Statistical imputation and validation of consumption microdata for EUROMOD

Consumption taxes are a crucial revenue source for EU Member States, yet they also potentially have non-negligible impact on income distribution. The EU's tax-benefit microsimulation model, EUROMOD, has recently been extended to simulate consumption taxes (CT) across all 27 EU countries allowing researchers and practitioners to examine carefully their design and assess trade-offs. The CT simulation uses consumption patterns derived from Household Budget Survey (HBS) microdata, which are imputed into EUROMOD's input data using the European Union Statistics on Income and Living Conditions (EU-SILC) microdata which contains detailed socio-demographic and socio-economic information. The imputation process employs a statistical matching procedure that joins HBS (the donor survey) with EU-SILC (the recipient survey) using a predictive mean matching method. Expenditure data are integrated into the recipient survey using a multi-stage procedure that involves the use of estimated probit and linear regression models combined with a distance-hot deck approach for the final observation mapping. This methodology offers enhanced results compared to traditional approaches such as only regression-based or distance-based. The imputation performance in distributional terms and the macro validation of the resulting datasets are thoroughly examined. We assess the impact of potential distortions from the statistical matching process by conducting a set of exploratory and comparative analyses, and also by using an administratively matched dataset for Czechia from 2019 to 2021. Our findings in this specific case indicate that, on average, the majority of imputed expenses are exactly the same when comparing the original HBS data with the matched SILC data that includes fitted expenditures.