IDEAS home Printed from https://ideas.repec.org/p/ags/eaa123/122541.html
   My bibliography  Save this paper

Yield trend estimation in the presence of non-constant technological change and weather effects

Author

Listed:
  • Conradt, Sarah
  • Bokusheva, Raushan
  • Finger, Robert
  • Kussaiynov, Talgat

Abstract

The application of yield time series in risk analysis prerequisites the estimation of technological trend which might be present in the data. In this paper, we show that in presence of highly volatile yield time series and non-constant technology, the consideration of the weather effect in the trend equation can seriously improve trend estimation results. We used ordinary least squares (OLS) and MM, a robust estimator. Our empirical analysis is based on weather data as well as farm-level and county-level yield data for a sample of grain-producing farms in Kazakhstan.

Suggested Citation

  • Conradt, Sarah & Bokusheva, Raushan & Finger, Robert & Kussaiynov, Talgat, 2012. "Yield trend estimation in the presence of non-constant technological change and weather effects," 123rd Seminar, February 23-24, 2012, Dublin, Ireland 122541, European Association of Agricultural Economists.
  • Handle: RePEc:ags:eaa123:122541
    as

    Download full text from publisher

    File URL: http://purl.umn.edu/122541
    Download Restriction: no

    References listed on IDEAS

    as
    1. Finger, Robert, 2010. "Evidence of slowing yield growth - The example of Swiss cereal yields," Food Policy, Elsevier, vol. 35(2), pages 175-182, April.
    2. Roger Claassen & Richard E. Just, 2010. "Heterogeneity and Distributional Form of Farm-Level Yields," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(1), pages 144-160.
    3. Robert Finger, 2010. "Revisiting the Evaluation of Robust Regression Techniques for Crop Yield Data Detrending," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(1), pages 205-211.
    4. Jerry R. Skees & J. Roy Black & Barry J. Barnett, 1997. "Designing and Rating an Area Yield Crop Insurance Contract," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(2), pages 430-438.
    5. Antoine Leblois & Philippe Quirion, 2013. "Agricultural insurances based on meteorological indices: realizations, methods and research challenges," Post-Print hal-00656778, HAL.
    6. Finger, Robert, 2012. "Biases in Farm-Level Yield Risk Analysis due to Data Aggregation," Journal of International Agricultural Trade and Development, Journal of International Agricultural Trade and Development, vol. 61(1).
    7. Joseph Atwood & Saleem Shaik & Myles Watts, 2003. "Are Crop Yields Normally Distributed? A Reexamination," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(4), pages 888-901.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Finger, Robert, 2012. "How strong is the “natural hedge”? The effects of crop acreage and aggregation levels," 123rd Seminar, February 23-24, 2012, Dublin, Ireland 122538, European Association of Agricultural Economists.
    2. Pavlova, Vera N. & Varcheva, Svetlana E. & Bokusheva, Raushan & Calanca, Pierluigi, 2014. "Modelling the effects of climate variability on spring wheat productivity in the steppe zone of Russia and Kazakhstan," Ecological Modelling, Elsevier, vol. 277(C), pages 57-67.
    3. Bokusheva, Raushan & Conradt, Sarah, 2012. "Catastrophic crop insurance effectiveness: does it make a difference how yield losses are conditioned?," 123rd Seminar, February 23-24, 2012, Dublin, Ireland 122443, European Association of Agricultural Economists.

    More about this item

    Keywords

    Yield detrending; weather information; robust trend estimation; aggregation; Risk and Uncertainty; Q19;

    JEL classification:

    • Q19 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Other

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:eaa123:122541. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (AgEcon Search). General contact details of provider: http://edirc.repec.org/data/eaaeeea.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.