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<dc:title xml:lang="en">New empirical insights on fiscal rules performance</dc:title>
<dcterms:alternative xml:lang="fr">Nouvelles perspectives empiriques sur la performance des règles budgétaires</dcterms:alternative>
<dc:subject xml:lang="fr">Règles budgétaires</dc:subject>
<dc:subject xml:lang="fr">Discipline budgétaire</dc:subject>
<dc:subject xml:lang="fr">Économétrie</dc:subject>
<dc:subject xml:lang="fr">Apprentissage automatique</dc:subject>
<dc:subject xml:lang="fr">Inférence causale</dc:subject>
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<dc:subject xml:lang="fr">Règle d’or</dc:subject>
<dc:subject xml:lang="en">Fiscal rules</dc:subject>
<dc:subject xml:lang="en">Fiscal discipline</dc:subject>
<dc:subject xml:lang="en">Econometrics</dc:subject>
<dc:subject xml:lang="en">Machine learning</dc:subject>
<dc:subject xml:lang="en">Causal inference</dc:subject>
<dc:subject xml:lang="en">National accounts</dc:subject>
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<dcterms:abstract xml:lang="fr">Cette thèse propose de combler le vide dans la littérature empirique sur la performance des règles budgétaires. Le premier chapitre utilise l'approche économétrique d'appariement par score de propension pour évaluer l'impact des règles budgétaires nationales sur la discipline budgétaire dans l'Union européenne. Le deuxième chapitre utilise des méthodes d'apprentissage automatique pour prévoir le respect du Pacte de stabilité et de croissance, qui souffre d'un manque de crédibilité et nécessite un cadre de gestion des risques. Le troisième chapitre analyse les effets secondaires des règles budgétaires nationales, notamment sur la composition des dépenses publiques, à l'aide d'une approche d'apprentissage automatique causale. Il souligne que les règles budgétaires peuvent être dommageables pour les dépenses sociales, les inégalités et donc le bien-être social dans son ensemble dans les pays de l'OCDE. Le dernier chapitre offre une analyse de sensibilité de la cible de la règle d'or pour montrer que la précision avec laquelle les séries d'investissements nets sont calculées, affecte l'évaluation de la performance des règles budgétaires.</dcterms:abstract>
<dcterms:abstract xml:lang="en">This thesis proposes to fill the gap in the existing empirical literature focusing on fiscal rules’ performance. The first chapter employs different econometrics methods, including propensity-score matching approach, to assess the impact of national fiscal rules on fiscal discipline in the European Union. The second chapter uses machine learnings methods to forecast the compliance with the Stability and Growth Pact as it highly suffers from a lack of credibility and needs a risk-management framework. The third chapter analyzes the side-effects of national fiscal rules, including on public spending composition, using causal machine learning approach. It highlights that fiscal rules may be damageable for social expenditure, inequalities and thus social welfare as a whole in OECD economies. Finally, the last chapter offers a sensitivity analysis of the target of the golden rule to point out how much the accuracy of net investment series’ calculationmatters to avoid any mistake in fiscal rules’ performance assessment.</dcterms:abstract>
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