IDEAS home Printed from https://ideas.repec.org/p/hal/spmain/hal-03926721.html
   My bibliography  Save this paper

Estimation and Inference of Semiparametric Models Using Data from Several Sources

Author

Listed:
  • Moshe Buchinsky

    (UCLA - University of California [Los Angeles] - UC - University of California, ECON - Département d'économie (Sciences Po) - Sciences Po - Sciences Po - CNRS - Centre National de la Recherche Scientifique)

  • Fanghua Li

    (UNSW - University of New South Wales [Sydney])

  • Zhipeng Liao

    (UCLA - University of California [Los Angeles] - UC - University of California)

Abstract

This paper studies the estimation and inference of nonlinear econometric models when the economic variables are contained in different data sets. We construct a semiparametric minimum distance (SMD) estimator of the unknown structural parameter of interest when there are some common conditioning variables in different data sets. The SMD estimator is shown to be consistent and has an asymptotic normal distribution. We provide the explicit form of the optimal weight for the SMD estimation. We provide a consistent estimator of the variance–covariance matrix of the SMD estimator, and hence inference procedures of the unknown parameter vector. The finite sample performances of the SMD estimators and the proposed inference procedures are investigated in few alternative Monte Carlo simulation studies.

Suggested Citation

  • Moshe Buchinsky & Fanghua Li & Zhipeng Liao, 2022. "Estimation and Inference of Semiparametric Models Using Data from Several Sources," SciencePo Working papers Main hal-03926721, HAL.
    • Handle: RePEc:hal:spmain:hal-03926721
    DOI: 10.1016/j.jeconom.2020.10.011
    Note: View the original document on HAL open archive server: https://hal-sciencespo.archives-ouvertes.fr/hal-03926721
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:hal:spmain:hal-03926721. 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: Contact - Sciences Po Departement of Economics (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.