A parametric approach to efficiency measurement using a flexible profit function

This paper primarily focused on developing a generalized profit function approach that accommodates both technical and allocative inefficiencies in a profit maximization framework. The relationship between production technical inefficiency (loss of output due to technical inefficiency) and profit technical inefficiency (profit loss due to technical inefficiency) is derived for a flexible profit function (translog). It is shown that if the profit function is translog, some popular approaches used in modeling technical and allocative inefficiency are incorrect. For example, (i) models that fail to include technical inefficiency and consider only allocative inefficiency yield biased and inconsistent parameter estimates; (ii) technical inefficiency cannot be modeled simply by appending a non-positive firm-specific term (either random or fixed) in the profit function; and (iii) if technical inefficiency is neglected, the measure of technical change will be biased. We also showed that in a profit maximizing framework with panel data it is possible to distinguish between technical change and time-varying technical efficiency. Such a distinction is, however, not possible if one uses either the production or the cost function in estimation. We used a panel data on ten investor-owned electric utilities in Texas to illustrate empirical implementation of our model. The empirical model rejected the time-varying technical inefficiency specification, but allocative inefficiencies were found to be varying over time. Technical progress was found to be neutral and it declined steadily from 7.70% in 1966 to 1.60% in 1985. Profit losses due to technical and allocative inefficiencies combined were found to vary widely among the utilities, ranging from 2.26% to 17.15%. Empirical support of the Averch-Johnson effect (over-capitalization) was found after the Public Utility Commission of Texas was established in 1977.