Abstract

The availability of multidimensional indicators on the economic resources and material deprivation of households is considered an indispensable tool for policies to combat poverty and inequality. However, the production of micro data on the joint distribution of household Income, Consumption and Wealth (ICW) continues to present many challenges. This paper highlights the production of experimental data on the joint distribution of ICW in Italy to fill the missing data gap through statistical matching of the surveys "EU Statistics on Income and Living Conditions - EU-SILC ", "Household Budget Survey - HBS” and “Survey on Household Income and Wealth - SHIW” of the Bank of Italy.
Since 2018, ISTAT and Bank of Italy started a close cooperation with the aim of creating a synthetic dataset in order to analyse the propensity to consume, to save, and asset-based poverty and wealth inequality. The paper describes the statistical matching methods applied by the Bank of Italy and ISTAT to produce experimental joint distributions of income, consumption and wealth. The Bank of Italy survey collects data on income, wealth, and information on consumption expenditures and after an adjustment of the collected income with fiscal data applies the hot deck procedures to impute the total consumption from HBS into SHIW.
The ISTAT method is more complex because it essentially proceeds with a double imputation: first, the total consumption from HBS and then it imputes the net wealth from SHIW, using a mixed method that takes into account the sampling weights. This is a well-known approach to the statistical matching of data from complex sample surveys modified to perform integration at the micro level and impute a continuous variable.
Finally, we present the results of the experimental ICW distributions and the quality assessment, which continues to be a crucial point for the estimates produced with statistical matching techniques.