Specification Testing of Production in a Stochastic Frontier Model

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, respectiv...

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Detalles Bibliográficos
Autores: Guo, Xu, Li, Gao-Rong, McAleer, Michael, Wong, Wing-Keung
Tipo de recurso: informe técnico
Fecha de publicación:2017
País:España
Institución:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/22929
Acceso en línea:https://hdl.handle.net/20.500.14352/22929
Access Level:acceso abierto
Palabra clave:C0
C13
C14
D81
Production frontier function
Stochastic frontier model
Specification testing
Wild bootstrap
Smoothing process
Empirical process
Simulations.
Econometría (Economía)
Microeconomía
5302 Econometría
5307.15 Teoría Microeconómica
Descripción
Sumario: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.