IDEAS home Printed from https://ideas.repec.org/p/toh/dssraa/104.html
   My bibliography  Save this paper

Estimation of Partially Linear Spatial Autoregressive Models with Autoregressive Disturbances

Author

Listed:
  • Takaki Sato

Abstract

This study considers semiparametric partially linear spatial autoregressive models with autoregressive disturbances that contain an unspecified nonparametric component and allow for spatial lags in both the dependent variables and disturbances. Having the nonparametric function approximated by basis functions, we propose a three-step estimation procedure for the proposed model. We also establish the consistency and asymptotic normality of the proposed estimators. Then, the finite sample performances of the proposed estimators are examined using Monte Carlo simulations. As an empirical application, we use the proposed model and estimation method to analyze Boston housing price data to evaluate the effect of air pollution on the value of owner-occupied homes.

Suggested Citation

  • Takaki Sato, 2019. "Estimation of Partially Linear Spatial Autoregressive Models with Autoregressive Disturbances," DSSR Discussion Papers 104, Graduate School of Economics and Management, Tohoku University.
    • Handle: RePEc:toh:dssraa:104
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10097/00126434
    Download Restriction: no
    ---><---

    More about this item

    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:toh:dssraa:104. 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: Tohoku University Library (email available below). General contact details of provider: https://edirc.repec.org/data/fetohjp.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.