IDEAS home Printed from https://ideas.repec.org/p/ags/umaesp/13954.html

Choice Of Regression Method For Detrending Time Series Data With Nonnormal Errors

Author

Listed:
  • Swinton, Scott M.
  • King, Robert P.

Abstract

No abstract is available for this item.

Suggested Citation

  • Swinton, Scott M. & King, Robert P., 1989. "Choice Of Regression Method For Detrending Time Series Data With Nonnormal Errors," Staff Papers 13954, University of Minnesota, Department of Applied Economics.
    • Handle: RePEc:ags:umaesp:13954
    DOI: 10.22004/ag.econ.13954
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/13954/files/p89-19.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.13954?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. Richard H. Day, 1965. "Probability Distributions of Field Crop Yields," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 47(3), pages 713-741.
    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. Zheng, Qiujie & Wang, H. Holly & Shi, Qinghua, 2008. "Estimating Farm Level Multivariate Yield Distribution Using Nonparametric Methods," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6509, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    2. Oleg Badunenko & Daniel J. Henderson, 2024. "Production analysis with asymmetric noise," Journal of Productivity Analysis, Springer, vol. 61(1), pages 1-18, February.
    3. Lee, Donna, 1991. "Evaluating Risky Input Decisions in Crop Response Analysis," WAEA/ WFEA Conference Archive (1929-1995) 321431, Western Agricultural Economics Association.
    4. Norwood, F. Bailey & Roberts, Matthew C. & Lusk, Jayson L., 2002. "How Are Crop Yields Distributed?," 2002 Annual meeting, July 28-31, Long Beach, CA 19733, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    5. Ayenew, Habtamu Yesigat & Sauer, Johannes & Abate-Kassa, Getachew, 2016. "Cost of Risk Exposure, Farm Disinvestment and Adaptation to Climate Uncertainties: The Case of Arable Farms in the EU," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235595, Agricultural and Applied Economics Association.
    6. Jesse B. Tack & David Ubilava, 2015. "Climate and agricultural risk: measuring the effect of ENSO on U.S. crop insurance," Agricultural Economics, International Association of Agricultural Economists, vol. 46(2), pages 245-257, March.
    7. Chen, Shu-Ling & Miranda, Mario J., 2006. "Modeling Yield Distribution In High Risk Counties: Application To Texas Upland Cotton," 2006 Annual meeting, July 23-26, Long Beach, CA 21392, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    8. Vitor A. Ozaki & Sujit K. Ghosh & Barry K. Goodwin & Ricardo Shirota, 2008. "Spatio-Temporal Modeling of Agricultural Yield Data with an Application to Pricing Crop Insurance Contracts," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(4), pages 951-961.
    9. Xiaodong Du & David A. Hennessy & Cindy L. Yu, 2012. "Testing Day's Conjecture that More Nitrogen Decreases Crop Yield Skewness," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 94(1), pages 225-237.
    10. Nauges, Céline & Bougherara, Douadia & Koussoubé, Estelle, 2021. "Fertilizer use and risk: New evidence from Sub-Saharan Africa," TSE Working Papers 21-1266, Toulouse School of Economics (TSE).
    11. Zeytoon Nejad Moosavian, Seyyed Ali & Goodwin, Barry K., "undated". "GENERALIZING THE GENERAL: Generalizing the CES Production Function to Allow for the Flexibility of Input-Driven Output Risk and Viability of Input Thresholds," 2018 Annual Meeting, August 5-7, Washington, D.C. 274352, Agricultural and Applied Economics Association.
    12. Berck, Peter, 1980. "Portfolio Theory and the Demand for Futures: theory and the case of California cotton," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt58j4t4qp, Department of Agricultural & Resource Economics, UC Berkeley.
    13. Roumasset, James, 2024. "Lexicographic Ordering and Loss Aversion among Low-Income Farmers," Journal of Economic Behavior & Organization, Elsevier, vol. 217(C), pages 483-492.
    14. Chen, Xiaomei & Wang, H. Holly & Makus, Larry D., 2007. "Production Risk and Crop Insurance Effectiveness: Organic Versus Conventional Apples," SCC-76 Meeting, 2007, March 15-17, Gulf Shores, Alabama 9381, SCC-76: Economics and Management of Risk in Agriculture and Natural Resources.
    15. Etherington, Dan M., 1977. "A Stochastic Model For The Optimal Replacement Of Rubber Trees," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 21(01), pages 1-19, April.
    16. Woodard, Joshua D. & Chiu Verteramo, Leslie & Miller, Alyssa P., 2015. "Adaptation of U.S. Agricultural Production to Drought and Climate Change," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205903, Agricultural and Applied Economics Association.
    17. Sherrick, Bruce J., 2002. "The Accuracy Of Producers' Probability Beliefs: Evidence And Implications For Insurance Valuation," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 27(01), pages 1-17, July.
    18. Ben Groom & Phoebe Koundouri & Celine Nauges & Alban Thomas, 2003. "Irrigation water management under risk: An application to Cyprus," DEOS Working Papers 0306, Athens University of Economics and Business.
    19. Ozaki, Vitor Augusto & Olinda, Ricardo & Faria, Priscila Neves & Campos, Rogério Costa, 2014. "Estimation of the Agricultural Probability of Loss: evidence for soybean in Paraná State," Revista de Economia e Sociologia Rural (RESR), Sociedade Brasileira de Economia e Sociologia Rural, vol. 52(01), January.
    20. van Zyl, J. & Groenewald, J. A., 1986. "A Comparison Of Certain Decision-Making Techniques Under Risk - An Empirical Investigation Of Maize Cultivar Selection," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 25(01), February.

    More about this item

    Keywords

    ;

    Statistics

    Access and download statistics

    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:umaesp:13954. 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://edirc.repec.org/data/daumnus.html .

    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.