eusilcA_smpAgg

The data set is a simple random sample of data set <code>eusilcA_pop</code>
which is based on <code>eusilcP</code> from package
simFrame. The data set is aggregated on the district level and contains
different variables that are related to income and a regional variable for
the districts.

datasets

Functions that support estimating, assessing and mapping regional
disaggregated indicators. So far, estimation methods comprise direct estimation,
the model-based unit-level approach Empirical Best Prediction (see "Small area
estimation of poverty indicators" by Molina and Rao (2010) <doi:10.1002/cjs.10051>),
the area-level model (see "Estimates of income for small places: An
application of James-Stein procedures to Census Data" by Fay and Herriot (1979)
<doi:10.1080/01621459.1979.10482505>) and various extensions of it (adjusted variance
estimation methods, log and arcsin transformation, spatial, robust and measurement
error models), as well as their precision estimates. The assessment of the used model
is supported by a summary and diagnostic plots. For a suitable presentation of
estimates, map plots can be easily created. Furthermore, results can easily be
exported to excel. For a detailed description of the package and the methods used
see "The R Package emdi for Estimating and Mapping Regionally Disaggregated Indicators"
by Kreutzmann et al. (2019) <doi:10.18637/jss.v091.i07> and the second package vignette
"A Framework for Producing Small Area Estimates Based on Area-Level Models in R".

Soeren Pannier

emdi

Estimating and Mapping Disaggregated Indicators

Sylvia Harmening

Ann-Kristin Kreutzmann

Felix Skarke

Natalia Rojas-Perilla

Nicola Salvati

Timo Schmid

Matthias Templ

Nikos Tzavidis

Nora Würz

eusilcA_smpAgg function

A data frame with 94 observations and 8 variables:<dl>
<dt>Mean</dt>
<dd>numeric; mean of a simplified version of the equivalized
household income.</dd><dt>MTMED</dt>
<dd>numeric; share of households who earn more than the national
median income.</dd><dt>Cash</dt>
<dd>numeric; mean of employee cash or near cash income.</dd><dt>Var_Mean</dt>
<dd>numeric; variance of a simplified version of the equivalized
household income.</dd><dt>Var_MTMED</dt>
<dd>numeric; variance of the share of households who earn more
than the national median income.</dd><dt>Var_Cash</dt>
<dd>numeric; variance of the employee cash or near cash income.</dd><dt>n</dt>
<dd>numeric; effective sample sizes.</dd><dt>Domain</dt>
<dd>factor; Austrian districts (94 levels).</dd>
</dl>

Format

Simulated eusilc data - aggregated sample data — eusilcA_smpAgg

A data frame with 94 observations and 8 variables:<dl>
<dt>Mean</dt>
<dd>numeric; mean of a simplified version of the equivalized
household income.</dd>

<dt>MTMED</dt>
<dd>numeric; share of households who earn more than the national
median income.</dd>

<dt>Cash</dt>
<dd>numeric; mean of employee cash or near cash income.</dd>

<dt>Var_Mean</dt>
<dd>numeric; variance of a simplified version of the equivalized
household income.</dd>

<dt>Var_MTMED</dt>
<dd>numeric; variance of the share of households who earn more
than the national median income.</dd>

<dt>Var_Cash</dt>
<dd>numeric; variance of the employee cash or near cash income.</dd>

<dt>n</dt>
<dd>numeric; effective sample sizes.</dd>

<dt>Domain</dt>
<dd>factor; Austrian districts (94 levels).</dd>


</dl>

Simulated eusilc data - aggregated sample data

eusilcA_smpAgg: Simulated eusilc data - aggregated sample data

Description

Usage

Arguments

Format