TY - UNPB

T1 - Estimating Stochastic Ray Production Frontiers

AU - Tsionas, Mike

AU - Henningsen, Arne

AU - Izzeldin, Marwan

AU - Paravalos, Evaggelos

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

M3 - Working paper

T3 - IFRO Working Paper

BT - Estimating Stochastic Ray Production Frontiers

PB - Department of Food and Resource Economics, University of Copenhagen

ER -