IDEAS home Printed from https://ideas.repec.org/a/rsr/supplm/v61y2013i1p38-43.html
   My bibliography  Save this article

Non-parametrical Estimation of the Regression used in Economic Analyses

Author

Listed:
  • Constantin ANGHELACHE

    („Artifex” University of Bucharest
    Academy of Economic Studies, Bucharest)

  • Gabriela Victoria ANGHELACHE

    (Academy of Economic Studies, Bucharest)

  • Liviu BEGU

    (Academy of Economic Studies, Bucharest)

  • Georgeta BARDASU

    (Academy of Economic Studies, Bucharest)

Abstract

Non-parametric methods are useful, but raises some problems. In practice, they require a large number of observations and are used for a relatively small number of explanatory variables. Moreover, the result is sensitive to the choice of the smoothing parameter and to a lesser extent in the nucleus. They pose a problem for the presentation of results that can not be contained in a compact formula but can only be described by graphs. A non-parametric analysis does not allow extrapolation outside the range of observation, but econometric is an advantage.

Suggested Citation

  • Constantin ANGHELACHE & Gabriela Victoria ANGHELACHE & Liviu BEGU & Georgeta BARDASU, 2013. "Non-parametrical Estimation of the Regression used in Economic Analyses," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 61(1), pages 38-43, March.
  • Handle: RePEc:rsr:supplm:v:61:y:2013:i:1:p:38-43
    as

    Download full text from publisher

    File URL: http://www.revistadestatistica.ro/suplimente/2013/1_2013/srrs1_2013a05.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    non-parametric methods; variables; regression function; appraisal;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

    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:rsr:supplm:v:61:y:2013:i:1:p:38-43. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Adrian Visoiu (email available below). General contact details of provider: https://edirc.repec.org/data/stagvro.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.