Template-Type: ReDIF-Paper 1.0
Author-Name: Mike Tsionas
Author-Name-First: Mike
Author-Name-Last: Tsionas
Author-Email: m.tsionas@lancaster.ac.uk
Author-Workplace-Name: Department of Economics, Lancaster University Management School
Author-Name: Marwan Izzeldin
Author-Name-First: Marwan
Author-Name-Last: Izzeldin
Author-Email: m.izzeldin@lancaster.ac.uk
Author-Workplace-Name: Department of Economics, Lancaster University Management School
Author-Name: Arne Henningsen
Author-Name-First: Arne
Author-Name-Last: Henningsen
Author-Email: arne@ifro.ku.dk
Author-Workplace-Name: Department of Food and Resource Economics, University of Copenhagen
Author-Name: Evaggelos Paravalos
Author-Name-First: Evaggelos
Author-Name-Last: Paravalos
Author-Email: paravalosev@aueb.gr
Author-Workplace-Name: Department of Economics, Athens University of Economics and Business (Greece)
Title: Estimating Stochastic Ray Production Frontiers
Abstract: In this paper, we consider the stochastic ray production function that has been revived recently by Henningsen et al. (2017). We use a profit-maximizing framework to resolve endogeneity problems that are likely to arise, as in all distance functions, and we derive the system of equations after incorporating technical inefficiency. As technical inefficiency enters non-trivially into the system of equations and the Jacobian is highly complicated, we propose Monte Carlo methods of inference. We illustrate the new approach using US banking data and we also address the problems of missing prices and selection of ordering for outputs.
Length: 10 pages
Creation-Date: 2019-09
File-URL: http://okonomi.foi.dk/workingpapers/WPpdf/WP2019/IFRO_WP_2019_06.pdf
File-Format: Application/pdf
Number: 2019/06
Classification-JEL: C11, C13, D24 
Keywords: Stochastic ray production frontier, Technical inefficiency, Profit maximization, Bayesian inference
Handle: RePEc:foi:wpaper:2019_06