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Farmer behavior under risk of failure

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  • Foster, Williams E.
  • Rausser, Gordon C.

Abstract

We analyze input decisions under risk of farm failure. Inputs with immediate cash outlays have greater effective than observed prices because their cost increases the probability of failure, and their optimal marginal products are higher than observed prices would warrant under strict profit maximizing without failure risk. An algebraic example illustrates the market equilibrium effects of failure risk. We apply the model to an analysis of Illinois corn production (1971–79). Results indicate that larger farms deviate less than smaller farms from strict profit maximization. Over the period studied, farmers moved further from setting marginal products equal to observed prices.
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Suggested Citation

  • Foster, Williams E. & Rausser, Gordon C., 1990. "Farmer behavior under risk of failure," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt5kk2g186, Department of Agricultural & Resource Economics, UC Berkeley.
  • Handle: RePEc:cdl:agrebk:qt5kk2g186
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    Cited by:

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    2. Josep M. Argilés, 1998. "Accounting information and the prediction of farm viability," Economics Working Papers 277, Department of Economics and Business, Universitat Pompeu Fabra.
    3. Elizaphan J. O. Rao & Bernhard Brümmer & Matin Qaim, 2012. "Farmer Participation in Supermarket Channels, Production Technology, and Efficiency: The Case of Vegetables in Kenya," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 94(4), pages 891-912.
    4. MacNicol, R. & Ortmann, Gerald F. & Ferrer, Stuart R.D., 2008. "Management decisions on commercial sugarcane farms in KwaZulu-Natal: a focus on choice bracketing behaviour for risk management," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 47(1), pages 1-24, March.
    5. Gordon C. Rausser & Harry de Gorter, 2013. "US Policy Contributions to Agricultural Commodity Price Fluctuations, 2006-12," WIDER Working Paper Series wp-2013-033, World Institute for Development Economic Research (UNU-WIDER).
    6. Olivier Mahul, 1996. "Décision d'investissement d'un agriculteur neutre au risque en présence d'une contrainte financière," Post-Print hal-02841740, HAL.
    7. Gordon C. Rausser, 1992. "Predatory versus Productive Government: The Case of U.S. Agricultural Policies," Journal of Economic Perspectives, American Economic Association, vol. 6(3), pages 133-157, Summer.
    8. Narayanan, Sudha, 2014. "Profits from participation in high value agriculture: Evidence of heterogeneous benefits in contract farming schemes in Southern India," Food Policy, Elsevier, vol. 44(C), pages 142-157.
    9. Li, Runwei & Wei, Chenyang & Afroz, Mahnaz Dil & Lyu, Jun & Chen, Gang, 2021. "A GIS-based framework for local agricultural decision-making and regional crop yield simulation," Agricultural Systems, Elsevier, vol. 193(C).
    10. Unknown, 1998. "References/Literature Cited," Commodity Costs and Returns Estimation Handbook,, Iowa State University.
    11. Basurto Hernandez, Saul & Maddison, David & Banerjee, Anindya, 2018. "The effect of PROCAMPO on farms’ technical efficiency: A Stochastic Frontier Analysis," 2018 Annual Meeting, August 5-7, Washington, D.C. 274376, Agricultural and Applied Economics Association.
    12. Atwood, Joseph A. & Buschena, David E., 2003. "Evaluating the magnitudes of financial transactions costs on risk behavior," Agricultural Systems, Elsevier, vol. 75(2-3), pages 235-249.

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