A random sample from the National Longitudinal Survey of Youth
NLSY79.2012feisr. It contains information on wages,
family status, and work experience for a random sample of men.
For a description of the original dataset and variable construction
see Ludwig.2018.0;textualfeisr.

datasets

Provides the function feis() to estimate fixed effects individual
slope (FEIS) models. The FEIS model constitutes a more general version of
the often-used fixed effects (FE) panel model, as implemented in the
package 'plm' by Croissant and Millo (2008) <doi:10.18637/jss.v027.i02>.
In FEIS models, data are not only person demeaned like in conventional
FE models, but detrended by the predicted individual slope of each
person or group. Estimation is performed by applying least squares lm()
to the transformed data. For more details on FEIS models see Bruederl and
Ludwig (2015, ISBN:1446252442); Frees (2001) <doi:10.2307/3316008>;
Polachek and Kim (1994) <doi:10.1016/0304-4076(94)90075-2>;
Ruettenauer and Ludwig (2020) <doi:10.1177/0049124120926211>;
Wooldridge (2010, ISBN:0262294354). To test consistency of conventional FE
and random effects estimators against heterogeneous slopes, the package
also provides the functions feistest() for an artificial regression test
and bsfeistest() for a bootstrapped version of the Hausman test.

Tobias Ruettenauer

feisr

Estimating Fixed Effects Individual Slope Models

Volker Ludwig

mwp function

A data frame with 3100 observations and 17 variables:<dl class="dl-horizontal">
 <dt>id</dt><dd>unique person identifier</dd>
 <dt>year</dt><dd>survey year</dd>
 <dt>lnw</dt><dd>natural log of hourly wage rate</dd>
 <dt>exp</dt><dd>work experience in current job, in years</dd>
 <dt>expq</dt><dd>work experience in current job squared</dd>
 <dt>marry</dt><dd>family status (=0 if not married, =1 if married)</dd>
 <dt>evermarry</dt><dd>indicator if ever married (=0 if never married, =1 if married at some point)</dd>
 <dt>enrol</dt><dd>current erolment in education (=0 not enroled, =1 enroled)</dd>
 <dt>yeduc</dt><dd>years of formal education</dd>
 <dt>age</dt><dd>respondents current age</dd>
 <dt>cohort</dt><dd>respondents birth cohort</dd>
 <dt>yeargr</dt><dd>grouped year (1=1979-1980, 2=1981-1985, 3=1986-1990, 4=1991-1995, 5=1996-2000)</dd>
 <dt>yeargr1</dt><dd>dummy indicating grouped year=1</dd>
 <dt>yeargr2</dt><dd>dummy indicating grouped year=2</dd>
 <dt>yeargr3</dt><dd>dummy indicating grouped year=3</dd>
 <dt>yeargr4</dt><dd>dummy indicating grouped year=4</dd>
 <dt>yeargr5</dt><dd>dummy indicating grouped year=5</dd>
</dl>

Format

Panel data including wages and family status — mwp

A data frame with 3100 observations and 17 variables:<dl class='dl-horizontal'>
 <dt>id</dt><dd>unique person identifier</dd>
 <dt>year</dt><dd>survey year</dd>
 <dt>lnw</dt><dd>natural log of hourly wage rate</dd>
 <dt>exp</dt><dd>work experience in current job, in years</dd>
 <dt>expq</dt><dd>work experience in current job squared</dd>
 <dt>marry</dt><dd>family status (=0 if not married, =1 if married)</dd>
 <dt>evermarry</dt><dd>indicator if ever married (=0 if never married, =1 if married at some point)</dd>
 <dt>enrol</dt><dd>current erolment in education (=0 not enroled, =1 enroled)</dd>
 <dt>yeduc</dt><dd>years of formal education</dd>
 <dt>age</dt><dd>respondents current age</dd>
 <dt>cohort</dt><dd>respondents birth cohort</dd>
 <dt>yeargr</dt><dd>grouped year (1=1979-1980, 2=1981-1985, 3=1986-1990, 4=1991-1995, 5=1996-2000)</dd>
 <dt>yeargr1</dt><dd>dummy indicating grouped year=1</dd>
 <dt>yeargr2</dt><dd>dummy indicating grouped year=2</dd>
 <dt>yeargr3</dt><dd>dummy indicating grouped year=3</dd>
 <dt>yeargr4</dt><dd>dummy indicating grouped year=4</dd>
 <dt>yeargr5</dt><dd>dummy indicating grouped year=5</dd>
</dl>

mwp: Panel data including wages and family status

Description

Usage

Arguments

Format

References