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Estimating Adoption of Cover Crops Using Preferences Revealed by a Dynamic Crop Choice Model

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  • Ji, Yongjie
  • Rabotyagov, sergey
  • Valcu-Lisman, Adriana

Abstract

In this paper, we propose a framework based on micro-level dynamic land use models to predict the adoption of cover crops in the Upper-Mississippi River Basin. We use preferences recovered using a dynamic discrete model of crop choice to build a dynamic optimization framework to evaluate a range of scenarios based on the cover crops’ effect on cash crop yields, costs of cover crop operations, and government support. We use a conditional choice probability method to estimate the dynamic crop choice model based on field-scale panel data and value function iteration method to assess counterfactual cover crop scenarios. The framework is expected to be applicable to modeling decisions to adopt conservation technologies in the absence of individual-level adoption data or for cases when conservation technology is new. The dynamic crop choice model yields expected results and reveals preferences for net revenues in line with previous literature. Simulation results predict baseline cover crop adoption rates which, although in line with some recent farmer surveys, are quite a bit higher than rates reported in 2012 Census of Agriculture. We attribute these results to substitution patterns implied by a dynamic logit model estimated, and suggest using aggregated Census of Agriculture data on state-wide adoption of cover crops to calibrate the constants in the the estimated dynamic logit model as a possible remedy under paucity of data related to individual decisions on cover crops adoption.

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  • Ji, Yongjie & Rabotyagov, sergey & Valcu-Lisman, Adriana, 2015. "Estimating Adoption of Cover Crops Using Preferences Revealed by a Dynamic Crop Choice Model," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205799, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea15:205799
    DOI: 10.22004/ag.econ.205799
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    1. Rust, John, 1987. "Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher," Econometrica, Econometric Society, vol. 55(5), pages 999-1033, September.
    2. Lubowski, Ruben N. & Plantinga, Andrew J. & Stavins, Robert N., 2006. "Land-use change and carbon sinks: Econometric estimation of the carbon sequestration supply function," Journal of Environmental Economics and Management, Elsevier, vol. 51(2), pages 135-152, March.
    3. JunJie Wu & Richard M. Adams & Catherine L. Kling & Katsuya Tanaka, 2004. "From Microlevel Decisions to Landscape Changes: An Assessment of Agricultural Conservation Policies," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(1), pages 26-41.
    4. Alessandro Pinto & Gerald C. Nelson, 2009. "Land Use Change with Spatially Explicit Data: A Dynamic Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 43(2), pages 209-229, June.
    5. Victor Aguirregabiria & Pedro Mira, 2002. "Swapping the Nested Fixed Point Algorithm: A Class of Estimators for Discrete Markov Decision Models," Econometrica, Econometric Society, vol. 70(4), pages 1519-1543, July.
    6. Michael Livingston & Michael J. Roberts & Yue Zhang, 2015. "Optimal Sequential Plantings of Corn and Soybeans Under Price Uncertainty," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(3), pages 855-878.
    7. Thierry Magnac & David Thesmar, 2002. "Identifying Dynamic Discrete Decision Processes," Econometrica, Econometric Society, vol. 70(2), pages 801-816, March.
    8. Hendricks, Nathan P. & Sinnathamby, Sumathy & Douglas-Mankin, Kyle & Smith, Aaron & Sumner, Daniel A. & Earnhart, Dietrich H., 2014. "The environmental effects of crop price increases: Nitrogen losses in the U.S. Corn Belt," Journal of Environmental Economics and Management, Elsevier, vol. 68(3), pages 507-526.
    9. Ruben N. Lubowski & Andrew J. Plantinga & Robert N. Stavins, 2008. "What Drives Land-Use Change in the United States? A National Analysis of Landowner Decisions," Land Economics, University of Wisconsin Press, vol. 84(4), pages 529-550.
    10. Keane, Michael P & Wolpin, Kenneth I, 1994. "The Solution and Estimation of Discrete Choice Dynamic Programming Models by Simulation and Interpolation: Monte Carlo Evidence," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 648-672, November.
    11. J. Arbuckle & Lois Morton & Jon Hobbs, 2013. "Farmer beliefs and concerns about climate change and attitudes toward adaptation and mitigation: Evidence from Iowa," Climatic Change, Springer, vol. 118(3), pages 551-563, June.
    12. Ji, Yongjie & Rabotyagov, Sergey & Kling, Catherine L., 2014. "Crop Choice and Rotational Effects: A Dynamic Model of Land Use in Iowa in Recent Years," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170366, Agricultural and Applied Economics Association.
    13. Peter Arcidiacono & Paul B. Ellickson, 2011. "Practical Methods for Estimation of Dynamic Discrete Choice Models," Annual Review of Economics, Annual Reviews, vol. 3(1), pages 363-394, September.
    14. Peter Arcidiacono & Robert A. Miller, 2011. "Conditional Choice Probability Estimation of Dynamic Discrete Choice Models With Unobserved Heterogeneity," Econometrica, Econometric Society, vol. 79(6), pages 1823-1867, November.
    15. David A. Hennessy, 2006. "On Monoculture and the Structure of Crop Rotations," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 88(4), pages 900-914.
    16. Cai, Ruohong & Bergstrom, John C. & Mullen, Jeffrey D. & Wetzstein, Michael E., 2011. "A Dynamic Optimal Crop Rotation Model in Acreage Response," Faculty Series 103949, University of Georgia, Department of Agricultural and Applied Economics.
    17. Kaspar, T.C. & Jaynes, D.B. & Parkin, T.B. & Moorman, T.B. & Singer, J.W., 2012. "Effectiveness of oat and rye cover crops in reducing nitrate losses in drainage water," Agricultural Water Management, Elsevier, vol. 110(C), pages 25-33.
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    Cited by:

    1. Wallander, Steven & Bowman, Maria & Beeson, Peter & Claassen, Roger, 2017. "Farmers and Habits: The Challenge of Identifying the Sources of Persistence in Tillage Decisions," 2018 Allied Social Sciences Association (ASSA) Annual Meeting, January 5-7, 2018, Philadelphia, Pennsylvania 266307, Agricultural and Applied Economics Association.
    2. Wallander, Steven & Bowman, Maria S. & Claassen, Roger L., 2017. "Temporary Subsidies and Persistent Behavior: Evidence from Conservation Tillage," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 259148, Agricultural and Applied Economics Association.

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    Land Economics/Use;

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