Factor price misspecification in bank cost function estimation

Abstract

Abstract Many studies of bank productivity implicitly assume that banks face imperfect factor markets in accessing labor and capital such that, in renting the same factor of production, at the same time, one bank will pay a price that will vary greatly from that of another bank. Usually, this implicit assumption is introduced by researchers’ simple expedience in calculating a factor price by dividing total cost attributable to a factor by the number of units rented. The range of factor prices so obtained, however, exceeds the reasonable bounds commonly observed in integrated factor markets. Our study contends that the wide variety of labor factor prices implicitly assumed is in fact a reflection of a variegated labor market and that the wide variety of financial capital costs is a reflection of incomplete specification of funds’ costs. We contend that, particularly in cross-sectional studies, it would generally be better for researchers to assume that banks faced competitive factor markets, thereby allowing the factor price term of cost functions to be eliminated. Not only would such elimination allow for a better estimate of true economies of scale and efficiency; it would also simplify greatly the estimation of many models. In this paper, we review briefly the significance of specifying factor prices in cost functions. Then we look at some actual factor prices that are reported in studies and used as inputs to cost function estimation. We conduct some simple tests to show what the reported factor prices in banking may actually represent. Having shown that factor prices reported are subject to misspecification, we estimate a set of cost functions with and without factor price specifications. We conclude by demonstrating that the improper specification of factor prices can affect inferences regarding measurement of inefficiency and returns to scale. Finally, we suggest methods by which these misspecifications may be rectified by use of time series, regional and international factor pricing data.