IDEAS home Printed from
   My bibliography  Save this paper

Asymptotically unbiased inference for a panel VAR model with p lags


  • Juan Sebastian Cubillos-Rocha

    () (Banco de la República de Colombia)

  • Luis Fernando Melo-Velandia

    () (Banco de la República de Colombia)


Panel dynamic estimators with fixed effects are biased due to the incidental parameters problem. At this regard, Hahn and Kuersteiner (2002) proposed an estimator to correct this issue. However, they only consider a panel VAR (PVAR) model with one lag. In this paper we extend this bias correction, its asymptotic and small sample properties for a more general case, a PVAR model with p lags. The simulation results indicate that the bias corrected estimator outperforms the OLS panel VAR estimator when sample size in time dimension is small, and when the persistence of the model is low. In these cases, the proposed estimator improves significantly in terms of both, the reduction of bias and mean square error. **** RESUMEN: Los estimadores de los parámetros de un modelo panel dinámico de efectos fijos son sesgados debido al problema de parámetros incidentales. Al respecto, Hahn y Kuersteiner (2002) proponen un estimador para corregir este problema. Sin embargo, ellos consideran únicamente un modelo panel VAR con un sólo un rezago. En este documento analizamos las propiedades asintóticas y de muestra pequeña del estimador corregido por sesgo para un caso más general, un modelo PVAR con p rezagos. Los resultados de las simulaciones indican que el estimador corregido por sesgo tiene un mejor desempeño con respecto al estimador panel VAR MCO cuando la dimensión temporal de la muestra (T) es pequeña, y cuando la persistencia del modelo es baja. En estos casos, el estimador propuesto presenta una disminución significativa en términos de sesgo, y de error cuadrático medio.

Suggested Citation

  • Juan Sebastian Cubillos-Rocha & Luis Fernando Melo-Velandia, 2018. "Asymptotically unbiased inference for a panel VAR model with p lags," Borradores de Economia 1059, Banco de la Republica de Colombia.
  • Handle: RePEc:bdr:borrec:1059

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Love, Inessa & Zicchino, Lea, 2006. "Financial development and dynamic investment behavior: Evidence from panel VAR," The Quarterly Review of Economics and Finance, Elsevier, vol. 46(2), pages 190-210, May.
    2. Jinyong Hahn & Guido Kuersteiner, 2002. "Asymptotically Unbiased Inference for a Dynamic Panel Model with Fixed Effects when Both "n" and "T" Are Large," Econometrica, Econometric Society, vol. 70(4), pages 1639-1657, July.
    3. Lee, Yoon-Jin & Okui, Ryo & Shintani, Mototsugu, 2018. "Asymptotic inference for dynamic panel estimators of infinite order autoregressive processes," Journal of Econometrics, Elsevier, vol. 204(2), pages 147-158.
    4. Lof, Matthijs & Malinen, Tuomas, 2014. "Does sovereign debt weaken economic growth? A panel VAR analysis," Economics Letters, Elsevier, vol. 122(3), pages 403-407.
    5. Maddala, G S, 1971. "The Use of Variance Components Models in Pooling Cross Section and Time Series Data," Econometrica, Econometric Society, vol. 39(2), pages 341-358, March.
    6. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    Full references (including those not matched with items on IDEAS)

    More about this item


    Panel VAR models; bias correction; restricted OLS; Modelos Panel VAR; corrección de sesgo; MCO restringido.;

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    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:bdr:borrec:1059. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Clorith Angélica Bahos Olivera). General contact details of provider: .

    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.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.