The Analysis of the Impact of Regulatory Environment on the Pace of Economic Growth of the World Countries According to the Bayesian Model Averaging

NBP Working Paper No. 165

92 Pages Posted: 18 Dec 2013

See all articles by Mariusz Próchniak

Mariusz Próchniak

Warsaw School of Economics (SGH)

Bartosz Witkowski

Warsaw School of Economics (SGH)

Date Written: December 2, 2013

Abstract

The study examines the relationship between the regulatory variables and economic growth on the basis of Bayesian model pooling applied to Blundell and Bond’s GMM system estimator. The areas of regulations (institutions) are measured by the following indicators: index of economic freedom, worldwide governance indicators, democracy index, doing business indicators, transition indicators. The models are estimated based on overlapping panel data and they include nonlinearities. In general, regulatory environment is an important determinant of economic growth. To achieve rapid growth, it is necessary to increase economic freedom, quality of governance, and market reforms. The association between regulatory variables and GDP dynamics is mostly nonlinear. The countries with greater scope of economic freedom record more rapid GDP growth but a given increase in economic freedom has a higher impact on growth in those countries that are economically not (or partly) free. However, the results are not robust in a lot of areas – with regard to the sample of countries, the exact measure of the regulatory variable, and the type of nonlinear impact (concave vs. convex functions). There are many factors affecting both regulations and GDP dynamics as well as many transmission channels between these areas and the results sometimes are mixed.

Keywords: economic growth, regulations, institutions, growth factors, Bayesian averaging

JEL Classification: C11, C23, O40, O43, O47

Suggested Citation

Prochniak, Mariusz and Witkowski, Bartosz, The Analysis of the Impact of Regulatory Environment on the Pace of Economic Growth of the World Countries According to the Bayesian Model Averaging (December 2, 2013). NBP Working Paper No. 165, Available at SSRN: https://ssrn.com/abstract=2367254 or http://dx.doi.org/10.2139/ssrn.2367254

Mariusz Prochniak (Contact Author)

Warsaw School of Economics (SGH) ( email )

aleja Niepodleglosci 162
PL-Warsaw, 02-554
Poland

Bartosz Witkowski

Warsaw School of Economics (SGH) ( email )

aleja Niepodleglosci 162
PL-Warsaw, 02-554
Poland

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