Estimating dynamic common-correlated effects in Stata

被引:202
作者
Ditzen, Jan [1 ,2 ]
机构
[1] Heriot Watt Univ, Ctr Energy Econ Res & Policy, Edinburgh, Midlothian, Scotland
[2] Heriot Watt Univ, Spatial Econ & Econometr Ctr, Edinburgh, Midlothian, Scotland
关键词
st0536; xtdcce2; xtcd2; parameter heterogeneity; dynamic panels; cross-section dependence; common correlated effects; pooled mean group estimator; mean group estimator; instrumental variables; ivreg2; SLOPE HOMOGENEITY; GROWTH EMPIRICS; DEPENDENCE; MODELS; PANELS;
D O I
10.1177/1536867X1801800306
中图分类号
O1 [数学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 0701 ; 070101 ;
摘要
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.
引用
收藏
页码:585 / 617
页数:33
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