Abstract
In this paper, we investigate the effect of bank size differences on cost efficiency heterogeneity using a heteroskedastic stochastic frontier model. This model is implemented by using an information theoretic maximum entropy approach. We explicitly model both bank size and variance heterogeneity simultaneously. We find that non-performing loans, federal insurance premium, legal expenses and director fees drive bank inefficiency as the bank becomes larger. Moral hazard, bank management and a “too big to fail” doctrine are likely explanations for the results from this study.
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Notes
The average price of labor is calculated by dividing total salary expenditure by the total number of bank employees. The average price of premises and fixed assets is calculated by dividing total expenditures on premises and fixed assets by total deposits. The average price of interest expense is obtained by dividing total interest expense by total deposits.
As explained in Caudill et al. (1995), this is done due to institutional age-related bias introduced if one divides physical capital spending by the book value of total physical capital, because physical capital is recorded at historical cost rather than market value.
For a detailed discussion on the different hypotheses, refer to Berger and DeYoung (1997).
This is consistent with Hughes and Mester (1993).
Refer to Boyd and De Nicolo (2005) for a thorough explanation on how a given market structure evolves.
Following Murray and White (1983), the cost elasticity is computed as follows:
$$ \eta = \sum\limits_i^n {\frac{{\partial \ln C}}{{\partial \ln {y_i}}} = \sum\nolimits_i^n {{\alpha_i} + \sum\nolimits_i^n {\sum\nolimits_k^n {{\sigma_{ik}}\ln {y_k}} + } } } \sum\nolimits_i^n {\sum\nolimits_j^m {{\delta_{ij}}\ln {p_j}} } $$If η > 1, the banks experience decreasing returns to scale as costs rise proportionately more than output.
An η = 1 indicates constant returns to scale and η < 1 indicates increasing returns to scale.
Panzar and Willig (1977) have shown that a multiproduct cost function exhibits economies of scope if \( \frac{{{\partial^2}C}}{{\partial {y_i}\partial {y_k}}} < 0 \). The approximate test for this condition is given by \( {\alpha_i}{\alpha_k} + {\sigma_{ik}} < 0 \).
References
Aigner D, Knox-Lovell CA, Schmidt P (1977) Formulation and estimation of stochastic frontier production function models. J Econom 6:21–37
Berger AN (1993) “Distribution-free” estimates of efficiency in the U.S. banking industry and tests of the standard distributional assumptions. J Prod Anal 4:261–292
Berger AN, DeYoung R (1997) Problem loans and cost efficiency in commercial banks. J Bank Financ 849–870
Berger AN, Mester LJ (1997) Inside the black box: what explains differences in the efficiencies of financial institutions? J Bank Finance 21:895–947
Boyd JH, De Nicolo G (2005) The theory of bank risk taking and competition revisited. J Finance LX 1329–1343
Caudill SB, Ford JM (1993) Biases in frontier estimation due to heteroskedasticity. Econ Lett 41:17–20
Caudill SB, Ford JM, Gropper DM (1995) Frontier estimation and firm-specific inefficiency measures in the presence of heteroskedasticity. J Bus Econ Stat 13:105–111
Christopoulos DK, Tsionas EG (2001) Banking economic efficiency in the deregulation period: results from heteroskedastic stochastic frontier models. Manch Sch 69:1463–6786
Clark J (1988) Economies of scale and scope at depository financial institutions: a review of the literature, in federal reserve bank of Kansas City (ed) Economic Review
Ferrier GD, Lovell CAK (1990) Measuring cost efficiency in banking: econometric and linear programming evidence. J Econom 46:229–245
Golan A, Judge G, Miller D (1996) Maximum entropy econometrics: robust estimation with limited information. Wiley
Golan A, Moretti E, Perloff J (2000) A small-sample estimation of the sample-selection model. American University
Hadri K (1999) Esimation of a doubly heteroskedastic stochastic frontier cost function. J Bus Econ Stat 359–363
Horrace WC, Schmidt P (1996) Confidence statements for efficiency estimates from stochastic frontier models. J Prod Anal 7:257–282
Hughes JP, Mester LJ (1993) A quality and risk-adjusted cost function for banks: evidence on the “too-big-to-fail” doctrine. J Prod Anal 4:293–315
Jensen U (2000) Is it efficient to analyse efficiency rankings? Empirical Econ 25:189–208
Kumbhakar SC, Knox-Lovell CA (2000) Stochastic frontier analysis. Cambridge University Press
Mester LJ (1987) A multiproduct cost study of savings and loans. J Finance 42:423–445
Mester LJ (1997) Measuring efficiency at U.S. banks: accounting for heterogeneity is important. Eur J Oper Res 98:230–242
Miller D (2002) Entropy-based methods of modeling stochastic production efficiency. Am J Agric Econ 84:1264–1270
Miller D (2007) An information theoretic approach to flexible stochastic frontier models. University of Missouri
Murray JD, White RW (1983) Economies of scale and economies of scope in multiproduct financial institutions: a study of british columbia credit unions. J Finance 38:887–902
Oude Lansink A, Silva E, Stefanou S (2001) Inter-firm and intra-firm efficiency measures. J Prod Anal 15:185–199
Panzar JC, Willig RD (1977) Economies of scale in multi-output production. Q J Econ 481–493
Ray SC (2007) Are some Indian banks too large? An examination of size efficiency in Indian banking. J Prod Anal 27:41–56
Reifschneider D, Stevenson R (1991) Systematic departures from the frontier: a framework for the analysis of firm inefficiency. Int Econ Rev 32:715–723
Ritter C, Simar L (1997) Pitfalls of normal-gamma stochastic frontier. J Prod Anal 8:167–182
Schmidt P (1986) Frontier production functions. Econom Rev 4:289–328
Sengupta J (1992) The maximum entropy approach in production frontier estimation. Math Soc Sci 25:41–57
Spong K, Sullivan RJ, DeYoung R (1995) What makes a bank efficient?—a look at financial characteristics and bank management and ownership structure. Financ Ind Perspect 1–19
Street A (2003) How much confidence should we place in efficiency estimates? Health Econ 12:895–907
Swamy PAVB, Tavlas GS, Lutton TJ (2003) An analysis of differences in earnings between small and large commercial banks. J Prod Anal 20:97–114
Valverde SC, Humphrey DB, Lopez del Paso R (2007) Opening the black box: finding the source of cost inefficiency. J Prod Anal 27:209–220
Wang H-J (2002) Heteroskedasticity and non-monotonic efficiency effects of a stochastic frontier model. J Prod Anal 18:241–253
Yuengert AW (1993) The measurement of efficiency in life insurance: estimates of a mixed normal-gamma error model. J Bank Finance 17:483–496
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Balasubramanyan, L., Stefanou, S.E. & Stokes, J.R. An entropy approach to size and variance heterogeneity in U.S. commercial banks. J Econ Finan 36, 728–749 (2012). https://doi.org/10.1007/s12197-010-9148-5
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DOI: https://doi.org/10.1007/s12197-010-9148-5