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Who Does Dot Respond to the Agricultural Resource Management Survey and Does It Matter?

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  • Jeremy G. Weber
  • Dawn Marie Clay

Abstract

The Agricultural Resource Management Survey is the primary annual source of information on U.S. farms, but in a typical year one-third of sampled farms do not respond. We use Census of Agriculture data to study nonresponse to the survey and how it affects estimates in two econometric models. Despite larger farms responding less, the coefficients estimated from the respondent subsample always fall inside confidence intervals based on draws from the full sample of respondents and nonrespondents. Although nonresponse bias can vary by application, the findings suggest that bias is unlikely to undermine conclusions based on econometrics using respondent data. Copyright 2013, Oxford University Press.

Suggested Citation

  • Jeremy G. Weber & Dawn Marie Clay, 2013. "Who Does Dot Respond to the Agricultural Resource Management Survey and Does It Matter?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 95(3), pages 755-771.
    • Handle: RePEc:oup:ajagec:v:95:y:2013:i:3:p:755-771
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    File URL: http://hdl.handle.net/10.1093/ajae/aas171
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    Citations

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    Cited by:

    1. Weber, Jeremy G. & Key, Nigel & O'Donoghue, Erik J., 2015. "Does Federal Crop Insurance Encourage Farm Specialization and Fertilizer and Chemical Use?," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 204972, Agricultural and Applied Economics Association.
    2. Boris E. Bravo‐Ureta & Víctor H. Moreira & Javier L. Troncoso & Alan Wall, 2020. "Plot‐level technical efficiency accounting for farm‐level effects: Evidence from Chilean wine grape producers," Agricultural Economics, International Association of Agricultural Economists, vol. 51(6), pages 811-824, November.
    3. Ifft, Jennifer & Kuethe, Todd & Morehart, Mitch, 2015. "Does Federal Crop Insurance lead to higher farm debt use? Evidence from the Agricultural Resource Management Survey," Working Papers 250011, Cornell University, Department of Applied Economics and Management.
    4. Penn, Jerrod & Hu, Wuyang & Alfaro-Inocente, Adriana & Bastola, Sapana, 2020. "Payment versus Charitable Donations to Attract Producer Survey Participation," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304329, Agricultural and Applied Economics Association.
    5. Jeremy G. Weber & Nigel Key & Erik O’Donoghue, 2016. "Does Federal Crop Insurance Make Environmental Externalities from Agriculture Worse?," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 3(3), pages 707-742.
    6. Key, Nigel & Prager, Daniel & Burns, Christopher, 2017. "Farm Household Income Volatility: An Analysis Using Panel Data From a National Survey," Economic Research Report 256710, United States Department of Agriculture, Economic Research Service.
    7. Ifft, Jennifer & Jodlowski, Margaret, 2022. "Is ICE freezing US agriculture? Farm-level adjustment to increased local immigration enforcement," Labour Economics, Elsevier, vol. 78(C).
    8. McCarthy Jaki & Wagner James & Sanders Herschel Lisette, 2017. "The Impact of Targeted Data Collection on Nonresponse Bias in an Establishment Survey: A Simulation Study of Adaptive Survey Design," Journal of Official Statistics, Sciendo, vol. 33(3), pages 857-871, September.
    9. Zhong, Hua & Hu, Wuyang & Penn, Jerrod M., 2018. "Application of Multiple Imputation in Dealing with Missing Data in Agricultural Surveys: The Case of BMP Adoption," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 43(1), January.

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