Consumption

This dataset is a subset from the 2016 Survey on Household Income and Wealth data, a statistical survey conducted by the Bank of Italy. The statistical units are the households and the head of the household is conventionally selected as the major income earner.

Functions to fit regression models for bounded continuous and discrete responses. In case of bounded continuous responses (e.g., proportions and rates), available models are the flexible beta (Migliorati, S., Di Brisco, A. M., Ongaro, A. (2018) <doi:10.1214/17-BA1079>), the variance-inflated beta (Di Brisco, A. M., Migliorati, S., Ongaro, A. (2020) <doi:10.1177/1471082X18821213>), the beta (Ferrari, S.L.P., Cribari-Neto, F. (2004) <doi:10.1080/0266476042000214501>), and their augmented versions to handle the presence of zero/one values (Di Brisco, A. M., Migliorati, S. (2020) <doi:10.1002/sim.8406>) are implemented. In case of bounded discrete responses (e.g., bounded counts, such as the number of successes in n trials), available models are the flexible beta-binomial (Ascari, R., Migliorati, S. (2021) <doi:10.1002/sim.9005>), the beta-binomial, and the binomial are implemented. Inference is dealt with a Bayesian approach based on the Hamiltonian Monte Carlo (HMC) algorithm (Gelman, A., Carlin, J. B., Stern, H. S., Rubin, D. B. (2014) <doi:10.1201/b16018>). Besides, functions to compute residuals, posterior predictives, goodness of fit measures, convergence diagnostics, and graphical representations are provided.

Roberto Ascari

FlexReg

Regression Models for Bounded Continuous and Discrete Responses

Consumption function

A <code>data.frame</code> containing 568 observations on the following 8 variables:<dl>
<dt><code>NComp</code></dt>
<dd>the number of household members.</dd><dt><code>Sex</code></dt>
<dd>the sex of the head of the household.</dd><dt><code>Age</code></dt>
<dd>the age of the head of the household.</dd><dt><code>NEarners</code></dt>
<dd>the number of household income earners.</dd><dt><code>Area</code></dt>
<dd>a factor indicating the geographical area where the household is located.</dd><dt><code>Citizenship</code></dt>
<dd>a factor indicating the citizenship of the head of household.</dd><dt><code>Income</code></dt>
<dd>the net disposable income.</dd><dt><code>Consumption</code></dt>
<dd>the propensity to consume, defined as the percentage of <code>Income</code> that is spent rather than saved.</dd>
</dl>

Format

Italian Households Consumption data — Consumption

A <code>data.frame</code> containing 568 observations on the following 8 variables:<dl>
<dt><code>NComp</code></dt>
<dd>the number of household members.</dd>

<dt><code>Sex</code></dt>
<dd>the sex of the head of the household.</dd>

<dt><code>Age</code></dt>
<dd>the age of the head of the household.</dd>

<dt><code>NEarners</code></dt>
<dd>the number of household income earners.</dd>

<dt><code>Area</code></dt>
<dd>a factor indicating the geographical area where the household is located.</dd>

<dt><code>Citizenship</code></dt>
<dd>a factor indicating the citizenship of the head of household.</dd>

<dt><code>Income</code></dt>
<dd>the net disposable income.</dd>

<dt><code>Consumption</code></dt>
<dd>the propensity to consume, defined as the percentage of <code>Income</code> that is spent rather than saved.</dd>


</dl>

Consumption: Italian Households Consumption data

Description

Arguments

Format

Details