IDEAS home Printed from https://ideas.repec.org/p/ags/unasrr/235033.html
   My bibliography  Save this paper

Adjusting the June Area Survey Estimate of the Number of U.S. Farms for Misclassification and Non-response

Author

Listed:
  • Lopiano, Kenneth K.
  • Lamas, Andrea C.
  • Abreu, Denise A.
  • Arroway, Pam
  • Young, Linda J.

Abstract

Each year, the National Agricultural Statistics Service (NASS) conducts the June Area Survey (JAS), which is based on an area frame. The JAS provides information on U.S. agriculture, including an estimate of the number of farms in the U.S. NASS also conducts the Census of Agriculture every five years in years ending in 2 and 7. The census, which uses both a list and the JAS area frame, also produces an estimate of the number of U.S. farms. In 2007, the two estimates were further apart than could be attributed to sampling error alone. Previous studies of the JAS identified misclassification of JAS sampled units as a source leading to an undercount in the number of farms in the U.S. Using data from the 2007 JAS and the 2007 Census, misclassification of tracts as agricultural or non-agricultural were identified. Research has also identified the estimation of agricultural activities for sampled tracts as another factor that contributes to the discrepancy in the JAS number of farms estimate. This research report presents methodology that adjusts for two known sources of error on the JAS: misclassification and estimation (which later will be addressed as non-response).

