Skip to main content
Log in

An entropy approach to size and variance heterogeneity in U.S. commercial banks

  • Published:
Journal of Economics and Finance Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

Notes

  1. 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.

  2. 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.

  3. For a detailed discussion on the different hypotheses, refer to Berger and DeYoung (1997).

  4. This is consistent with Hughes and Mester (1993).

  5. Refer to Boyd and De Nicolo (2005) for a thorough explanation on how a given market structure evolves.

  6. 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.

  7. 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Christopoulos DK, Tsionas EG (2001) Banking economic efficiency in the deregulation period: results from heteroskedastic stochastic frontier models. Manch Sch 69:1463–6786

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Jensen U (2000) Is it efficient to analyse efficiency rankings? Empirical Econ 25:189–208

    Article  Google Scholar 

  • 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

    Google Scholar 

  • Mester LJ (1997) Measuring efficiency at U.S. banks: accounting for heterogeneity is important. Eur J Oper Res 98:230–242

    Article  Google Scholar 

  • Miller D (2002) Entropy-based methods of modeling stochastic production efficiency. Am J Agric Econ 84:1264–1270

    Article  Google Scholar 

  • 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

    Google Scholar 

  • Oude Lansink A, Silva E, Stefanou S (2001) Inter-firm and intra-firm efficiency measures. J Prod Anal 15:185–199

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Reifschneider D, Stevenson R (1991) Systematic departures from the frontier: a framework for the analysis of firm inefficiency. Int Econ Rev 32:715–723

    Article  Google Scholar 

  • Ritter C, Simar L (1997) Pitfalls of normal-gamma stochastic frontier. J Prod Anal 8:167–182

    Article  Google Scholar 

  • Schmidt P (1986) Frontier production functions. Econom Rev 4:289–328

    Article  Google Scholar 

  • Sengupta J (1992) The maximum entropy approach in production frontier estimation. Math Soc Sci 25:41–57

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Wang H-J (2002) Heteroskedasticity and non-monotonic efficiency effects of a stochastic frontier model. J Prod Anal 18:241–253

    Article  Google Scholar 

  • Yuengert AW (1993) The measurement of efficiency in life insurance: estimates of a mixed normal-gamma error model. J Bank Finance 17:483–496

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Lakshmi Balasubramanyan.

Rights and permissions

Reprints and permissions

About this article

Cite this article

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

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12197-010-9148-5

Keywords

JEL Classification

Navigation