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.
# 17-097/III (2017-10-26)
- Xu Guo, Beijing Normal University; Gao-Rong Li, Beijing University of Technology; Michael McAleer, Econometric Institute, Erasmus University Rotterdam; Wing-Keung Wong, Asia University, Lingnan University
- Production frontier function, Stochastic frontier model, Specification testing, Wild bootstrap, Smoothing process, Empirical process, Simulations
- JEL codes:
- C0, C13, C14, D81