2023-05-24-IMF-新冠肺炎期间的汇款和社会安全网_来自格鲁吉亚和吉尔吉斯斯坦共和国的证据（英）_27页_712kb

Remittances and Social Safety Nets during COVID-19: Evidence from Georgia and the Kyrgyz Republic

Overview
This working paper analyzes how COVID-19 impacted remittance flows and household incomes in Georgia and the Kyrgyz Republic, examining heterogeneity across income groups and the role of social safety nets. Remittances remained resilient during the pandemic but affected households differently, with outcomes heavily influenced by social protection systems.

Key Findings

1. Remittance Resilience and Initial Impact:

   • Global remittances proved resilient during the pandemic, but their impact varied by country.
   • In Georgia, remittances recovered by mid-2020, while in the Kyrgyz Republic, they did not bounce back to pre-pandemic levels.

2. Income Distribution Effects:

   • Georgia: Wealthier remittance-receiving households experienced larger income declines compared to non-receivers, while poorer remittance-receiving households saw less severe impacts, partly due to effective social transfers.
   • Kyrgyz Republic: Poorer remittance-receiving households were more adversely affected, while wealthier households showed no significant difference from non-receivers.

3. Social Safety Nets:

   • Georgia’s social transfers mitigated income losses for poor remittance-receiving households, while the Kyrgyz Republic’s systems were insufficient, exacerbating income shocks.

4. Country-Specific Factors:

   • Restrictions in remittance-sending countries (e.g., Russia for Kyrgyz Republic vs. European nations for Georgia) influenced remittance flows but social protections played a decisive role in cushioning economic fallout.

Policy Implications

• Strengthen social safety nets, improve targeting, and ensure timely transfers to protect vulnerable households during economic shocks.
• Enhance digitalization and reduce costs of remittance services to improve resilience.
• Integrate social programs into a unified registry to improve efficiency and reach.

Methodology
The analysis uses longitudinal household panel data and a difference-in-differences approach to isolate pandemic impacts, accounting for pre-existing vulnerabilities and policy responses.