Estimating dynamic common-correlated effects in Stata

Jan Ditzen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

118 Citations (Scopus)

Abstract

In this article, I introduce a new command, xtdcce2, that fits a dynamic common-correlated effects model with heterogeneous coefficients in a panel with a large number of observations over cross-sectional units and time periods. The estimation procedure mainly follows Chudik and Pesaran (2015b, Journal of Econometrics 188: 393–420) but additionally supports the common correlated effects estimator (Pesaran, 2006, Econometrica 74: 967–1012), the mean group estimator (Pesaran and Smith, 1995, Journal of Econometrics 68: 79–113), and the pooled mean group estimator (Pesaran, Shin, and Smith, 1999, Journal of the American Statistical Association, 94: 621–634). xtdcce2 allows heterogeneous or homogeneous coefficients and supports instrumental-variable regressions and unbalanced panels. The cross-sectional dependence test is automatically calculated and presented in the estimation output. Small-sample time-series bias can be corrected by “half-panel” jackknife correction or recursive mean adjustment. I carry out a simulation to prove the estimator’s consistency.

Original languageEnglish
Pages (from-to)585-617
Number of pages33
JournalStata Journal
Volume18
Issue number3
Publication statusPublished - 2018

Keywords

  • Common correlated effects
  • Crosssection dependence
  • Dynamic panels
  • Instrumental variables
  • Ivreg2
  • Mean group estimator
  • Parameter heterogeneity
  • Pooled mean group estimator
  • St0536
  • Xtcd2
  • Xtdcce2

ASJC Scopus subject areas

  • Mathematics (miscellaneous)

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