Estimation of heterogeneous autoregressive parameters with short panel data

被引：9

作者：

Mavroeidis, Sophocles ^{[1
]}

Sasaki, Yuya ^{[2
]}

Welch, Ivo ^{[3
]}

机构：

[1] Univ Oxford, Dept Econ, Oxford OX1 2JD, England

[2] Johns Hopkins Univ, Dept Econ, Baltimore, MD 21218 USA

[3] Univ Calif Los Angeles, Anderson Grad Sch Management, Los Angeles, CA 90024 USA

来源：

JOURNAL OF ECONOMETRICS | 2015年 / 188卷 / 01期

关键词：

Panel data; Employment dynamics; Heterogeneous autoregressive parameters; Initial conditions; Maximum likelihood; INITIAL CONDITIONS; DATA MODELS;

D O I：

10.1016/j.jeconom.2015.05.001

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

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. (C) 2015 Elsevier B.V. All rights reserved.

引用

页码：219 / 235

页数：17

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