IDEAS home Printed from https://ideas.repec.org/a/taf/emetrv/v32y2013i5-6p734-753.html
   My bibliography  Save this article

Two-Stage Least Squares Estimation of Spatial Autoregressive Models with Endogenous Regressors and Many Instruments

Author

Listed:
  • Xiaodong Liu
  • Lung-Fei Lee

Abstract

This paper considers the IV estimation of spatial autoregressive models with endogenous regressors in the presence of many instruments. To improve asymptotic efficiency, it may be desirable to use many valid instruments. However, finite sample properties of IV estimators can be sensitive to the number of instruments. For a spatial model with endogenous regressors, this paper derives the asymptotic distribution of the two-stage least squares (2SLS) estimator when the number of instruments grows with the sample size, and suggests a bias-correction procedure based on the leading-order many-instrument bias. The paper also gives the Nagar-type approximate mean square errors (MSEs) of the 2SLS estimator and the bias-corrected 2SLS estimator, which can be minimized to choose instruments as in Donald and Newey (2001). A limited Monte Carlo experiment is carried out to study the finite sample performance of the instrument selection procedure.

Suggested Citation

  • Xiaodong Liu & Lung-Fei Lee, 2013. "Two-Stage Least Squares Estimation of Spatial Autoregressive Models with Endogenous Regressors and Many Instruments," Econometric Reviews, Taylor & Francis Journals, vol. 32(5-6), pages 734-753, August.
    • Handle: RePEc:taf:emetrv:v:32:y:2013:i:5-6:p:734-753
    DOI: 10.1080/07474938.2013.741018
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/07474938.2013.741018
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/07474938.2013.741018?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fei Jin & Lung‐fei Lee & Kai Yang, 2024. "Best linear and quadratic moments for spatial econometric models with an application to spatial interdependence patterns of employment growth in US counties," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(4), pages 640-658, June.
    2. Xiaodong Liu, 2020. "GMM identification and estimation of peer effects in a system of simultaneous equations," Journal of Spatial Econometrics, Springer, vol. 1(1), pages 1-27, December.
    3. Luisa Alamá-Sabater & Teresa Fernández-Núñez & Miguel Ángel Márquez & Javier Salinas-Jimenez, 2020. "Do Countries with Similar Levels of Corruption Compete to Attract Foreign Investment? Evidence Using World Panel Data," Sustainability, MDPI, vol. 12(15), pages 1-15, July.
    4. Fei Jin & Lung-fei Lee, 2013. "Generalized Spatial Two Stage Least Squares Estimation of Spatial Autoregressive Models with Autoregressive Disturbances in the Presence of Endogenous Regressors and Many Instruments," Econometrics, MDPI, vol. 1(1), pages 1-44, May.
    5. Sylvain Barde & Rowan Cherodian & Guy Tchuente, 2024. "Moran's I 2-Stage Lasso: for Models with Spatial Correlation and Endogenous Variables," Papers 2404.02584, arXiv.org.
    6. Nestor Garza & Colin Lizieri, 2019. "An empirical approach to urban land monopoly: A case study of the city of Barranquilla, Colombia," Urban Studies, Urban Studies Journal Limited, vol. 56(10), pages 1931-1950, August.
    7. Tadao Hoshino, 2018. "Semiparametric Spatial Autoregressive Models With Endogenous Regressors: With an Application to Crime Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 160-172, January.
    8. Maite Alguacil & Luisa Alamá-Sabater, 2021. "Migration in Spain: The Role of Cultural Diversity Revisited," Politics and Governance, Cogitatio Press, vol. 9(4), pages 118-132.
    9. Povilas Lastauskas & Eirini Tatsi, 2013. "Spatial Nexus in Crime and unemployment in Times of crisis: Evidence from Germany," Cambridge Working Papers in Economics 1359, Faculty of Economics, University of Cambridge.
    10. Simplice A. Asongu & Samba Diop, 2021. "Human development and governance in Africa: do good fences make good neighbours?," Working Papers 21/051, European Xtramile Centre of African Studies (EXCAS).
    11. Hoshino, Tadao, 2022. "Sieve IV estimation of cross-sectional interaction models with nonparametric endogenous effect," Journal of Econometrics, Elsevier, vol. 229(2), pages 263-275.
    12. Guy Tchuente, 2016. "Estimation of social interaction models using regularization," Studies in Economics 1607, School of Economics, University of Kent.
    13. You, Jing & Huang, Yongfu, 2013. "Green-to-Grey China: Determinants and Forecasts of its Green Growth," MPRA Paper 57468, University Library of Munich, Germany, revised 16 Jul 2014.
    14. Jean‐Claude Kouladoum, 2023. "Technology and control of corruption in Africa," Journal of International Development, John Wiley & Sons, Ltd., vol. 35(6), pages 1163-1180, August.
    15. Jin, Fei & Lee, Lung-fei, 2018. "Irregular N2SLS and LASSO estimation of the matrix exponential spatial specification model," Journal of Econometrics, Elsevier, vol. 206(2), pages 336-358.
    16. Malabika Koley & Anil K. Bera, 2022. "Testing for spatial dependence in a spatial autoregressive (SAR) model in the presence of endogenous regressors," Journal of Spatial Econometrics, Springer, vol. 3(1), pages 1-46, December.
    17. Liu, Xiaodong & Saraiva, Paulo, 2015. "GMM estimation of SAR models with endogenous regressors," Regional Science and Urban Economics, Elsevier, vol. 55(C), pages 68-79.
    18. Bernard Fingleton, 2023. "Estimating dynamic spatial panel data models with endogenous regressors using synthetic instruments," Journal of Geographical Systems, Springer, vol. 25(1), pages 121-152, January.
    19. Solmaria Halleck Vega & J. Paul Elhorst, 2015. "The Slx Model," Journal of Regional Science, Wiley Blackwell, vol. 55(3), pages 339-363, June.

    More about this item

    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:taf:emetrv:v:32:y:2013:i:5-6:p:734-753. 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: the person in charge (email available below). General contact details of provider: http://www.tandfonline.com/LECR20 .

    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.