eusilcA_pop

The data set is synthetic EU-SILC data based on the data set
<code><a rd-options="simFrame" href="/link/eusilcP?package=emdi&version=1.1.1&to=simFrame" data-mini-rdoc="simFrame::eusilcP">eusilcP</a></code> from package simFrame. The data set is 
reduced to 17 variables containing three regional variables for the states, 
districts and counties.

datasets

Functions that support estimating, assessing and mapping regional
disaggregated indicators. So far, estimation methods comprise direct estimation
and the model-based approach Empirical Best Prediction (see "Small area
estimation of poverty indicators" by Molina and Rao (2010) <doi:10.1002/cjs.10051>),
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.

Soeren Pannier

emdi

Estimating and Mapping Disaggregated Indicators

Ann-Kristin Kreutzmann

Natalia Rojas-Perilla

Timo Schmid

Matthias Templ

Nikos Tzavidis

eusilcA_pop function

A data frame with 25000 observations and 17 variables:<dl class="dl-horizontal">
<dt>eqIncome</dt><dd>numeric; a simplified version of the equivalized household income.</dd>
<dt>eqsize</dt><dd>numeric; the equivalized household size according to the 
modified OECD scale.</dd>
<dt>gender</dt><dd>factor; the person's gender (levels male and female).</dd>
<dt>cash</dt><dd>numeric; employee cash or near cash income (net).</dd>
<dt>self_empl</dt><dd>numeric; cash benefits or losses from self-employment (net).</dd>
<dt>unempl_ben</dt><dd>numeric; unemployment benefits (net).</dd>
<dt>age_ben</dt><dd>numeric; old-age benefits (net).</dd>
<dt>surv_ben</dt><dd>numeric; survivor's benefits (net).</dd>
<dt>sick_ben</dt><dd>numeric; sickness benefits (net).</dd>
<dt>dis_ben</dt><dd>numeric; disability benefits (net).</dd>
<dt>rent</dt><dd>numeric; income from rental of a property or land (net).</dd>
<dt>fam_allow</dt><dd>numeric; family/children related allowances (net).</dd>
<dt>house_allow</dt><dd>numeric; housing allowances (net).</dd>
<dt>cap_inv</dt><dd>numeric; interest, dividends, profit from capital investments
 in unincorporated business (net).</dd>
<dt>tax_adj</dt><dd>numeric; repayments/receipts for tax adjustment (net).</dd>
<dt>state</dt><dd>factor; state (nine levels)</dd>
<dt>district</dt><dd>factor; districts (96 levels)</dd>
</dl>

Format

The data set is synthetic EU-SILC data based on the data set
<code><a rd-options='simFrame' href='eusilcP'>eusilcP</a></code> from package simFrame. The data set is 
reduced to 17 variables containing three regional variables for the states, 
districts and counties.

Simulated eusilc data - population data — eusilcA_pop

A data frame with 25000 observations and 17 variables:<dl class='dl-horizontal'>
<dt>eqIncome</dt><dd>numeric; a simplified version of the equivalized household income.</dd>
<dt>eqsize</dt><dd>numeric; the equivalized household size according to the 
modified OECD scale.</dd>
<dt>gender</dt><dd>factor; the person's gender (levels male and female).</dd>
<dt>cash</dt><dd>numeric; employee cash or near cash income (net).</dd>
<dt>self_empl</dt><dd>numeric; cash benefits or losses from self-employment (net).</dd>
<dt>unempl_ben</dt><dd>numeric; unemployment benefits (net).</dd>
<dt>age_ben</dt><dd>numeric; old-age benefits (net).</dd>
<dt>surv_ben</dt><dd>numeric; survivor's benefits (net).</dd>
<dt>sick_ben</dt><dd>numeric; sickness benefits (net).</dd>
<dt>dis_ben</dt><dd>numeric; disability benefits (net).</dd>
<dt>rent</dt><dd>numeric; income from rental of a property or land (net).</dd>
<dt>fam_allow</dt><dd>numeric; family/children related allowances (net).</dd>
<dt>house_allow</dt><dd>numeric; housing allowances (net).</dd>
<dt>cap_inv</dt><dd>numeric; interest, dividends, profit from capital investments
 in unincorporated business (net).</dd>
<dt>tax_adj</dt><dd>numeric; repayments/receipts for tax adjustment (net).</dd>
<dt>state</dt><dd>factor; state (nine levels)</dd>
<dt>district</dt><dd>factor; districts (96 levels)</dd>
</dl>

eusilcA_pop: Simulated eusilc data - population data

Description

Usage

Arguments

Format