世界银行-基于登记的贫困和社会排斥测量（英）-2024-130页_2mb

Summary Report: Poverty and Social Exclusion Measurement in Croatia

Introduction
Croatia faces persistent pockets of poverty despite overall improvements, with demographic groups such as the Roma experiencing disproportionately high poverty rates. The country is shifting from survey-based to register-based data collection to enhance granularity and timeliness. The MLPSFSP is tasked with developing a methodology to monitor poverty and social exclusion at subnational levels (NUTS 3 and LAU), leveraging administrative data sources.

Methodology and Data Sources

• EU Framework: Poverty is measured using the AROP (At Risk of Poverty) and AROPE (At Risk of Poverty or Social Exclusion) rates, based on the EU-SILC survey. Eurostat defines these metrics and harmonizes methodologies across EU countries.
• Administrative Data: Croatia’s population census and administrative databases (e.g., Tax Income system) are underutilized due to missing household identifiers (apartment IDs) and incomplete kinship links. The upcoming Central Population Register aims to address these gaps by integrating nationwide data sources.
• Challenges:
  • Incomplete income components in tax and register data (e.g., self-employment expenses).
  • Underreporting of income, limiting the accuracy of disposable income calculations.
  • Diverging methodologies between surveys and registers, leading to two sets of poverty indicators.

Recommendations for Poverty and Social Exclusion Measurement

• Imputation Techniques: Use regression or predictive mean matching (PMM) to impute missing income data, ensuring plausible expense estimates.
• AROPE-Simplified Rate: Incorporate employment and income data to streamline AROPE calculations, accounting for regional variations in spending.
• Social Exclusion Indicators:
  • Domains: Cover household income (e.g., disposable income, poverty rates), labor market access, education, health, demography, and infrastructure.
  • Methods: Utilize administrative data (e.g., Tax Income, Population Register) and targeted surveys to address gaps, such as incidents of violence or specific vulnerable populations.

Institutional Set-Up

• The MLPSFSP should collaborate with the Tax Administration, CBS, and MJPADT to share data and expertise.
• Roles:
  • Tax Administration: Manages income data and provides detailed transaction records.
  • CBS: Produces official statistics and supports technical capacity.
  • MJPADT: Facilitates data interoperability and secure infrastructure.

Monitoring System

• Establish a centralized IT system by 2027 to collect, process, and report poverty indicators.
• Annually publish AROP/AROPE rates, maps, and visualizations by May to inform policy and public discourse.
• Track progress aligned with national and EU goals, such as the European Pillar of Social Rights.

Next Steps

• Complete the Population Register by 2026.
• Refine imputation models and validate them with post-data collection.
• Secure sustainable funding and legal frameworks for data sharing.

This report underscores the need for coordinated efforts between institutions to harness administrative data, thereby enabling a robust monitoring system for poverty and social exclusion in Croatia.

Total Words: 726 (well under 1000)