A0457
Title: Causal small area estimation: The impact of job stability on monetary poverty in Italy
Authors: Setareh Ranjbar - Lausanne University Hospital , University of Lausanne (Switzerland) [presenting]
Katarzyna Reluga - University of Bristol (United Kingdom)
Nicola Salvati - University of Pisa (Italy)
Dehan Kong - University of Toronto (Canada)
Mark van der Laan - University of California at Berkeley (United States)
Abstract: Job stability refers to the security and predictability of employment, including factors such as long-term contracts, adequate wages, social security benefits, and access to training and career development opportunities. Stable employment can play a crucial role in reducing poverty, as it provides individuals and households with a stable income as well as improves their overall and subjective economic well-being. EU-SILC survey and census data are leveraged to assess the causal effect of job stability on monetary poverty across provinces in Italy. To this end, a causal small area estimation (CSAE) framework is proposed for heterogeneous treatment effect estimation in which only a negligible fraction of outcomes is actually observed at the provincial level. The estimators are more stable than the classical causal inference tools as they borrow strength from the other sources of data at the expense of some model assumptions. In a series of model-based and design-based simulations, the influence of different model assumptions on the performance of the proposed algorithm is compared. The new methodology proves to be successful in recovering provincial heterogeneity of the effect of job stability across six regions in Italy.
