In December 2025, Matic Verbič from University of Ljubljana (Slovenia) attended the 2nd International PhD Research Symposium organised by the ACE Association (Alliance of Chinese and European Business Schools Network) in Xiamen (China) to present his work on Statistical Matching of Income and Consumption data for Gendered Analysis in Ageing European Societies. The research covers 23 EU Countries analysing demographic, socioeconomic and geographic data from 2008 to 2018 period. It provides the “first systematic, multi-country integrated analysis of income and consumption micrdata revealing how gender inequalities in aging crystallise through mechanisms which are invisible in single-source data”. It successfully integrates the EU-SILC and HBS datasets and provides harmonised micro-level data allowing a detailed gender analysis across the life cycle. The approach also captures critical heterogeneity related to age and household composition that often remains hidden in aggregate-level analysis.
By developing a statistical matching framework that integrates EU statistics on income and living conditions (EU-SILC), income data with Household Budget Survey (HBS) consumption data, it enables a comprehensive gender analysis across European countries. Since income and consumption information are rarely available together in a single microdata source, previous approaches relied on imputing age and gender specific averages, which limited analytical precision. The methodological workflow includes harmonisation of socio-demographic variables such as age, gender, household structure, housing tenure and income quintile, alongside systematic treatment of measurement errors and missing data.
Diagnostic assessments confirm robust covariate balance for both men and women. The consumption patterns observed in the original HBS data closely align with those in the matched HBS datasets, indicating that the integrated microdata reliably preserves key consumption characteristics. The resulting harmonised microdata captures critical heterogeneity related to age and household composition that often remains hidden in aggregate statistics, enabling clearer analysis of economic differences between men and women throughout the life course. This reproducible framework demonstrates that high-quality integrated microdata can be achieved using existing European surveys, offering a practical template for future gender and age-related socio-economic research.
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