Suggested Citation

  • Lopiano, Kenneth K. & Lamas, Andrea C. & Abreu, Denise A. & Arroway, Pam & Young, Linda J., 2011. "Adjusting the June Area Survey Estimate of the Number of U.S. Farms for Misclassification and Non-response," NASS Research Reports 235033, United States Department of Agriculture, National Agricultural Statistics Service.
  • Handle: RePEc:ags:unasrr:235033
    DOI: 10.22004/ag.econ.235033
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/235033/files/RDD-11-04-Adjusting_JAS.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.235033?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Abreu, Denise A. & Dickey, Nancy J. & McCarthy, Jaki S., 2009. "2007 Classification Error Survey for the United States Census of Agriculture," NASS Research Reports 235071, United States Department of Agriculture, National Agricultural Statistics Service.
    2. Abreu, Denise A. & McCarthy, Jaki S. & Colburn, Leslie A., 2010. "Impact of the Screening Procedures of the June Area Survey on the Number of Farms Estimates," NASS Research Reports 234374, United States Department of Agriculture, National Agricultural Statistics Service.
    3. Silvia Ferrari & Francisco Cribari-Neto, 2004. "Beta Regression for Modelling Rates and Proportions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 31(7), pages 799-815.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. repec:ags:unassr:235033 is not listed on IDEAS
    2. Abreu, Denise A. & Lamas, Andrea C. & Sang, Hailin & Lopiano, Kenneth K. & Arroway, Pam & Young, Linda J., 2011. "On the Feasibility of Using NASS’s Sampling List Frame to Evaluate Misclassification Errors of the June Area Survey," NASS Research Reports 235030, United States Department of Agriculture, National Agricultural Statistics Service.
    3. repec:ags:unassr:235030 is not listed on IDEAS
    4. Matthias Schmid & Florian Wickler & Kelly O Maloney & Richard Mitchell & Nora Fenske & Andreas Mayr, 2013. "Boosted Beta Regression," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-15, April.
    5. Linda J. Young & Michael Jacobsen, 2022. "Sample Design and Estimation When Using a Web-Scraped List Frame and Capture-Recapture Methods," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(2), pages 261-279, June.
    6. Admassu N. Lamu, 2020. "Does linear equating improve prediction in mapping? Crosswalking MacNew onto EQ-5D-5L value sets," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 21(6), pages 903-915, August.
    7. Ni, Linglin & Wang, Xiaokun, 2021. "Load factors of less-than-truckload delivery tours: An analysis with operation data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 150(C).
    8. Paulus, Anne & Hagemann, Nina & Baaken, Marieke C. & Roilo, Stephanie & Alarcón-Segura, Viviana & Cord, Anna F. & Beckmann, Michael, 2022. "Landscape context and farm characteristics are key to farmers' adoption of agri-environmental schemes," Land Use Policy, Elsevier, vol. 121(C).
    9. Souza, Tatiene C. & Cribari–Neto, Francisco, 2018. "Intelligence and religious disbelief in the United States," Intelligence, Elsevier, vol. 68(C), pages 48-57.
    10. Domenico Piccolo & Rosaria Simone, 2019. "The class of cub models: statistical foundations, inferential issues and empirical evidence," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 389-435, September.
    11. Sofia Vasilopoulou & Katjana Gattermann, 2021. "Does Politicization Matter for EU Representation? A Comparison of Four European Parliament Elections," Journal of Common Market Studies, Wiley Blackwell, vol. 59(3), pages 661-678, May.
    12. Jorge I. Figueroa-Zúñiga & Cristian L. Bayes & Víctor Leiva & Shuangzhe Liu, 2022. "Robust beta regression modeling with errors-in-variables: a Bayesian approach and numerical applications," Statistical Papers, Springer, vol. 63(3), pages 919-942, June.
    13. S. Balia, 2007. "Reporting expected longevity and smoking: evidence from the SHARE," Working Paper CRENoS 200705, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    14. Yayan Hernuryadin & Koji Kotani & Tatsuyoshi Saijo, 2020. "Time Preferences of Food Producers: Does “Cultivate and Grow” Matter?," Land Economics, University of Wisconsin Press, vol. 96(1), pages 132-148.
    15. Monica Billio & Roberto Casarin, 2010. "Bayesian Estimation of Stochastic-Transition Markov-Switching Models for Business Cycle Analysis," Working Papers 1002, University of Brescia, Department of Economics.
    16. Mhamed Ben Salah & Cédric Chambru & Maleke Fourati, 2022. "The colonial legacy of education: evidence from of Tunisia," ECON - Working Papers 411, Department of Economics - University of Zurich, revised Sep 2024.
    17. Muhammad Suhail Rizwan & Asifa Obaid & Dawood Ashraf, 2017. "The Impact of Corporate Social Responsibility on Default Risk: Empirical evidence from US Firms," Business & Economic Review, Institute of Management Sciences, Peshawar, Pakistan, vol. 9(3), pages 36-70, September.
    18. Giovanna Bua & Carmine Trecroci, 2019. "International equity markets interdependence: bigger shocks or contagion in the 21st century?," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 155(1), pages 43-69, February.
    19. Korkeamäki, Timo & Virk, Nader & Wang, Haizhi & Wang, Peng, 2018. "Learning Chinese? The changing investment behavior of foreign institutions in the Chinese stock market," BOFIT Discussion Papers 19/2018, Bank of Finland Institute for Emerging Economies (BOFIT).
    20. Tien D. N. Ho & John K. M. Kuwornu & Takuji W. Tsusaka, 2022. "Factors Influencing Smallholder Rice Farmers’ Vulnerability to Climate Change and Variability in the Mekong Delta Region of Vietnam," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 34(1), pages 272-302, February.
    21. Ameztegui, Aitor & Coll, Lluís & Messier, Christian, 2015. "Modelling the effect of climate-induced changes in recruitment and juvenile growth on mixed-forest dynamics: The case of montane–subalpine Pyrenean ecotones," Ecological Modelling, Elsevier, vol. 313(C), pages 84-93.
    22. Guillermo Martínez-Flórez & Roger Tovar-Falón & Víctor Leiva & Cecilia Castro, 2024. "Skew-Normal Inflated Models: Mathematical Characterization and Applications to Medical Data with Excess of Zeros and Ones," Mathematics, MDPI, vol. 12(16), pages 1-23, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:unasrr:235033. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://www.nass.usda.gov/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.