The impact of job stability on monetary poverty in Italy: causal small area estimation

TL;DR

This paper introduces a novel causal small area estimation framework to quantify how job stability affects monetary poverty across Italian provinces, addressing data sparsity and regional disparities.

Contribution

It develops a new CSAE method combining global and local strategies for heterogeneous treatment effect estimation with a bootstrap scheme for confidence intervals.

Findings

Significant link between job stability and poverty in Italy

Regional disparities in the impact of job stability

Proposed estimators outperform classical methods

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 leverages 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 across six Italian regions, offering critical insights into regional disparities and their implications for evidence-based policy design.