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Recovering Technologies That Account for Generalized Managerial Preferences: An Application to Non-Risks-Neutral Banks

Author

Listed:
  • Joseph P. Hughes

    () (Rutgers University)

  • William Lang

    () (Office of the Comptroller of the Currency)

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 eq
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Joseph P. Hughes & William Lang, 1997. "Recovering Technologies That Account for Generalized Managerial Preferences: An Application to Non-Risks-Neutral Banks," Departmental Working Papers 199521, Rutgers University, Department of Economics.
  • Handle: RePEc:rut:rutres:199521
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    Cited by:

    1. 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.
    2. Berger, Allen N. & Mester, Loretta J., 1997. "Inside the black box: What explains differences in the efficiencies of financial institutions?," Journal of Banking & Finance, Elsevier, vol. 21(7), pages 895-947, July.
    3. Hughes, Joseph P. & Mester, Loretta J. & Moon, Choon-Geol, 2001. "Are scale economies in banking elusive or illusive?: Evidence obtained by incorporating capital structure and risk-taking into models of bank production," Journal of Banking & Finance, Elsevier, vol. 25(12), pages 2169-2208, December.
    4. Joseph Hughes & William Lang & Loretta Mester & Choon-Geol Moon, 2000. "Recovering Risky Technologies Using the Almost Ideal Demand System: An Application to U.S. Banking," Journal of Financial Services Research, Springer;Western Finance Association, vol. 18(1), pages 5-27, October.
    5. Kumbhakar, Subal C, et al, 2001. "The Effects of Deregulation on the Performance of Financial Institutions: The Case of Spanish Savings Banks," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 33(1), pages 101-120, February.
    6. Joseph P. Hughes & William W. Lang & Loretta J. Mester & Choon-Geol Moon, 1996. "Safety in numbers? Geographic diversification and bank insolvency risk," Proceedings 504, Federal Reserve Bank of Chicago.
    7. Subal kumbhakar & Ana Lozano-Vivas, 2005. "Deregulation and Productivity: The Case of Spanish Banks," Journal of Regulatory Economics, Springer, vol. 27(3), pages 331-351, January.
    8. Hughes, Joseph P. & Lang, William W. & Mester, Loretta J. & Moon, Choon-Geol, 1999. "The dollars and sense of bank consolidation," Journal of Banking & Finance, Elsevier, vol. 23(2-4), pages 291-324, February.
    9. Joseph P. Hughes, 1998. "Measuring efficiency when market prices are subject to adverse selection," Working Papers 98-3, Federal Reserve Bank of Philadelphia.
    10. Mester, Loretta J., 1997. "Measuring efficiency at U.S. banks: Accounting for heterogeneity is important," European Journal of Operational Research, Elsevier, vol. 98(2), pages 230-242, April.
    11. 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.
    12. Steven Ongena, 1999. "Lending Relationships, Bank Default and Economic Activity," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 6(2), pages 257-280.
    13. Subal Kumbhakar & Ana Lozano-Vivas, 2004. "Does deregulation make markets more competitive? Evidence of mark-ups in Spanish savings banks," Applied Financial Economics, Taylor & Francis Journals, vol. 14(7), pages 507-515.
    14. DeYoung, Robert E. & Hughes, Joseph P. & Moon, Choon-Geol, 2001. "Efficient risk-taking and regulatory covenant enforcement in a deregulated banking industry," Journal of Economics and Business, Elsevier, vol. 53(2-3), pages 255-282.
    15. Buch, Claudia M., 1995. "The emerging financial systems of the Eastern European economics: A progress report," Kiel Working Papers 716, Kiel Institute for the World Economy (IfW).
    16. 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.
    17. Simon Kwan & Robert A. Eisenbeis, 1995. "Bank Risk, Capitalization and Inefficiency," Center for Financial Institutions Working Papers 96-35, Wharton School Center for Financial Institutions, University of Pennsylvania.
    18. Manlagñit, Maria Chelo V., 2011. "Cost efficiency, determinants, and risk preferences in banking: A case of stochastic frontier analysis in the Philippines," Journal of Asian Economics, Elsevier, vol. 22(1), pages 23-35, February.
    19. Li-Gang Liu & Changchun Hua, 2010. "Risk-return Efficiency, Financial Distress Risk, and Bank Financial Strength Ratings," Working Papers id:2944, eSocialSciences.
    20. Changchun Hua & Li-Gang Liu, 2010. "Risk-return Efficiency, Financial Distress Risk, and Bank Financial Strength Ratings," Finance Working Papers 22756, East Asian Bureau of Economic Research.
    21. 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.

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