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.

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Keywords Production frontier function, Stochastic frontier model, Specification testing, Wild bootstrap, Smoothing process, Empirical process, Simulations
JEL Mathematical and Quantitative Methods: General (jel C0), Estimation (jel C13), Semiparametric and Nonparametric Methods (jel C14), Criteria for Decision-Making under Risk and Uncertainty (jel D81)
Persistent URL
Series Econometric Institute Research Papers
Guo, X, Li, G.-R, McAleer, M.J, & Wong, W.-K. (2017). Specification Testing of Production in a Stochastic Frontier Model (No. EI 2017-27). Econometric Institute Research Papers. Retrieved from