select_observations_to_be_trimmed

This function implements the trimming rule proposed by Huber, Lechner,
and Wunsch (2014). Observations above the trimming threshold are trimmed in
the reference group and in the comparison group. Per default, the timming
is set to sqrt(N)/N, where N is the number of observation in the reweighted
reference group. The function returns vector index of observation to be trimmed.

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

select_observations_to_be_trimmed function

<dl><dt>reweighting_factor</dt>
<dd>Estimated reweigting factor</dd>
<dt>group_variable</dt>
<dd>Variable identifying the reference and comparison group, respectively.</dd>
<dt>group</dt>
<dd>Identifier of reference group</dd>
<dt>trimming_threshold</dt>
<dd>threshold defining the maximal accepted relative weight of a reweighting factor/observation. If `NULL`, the threshold is set to `sqrt(N)/N`, where N is the number of observations in the reference group.</dd></dl>

Arguments

Select observations with little common support to be trimmed — select_observations_to_be_trimmed

<dl>

<dt>reweighting_factor</dt>
<dd>Estimated reweigting factor</dd>


<dt>group_variable</dt>
<dd>Variable identifying the reference and comparison group, respectively.</dd>


<dt>group</dt>
<dd>Identifier of reference group</dd>


<dt>trimming_threshold</dt>
<dd>threshold defining the maximal accepted relative weight of a reweighting factor/observation. If `NULL`, the threshold is set to `sqrt(N)/N`, where N is the number of observations in the reference group.</dd>

</dl>

select_observations_to_be_trimmed: Select observations with little common support to be trimmed

Description

Usage

Arguments