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Measuring dynamic efficiency under uncertainty

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  • Huettel, Silke
  • Narayana, Rashmi
  • Odening, Martin

Abstract

In this paper we develop a theoretical model that links dynamic efficiency measurement and optimal investment under uncertainty. It is widely acknowledged that uncertainty has an impact on the optimal factor use of a profit maximizing firm. This is particularly true for the optimal adjustment of the firm’s capital stock. While uncertainty has been considered in the static efficiency measurement literature it has been ignored so far in the context of dynamic efficiency measurement. This paper targets at closing this gap. For that purpose we take up a dynamic efficiency model which embeds a stochastic intertemporal duality model into a shadow cost framework and allows for measuring technical and allocative inefficiency. We derive hypotheses on how uncertainty affects the measurement of efficiency. The factor demand equations, which we derive, may serve as a starting point for an empirical validation of these hypotheses.

Suggested Citation

  • Huettel, Silke & Narayana, Rashmi & Odening, Martin, 2011. "Measuring dynamic efficiency under uncertainty," Structural Change in Agriculture/Strukturwandel im Agrarsektor (SiAg) Working Papers 129062, Humboldt University Berlin, Department of Agricultural Economics.
  • Handle: RePEc:ags:huscpw:129062
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    File URL: http://purl.umn.edu/129062
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    References listed on IDEAS

