GU_normalization

The function performs the normalization of the factor variables
proposed by Gardeazabal and Ugidos (2004, GU) to estimate detailed decompositions
that do not depend on the chosen reference levels of the factor variables.

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

GU_normalization function

<dl><dt>formula</dt>
<dd>an object of class "formula". See <a href="/link/lm?package=ddecompose&version=1.0.0" data-mini-rdoc="ddecompose::lm">lm</a> for further details.</dd>
<dt>data</dt>
<dd>a data frame containing the variables in the model.</dd>
<dt>weights</dt>
<dd>numeric vector of non-negative observation weights, hence of same length as <code>dep_var</code>.</dd>
<dt>group</dt>
<dd>name of the a binary variable (numeric or factor) identifying the two groups that will be compared.</dd></dl>

Arguments

Gardeazabal and Ugidos normalization of factor variables — GU_normalization

<dl>

<dt>formula</dt>
<dd>an object of class "formula". See <a href='https://rdrr.io/r/stats/lm.html'>lm</a> for further details.</dd>


<dt>data</dt>
<dd>a data frame containing the variables in the model.</dd>


<dt>weights</dt>
<dd>numeric vector of non-negative observation weights, hence of same length as <code>dep_var</code>.</dd>


<dt>group</dt>
<dd>name of the a binary variable (numeric or factor) identifying the two groups that will be compared.</dd>

</dl>

GU_normalization: Gardeazabal and Ugidos normalization of factor variables

Description

Usage

Value

Arguments

References

Examples