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Farmer Behavior under Risk of Failure

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  • William E. Foster
  • Gordon C. Rausser

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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  • William E. Foster & Gordon C. Rausser, 1991. "Farmer Behavior under Risk of Failure," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 73(2), pages 276-288.
    • Handle: RePEc:oup:ajagec:v:73:y:1991:i:2:p:276-288.
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    2. 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.
    3. McDonald, Roberta & Karina, Pierce & Reamonn, Fealy & Horan, Brendan, 2013. "Characteristics, intentions and expectations of new entrant dairy farmers entering the Irish dairy industry through the New Entrant Scheme," International Journal of Agricultural Management, Institute of Agricultural Management, vol. 2(4), pages 1-12, July.
    4. Josep M. Argilés, 1998. "Accounting information and the prediction of farm viability," Economics Working Papers 277, Department of Economics and Business, Universitat Pompeu Fabra.
    5. 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.
    6. 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).
    7. Rausser, Gordon C., 1991. "Predatory versus productive government: the case of U.S. agricultural policies," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt21913950, Department of Agricultural & Resource Economics, UC Berkeley.
    8. 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).
    9. 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.
    10. 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.
    11. Unknown, 1998. "References/Literature Cited," Commodity Costs and Returns Estimation Handbook,, Iowa State University.
    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.
    13. Olivier Mahul, 1996. "Décision d'investissement d'un agriculteur neutre au risque en présence d'une contrainte financière," Post-Print hal-02841740, HAL.

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