Article ID: | iaor201111544 |
Volume: | 217 |
Issue: | 3 |
Start Page Number: | 509 |
End Page Number: | 518 |
Publication Date: | Mar 2012 |
Journal: | European Journal of Operational Research |
Authors: | Kumbhakar Subal C |
Keywords: | simulation: applications, combinatorial optimization, supply & supply chains |
While estimating production technology in a primal framework production function, input and output distance functions and input requirement functions are widely used in the empirical literature. This paper shows that these popular primal based models are algebraically equivalent in the sense that they can be derived from the same underlying transformation (production possibility) function. By assuming that producers maximize profit, we show that in all cases, except one, the use of ordinary least squares (OLS) gives inconsistent estimates irrespective of whether the production, input distance and input requirement functions are used. Based on several specifications of the production and input distance function models, we conclude that one can estimate the input elasticities and returns to scale consistently using instruments on only one regressor. No instruments are needed if either it is assumed that producers know the technology entirely (including the so‐called error term) or a system approach is used. We used Norwegian timber harvesting data to illustrate workings of various model specifications.