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Abstract

The paper discusses Bayesian productivity analysis of 27 EU Member States, USA, Japan and Switzerland. Bayesian Stochastic Frontier Analysis and a two-stage 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.

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Authors and Affiliations

Kamil Makieła

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