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Recovering Technologies that Account for Generalized Managerial Preferences: An Application to Non-Risk-Neutral Banks

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Author Info
Joseph P. Hughes
William Lang
Loretta J. Mester
Choon-Geol Moon

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Abstract

The authors suggest that risk plays an important role in managerial production decisions. Managers make implicit and explicit decisions related to risk, return, and cost in setting target market, product, pricing and delivery decisions. Standard models of production and cost do not explicitly account for risk, assuming that managers are neutral toward risk. This simplification may undermine the model's usefulness when applied to an industry such as banking where risk plays an important economic role in the business. The standard model would label risk-averse banks at best, allocatively inefficient and at worst, technically inefficient.

The authors attempt to maximize a managerial utility function, defined over profit, inputs, and outputs with respect to the mix of inputs and with respect to profit subject to the production constraint that the input mix must produce the given output vector. The solution to this utility maximization problem gives the manager's most preferred production plan. To the extent that managers have favored inputs whose employment they will increase at the expense of profit, the most preferred production plan will not be allocatively efficient. In fact, it may not even be technically efficient.

The cost function that follows from the utility-maximizing production plan is sufficiently general to incorporate non-neutrality toward risk and to allow other managerial objectives in addition to profit maximization.

Formulating the production plan from a model of constrained utility maximization suggests that the functional forms needed to implement the model can be derived by analogy to those of consumer theory. The Almost Ideal (AI) Demand System, adapted to accommodate generalized managerial preferences, yields input share equations and a profit (cost) function that, in the case of cost minimization, are identical to the translog cost function and input share equations.

The model is estimated using 1989 and 1990 data from U.S. banks whose assets equal or exceed $1 billion. The AI System fits the data well; risk neutrality is conclusively rejected. The measure of scale economies obtained from the most preferred cost function is considerably larger than those obtained from more conventional cost functions, and it increases with bank asset size, suggesting that the diversification economies enjoyed by larger banks allow them to reduce the share of resources used to control risk which magnifies the diversification economies. When risk neutrality is imposed and financial capital is deleted from the model, the measure of scale elasticity drops considerably and resembles the magnitudes generally found in studies that employ the standard framework. Thus, this evidence provides some explanation of the seeming inconsistency between the actual merger wave that has been occurring and the standard literature that finds little motivation from cost savings.

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Publisher Info
Paper provided by Wharton School Center for Financial Institutions, University of Pennsylvania in its series Center for Financial Institutions Working Papers with number 95-16.

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Date of creation: Apr 1995
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Handle: RePEc:wop:pennin:95-16

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  1. Subal C. Kumbhakar & Ana Lozano-Vivas & C. A. Knox Lovell & Iftekhar Hasan, 1999. "The Effects of Deregulation on the Performance of Financial Institutions: The Case of Spanish Savings Banks," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-064, New York University, Leonard N. Stern School of Business-. [Downloadable!]
    Other versions:
  2. Steven Ongena, 1999. "Lending Relationships, Bank Default and Economic Activity," International Journal of the Economics of Business, Taylor and Francis Journals, vol. 6(2), pages 257-280, July. [Downloadable!] (restricted)
  3. Christopher Marshall & Michael Siegel, 1996. "Value at Risk: Implementing a Risk Measurement Standard," Center for Financial Institutions Working Papers 96-47, Wharton School Center for Financial Institutions, University of Pennsylvania. [Downloadable!]
  4. Joseph P. Hughes & Loretta J. Mester & Choon-Geol Moon, 2000. "Are Scale Economies in Banking Elusive or Illusive?," Departmental Working Papers 200004, Rutgers University, Department of Economics. [Downloadable!]
  5. Subal C. Kumbhakar & Ana Lozano-Vivas, 2004. "Does deregulation make markets more competitive? Evidence of mark-ups in Spanish savings banks," Applied Financial Economics, Taylor and Francis Journals, vol. 14(7), pages 507-515, April. [Downloadable!] (restricted)
  6. Joseph P. Hughes & William W. Lang & Loretta J. Mester & Choon-Geol Moon, 2000. "Recovering risky technologies using the almost ideal demand system: an application to U.S. banking," Working Papers 00-5, Federal Reserve Bank of Philadelphia. [Downloadable!]
    Other versions:
  7. Allen N. Berger & Loretta J. Mester, 1997. "Inside the black box: what explains differences in the efficiencies of financial institutions?," Working Papers 97-1, Federal Reserve Bank of Philadelphia. [Downloadable!]
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  8. Joseph P. Hughes & Loretta J. Mester & Choon-Geol Moon, 2000. "Are scale economies in banking elusive or illusive? Evidence obtained by incorporating capital structure and risk-taking into models of bank production," Working Papers 00-4, Federal Reserve Bank of Philadelphia. [Downloadable!]
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  9. John S. Jordan, 1998. "Problem loans at New England banks, 1989 to 1992: evidence of aggressive loan policies," New England Economic Review, Federal Reserve Bank of Boston, issue Jan, pages 23-38. [Downloadable!]
  10. Joseph P. Hughes & Choon-Geol Moon & Robert DeYoung, 2000. "Efficient Risk-Taking and Regulatory Covenant Enforcement in a Deregulated Banking Industry," Departmental Working Papers 200007, Rutgers University, Department of Economics. [Downloadable!]
  11. Joseph P. Hughes & Loretta J. Mester & Choon-Geol Moon, 2000. "Are All Scale Economies in Banking Elusive or Illusive: Evidence Obtained by Incorporating Capital Structure and Risk Taking into Models of Bank Production," Center for Financial Institutions Working Papers 00-33, Wharton School Center for Financial Institutions, University of Pennsylvania. [Downloadable!]
  12. Joseph P. Hughes & William Lang & Loretta J. Mester & Choon-Geol Moon, 1998. "The Dollars and Sense of Bank Consolidation," Center for Financial Institutions Working Papers 99-04, Wharton School Center for Financial Institutions, University of Pennsylvania. [Downloadable!]
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  13. Subal C. Kumbhakar & Ana Lozano-Vivas, 2004. "Deregulation and Productivity: The Case of Spanish Banks," Economic Working Papers at Centro de Estudios Andaluces E2004/24, Centro de Estudios Andaluces. [Downloadable!]
    Other versions:
  14. Joseph P. Hughes & William W. Lang & Loretta J. Mester & Choon-Geol Moon, 1996. "Safety in numbers? Geographic diversification and bank insolvency risk," Working Papers 96-14, Federal Reserve Bank of Philadelphia. [Downloadable!]
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  15. Loretta J. Mester, 1996. "Measuring efficiency at U.S. banks: accounting for heterogeneity is important," Working Papers 96-11/R, Federal Reserve Bank of Philadelphia. [Downloadable!]
    Other versions:
  16. Joseph P. Hughes, 1998. "Measuring efficiency when market prices are subject to adverse selection," Working Papers 98-3, Federal Reserve Bank of Philadelphia. [Downloadable!]
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