men8305

A sample of the the Merged Outgoing Rotation Group of the
Current Population Survey from 1983 to 1985 and 2003 to 2005, respectively,
used as example by Fortin, Lemieux &amp; Firpo (2011) in their handbook chapter.
The data set contains a selection of 8 variables and a sample of 40,347 observations
of male workers (i.e., a tenth of the origninal data set).

datasets

Implements the Oaxaca-Blinder decomposition method and generalizations of it that decompose differences in distributional statistics beyond the mean.
The function ob_decompose() decomposes differences in the mean outcome between two groups into one part explained by different covariates (composition effect) and into another part due to differences in the way covariates are linked to the outcome variable (structure effect). The function further divides the two effects into the contribution of each covariate and allows for weighted doubly robust decompositions. For distributional statistics beyond the mean, the function performs the recentered influence function (RIF) decomposition proposed by Firpo, Fortin, and Lemieux (2018).
The function dfl_decompose() divides differences in distributional statistics into an composition effect and a structure effect using inverse probability weighting as introduced by DiNardo, Fortin, and Lemieux (1996). The function also allows to sequentially decompose the composition effect into the contribution of single covariates.
References:
Firpo, Sergio, Nicole M. Fortin, and Thomas Lemieux. (2018) <doi:10.3390/econometrics6020028>. "Decomposing Wage Distributions Using Recentered Influence Function Regressions."
Fortin, Nicole M., Thomas Lemieux, and Sergio Firpo. (2011) <doi:10.3386/w16045>. "Decomposition Methods in Economics."
DiNardo, John, Nicole M. Fortin, and Thomas Lemieux. (1996) <doi:10.2307/2171954>. "Labor Market Institutions and the Distribution of Wages, 1973-1992: A Semiparametric Approach."
Oaxaca, Ronald. (1973) <doi:10.2307/2525981>. "Male-Female Wage Differentials in Urban Labor Markets."
Blinder, Alan S. (1973) <doi:10.2307/144855>. "Wage Discrimination: Reduced Form and Structural Estimates."

Samuel Meier

ddecompose

Detailed Distributional Decomposition

men8305 function

A data frame with 40,347 rows and 8 variables.<dl>
 <dt>wage</dt>
<dd>Hourly wage in US dollars at constant prices</dd> <dt>union</dt>
<dd>Union status indicator</dd> <dt>education</dt>
<dd>Factor variable with 6 education levels: high-school graduates (reference), elementary, high-school dropouts , some college, college graduates, post college graduates</dd> <dt>experience</dt>
<dd>Factor variable with 9 potential experience levels, each of five years gap, 20 to 24 years as reference level)</dd> <dt>married</dt>
<dd>Married indicator</dd> <dt>nonwhite</dt>
<dd>Non-white indicator</dd> <dt>year</dt>
<dd>Indicator distinguishing pooled observations from the 1983 to 1985 period and those from 2003 to 2005</dd> <dt>weights</dt>
<dd>CPS sample weights</dd>
</dl>

Format

Sample of male wage data from the CPS 1983-1985 and 2003-2005 — men8305

A data frame with 40,347 rows and 8 variables.<dl>
 <dt>wage</dt>
<dd>Hourly wage in US dollars at constant prices</dd>

 <dt>union</dt>
<dd>Union status indicator</dd>

 <dt>education</dt>
<dd>Factor variable with 6 education levels: high-school graduates (reference), elementary, high-school dropouts , some college, college graduates, post college graduates</dd>

 <dt>experience</dt>
<dd>Factor variable with 9 potential experience levels, each of five years gap, 20 to 24 years as reference level)</dd>

 <dt>married</dt>
<dd>Married indicator</dd>

 <dt>nonwhite</dt>
<dd>Non-white indicator</dd>

 <dt>year</dt>
<dd>Indicator distinguishing pooled observations from the 1983 to 1985 period and those from 2003 to 2005</dd>

 <dt>weights</dt>
<dd>CPS sample weights</dd>


</dl>

men8305: Sample of male wage data from the CPS 1983-1985 and 2003-2005

Description

Usage

Arguments

Format