IDEAS home Printed from https://ideas.repec.org/p/sgo/wpaper/2007.html

Cross-sectional quasi maximum likelihood and bias-corrected pooled least squares estimators for short dynamic panels

Author

Listed:
  • In Choi

    (Department of Economics, Sogang University, Seoul)

  • Sanghyun Jung

    (Department of Economics, Sogang University, Seoul)

Abstract

This paper proposes new estimators for the panel autoregressive (PAR) model of order 1 with short time dimensions and large cross sections. These estimators are based on the cross-sectional regression model using the first time series observations as a regressor and the last as a dependent variable. The regressors and errors of this regression model are correlated. The first estimator is the quasi maximum likelihood estimator (QMLE). The second estimator is the bias-corrected pooled least squares estimator (BCPLSE) that eliminates the asymptotic bias of the pooled least squares estimator by using the QMLE. The QMLE and BCPLSE are extended to the PAR model with endogenous regressors. The QMLE and BCPLSE provide consistent estimates of the PAR coefficients for stationary, unit root and explosive PAR models and consistently estimate the coefficients of endogenous regressors. Their finite sample properties are compared with those of some other estimators for the PAR model of order 1. This paper's estimators are shown to perform quite well in finite samples.

Suggested Citation

  • In Choi & Sanghyun Jung, 2020. "Cross-sectional quasi maximum likelihood and bias-corrected pooled least squares estimators for short dynamic panels," Working Papers 2007, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    • Handle: RePEc:sgo:wpaper:2007
    as

    Download full text from publisher

    File URL: https://buly.kr/9XMhkx6
    File Function: First version, 2020
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

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


    Cited by:

    1. is not listed on IDEAS
    2. Qi Li & Vasilis Sarafidis & Joakim Westerlund, 2021. "Essays in honor of Professor Badi H Baltagi," Empirical Economics, Springer, vol. 60(1), pages 1-11, January.
    3. Li, Qi & Sarafidis, Vasilis & Westerlund, Joakim, 2020. "Essays in Honor of Professor Badi H Baltagi: Editorial," MPRA Paper 104751, University Library of Munich, Germany.
    4. Fei Chen & Guotong Qiao & Na Wang & Dandan Zhang, 2022. "Study on the Influence of Population Urbanization on Agricultural Eco-Efficiency and on Agricultural Eco-Efficiency Remeasuring in China," Sustainability, MDPI, vol. 14(20), pages 1-18, October.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    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:sgo:wpaper:2007. 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: Jung Hur (email available below). General contact details of provider: https://edirc.repec.org/data/risogkr.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.