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Drivers of Profit Inefficiency in Iowa Crop Production

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  • Sawadgo, Wendiam PM
  • Plastina, Alejandro

Abstract

In this paper, we use data envelopment analysis and a panel of Iowa farms to evaluate profit inefficiency in corn and soybean production. We find that farms have, on average, profit inefficiency scores of 89.4% in combined corn and soybean production, suggesting that profit could be increased by 89.4% if farms eliminated technical and allocative inefficiencies. Overall, profit efficiency improved from 2011 to 2018, a period generally characterized by decreasing farm net worth. Moreover, while factors such as farm size and operator age affect technical inefficiency, these variables do not have a significant effect on profit inefficiency, while farms’ net worth per acre and crop insurance indemnity payments positively affect profit inefficiency. Land tenure does not have a significant effect on technical or profit inefficiency.
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  • Sawadgo, Wendiam PM & Plastina, Alejandro, 2020. "Drivers of Profit Inefficiency in Iowa Crop Production," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304356, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea20:304356
    DOI: 10.22004/ag.econ.304356
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    References listed on IDEAS

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    1. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    2. Ray,Subhash C., 2012. "Data Envelopment Analysis," Cambridge Books, Cambridge University Press, number 9781107405264, November.
    3. Amin W. Mugera & Michael R. Langemeier & Andrew Ojede, 2016. "Contributions of Productivity and Relative Price Changes to Farm-level Profitability Change," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(4), pages 1210-1229.
    4. Wilson, Paul W, 1993. "Detecting Outliers in Deterministic Nonparametric Frontier Models with Multiple Outputs," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(3), pages 319-323, July.
    5. Yeager, Elizabeth A. & Langemeier, Michael R., 2011. "Productivity Divergence across Kansas Farms," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 40(2), pages 1-11, August.
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    7. Sansi Yang & C. Richard Shumway, 2016. "Dynamic Adjustment in US Agriculture under Climate Change," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(3), pages 910-924.
    8. Mugera, Amin W. & Langemeier, Michael R., 2011. "Does Farm Size and Specialization Matter for Productive Efficiency? Results from Kansas," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 43(4), pages 515-528, November.
    9. Croissant, Yves & Millo, Giovanni, 2008. "Panel Data Econometrics in R: The plm Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i02).
    10. Frederic Ang & Alfons Oude Lansink, 2018. "Decomposing dynamic profit inefficiency of Belgian dairy farms," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 45(1), pages 81-99.
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    Keywords

    Agricultural Finance; Productivity Analysis; Production Economics;
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