nopodec_mean | R Documentation |
The results are all the components necessary to perform a decomposition of the average wage difference between two groups, in four components (as in Nopo (2004)).
nopodec_mean(...)
## Default S3 method:
nopodec_mean(.reweight_strata_all, y = NULL, weights = NULL, ...)
## S3 method for class 'reweighted'
nopodec_mean(.reweighted, ...)
... |
arguments passed to or from other methods. |
.reweight_strata_all |
output of |
y |
name of the outcome variable for which you want to make the decomposition. If NULL (default), the value is inherited from the attributes of |
weights |
name of the weight variable (sample weights). If NULL (default), the value is inherited from the attributes of |
.reweighted |
an object of class |
A data frame with two, three or four rows, with the following columns:
the name of the treatment column used in reweight_strata_all2
;
common_support
logical indicating if in or out the common support;
ybar
average of the y variable, weighted by the given weights;
ybar_C_A
counterfactual average y of group A as if they had the same distribution of characteristics of group B. This is computed in the common support only and for group A individuals. It is computed with the weights w_AB
that result from reweight_strata_all2
;
ybar_C_B
counterfactual average y of group B as if they had the same distribution of characteristics of group A. This is computed in the common support only and for group B individuals. It is computed with the weights w_BA
that result from reweight_strata_all2
;
Nhat
estimate of the number of individuals.
The number of rows is given by the combinations of the distinct values of
the first two columns: treatment
and common_support
.
In the "typical" case, the resulting data frame will have 4 rows. It can have three rows if all the individuals of one group are in the common support.
In case of no common support or no out-of-support, the data frame will have two rows.
data(invented_wages)
r00 <- reweight_strata_all2(invented_wages, treatment = "gender",
variables = c("sector", "education"),
y = "wage", weights = "sample_weights")
nopodec_mean(r00)
data(invented_wages)
r00 <- reweight_strata_all4(invented_wages, treatment = "gender",
variables = c("sector", "education"),
y = "wage", weights = "sample_weights")
str(r00)
names(r00)
class(r00)
nopodec_mean(r00)
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