| feisr-package {feisr} | R Documentation |
Estimating Fixed Effects Individual Slope Models
Description
The main purpose of the package feisr is the estimation of fixed
effects individual slopes models and respective test statistics.
The fixed effects individual slopes (FEIS) estimator is a more general
version of the well-known fixed effects estimator (FE), which allows to
control for heterogeneous slopes in addition to time-constant heterogeneity
(Bruederl and Ludwig 2015; Ruettenauer and Ludwig 2020; Wooldridge 2010).
This is done by running an lm() model on pre-transformed data, where
we (1) estimate the individual-specific predicted values for the dependent
variable and each covariate based on an individual intercept and the additional
slope variables, (2) detrend the original data by these individual-specific
predicted values, and (3) run an OLS model on the residual data. The package
also provides two specification test for heterogeneous slopes
(more details and examples can be found in Ruettenauer and Ludwig 2020).
Details
The main functions of the feisr package are:
- feis(): fixed effects individual slopes estimator by
applying lm to detrended data.
- feistest(): regression-based Hausman test for fixed effects
individual slope models.
- bsfeistest(): bootstrapped Hausman test for fixed effects
individual slope models.
The functions included in the R package feisr are also available in the
xtfeis ado (https://ideas.repec.org/c/boc/bocode/s458045.html)
for Stata. The plm-package provides functions
for estimation of related models, like the mean group (MG) or common
correlated effects mean groups (CCEMG) estimator via pmg or
models with variable coefficients via pvcm.
Author(s)
Tobias Ruettenauer
Volker Ludwig
References
Bruederl J, Ludwig V (2015).
“Fixed-Effects Panel Regression.”
In Best H, Wolf C (eds.), The Sage Handbook of Regression Analysis and Causal Inference, 327–357.
Sage, Los Angeles.
ISBN 1446252442.
Ruettenauer T, Ludwig V (2020).
“Fixed Effects Individual Slopes: Accounting and Testing for Heterogeneous Effects in Panel Data or Other Multilevel Models.”
Sociological Methods and Research, OnlineFirst.
ISSN 0049-1241, doi: 10.1177/0049124120926211.
Wooldridge JM (2010).
Econometric Analysis of Cross Section and Panel Data.
MIT Press, Cambridge, Mass.
ISBN 0262294354.