COMBINE | Combine measures of social assistance benefit indicators to correct for measurement error

Summary
Aim: To break new ground in the field of official statistics, COMBINE produces error-corrected figures on (1) the number of individuals receiving social assistance benefit at a given point in time and (2) the transition rate out of social assistance between two points in time.
Background: Social assistance benefits are an important pillar of the welfare state. Policy making on social assistance benefits is based on official statistics that are produced by National Statistical Institutes with the use of register data. However, register data suffer from measurement error that can severely bias official statistics and, consequently, policy-making that uses these statistics.
Innovation: COMBINE tests, applies and evaluates a novel model-based error-detection and correction method on social assistance benefits. This method does not require concrete knowledge of the causes of measurement error. With this method, we produce different and more reliable official statistics on social assistance benefits. Moreover, this method is more efficient than the practices of data-quality improvement that National Statistical Institutes currently apply.
Plan: The project is carried out in collaboration with Statistics Netherlands and, in particular, with its Department of Demographic and Socioeconomic Statistics. Besides producing error-corrected official statistics on social assistance benefits, COMBINE delivers an implementation plan of the method to other official statistics (by Statistics Netherlands or other National Statistical Institutes) and a dissemination plan for approaching policymakers and other users of the statistics.
Impact: COMBINE will encourage a cultural shift in official statistics by boosting the confidence of National Statistical Institutes in producing model-based error-corrected statistics. In the policy field, as the method is applicable to a wide range of topics, the project contributes to evidence-based policy-making.
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/101157882
Start date: 01-09-2024
End date: 28-02-2026
Total budget - Public funding: - 150 000,00 Euro
Cordis data

Original description

Aim: To break new ground in the field of official statistics, COMBINE produces error-corrected figures on (1) the number of individuals receiving social assistance benefit at a given point in time and (2) the transition rate out of social assistance between two points in time.
Background: Social assistance benefits are an important pillar of the welfare state. Policy making on social assistance benefits is based on official statistics that are produced by National Statistical Institutes with the use of register data. However, register data suffer from measurement error that can severely bias official statistics and, consequently, policy-making that uses these statistics.
Innovation: COMBINE tests, applies and evaluates a novel model-based error-detection and correction method on social assistance benefits. This method does not require concrete knowledge of the causes of measurement error. With this method, we produce different and more reliable official statistics on social assistance benefits. Moreover, this method is more efficient than the practices of data-quality improvement that National Statistical Institutes currently apply.
Plan: The project is carried out in collaboration with Statistics Netherlands and, in particular, with its Department of Demographic and Socioeconomic Statistics. Besides producing error-corrected official statistics on social assistance benefits, COMBINE delivers an implementation plan of the method to other official statistics (by Statistics Netherlands or other National Statistical Institutes) and a dissemination plan for approaching policymakers and other users of the statistics.
Impact: COMBINE will encourage a cultural shift in official statistics by boosting the confidence of National Statistical Institutes in producing model-based error-corrected statistics. In the policy field, as the method is applicable to a wide range of topics, the project contributes to evidence-based policy-making.

Status

SIGNED

Call topic

ERC-2023-POC

Update Date

24-12-2024
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Horizon Europe
HORIZON.1 Excellent Science
HORIZON.1.1 European Research Council (ERC)
HORIZON.1.1.0 Cross-cutting call topics
ERC-2023-POC ERC PROOF OF CONCEPT GRANTS
HORIZON.1.1.1 Frontier science
ERC-2023-POC ERC PROOF OF CONCEPT GRANTS