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Measures of Effectiveness for Governmental Organizations

Author

Listed:
  • Kishore Gawande

    (Department of Economics, University of New Mexico, Albuquerque, New Mexico 87131)

  • Timothy Wheeler

    (Environmental Risk Assessment and Regulatory Analysis Department, Sandia National Laboratories, Albuquerque, New Mexico 87185)

Abstract

For organizations whose objective is not necessarily the maximization of a financial quantity, there is little written in the economics and management literature about methods that quantify their effectiveness. Potential users of such methodologies are typically governmental organizations and agencies to whom Congress allocates funding periodically, but may also include many nonprofit organizations. Such research is importantly needed because government is no longer making outlay allocations on a merely historical basis, but is using as a criterion how effectively an organization uses its resources in meeting its objectives. In this paper we analyze the Maritime Safety Program of the U.S. Coast Guard (USCG), which is responsible for monitoring the quality of vessels that sail in U.S. waters, and present measures of effectiveness (MOEs) for the Program. We do this at two levels of activity: at an overall program level (Level I) and at a component activity level (Level II). Poisson models are used to construct the MOEs using data on maritime casualties (accidents) between 1990--1993 from the real-time Marine Safety Management System (MSMS) database maintained by the Coast Guard. A feature of the empirical methodology is the Bayesian imputation of missing data. The MOEs constructed here have at least four important uses. First, as the name suggests, they perform the function that financial quantities such as returns on equity or returns on sales perform for private-sector organizations---that is, they are indicators of efficiency. Second, they can be used as inputs into allocative decisions within the organization. For example, the Level II MOEs can be used as inputs into a programming problem that determines the optimal allocation of resources among component activities. Third, internal performance evaluation across USCG Programs or across Port Units (called Marine Safety Offices) can be based on their respective Level I MOEs. Fourth, and possibly the most important long-run consideration, MOEs provide the basis for better regulation by the government. Without MOEs the nature of regulation is probably suboptimal. By adopting these MOEs as criteria, it will be easier for the government to redesign those aspects of its regulation of the Coast Guard which curtail incentives.

Suggested Citation

  • Kishore Gawande & Timothy Wheeler, 1999. "Measures of Effectiveness for Governmental Organizations," Management Science, INFORMS, vol. 45(1), pages 42-58, January.
  • Handle: RePEc:inm:ormnsc:v:45:y:1999:i:1:p:42-58
    DOI: 10.1287/mnsc.45.1.42
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    File URL: http://dx.doi.org/10.1287/mnsc.45.1.42
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    References listed on IDEAS

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    1. Cohen, Mark A, 1987. "Optimal Enforcement Strategy to Prevent Oil Spills: An Application of a Principal-Agent Model with Moral Hazard," Journal of Law and Economics, University of Chicago Press, vol. 30(1), pages 23-51, April.
    2. Laffont, Jean-Jacques, 1995. "Regulation, moral hazard and insurance of environmental risks," Journal of Public Economics, Elsevier, vol. 58(3), pages 319-336, November.
    3. Laffont, Jean-Jacques, 1994. "The New Economics of Regulation Ten Years After," Econometrica, Econometric Society, vol. 62(3), pages 507-537, May.
    4. John E. Brandl, 1989. "How organization counts: Incentives and inspiration," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 8(3), pages 489-494.
    5. John M. Quigley & Suzanne Scotchmer, 1989. "What counts? analysis counts," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 8(3), pages 483-489.
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    Citations

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    Cited by:

    1. Singer, Marcos & Donoso, Patricio & Poblete, Francisco, 2002. "Semi-autonomous planning using linear programming in the Chilean General Treasury," European Journal of Operational Research, Elsevier, vol. 140(2), pages 517-529, July.
    2. Lucija Muehlenbachs & Stefan Staubli & Mark A. Cohen, 2016. "The Impact of Team Inspections on Enforcement and Deterrence," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 3(1), pages 159-204.
    3. Muehlenbachs, Lucija & Staubli, Stefan & Cohen, Mark A., 2013. "The Effect of Inspector Group Size and Familiarity on Enforcement and Deterrence," IZA Discussion Papers 7876, Institute of Labor Economics (IZA).
    4. Garrett, Richard A. & Sharkey, Thomas C. & Grabowski, Martha & Wallace, William A., 2017. "Dynamic resource allocation to support oil spill response planning for energy exploration in the Arctic," European Journal of Operational Research, Elsevier, vol. 257(1), pages 272-286.
    5. maurice moffett & alok k. bohara & kishore gawande, 2005. "Governance and Performance: Theory-Based Evidence from US Coast Guard Inspections," Public Economics 0505002, University Library of Munich, Germany.

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