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Doing the survey two-step : the effects of reticence on estimates of corruption in two-stage survey questions

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  • Karalashvili,Nona
  • Kraay,Aart C.
  • Murrell,Peter

Abstract

This paper develops a structural approach for modeling how respondents answer survey questions and uses it to estimate the proportion of respondents who are reticent in answering corruption questions, as well as the extent to which reticent behavior biases down conventional estimates of corruption. The context is a common two-step survey question, first inquiring whether a government official visited a business, and then asking about bribery if a visit was acknowledged. Reticence is a concern for both steps, since denying a visit sidesteps the bribe question. This paper considers two alternative models of how reticence affects responses to two-step questions, with differing assumptions on how reticence affects the first question about visits. Maximum-likelihood estimates are obtained for seven countries using data on interactions with tax officials. Different models work best in different countries, but cross-country comparisons are still valid because both models use the same structural parameters. On average, 40 percent of corruption questions are answered reticently, with much variation across countries. A statistic reflecting how much standard measures underestimate the proportion of all respondents who had a bribe interaction is developed. The downward bias in standard measures is highly statistically significant in all countries, varying from 12 percent in Nigeria to 90 percent in Turkey. The source of bias varies widely across countries, between denying a visit and denying a bribe after admitting a visit.

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  • Karalashvili,Nona & Kraay,Aart C. & Murrell,Peter, 2015. "Doing the survey two-step : the effects of reticence on estimates of corruption in two-stage survey questions," Policy Research Working Paper Series 7276, The World Bank.
  • Handle: RePEc:wbk:wbrwps:7276
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    References listed on IDEAS

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    1. Omar Azfar & Peter Murrell, 2009. "Identifying Reticent Respondents: Assessing the Quality of Survey Data on Corruption and Values," Economic Development and Cultural Change, University of Chicago Press, vol. 57(2), pages 387-411, January.
    2. Olken, Benjamin A., 2009. "Corruption perceptions vs. corruption reality," Journal of Public Economics, Elsevier, vol. 93(7-8), pages 950-964, August.
    3. Ritva Reinikka & Jakob Svensson, 2004. "Local Capture: Evidence from a Central Government Transfer Program in Uganda," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 119(2), pages 679-705.
    4. Bianca Clausen & Aart Kraay & Peter Murrell, 2011. "Does Respondent Reticence Affect the Results of Corruption Surveys? Evidence from the World Bank Enterprise Survey for Nigeria," Chapters, in: Susan Rose-Ackerman & Tina Søreide (ed.), International Handbook on the Economics of Corruption, Volume Two, chapter 15, Edward Elgar Publishing.
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    Cited by:

    1. Gutmann, Jerg & Padovano, Fabio & Voigt, Stefan, 2020. "Perception vs. experience: Explaining differences in corruption measures using microdata," European Journal of Political Economy, Elsevier, vol. 65(C).
    2. Ilona Wysmułek, 2019. "Using public opinion surveys to evaluate corruption in Europe: trends in the corruption items of 21 international survey projects, 1989–2017," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(5), pages 2589-2610, September.
    3. George R. G. Clarke, 2021. "How Do Women Managers Avoid Paying Bribes?," Economies, MDPI, vol. 9(1), pages 1-18, February.
    4. Jarosław Wątróbski & Ewa Ziemba & Artur Karczmarczyk & Jarosław Jankowski, 2018. "An Index to Measure the Sustainable Information Society: The Polish Households Case," Sustainability, MDPI, vol. 10(9), pages 1-30, September.

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