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Demand For Herbicide In Corn: An Entropy Approach Using Micro-Level Data

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  • Arndt, Channing

Abstract

Price responsiveness of herbicide demand in corn for farmers in Indiana's White River Basin using cross-section data from individual farms is estimated. Particular attention is paid to appropriate treatment of binding nonnegativity constraints. Estimation was first attempted using an approach to demand systems estimation suggested by Lee and Pitt. However, analytical and computational difficulties effectively preclude estimation by the Lee and Pitt approach. As an alternative, a maximum entropy (ME) approach is presented and discussed. Results from the ME estimator tentatively indicate limited response of herbicide demand to changes in own prices. The maximum entropy approach to demand systems estimation appears to have merit and warrants further attention.

Suggested Citation

  • Arndt, Channing, 1999. "Demand For Herbicide In Corn: An Entropy Approach Using Micro-Level Data," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 24(01), pages 1-18, July.
    • Handle: RePEc:ags:jlaare:30866
    DOI: 10.22004/ag.econ.30866
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    References listed on IDEAS

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    1. Meyerhoefer, Chad D. & Ranney, Christine K. & Sahn, David E., 2004. "Consistent Estimation Of Longitudinal Censored Demand Systems," 2004 Annual meeting, August 1-4, Denver, CO 19992, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    2. Adélaïde Fadhuile & Stéphane Lemarié & Alain Pirotte, 2016. "Disaggregating the Demand for Pesticides: Does it Matter?," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 64(2), pages 223-252, June.
    3. Obafèmi P. Koutchadé & Alain Carpentier & Fabienne Femenia, 2021. "Modeling Corners, Kinks, and Jumps in Crop Acreage Choices: Impacts of the EU Support to Protein Crops," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(4), pages 1502-1524, August.
    4. Fadhuile, Adelaide & Lemarie, Stephane & Pirotte, Alain, "undated". "Pesticides Uses in Crop Production: What Can We Learn from French Farmers Practices?," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 103654, Agricultural and Applied Economics Association.
    5. Xiaonan Liu & Jeffrey T. LaFrance & Hayley H. Chouinard & Thomas L. Marsh, 2013. "A Generalized Utility Model with Binding Non-Negativity Constraints: Demand for Beer," 2013 Papers pli830, Job Market Papers.
    6. Ou Yang & Peter Sivey & Andrea M. de Silva & Anthony Scott, 2016. "Preschool Children’s Demand for Sugar Sweetened Beverages: Evidence from Stated-Preference Panel Data," Melbourne Institute Working Paper Series wp2016n25, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    7. Zheng, Yu & Alexandre, Gohin, "undated". "Agricultural productivity and price volatility in France: a dynamic stochastic partial equilibrium approach," 2018 Annual Meeting, August 5-7, Washington, D.C. 274354, Agricultural and Applied Economics Association.
    8. Thomas, Alban & Chakir, Raja, 2020. "Unintended consequences of environmental policies: the case of set-aside and agricultural intensification," TSE Working Papers 20-1066, Toulouse School of Economics (TSE).
    9. Meyerhoefer, Chad D. & Ranney, Christine K. & Sahn, David E., 2003. "Consistent Estimation Of Longitudinal Censored Demand Systems: An Application To Transition Country Data," Working Papers 127252, Cornell University, Department of Applied Economics and Management.
    10. Golan, Amos & LaFrance, Jeffrey T & Perloff, Jeffrey M. & Seabold, Skipper, 2017. "Estimating a Demand System with Choke Prices," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt4qt9q8vr, Department of Agricultural & Resource Economics, UC Berkeley.
    11. Millimet, Daniel L. & Tchernis, Rusty, 2008. "Estimating high-dimensional demand systems in the presence of many binding non-negativity constraints," Journal of Econometrics, Elsevier, vol. 147(2), pages 384-395, December.

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