Abstract
This study examines the relationship between firm-level tax evasion and corruption. The literature has considered the corruption-firm tax evasion nexus to some extent, however, the heterogeneous impact of bribes on tax evasion has been largely ignored. We posit that the impact of bribes on tax evasion is conditional on the prevalence of tax evasion. Using firm-level information from the Business Environment and Enterprise Performance Survey (BEEPS) across 25 transition economies for the years 2002 and 2005, we estimate the heterogeneous impact of bribes on tax evasion using the censored quantile instrumental variables technique. The results show that corruption has a larger impact when tax evasion is more widespread. Among other results, firm-level characteristics also show heterogeneous effects across the conditional distribution of tax evasion. In terms of the policy implications, the results suggest that policies that focus on reducing the tax burden and controlling corruption will be more effective when tax evasion is more prevalent.
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Notes
Notice that the phrasing of the question on tax evasion and bribery refers to a typical firm as opposed to your firm, which should help mitigate, at least to some degree, concerns of dishonesty.
For more details on the CQIV technique see Kowalski (2016).
See Eqs. 2.1, 2.2 and 2.3 in Chernozhukov et al. (2015).
As an example, Kowalski (2016) provided a recent application of the CQIV estimator with respect to the estimation of the price elasticity of medical care expenditures and allowed this estimate to vary across the distribution of medical care expenditures while also accounting for endogeneity and censoring. The results suggest that price elasticity varies significantly across the conditional distribution of medical expenditures and highlights the importance of accounting for this heterogeneity, which has important policy implications.
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Payne, J.E., Saunoris, J.W. Corruption and Firm Tax Evasion in Transition Economies: Results from Censored Quantile Instrumental Variables Estimation. Atl Econ J 48, 195–206 (2020). https://doi.org/10.1007/s11293-020-09666-2
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DOI: https://doi.org/10.1007/s11293-020-09666-2