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The Rationality of Farmland Price Expectations for Measures of Central Tendency

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  • Robertson, Dewey

Abstract

Farmland price expectations play an important role in price discovery, investing, and lending. Previous studies find that farmland price expectations collected through surveys are often not rational (biased or inefficient), based on tests that assume respondents report the mean of their distribution of expectations. However, the exact statistical quantity that respondents report is often unknown. Using price expectations from the Purdue Farmland Values and Cash Rents Survey, 1980-2023, we examine the degree to which respondents’ price expectations may be considered rational at the mean, median, or mode, as well as convex combinations thereof. We find that farmland price expectations are mean-rational in only half of the cases. Yet, farmland price expectations are mode-rational in roughly 72% of cases, including those that are both mean and mode rational. Thus, all cases are rational at either the mean, mode, or both, and our results suggest that respondents likely report the mode or “most likely” value.

Suggested Citation

  • Robertson, Dewey, 2025. "The Rationality of Farmland Price Expectations for Measures of Central Tendency," 2025 AAEA & WAEA Joint Annual Meeting, July 27-29, 2025, Denver, CO 360669, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaea25:360669
    DOI: 10.22004/ag.econ.360669
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    1. Natalia Nolde & Johanna F. Ziegel, 2016. "Elicitability and backtesting: Perspectives for banking regulation," Papers 1608.05498, arXiv.org, revised Feb 2017.
    2. Kuethe, Todd H. & Hubbs, Todd, . "Bankers' Forecasts of Farmland Values: A Qualitative and Quantitative Evaluation," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 49(4).
    3. Gneiting, Tilmann, 2011. "Making and Evaluating Point Forecasts," Journal of the American Statistical Association, American Statistical Association, vol. 106(494), pages 746-762.
    4. Todd H. Kuethe & Brady Brewer & Chad Fiechter, 2022. "Loss Aversion in Farmland Price Expectations," Land Economics, University of Wisconsin Press, vol. 98(1), pages 98-114.
    5. Keith C. Brown & Deborah J. Brown, 1984. "Heterogenous Expectations and Farmland Prices," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 66(2), pages 164-169.
    6. Graham Elliott & Allan Timmermann & Ivana Komunjer, 2005. "Estimation and Testing of Forecast Rationality under Flexible Loss," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(4), pages 1107-1125.
    7. Todd H Kuethe & David Oppedahl, 2021. "Agricultural bankers’ farmland price expectations," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 48(1), pages 42-59.
    8. Chad Fiechter & Todd Kuethe & Wendong Zhang, 2025. "Information Rigidities and Farmland Value Expectations," Land Economics, University of Wisconsin Press, vol. 101(2), pages 218-229.
    9. Valentina Hartarska & Denis Nadolnyak & Xuan Shen, 2015. "Agricultural credit and economic growth in rural areas," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 75(3), pages 302-312, September.
    10. Valentina Hartarska & Denis Nadolnyak & Xuan Shen, 2015. "Agricultural credit and economic growth in rural areas," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 75(3), pages 302-312, September.
    11. Weber, Elke U & Kirsner, Britt, 1997. "Reasons for Rank-Dependent Utility Evaluation," Journal of Risk and Uncertainty, Springer, vol. 14(1), pages 41-61, January.
    12. Kuethe, Todd H. & Hubbs, Todd, 2017. "Bankers’ Forecasts Of Farmland Values: A Qualitative And Quantitative Evaluation," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 49(4), pages 617-633, November.
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