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Journal of Economics and Finance

Erschienen in:

22.03.2022

Dimensions of size and corruption perceptions versus corruption experiences by firms in emerging economies

verfasst von: Rajeev K. Goel, Ummad Mazhar, Rati Ram

Erschienen in: Journal of Economics and Finance | Ausgabe 2/2022

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Abstract

This study uses a large firm-level data set covering more than 80 countries to explore the effects of firm size, city size, and government size on perceived and experienced corruption. Four points summarize our main findings, which seem instructive and new. First, there is a broad structural similarity in the major determinants of perceived and experienced corruption. Second, larger firms and larger government sizes reduce the perceptions and experiences of corruption. Third, larger cities raise corruption perceptions and experience. Fourth, when the sample is limited to large cities, the corruption-lowering effect of government size loses significance throughout, while firm size loses significance in experience regressions.

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A recent study by Gutmann et al. (2020) compares corruption experiences and corruption perceptions using a different sample and an alternative source of the corruption data. The present study uses data on corruption perceptions and experiences from firms’ managers and owners and uniquely focuses on the impacts of different dimensions of size.

https://www.enterprisesurveys.org/content/dam/enterprisesurveys/documents/ES-map-global-coverage.pdf.

The data for corruption perceptions (but not corruption experience) includes multiple response options (see www.enterprisesurveys.org and Table 1 for details). This makes doing a multinomial analysis possible. We restrict our analysis to a 0–1 choice to facilitate comparisons between the two measures of corruption (CORRperc and CORRexp).

https://blogs.worldbank.org/developmenttalk/india-s-it-industry-and-industrial-policy

See https://www.enterprisesurveys.org/en/methodology.

Although some nations had multiple years (not consecutive years) of surveys, it is unclear if the same firms were surveyed over time (due to market exit or unresponsiveness; also see https://www.enterprisesurveys.org/en/methodology). Thus, it is not possible to capture the effect of “learning in corrupt relations” by using the information in the subset of nations with multiple years of survey data.

Government size can alternatively be measured in terms of public sector employment. However, measuring government size via government consumption expenditures is somewhat broader as it takes account of government spending on automation and other capital expenditures as well. Such automation might be relevant in the context of corruption via e-government services, for instance (see Goel and Saunoris (2016)).

The coefficient on CitySIZE is statistically significant in two of the four models in Table 3.

The impact of city size provides an interesting contrast from earlier findings of Mocan (2008), where, based on data from individual respondents about their being asked for a bribe, he found that individuals in small and medium-sized cities were less likely to be asked for bribes.

It should be noted that we are reporting a one SD change in CitySIZE to make it comparable with other variables. Otherwise, a better way to discern its influence is through a discrete change. Adopting the latter interpretation, the results in Model 2.1 suggest six percent higher corruption perceptions for firms in cities with more than 1 million population compared to firms located in less populated cities.

The underlying survey respondent across firms is not necessarily the top manager. It could be, depending upon the firm and the time of the survey, the business owner or other managers/accountants (see https://www.enterprisesurveys.org/en/methodology).

In general, with the multiple roles of the government, with the causes and effects of government size in almost all economic activity, finding good instruments for government size that do not affect corruption is a challenge (see, for a recent example, Goel and Nelson (2021)).

Results based on the use of a micro-level variable to instrument a macro-variable should be interpreted with appropriate caution (see Angrist and Krueger (2001); Imbens and Lancaster (1994)).

One exception is the negative sign on CitySIZE in Model 4.3. However, the main variable of interest here is GovtSIZE and the signs of other coefficients can be biased (Stock and Watson (2000)).

The size of cities is likely to be largely exogenous, at least in the short term. So CitySIZE can reasonably be taken to be exogenous.

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Titel: Dimensions of size and corruption perceptions versus corruption experiences by firms in emerging economies
verfasst von: Rajeev K. Goel
Ummad Mazhar
Rati Ram
Publikationsdatum: 22.03.2022
Verlag: Springer US
Erschienen in: Journal of Economics and Finance / Ausgabe 2/2022
Print ISSN: 1055-0925
Elektronische ISSN: 1938-9744
DOI: https://doi.org/10.1007/s12197-022-09571-1

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