Risk‐adjusted efficiency and risk aversion in the agricultural banking industry

Abstract

Purpose

The purpose of this paper is to examine the performance of the agricultural banking industry using both traditional and risk‐adjusted non‐parametric efficiency measurement techniques. In addition to computing efficiency scores, the risk preference structure of the agricultural banking industry is examined.

Design/methodology/approach

The paper used data envelopment analysis (DEA) to examine the efficiency of agricultural banks in the year 2001. Standard cost efficiency is computed and compared to both profit and risk‐adjusted profit efficiency scores. The risk‐adjustment is a modification of traditional DEA wherein firm preferences are represented via a mean‐variance criterion. The risk‐adjusted technique also provides estimates of firm level risk aversion.

Findings

Results from the traditional approach that does not account for risk indicate a low degree of efficiency in the banking industry, while the risk‐adjusted approach indicates banks are much more efficient. On average, 77 percent of the inefficiency identified by the standard DEA formulation is actually attributable to risk averse behavior by the firm. In addition, most banks appear to be substantially risk averse.

Research limitations/implications

The risk‐adjusted DEA technique used in this study should be applied to other, diverse data sets to examine its performance in a broader context.

Practical implications

Results from this study support the idea that traditional DEA methods may mischaracterize the level of efficiency in the data if agents are risk averse. In addition, the paper outlines a practical method for deriving firm level risk aversion coefficients.

Originality/value

This paper sheds light on the agricultural banking industry and illustrates the power of a new efficiency and risk analysis technique.

Citation

Settlage, D.M., Preckel, P.V. and Settlage, L.A. (2009), "Risk‐adjusted efficiency and risk aversion in the agricultural banking industry", Agricultural Finance Review, Vol. 69 No. 3, pp. 314-329. https://doi.org/10.1108/00021460911002699