The Stochastic Simulations of the Commission's Debt Sustainability Analysis: A Refined Approach

Simulations stochastiques de l'analyse de la soutenabilité de la dette de la Commission Européenne: Une approche affinée

Frédérique Bec (), François Courtoy, Philipp Mohl () and Frederic Opitz ()
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Frédérique Bec: THEMA - Théorie économique, modélisation et applications - UCP - Université de Cergy Pontoise - Université Paris-Seine - CNRS - Centre National de la Recherche Scientifique, CY - CY Cergy Paris Université
François Courtoy: European Commission [Brussels], Directorate General for Economic and Financial Affairs (DG ECFIN) - European Commission
Philipp Mohl: European Commission [Brussels], Directorate General for Economic and Financial Affairs (DG ECFIN) - European Commission
Frederic Opitz: European Commission [Brussels], Directorate General for Economic and Financial Affairs (DG ECFIN) - European Commission

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Abstract: Stochastic debt projections are essential for understanding uncertainties in debt dynamics and ensuring robust debt sustainability analyses. The Commission's stochastic debt sustainability analysis (SDSA) currently features two technical aspects that deserve to be addressed: i) the non-consideration of the persistence of shocks and ii) the assumption of a Gaussian distribution for simulating shock trajectories. This paper presents two technical refinements to improve the Commission's SDSA by i) allowing for the persistence of shocks by applying a pre-filtering approach with a shock-specific lag structure across all countries and ii) implementing a bootstrapping technique to relax the Gaussian distribution assumption. These new features will be incorporated in the Commission's DSA, to identify fiscal sustainability risks.

Keywords: C53 Debt sustainability analysis; Monte Carlo simulations; bootstrapping; fiscal risks; EU fiscal policy; filtered shocks; stochastic debt projections; C53 Debt sustainability analysis stochastic debt projections filtered shocks EU fiscal policy fiscal risks bootstrapping Monte Carlo simulations; C22; C15; E62; JEL Classification: H63 (search for similar items in EconPapers)
Date: 2025-10
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Persistent link: https://EconPapers.repec.org/RePEc:hal:wpaper:hal-05574615

DOI: 10.2765/2628965

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