Centering and reference groups for estimates of fixed effects: Modifications to felsdvreg
Abstract. Availability of large, multilevel longitudinal databases in various fields
including labor economics (with workers and firms observed over time) and
education research (with students and teachers observed over time) has
increased the application of panel-data models with multiple levels of
fixed-effects. Existing software routines for fitting fixed-effects models
were not designed for applications in which the primary interest is
obtaining estimates of any of the fixed-effects parameters. Such routines
typically report estimates of fixed effects relative to arbitrary holdout
units. Contrasts to holdout units are not ideal in cases where the
fixed-effects parameters are of interest because they can change
capriciously, they do not correspond to the structural parameters that are
typically of interest, and they are inappropriate for empirical Bayes
(shrinkage) estimation. We develop an improved parameterization of
fixed-effects models using sum-to-zero constraints that provides estimates
of fixed effects relative to mean effects within well-defined reference
groups (e.g., all firms of a given type or all teachers of a given grade)
and provides standard errors for those estimates that are appropriate for
shrinkage estimation. We implement our parameterization in a Stata routine
called felsdvregdm by modifying the felsdvreg routine designed
for fitting highdimensional fixed-effects models. We demonstrate our routine
with an example dataset from the Florida Education Data Warehouse.
View all articles by these authors:
Kata Mihaly, Daniel F. McCaffrey, J. R. Lockwood, Tim R. Sass
View all articles with these keywords:
felsdvreg, felsdvregdm, fixed effects, linked employer–employee data, longitudinal achievement data
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