IDEAS home Printed from https://ideas.repec.org/a/spr/empeco/v28y2003i1p3-22.html
   My bibliography  Save this article

A generalized additive Tobit model

Author

Listed:
  • Armando Levy

Abstract

This paper proposes a semi-parametric approach to estimation in Tobit models. A generalized additive Tobit model of residential local long distance (intra-LATA) telephone demand is estimated on a cross-section of residential telephone consumers across twenty-eight states. While past studies of telecommunications demand have used fully parametric models, the model presented here is non-parametric in two dimensions: first no distributional assumption is made for the error distribution, and second, the demand equation is non-parametric with respect to price. We find that the elasticity of demand is substantially lower (in absolute value) that found in previous studies for a 40% cut in tariffs. Copyright Springer-Verlag Berlin Heidelberg 2003

Suggested Citation

  • Armando Levy, 2003. "A generalized additive Tobit model," Empirical Economics, Springer, vol. 28(1), pages 3-22, January.
  • Handle: RePEc:spr:empeco:v:28:y:2003:i:1:p:3-22
    DOI: 10.1007/s001810100112
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s001810100112
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s001810100112?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Keywords

    Key words: semi-parametric; general additive models; Tobit; truncated regression; telecommunications; JEL classification: C14; C24; C51; D12;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis

    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:spr:empeco:v:28:y:2003:i:1:p:3-22. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.