A review of Stata commands for fixed-effects estimation in normal linear models
Abstract. Availability of large multilevel longitudinal databases in various fields of
research, including labor economics (with workers and firms observed over
time) and education (with students, teachers, and schools observed over time),
has increased the application of models with one level or multiple levels of
fixed effects (for example, teacher and student effects). There has been a
corresponding rapid development of Stata commands designed for fitting these
types of models. The commands parameterize the fixed-effects portions of
models differently. In cases where estimates of the fixed-effects parameters
are of interest, it is critical to understand precisely what parameters are
being estimated by different commands. In this article, we catalog the
estimates of reported fixed effects provided by different commands for several
canonical cases of both one-level and two-level fixed-effects models. We also
discuss issues regarding computational efficiency and standard-error
estimation.
View all articles by these authors:
Daniel F. McCaffrey, J. R. Lockwood, Kata Mihaly, Tim R. Sass
View all articles with these keywords:
longitudinal data, linked employer–employee data, fixed-effects estimators, regress, areg, a2reg, gpreg, reg2hdfe, xtreg, fese, felsdvregdm, software review
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