Bayesian Stochastic Frontier Analysis of Economic Growth and Productivity Change in the EU, USA, Japan and Switzerland

Kamil Makieła

Central European Journal of Economic Modelling and Econometrics, 2014, vol. 6, issue 3, 193-216

Abstract: The paper discusses Bayesian productivity analysis of 27 EU Member States, USA, Japan and Switzerland. Bayesian Stochastic Frontier Analysis and a twostage structural decomposition of output growth are used to trace sources of output growth. This allows us to separate the impacts of capital accumulation, labour growth, technical progress and technical efficiency change on economic development. Since estimates of the growth components are conditioned upon model parameterisation and the underlying assumptions, a number of possible specifications are considered. The best model for decomposing output growth is chosen based on the highest marginal data density, which is calculated using adjusted harmonic mean estimator.

Keywords: stochastic frontier analysis; Bayesian inference; productivity analysis; economic growth decomposition (search for similar items in EconPapers)
JEL-codes: C11 C23 O47 O52 (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:psc:journl:v:6:y:2014:i:3:p:193-216

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