Guo, Xu Li, Gao-Rong McAleer, Michael Wong, Wing-Keung
Year of Publication:
Tinbergen Institute Discussion Paper 17-097/III
Parametric production frontier functions are frequently used in stochastic frontier models, but there do not seem to be any empirical test statistics for its plausibility. To bridge the gap in the literature, we develop two test statistics based on local smoothing and an empirical process, respectively. Residual-based wild bootstrap versions of these two test statistics are also suggested. The distributions of technical inefficiency and the noise term are not specified, which allows specification testing of the production frontier function even under heteroscedasticity. Simulation studies and a real data example are presented to examine the finite sample sizes and powers of the test statistics. The theory developed in this paper is useful for production mangers in their decisions on production.
Production frontier function Stochastic frontier model Specification testing Wild bootstrap Smoothing process Empirical process Simulations