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Estimation of heterogeneous autoregressive parameters with short panel data

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  • Mavroeidis, Sophocles
  • Sasaki, Yuya
  • Welch, Ivo

Abstract

This paper presents a maximum likelihood approach to estimation of cross sectional distributions of heterogeneous autoregressive (AR) parameters with short panel data. We construct a panel likelihood by integrating the unknown cross sectional density of heterogeneous AR parameters with respect to a known time-series data generating kernel. The solution to this extremal criterion recovers the unknown density of heterogeneous AR parameters. Applying our method to a model of employment dynamics with the firm-level data of Arellano and Bond (1991), we find that adjustment rates of employment are significantly heterogeneous across firms.

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  • Mavroeidis, Sophocles & Sasaki, Yuya & Welch, Ivo, 2015. "Estimation of heterogeneous autoregressive parameters with short panel data," Journal of Econometrics, Elsevier, vol. 188(1), pages 219-235.
    • Handle: RePEc:eee:econom:v:188:y:2015:i:1:p:219-235
    DOI: 10.1016/j.jeconom.2015.05.001
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