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

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.