IDEAS home Printed from https://ideas.repec.org/p/ags/eaae11/114280.html
   My bibliography  Save this paper

Using Non-parametric Methods in Econometric Production Analysis: An Application to Polish Family Farms

Author

Listed:
  • Czekaj, Tomasz
  • Henningsen, Arne

Abstract

Econometric estimation of production functions is one of the most common methods in applied economic production analysis. These studies usually apply parametric estimation techniques, which obligate the researcher to specify the functional form of the production function. Most often, the Cobb-Douglas or the Translog production function is used. However, the specification of a functional form for the production function involves the risk of specifying a functional form that is not similar to the “true” relationship between the inputs and the output. This misspecification might result in biased estimation results—including measures that are of interest of applied economists, such as elasticities. Therefore, we propose to use nonparametric econometric methods. First, they can be applied to verify the functional form used in parametric estimations of production functions. Second, they can be directly used for estimating production functions without specifying a functional form and thus, avoiding possible misspecification errors. We use a balanced panel data set of farms specialized in crop production that is constructed from Polish FADN data for the years 2004-2007. Our analysis shows that neither the Cobb-Douglas function nor the Translog function are consistent with the “true” relationship between the inputs and the output in our data set. We solve this problem by using non-parametric regression. This approach delivers reasonable results, which are on average not too different from the results of the parametric estimations but many individual results are rather different.

Suggested Citation

  • Czekaj, Tomasz & Henningsen, Arne, 2011. "Using Non-parametric Methods in Econometric Production Analysis: An Application to Polish Family Farms," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114280, European Association of Agricultural Economists.
  • Handle: RePEc:ags:eaae11:114280
    as

    Download full text from publisher

    File URL: http://purl.umn.edu/114280
    Download Restriction: no

    References listed on IDEAS

    as
    1. Croissant, Yves & Millo, Giovanni, 2008. "Panel Data Econometrics in R: The plm Package," Journal of Statistical Software, Foundation for Open Access Statistics.
    2. Hayfield, Tristen & Racine, Jeffrey S., 2008. "Nonparametric Econometrics: The np Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i05).
    3. Racine, Jeff & Li, Qi, 2004. "Nonparametric estimation of regression functions with both categorical and continuous data," Journal of Econometrics, Elsevier, vol. 119(1), pages 99-130, March.
    4. Hsiao, Cheng & Li, Qi & Racine, Jeffrey S., 2007. "A consistent model specification test with mixed discrete and continuous data," Journal of Econometrics, Elsevier, vol. 140(2), pages 802-826, October.
    5. Jeffery Racine & Jeffrey Hart & Qi Li, 2006. "Testing the Significance of Categorical Predictor Variables in Nonparametric Regression Models," Econometric Reviews, Taylor & Francis Journals, vol. 25(4), pages 523-544.
    6. Racine, Jeff, 1997. "Consistent Significance Testing for Nonparametric Regression," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(3), pages 369-378, July.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Farm Management;

    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:eaae11:114280. 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.