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In this paper we discuss statistical data requirements and modeling frameworks used for macro prudential analysis and policy making. We start with a short overview of causes, for which this kind of policy was introduced after the last financial crisis and its links with traditional micro-level supervisory and challenges generated for national and international statistical systems. We point out a group of implications which financial stability, seen from macro perspective, brings for data andmodels requirements, determined with introduction of consecutive Basel Accords and made operational with FINREP and COREP packages. Our special attention is paid to systemic risk models, which provide very precious knowledge about institutions’ dependencies and probabilities of shock spillovers within and across sectors. Expected problems with statistical data requirements fulfillment and models structure specification are also discussed and some possible solutions are hinted.
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