Assessing the impact of COVID‐19 and related interventions on poverty and economic growth in Pakistan: A structural path analysis

Abstract

This study uses social accounting matrix multipliers and structural path analyses to estimate effects of COVID‐19 and related fiscal stimuli on five household groups. The COVID‐19 lockdown increased poverty in Pakistan by 15%, which was addressed using a $1.5 billion, digitally implemented Ehsaas Emergency Cash (EEC) program that reached 14.8 million poor households. The study's models show that the largest multipliers from Ehsaas program finance were in agriculture, as a 1 Rupee shock adds 0.225 Rupee income to households. About 30% of that gain was estimated to go to poor farm families. In contrast, our models find that construction and trade growth added three times as much income to poor nonfarm and urban households as to farm households. However, those sectors added only one third as much total income as agriculture. From the structural path analysis, the importance of capital assets in generating income was seen, as was the possibility of greater poverty reduction from sectors with proportionally fewer intermediate inputs and more value added.

Lessons from a time of upheaval: COVID‐19 in South Asia

“…Modeling approaches like Social Accounting Matrices and Computable General Equilibrium models can predict consequences for growth and distribution, sectoral impacts, and impacts across different types of households and enterprises. In this issue, Boughton et al (2023), Davies et al (2023), Ecker et al (2023) and Dorosh et al (2023) use these methods. Additionally, models of the spread of the disease itself can enable policymakers to better direct their limited resources.…”

“…Khan et al (2023) attempt to obtain subnational estimates of COVID-19 exposure to estimate how many are likely to be affected by the pandemic, which would help governments better prepare to support and identify geographies for targeting. Davies et al (2023) document the Ehsaas program that leveraged a 2008 transfer program called the Benazir Income Support Programme (BISP).…”

“…They model the potential impact of five hypothetical social protection interventions in Myanmar and Bangladesh and note that the mitigation effects of cash transfer, in-kind food transfer, and food voucher programs with a typical monetary value ($13 per-household per-month) and common population coverage is expected to be quite modest in terms of dietary and nutritional outcomes but could be substantially increased through food fortification. Davies et al (2023) compare the relative benefits and distributional consequences of cash transfers and a rural construction program in Pakistan.…”

“…The targeting and identification of beneficiaries and the new poor might inadvertently lead to exclusion errors, whereby deserving individuals are denied access to benefits. Davies et al (2023) note the challenges of the Pakistani Government to identify the new poor for the enhanced cash transfer program. In contrast, Varshney and Meenakshi (2023) highlight the potential of the MGNREGA, a universal scheme that self-selects participants without the state trying to identify and target individual beneficiaries.…”

“…insights into the medium-and longer-term economic impacts of the pandemic, including when coupled with other shocks as was the case in Myanmar. Boughton et al (2023) and Davies et al (2023) further explore the role and distributional consequences of social protection.…”