2016
DOI: 10.1016/j.ejpoleco.2016.02.002
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Bribery environments and firm performance: Evidence from CEE countries

Abstract: We examine the relation between bureaucratic corruption and firm performance in CEE countries. We show that divergent consequences of corruption found in previous studies can be explained by the specifics of the local bribery environment in which firms operate.A higher mean bribery is associated with lower firm performance, while higher dispersion of individual firm bribes appears to facilitate it. We also conduct a detailed analysis by firm sector and size, and countries' institutional environments.

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Cited by 82 publications
(74 citation statements)
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“…Moreover, since the existing literature has largely focused on how corruption affects within-firm productivity (e.g. Hanousek and Kochanova 2015;De Rosa, Gooroochurn and Görg 2010), our contribution to the literature is to assess whether bribes may affect TFP growth via the alternative misallocation channel, which we next focus on. We therefore explore how corruption affects one of the determinants of TFP growth, input misallocation, according to alternative model specifications.…”
Section: The Baseline Resultsmentioning
confidence: 99%
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“…Moreover, since the existing literature has largely focused on how corruption affects within-firm productivity (e.g. Hanousek and Kochanova 2015;De Rosa, Gooroochurn and Görg 2010), our contribution to the literature is to assess whether bribes may affect TFP growth via the alternative misallocation channel, which we next focus on. We therefore explore how corruption affects one of the determinants of TFP growth, input misallocation, according to alternative model specifications.…”
Section: The Baseline Resultsmentioning
confidence: 99%
“…Most of the empirical literature has focused either on the effect of firm-level bribery on within-firm productivity (for example, De Rosa, Gooroochurn and Görg 2010; Hanousek and Kochanova 2015) or on the impact of total-economy corruption on a country's aggregate economic performance (for instance, Mauro 1995;Tanzi and Davoodi 1997). In this paper, instead, we use firm-level data on corruption and investigate its relationship with a measure of within-sector misallocation of inputs, in turn a driver of sectorial TFP growth.…”
Section: Introductionmentioning
confidence: 99%
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“…Capital is proxied by total fixed assets plus working capital, which is defined as current assets minus current 11 This approach helps us to deal later with potential endogeneity between corruption and efficiency, unobserved firm level heterogeneity and selection bias that cannot be properly addressed when using BEEPS alone, as the dataset does not have a panel structure. A similar approach has been used by Commander and Svejnar (2011), Hanousek and Kochanova (2016), and Fungáčová et al (2015). 12 See Aigner et al (1977) and Meeusen and van Den Broeck (1977) for stochastic frontier analysis and Schmidt and Sickles (1984), Kumbhakar (1990), andGreene (2005) for panel data application to stochastic frontier analysis.…”
Section: Firm Efficiency -Stochastic Frontier Analysismentioning
confidence: 99%