Informal Labor Market in Pakistan: Evaluating the Effectiveness of Government Relief Programs using Econometrics and Machine Learning Approach

Abstract

This paper provides a comprehensive empirical analysis of the efficacy of social safety nets within Pakistan's labor market, with a specific focus on periods of significant economic shock. Utilizing a mixed-methods approach, we combine household-level microdata from the Pakistan Social and Living Standards Measurement (PSLM) surveys with administrative data on major relief programs, such as the Benazir Income Support Program (BISP). Our research assesses the targeting efficiency, coverage, and welfare impact of these transfers on key outcomes, including poverty headcount, consumption smoothing, and labor force participation. The findings reveal a critical paradox: while these programs provide essential relief to documented segments of the population, a significant efficacy gap exists due to Pakistan's vast informal sector. A substantial proportion of the most vulnerable, informal workers, remain systematically excluded from formal relief mechanisms, severely limiting the programs' overall protective capacity. The study concludes that the structural constraints of informality are a primary determinant of relief program effectiveness. We therefore recommend policy reforms aimed at integrating informal workers into the social protection framework through innovative targeting and delivery mechanisms to enhance resilience against future economic crises.