THE SOCIAL DIMENSION OF PUBLIC DEBT AND DEBT POLICY

Abstract

The relevance of the study is determined by the growing debt burden on public finances and the need to consider how the consequences of debt and fiscal decisions are distributed across social groups and generations. The purpose of the article is to substantiate the social consequences of public debt and debt policy by identifying the channels through which the fiscal burden is distributed, identifying vulnerable groups, developing an approach to public accountability, and outlining the potential use of artificial intelligence for assessing distributional effects. The object of the study is public debt and debt policy as components of public finance, while the subject comprises the social-distributional, intergenerational, institutional, and digital dimensions of their impact. The methodological framework combines systems, comparative, distributional, and institutional analysis, as well as Eurostat data on public debt, social risk, social protection, and inequality in EU countries. The study systematizes six channels through which debt policy affects social outcomes and demonstrates that the debt level alone does not determine the social result, since the structure of fiscal policy, the scale of social protection, labour-market conditions, inequality, and institutional capacity are also important. An original social vulnerability matrix based on the logic of "exposure – sensitivity – adaptive capacity" is proposed, along with a distributional impact assessment to ex ante explain the social consequences of the most significant debt-policy decisions. Artificial intelligence is defined as a supporting tool for data integration, risk group identification, scenario analysis, and monitoring, under a human-in-the-loop principle. The practical value of the findings lies in their potential use when updating debt-strategy provisions and designing fiscal-consolidation programs.