Markov switching stochastic frontier model

Abstract

In this paper, we propose a new approach to stochastic frontier models, viz., a Markov switching structure to accommodate cross‐sectional parameter heterogeneity and temporal variation in the parameters and technical inefficiency distributions. The Markov Chain Monte Carlo techniques are developed and implemented for Bayesian inferences on parameters and technical efficiency. We illustrate new methods by estimating world production frontiers using international panel data on 59 countries observed for 26 years.

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