Estimation of heterogeneous autoregressive parameters with short panel data

Sophocles Mavroeidis, Yuya Sasaki and Ivo Welch

Journal of Econometrics, 2015, vol. 188, issue 1, 219-235

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.

Keywords: Panel data; Employment dynamics; Heterogeneous autoregressive parameters; Initial conditions; Maximum likelihood (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:188:y:2015:i:1:p:219-235

DOI: 10.1016/j.jeconom.2015.05.001

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