New Publication: The impact of job stability on monetary poverty in Italy: Causal small area estimation

Katarzyna Reluga, Dehan Kong, Setareh Ranjbar, Nicola Salvati, and Mark van der Laan have published their article The impact of job stability on monetary poverty in Italy: Causal small area estimation in the Journal of the American Statistical Association.

Abstract:

Job stability – encompassing secure contracts, adequate wages, social benefits, and career opportunities – is a critical determinant in reducing monetary poverty, as it provides households with reliable income and enhances economic well-being. This study draws on EU-SILC survey and census data to estimate the causal effect of job stability on monetary poverty across Italian provinces, quantifying its influence, and analyzing regional disparities. We introduce a novel causal small area estimation (CSAE) framework that integrates global and local estimation strategies for heterogeneous treatment effect estimation, effectively addressing data sparsity at the provincial level. Furthermore, we develop a general bootstrap scheme to construct reliable confidence intervals, applicable regardless of the method used for estimating nuisance parameters. Extensive simulation studies demonstrate that our proposed estimators outperform classical causal inference methods in terms of stability while maintaining computational scalability for large datasets. Applying this methodology to real-world data, we uncover significant relationships between job stability and poverty in six Italian regions, offering critical insights into regional disparities and their implications for evidence-based policy design.