Subhash C. Ray

Productivity growth in large US commercial banks: The initial post-deregulation experience

Abstract We explore productivity growth for a group of 201 large US commercial banks over the initial post-deregulation period from 1984 to 1990, using data envelopment analysis (DEA). We measure productivity growth using Malmquist productivity indexes and isolate the contributions of technical change, technical efficiency change, and scale change to productivity growth. We find overall productivity growth at the rate of about 4.5% per year on average, but productivity declined by 7.61% between 1984 and 1985 and by 0.33% between 1988 and 1989. Our second-stage panel regressions reveal that larger asset size and specialization of product mix associate with higher productivity growth while higher equity to assets associates with lower productivity growth.

Returns to Scale and Input Substitution for Large U.S. Banks

THE UNITED STATES COMMERCIAL BANKING INDUSTRY has experienced significant changes in recent years. The recent wave of mergers and the near-term prospects of interstate banking suggests that the industry is moving toward much larger average banking organizations (Rhoades 1985). Will a more concentrated banking industry result in lower costs due to scale economies? We address this question by examining the cost function for large banks. Numerous studies of economies of scale in banking exist, generally tracing their roots to the classic papers by Benston ( 1965) and Bell and Murphy ( 1968). A good review of the most recent studies can be found in Clark ( 1988). The majority of the papers uses samples of smaller banks (that is, under

A Translog Cost Function Analysis of U.S. Agriculture, 1939–77

1 billion in deposits), finding generally that economies of scale are quickly exhausted and that further increases in bank size occur at constant, or possibly increasing, cost. The extrapolation of previous findings for samples of smaller banks to large banks may be problematic, especially in the current environment. First, large banks service a different mix of markets and customers than small banks, suggesting that large and small banks probably face different cost structures. Second, the process of deregulation may have rendered the results of prior studies moot, since the data pertain to periods before significant deregulation. Since we

Distribution of cost and profit efficiency: Evidence from Indian banking

The translog cost function provides a convenient framework for analyzing U.S. agricultural production in a multioutput context. Treating crops and livestock as two distinct outputs, this study utilizes standard results of neoclassical duality theory to obtain measures of pairwise elasticities of substitution between inputs, price elasticities of factor demands, and the rate of Hicks-neutral technical change. Results obtained from joint GLS estimation of parameters of cost and share equations indicate a declining trend in the degree of substitutability between capital and labor. Price elasticity of demand for all inputs increased over time. The measured rate of technical change was 1.8%per year.

Data envelopment analysis, nondiscretionary inputs and efficiency: an alternative interpretation

This paper uses the nonparametric DEA methodology to estimate cost and profit efficiency of Indian banks during the post-reform period. The results show considerable variation in average levels of profit efficiency across various ownership categories of banks. In general, state owned banks are found to be more efficient than their private counter parts. Further, efficiency tends to be low among the small banks (assets up to Rs. 50 billion), indicating that at the existing scale of operations, these banks are operating far below the efficient frontier. We also examine the distribution of efficiency using nonparametric kernel density estimates. The analysis reveals a rightward-shift of the efficiency distribution over the years. A major part of this shift comes from the state owned banks. Based on the conditional distribution, the study finds strong evidence of ownership explaining the efficiency differential of banks. Additionally, bank size and product-mix are also found to be important, although to a lesser extent.

Measuring Scale Efficiency from a Translog Production Function

Abstract Various methods using econometric or mathematical programming techniques are available in the literature for measurement of efficiency of firms. None of these, however, investigates the sources of differences in efficiency across productive units. In this paper we used the method of Data Envelopment Analysis introduced by Charnes, Cooper and Rhodes as the basic format to show that observed differences in efficiency can be explained in terms of differences in nondiscretionary inputs across firms.

DECOMPOSITION OF THE FISHER IDEAL INDEX OF PRODUCTIVITY: A NON-PARAMETRIC DUAL ANALYSIS OF US AIRLINES DATA*

In parametric analysis based on a frontier production function, usually the scale elasticity rather than scale efficiency level is reported. In this paper we show how one can use an estimated translog production function to obtain output- and input-oriented measures of scale efficiency at an observed input bundle. We also show how the estimated model can be used to determine the optimal quantity of labor input for an exogenously fixed quantity of capital.

Reputation and efficiency: A non-parametric assessment of America's top-rated MBA programs

In this paper, the authors offer a nonparametric method of decomposing the Fisher ideal index of productivity into individual factors measuring technical efficiency change, allocative efficiency change, shift in the cost function, scale economies due to output change, and an adjustment factor reflecting change in the output attributes. Cross-section data from the U.S. airline industry for the years 1983 and 1984 are utilized in an empirical application illustrating this method. Copyright 1996 by Royal Economic Society.

The Directional Distance Function and Measurement of Super-Efficiency: An Application to Airlines Data

Widely publicized reports of fresh MBAs getting multiple job offers with six-figure annual salaries leave a long-lasting general impression about the high quality of selected business schools. While such spectacular achievement in job placement rightly deserves recognition, one should not lose sight of the resources expended in order to accomplish this result. In this study, we employ a measure of Pareto-Koopmans global efficiency to evaluate the efficiency levels of the MBA programs in Business Weeks top-rated list. We compute input- and output-oriented radial and non-radial efficiency measures for comparison. Among three tier groups, the schools from a higher tier group on average are more efficient than those from lower tiers, although variations in efficiency levels do occur within the same tier, which exist over different measures of efficiency.

The individual over time: Time series applications in health care research

In a recent paper published in this Journal, Lovell and Rouse (LR) proposed a modification of the standard data envelopment analysis (DEA) model that overcomes the infeasibility problem often encountered in computing super-efficiency. In the LR procedure one appropriately scales up the observed input vector (scale down the output vector) of the relevant super-efficient firm thereby usually creating its inefficient surrogate. By contrast, Chen suggested a different procedure that replaces input–output bundles that are found to be inefficient in standard DEA by their efficient projections. An alternative procedure proposed in this paper uses the directional distance function and the resulting Nerlove–Luenberger measure of super-efficiency. The fact that the directional distance function combines, by definition, features of both an input-oriented and an output-oriented model, generally leads to a complete ranking of the observations and is easily interpreted. A dataset on international airlines is utilized in an illustrative empirical application.