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    1. Kyösti S. Pietola & Robert J. Myers, 2000. "Investment under Uncertainty and Dynamic Adjustment in the Finnish Pork Industry," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 82(4), pages 956-967.
    2. Christopher O’Donnell & Robert Chambers & John Quiggin, 2010. "Efficiency analysis in the presence of uncertainty," Journal of Productivity Analysis, Springer, vol. 33(1), pages 1-17, February.
    3. C. J. O'Donnell & W. E. Griffiths, 2006. "Estimating State-Contingent Production Frontiers," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 88(1), pages 249-266.
    4. Abel, Andrew B & Eberly, Janice C, 1994. "A Unified Model of Investment under Uncertainty," American Economic Review, American Economic Association, vol. 84(5), pages 1369-1384, December.
    5. Lau, Lawrence J & Yotopoulos, Pan A, 1971. "A Test for Relative Efficiency and Application to Indian Agriculture," American Economic Review, American Economic Association, vol. 61(1), pages 94-109, March.
    6. Atkinson, Scott E & Cornwell, Christopher, 1994. "Parametric Estimation of Technical and Allocative Inefficiency with Panel Data," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(1), pages 231-243, February.
    7. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
    8. Hung-Jen Wang, 2002. "Heteroscedasticity and Non-Monotonic Efficiency Effects of a Stochastic Frontier Model," Journal of Productivity Analysis, Springer, vol. 18(3), pages 241-253, November.
    9. Nauges, Celine & O'Donnell, Christopher J. & Quiggin, John C., 2009. "Uncertainty and technical efficiency in Finnish Agriculture," 2009 Conference (53rd), February 11-13, 2009, Cairns, Australia 48062, Australian Agricultural and Resource Economics Society.
    10. Rungsuriyawiboon, Supawat & Stefanou, Spiro E., 2007. "Dynamic Efficiency Estimation: An Application to U.S. Electric Utilities," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 226-238, April.
    11. Elvira Silva & Spiro Stefanou, 2003. "Nonparametric Dynamic Production Analysis and the Theory of Cost," Journal of Productivity Analysis, Springer, vol. 19(1), pages 5-32, January.
    12. Demsetz, Harold, 1973. "Industry Structure, Market Rivalry, and Public Policy," Journal of Law and Economics, University of Chicago Press, vol. 16(1), pages 1-9, April.
    13. Robert G. Chambers & John Quiggin, 2002. "The State-Contingent Properties of Stochastic Production Functions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(2), pages 513-526.
    14. Caudill, Steven B. & Ford, Jon M., 1993. "Biases in frontier estimation due to heteroscedasticity," Economics Letters, Elsevier, vol. 41(1), pages 17-20.
    15. Subal C. Kumbhakar, 2002. "Specification and Estimation of Production Risk, Risk Preferences and Technical Efficiency," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(1), pages 8-22.
    16. Sandri, Serena & Schade, Christian & Mußhoff, Oliver & Odening, Martin, 2010. "Holding on for too long? An experimental study on inertia in entrepreneurs' and non-entrepreneurs' disinvestment choices," Journal of Economic Behavior & Organization, Elsevier, vol. 76(1), pages 30-44, October.
    17. Kumbhakar, Sabul C., 1993. "Production risk, technical efficiency, and panel data," Economics Letters, Elsevier, vol. 41(1), pages 11-16.
    18. Pietola, Kyosti & Myers, Robert J., 1998. "Investment Under Uncertainty And Dynamic Adjustment In Finnish Pork Industry," 1998 Annual meeting, August 2-5, Salt Lake City, UT 20953, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    19. Bernhard Brümmer & Thomas Glauben & Geert Thijssen, 2002. "Decomposition of Productivity Growth Using Distance Functions: The Case of Dairy Farms in Three European Countries," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(3), pages 628-644.
    20. Nemoto, Jiro & Goto, Mika, 1999. "Dynamic data envelopment analysis: modeling intertemporal behavior of a firm in the presence of productive inefficiencies," Economics Letters, Elsevier, vol. 64(1), pages 51-56, July.
    21. G. Battese & A. Rambaldi & G. Wan, 1997. "A Stochastic Frontier Production Function with Flexible Risk Properties," Journal of Productivity Analysis, Springer, vol. 8(3), pages 269-280, August.
    22. Elvira Silva & Spiro E. Stefanou, 2007. "Dynamic Efficiency Measurement: Theory and Application," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(2), pages 398-419.
    23. Ellen Goddard & Alfons Weersink & Kevin Chen & Calum G. Turvey, 1993. "Economics of Structural Change in Agriculture," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 41(4), pages 475-489, December.
    24. Epstein, Larry G & Denny, Michael G S, 1983. "The Multivariate Flexible Accelerator Model: Its Empirical Restrictions and an Application to U.S. Manufacturing," Econometrica, Econometric Society, vol. 51(3), pages 647-674, May.
    25. Stefanou, Spiro E., 1989. "Learning, experience, and firm size," Journal of Economics and Business, Elsevier, vol. 41(4), pages 283-296, November.
    26. Jan Hinrichs & Oliver Musshoff & Martin Odening, 2008. "Economic hysteresis in hog production," Applied Economics, Taylor & Francis Journals, vol. 40(3), pages 333-340.
    27. Roberto Mosheim & C.A. Knox Lovell, 2007. "Scale Economies and Inefficiency of U.S. Dairy Farms," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(3), pages 777-794.
    28. Daniel S. Hamermesh & Gerard A. Pfann, 1996. "Adjustment Costs in Factor Demand," Journal of Economic Literature, American Economic Association, vol. 34(3), pages 1264-1292, September.
    29. OW Maietta, 2000. "The decomposition of cost inefficiency into technical and allocative components with panel data of Italian dairy farms," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 27(4), pages 473-495, December.
    30. Chambers, Christopher P. & Miller, Alan D., "undated". "Inefficiency," Working Papers WP2011/14, University of Haifa, Department of Economics, revised 30 Nov 2011.
    31. Kumbhakar,Subal C. & Lovell,C. A. Knox, 2003. "Stochastic Frontier Analysis," Cambridge Books, Cambridge University Press, number 9780521666633, April.
    32. Silke Hüttel & Oliver Mußhoff & Martin Odening, 2010. "Investment reluctance: irreversibility or imperfect capital markets?," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 37(1), pages 51-76, March.
    33. Jean-Paul Chavas, 2008. "A Cost Approach to Economic Analysis Under State-Contingent Production Uncertainty," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(2), pages 435-466.
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    Citations

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    Cited by:

    1. Pieralli, Simone & Hüttel, Silke & Odening, Martin, 2013. "A model of firm exit under inefficiency and uncertainty," Structural Change in Agriculture/Strukturwandel im Agrarsektor (SiAg) Working Papers 155700, Humboldt University Berlin, Department of Agricultural Economics.
    2. Supawat Rungsuriyawiboon & Heinrich Hockmann, 2015. "Adjustment costs and efficiency in Polish agriculture: a dynamic efficiency approach," Journal of Productivity Analysis, Springer, vol. 44(1), pages 51-68, August.
    3. Wagner, Christina & Huttel, Silke & Odening, Martin, 2012. "Dynamic Efficiency Under Uncertainty: An Application To German Dairy Farms," 52nd Annual Conference, Stuttgart, Germany, September 26-28, 2012 133826, German Association of Agricultural Economists (GEWISOLA).

    More about this item

    Keywords

    efficiency; shadow cost approach; dynamic duality; uncertainty; Agribusiness; Agricultural and Food Policy; Agricultural Finance; Crop Production/Industries; Demand and Price Analysis; Farm Management; D61; D81; Q12;

    JEL classification:

    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets

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