Microsimulation & Econometric Data Analysis

One aim of Kindergrundsicherung discussed in Germany was to make it easier for families to claim social benefits for their children. On behalf of the Federal Ministry for Family Affairs, we examined the accuracy of a simplified eligibility check that requires less data. Our analysis shows that even even common-sense assumptions in the place of missing data allow to determine eligibility with sufficient accuracy.

The previous German government had planned Kindergrundsicherung to consolidate and improve the existing diverse social benefits for low-income families with kids. One critical issue to be corrected was the lack of transparency of the available benefits. As a result, many families do not claim the full amount of benefits they are entitled to. The Kindergrundsicherung aimed to remedy this situation. A particular challenge was that, although all eligible families would be entitled to a basic level of benefits, lower-income families were to receive additional payments depending on their income and individual needs. This Kinderzusatzbetrag (Additional child allowance) was to compensate losses against benefits previously derived from Bürgergeld (Minimum income support program) and Kinderzuschlag (Child allowance supplement).

The idea behind the planned Kindergrundsicherungs-Check was to actively inform families about their eligibility for Kinderzusatzbetrag depending on a simple online check procedure. In order to accurately determine a family's entitlement to benefits, various information about the household must be available, such as the number of children, income and housing costs. The effort required to provide this information may discourage families from applying. Thus, the check procedure should inform families as accurately as possible about their entitlement without them having to provide additional information. To this end, data already available to various government agencies, e.g. income from the social pension program, can be automatically retrieved. Information that is not easily available in the online check, such as housing costs or maintenance, is being replaced by educated guesses.

Our simulations of such a simplified check procedure show that, even with common-sense assumptions in place of missing information, it is highly accurate and can correctly identify the vast majority of families as eligible or ineligible. This finding is an important step towards a simpler and automated eligibility-testing process that might be applied to many social benefits in the future.