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Comparing the Use of Risk influencing Production Inputs and Experimentally Measured Risk Attitude: Do the Decisions of Indonesian Small scale Rubber Farmers Match?

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  • Moser, Stefan
  • Mußhoff, Oliver

Abstract

This article compares the use of risk-increasing and risk-reducing production inputs with the experimentally measured risk attitudes of farmers. For this purpose, a Just-Pope production function indicates production inputs’ influence on output risk, and a Holt-Laury lottery is used to measure farmers’ risk attitudes. We then test whether more risk averse farmers use more risk-reducing and less risk-increasing production inputs. To do so, a unique data set which includes 185 small-scale rubber farmers on the island of Sumatra, Indonesia, is used. The Just-Pope production function suggests that higher fertiliser usage has a risk-reducing effect, whereas higher herbicide usage has a risk-increasing effect. Comparing this with the outcome of a Holt-Laury lottery, we found that more risk averse farmers use more fertiliser (risk-reducing) and less herbicides (risk-increasing). The consistency of these results can be interpreted as reinforcing the external validity of measuring risk attitude with a Holt-Laury lottery.

Suggested Citation

  • Moser, Stefan & Mußhoff, Oliver, 2017. "Comparing the Use of Risk influencing Production Inputs and Experimentally Measured Risk Attitude: Do the Decisions of Indonesian Small scale Rubber Farmers Match?," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 66(2), June.
  • Handle: RePEc:ags:gjagec:303544
    DOI: 10.22004/ag.econ.303544
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    1. Subal C. Kumbhakar & Ragnar Tveterås, 2003. "Risk Preferences, Production Risk and Firm Heterogeneity," Scandinavian Journal of Economics, Wiley Blackwell, vol. 105(2), pages 275-293, June.
    2. Rulon D. Pope, 2003. "Agricultural Risk Analysis: Adequacy of Models, Data, and Issues," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(5), pages 1249-1256.
    3. Hans P. Binswanger, 1980. "Attitudes Toward Risk: Experimental Measurement in Rural India," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 62(3), pages 395-407.
    4. Jim Engle-Warnick & Javier Escobal & Sonia Laszlo, 2007. "Ambiguity Aversion as a Predictor of Technology Choice: Experimental Evidence from Peru," CIRANO Working Papers 2007s-01, CIRANO.
    5. Lisa Anderson & Jennifer Mellor, 2009. "Are risk preferences stable? Comparing an experimental measure with a validated survey-based measure," Journal of Risk and Uncertainty, Springer, vol. 39(2), pages 137-160, October.
    6. Ihli, Hanna Julia & Musshoff, Oliver, 2013. "Understanding the Investment Behavior of Ugandan Smallholder Farmers: An Experimental Analysis," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150331, Agricultural and Applied Economics Association.
    7. Subal C. Kumbhakar, 2002. "Risk preference and productivity measurement under output price uncertainty," Empirical Economics, Springer, vol. 27(3), pages 461-472.
    8. Z. Bar‐Shira & R.E. Just & D. Zilberman, 1997. "Estimation of farmers' risk attitude: an econometric approach," Agricultural Economics, International Association of Agricultural Economists, vol. 17(2-3), pages 211-222, December.
    9. Cornelis Gardebroek & María Daniela Chavez & Alfons Oude Lansink, 2010. "Analysing Production Technology and Risk in Organic and Conventional Dutch Arable Farming using Panel Data," Journal of Agricultural Economics, Wiley Blackwell, vol. 61(1), pages 60-75, February.
    10. Florin-Marius PAVELESCU, 2011. "Some aspects of the translog production function estimation," Romanian Journal of Economics, Institute of National Economy, vol. 32(1(41)), pages 131-150, June.
    11. Otsuka, Keijiro & Suyanto, S. & Sonobe, Tetsushi & Tomich, Thomas P., 2001. "Evolution of land tenure institutions and development of agroforestry: evidence from customary land areas of Sumatra," Agricultural Economics, Blackwell, vol. 25(1), pages 85-101, June.
    12. Sergio H. Lence, 2007. "Joint Estimation of Risk Preferences and Technology: Flexible Utility or Futility?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(3), pages 581-598.
    13. Just, Richard E. & Pope, Rulon D., 1978. "Stochastic specification of production functions and economic implications," Journal of Econometrics, Elsevier, vol. 7(1), pages 67-86, February.
    14. Key, Nigel D. & MacDonald, James M., 2006. "Agricultural Contracting Trading Autonomy for Risk Reduction," Amber Waves:The Economics of Food, Farming, Natural Resources, and Rural America, United States Department of Agriculture, Economic Research Service, pages 1-6, February.
    15. Richard E. Just & Rulon D. Pope, 1979. "Production Function Estimation and Related Risk Considerations," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 61(2), pages 276-284.
