Property rights, extortion and the misallocation of talent

Abstract

Extortion is a severe obstacle to doing business in many countries, varies both in its frequency and magnitude across establishments. This paper presents a model of extortion to account for these features and assess its quantitative effects. In the model, entrepreneur capital is subject to extortion which affects both the extensive and intensive margins of entrepreneurship. Despite common property rights, extortion rates arise endogenously and are hump-shaped in entrepreneur ability. To discipline the quantitative analysis, the model is calibrated to match establishment-level evidence related to extortion in Poland and yields a number of implications broadly consistent with establishment-level facts in developing economies. For measures of property rights within a plausible range, output losses can be upwards of 10 percent.

Financial Frictions and the Rule of Law

“…The macro literature emphasizing financial frictions include Jeong and Townsend (2007), Amaral and Quintin (2010), , Buera and Shin (2013), Caselli and Gennaioli (2013), Greenwood et al (2013), Midrigan and Xu (2014), Moll (2014), among many others. Fewer studies examine the macro effects of crime, an exception being Ranasinghe (2017) who studies the effects of extortion in Eastern Europe. Our framework integrates these two relevant institutions studying their interaction and potential to account for the substantial differences in output per capita across countries.…”

Crime and Establishment Size: Evidence from South America

“…We consider an otherwise standard model of heterogeneous establishments/producers and incorporate a channel for crime as in Ranasinghe (2014). In our framework, establishment production is influenced by expected losses from crime.…”

“…Given that close to one-third of establishments have high crime expectation in the sample, it implies aggregate output losses of about 8 percent percent relative to a crime-free economy, which is larger than the magnitudes founds in general equilibrium macro models of crime/extortion (Ranasinghe 2014;Ranasinghe and Restuccia, 2015). 17 The effects on capital are negative but not significant.…”

“…We focus on b = ρ = ψ = 2 because it simplifies the solutions without altering anything central to the model. See Ranasinghe (2014) for a discussion on the sensitivity of the analytical results from alternate cost functions for crime and protection.…”

“…Moreover, we show that establishments may strategically under-produce to avoid losses from crime, which lowers average establishment size in these countries, which is consistent with Bento and Restuccia (2015) who document a clear negative relationship between establishment size and development. Related is Ranasinghe (2014) and Ranasinghe and Restuccia (2015) who study extortion and crime using quantitative macro models that feature heterogeneous producers. Our results are complimentary to theirs, though we use micro-level data to estimate the implied effects of crime on establishment production.…”