F and Shleifer, A . 2002: The regulation of entry. Quarterly Journal of Economics 117 (1): 1–37.
Edgell, SE, Himmelfarb, S and Duchan, KL . 1982: Validity of forced responses in a randomized response model. Sociological Methods and Research 11 (1): 89–100.
Fisher, RJ and Tellis, GJ . 1998: Removing social desirability bias with indirect questioning: Is the cure worse than the disease. Advances in Consumer Research 25 (1): 563–567.
Fox, JA and Tracy, PE . 1986: Randomized response: A method for sensitive surveys. Sage Publications: Newbury Park, CA.
Friesenbichler, KS, Clarke, GRG and Wong, M . 2014: Price competition and market transparency: Evidence from a random response technique. Empirica 41 (1): 5–21.
Iarossi, G . 2006: The power of survey design. World Bank: Washington DC.
Jensen, NM and Rahman, A . 2011: The silence of corruption: Identifying underreporting of business corruption through randomized response techniques. Policy Research Working Paper No. 5696. World Bank: Washington DC.
Johnson, S, Kaufmann, D, McMillan, J and Woodruff, C . 2000: Why do firms hide? Bribes and unofficial activity after communism. Journal of Public Economics 76 (3): 495–520.
Johnson, S, McMillan, J and Woodruff, C . 2002: Property rights and finance. American Economic Review 92 (5): 1335–1356.
Karlan, D and Zinman, J . 2012: List randomization for sensitive behavior: An application for measuring use of loan proceeds. Journal of Development Economics 98 (1): 71–75.
Lee, RM . 1993: Doing research on sensitive topics. Sage Publications: London, UK.
Lensvelt-Mulders, GJLM, Hox, JJ, Van Der Heuden, PGM and Maas, CJM . 2005: Meta-analysis of randomized response research: Thirty-five years of validation. Sociological Methods and Research 35 (3): 319–348.
Lewbel, A, Dong, Y and Yang, TT . 2012: Comparing features of convenient estimators for binary choice models with endogenous regressors. Canadian Journal of Economics 45 (3): 810–829.
Recanatini, F, Wallsten, S and Xu, LC . 2000: Surveying surveys and questioning questions: Learning from World Bank experience. Policy Research Working Paper No. 2307. World Bank: Washington DC.
Safavian, MS, Graham, DH and Gonzalez-Vega, C . 2001: Corruption and microenterprises in Russia. World Development 29 (7): 1215–1224.
Smith, RJ and Blundell, RW . 1986: An exogeneity test for a simultaneous equation Tobit model with an application to labor supply. Econometrica 54 (4): 679–686.
Svensson, J . 2003: Who must pay bribes and how much? Evidence from a cross section of firms. Quarterly Journal of Economics 118 (1): 207–230.
Tourangeau, R, Rips, LJ and Rasinski, K . 2000: The psychology of survey response. Cambridge University Press: Cambridge, UK.
Treisman, D . 2007: What have we learned about the causes and corruption from ten years of cross-national empirical research. Annual Review of Political Science 10 (1): 211–244.
Warner, SL . 1965: Randomized response: A survey technique for eliminating evasive answer bias. Journal of the American Statistical Association 60 (309): 63–66.
World Bank. 2012a: Enterprise surveys: Indicator descriptions. World Bank: Washington DC.
World Bank. 2012b: Sri Lanka 2011: Management practices surveys data set. World Bank: Washington DC.
Acknowledgements
The data used in this paper are from the Enterprise Surveys (http://www.enterprisesurveys.org), The World Bank. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Responsibility for all errors, omissions, and opinions rests solely with the authors. We would like to thank Jeff Nugent and Bilin Neyapti and participants at the Western Economic Association annual meetings, Public Choice Society annual meetings, and a seminar at Texas A&M International University for comments on earlier drafts. Finally, we would like to thank Josef Brada and anonymous referees for their helpful advice.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Clarke, G., Friesenbichler, K. & Wong, M. Do Indirect Questions Reduce Lying about Corruption? Evidence from a Quasi-Field Experiment. Comp Econ Stud 57, 103–135 (2015). https://doi.org/10.1057/ces.2014.43
Published:
Issue Date:
DOI: https://doi.org/10.1057/ces.2014.43