    16. Charles A. Holt & Susan K. Laury, 2002. "Risk Aversion and Incentive Effects," American Economic Review, American Economic Association, vol. 92(5), pages 1644-1655, December.
    17. Murat Isik & Madhu Khanna, 2003. "Stochastic Technology, Risk Preferences, and Adoption of Site-Specific Technologies," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(2), pages 305-317.
    18. 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.
    19. Anderson, Lisa R. & Mellor, Jennifer M., 2008. "Predicting health behaviors with an experimental measure of risk preference," Journal of Health Economics, Elsevier, vol. 27(5), pages 1260-1274, September.
    20. Christian Gollier, 2004. "The Economics of Risk and Time," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262572249, December.
    21. Brian E. Roe & David R. Just, 2009. "Internal and External Validity in Economics Research: Tradeoffs between Experiments, Field Experiments, Natural Experiments, and Field Data," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(5), pages 1266-1271.
    22. Chavas, Jean-Paul & Holt, Matthew T, 1996. "Economic Behavior under Uncertainty: A Joint Analysis of Risk Preferences and Technology," The Review of Economics and Statistics, MIT Press, vol. 78(2), pages 329-335, May.
    23. Masclet, David & Colombier, Nathalie & Denant-Boemont, Laurent & Lohéac, Youenn, 2009. "Group and individual risk preferences: A lottery-choice experiment with self-employed and salaried workers," Journal of Economic Behavior & Organization, Elsevier, vol. 70(3), pages 470-484, June.
    24. Ruth Vargas Hill, 2009. "Using Stated Preferences and Beliefs to Identify the Impact of Risk on Poor Households," Journal of Development Studies, Taylor & Francis Journals, vol. 45(2), pages 151-171.
    25. Christopher B. Barrett & Christine M. Moser & Oloro V. McHugh & Joeli Barison, 2004. "Better Technology, Better Plots, or Better Farmers? Identifying Changes in Productivity and Risk among Malagasy Rice Farmers," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(4), pages 869-888.
    26. Torben Tiedemann & Uwe Latacz-Lohmann, 2013. "Production Risk and Technical Efficiency in Organic and Conventional Agriculture – The Case of Arable Farms in Germany," Journal of Agricultural Economics, Wiley Blackwell, vol. 64(1), pages 73-96, February.
    27. Daniel Hellerstein & Nathaniel Higgins & John Horowitz, 2013. "The predictive power of risk preference measures for farming decisions -super-†," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 40(5), pages 807-833, December.
    28. Abdullahi Abdulkadri, 2003. "Estimating risk aversion coefficients for dry land wheat, irrigated corn and dairy producers in Kansas," Applied Economics, Taylor & Francis Journals, vol. 35(7), pages 825-834.
    29. Charness, Gary & Gneezy, Uri & Kuhn, Michael A., 2013. "Experimental methods: Extra-laboratory experiments-extending the reach of experimental economics," Journal of Economic Behavior & Organization, Elsevier, vol. 91(C), pages 93-100.
    30. Lence, Sergio H., 2009. "Ajae Appendix For “Joint Estimation Of Risk Preferences And Technology: Flexible Utility Or Futility?”," American Journal of Agricultural Economics APPENDICES, Agricultural and Applied Economics Association, vol. 91(3), pages 1-6, January.
    31. Jean-Paul Chavas & Robert G. Chambers & Rulon D. Pope, 2010. "Production Economics and Farm Management: a Century of Contributions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(2), pages 356-375.
    32. Richard E. Just, 2001. "Addressing the Changing Nature of Uncertainty in Agriculture," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(5), pages 1131-1153.
    33. Ihli, Hanna Julia & Musshoff, Oliver, 2013. "Investment Behavior of Ugandan Smallholder Farmers: An Experimental Analysis," GlobalFood Discussion Papers 154775, Georg-August-Universitaet Goettingen, GlobalFood, Department of Agricultural Economics and Rural Development.
    34. Steven D. Levitt & John A. List, 2007. "What Do Laboratory Experiments Measuring Social Preferences Reveal About the Real World?," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 153-174, Spring.
    35. George E. Battese, 1997. "A Note On The Estimation Of Cobb‐Douglas Production Functions When Some Explanatory Variables Have Zero Values," Journal of Agricultural Economics, Wiley Blackwell, vol. 48(1‐3), pages 250-252, January.
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    More about this item

    Keywords

    Farm Management; Institutional and Behavioral Economics; Production Economics; Productivity Analysis; Research Methods/ Statistical Methods; Risk and Uncertainty;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • 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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