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Likelihood inference and the role of initial conditions for the dynamic panel data model

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  • Barbosa, José Diogo
  • Moreira, Marcelo J.

Abstract

Lancaster (2002) proposes an estimator for the dynamic panel data model with homoskedastic errors and zero initial conditions. In this paper, we show this estimator is invariant to orthogonal transformations, but is inefficient because it ignores additional information available in the data. The zero initial condition is trivially satisfied by subtracting initial observations from the data. We show that differencing out the data further erodes efficiency compared to drawing inference conditional on the first observations.

Suggested Citation

  • Barbosa, José Diogo & Moreira, Marcelo J., 2021. "Likelihood inference and the role of initial conditions for the dynamic panel data model," Journal of Econometrics, Elsevier, vol. 221(1), pages 160-179.
    • Handle: RePEc:eee:econom:v:221:y:2021:i:1:p:160-179
    DOI: 10.1016/j.jeconom.2020.04.039
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    More about this item

    Keywords

    Autoregressive; Panel data; Invariance; Efficiency;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General

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