Forecasting the Stability and Growth Pact compliance using Machine Learning
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DOI: 10.1111/twec.13518
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- Kea Baret & Amelie Barbier-Gauchard & Theophilos Papadimitriou, 2022. "Forecasting the Stability and Growth Pact compliance using Machine Learning," Working Papers 2022.11, International Network for Economic Research - INFER.
- Kéa Baret & Amélie Barbier-Gauchard & Théophilos Papadimitriou, 2021. "Forecasting the Stability and Growth Pact compliance using Machine Learning," Working Papers of BETA 2021-01, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
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Cited by:
- Kea BARET, 2021. "Fiscal rules’ compliance and Social Welfare," Working Papers of BETA 2021-38, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
- Carlos Fonseca Marinheiro, 2021. "The Expenditure Benchmark: Complex and Unsuitable for Independent Fiscal Institutions," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 63(3), pages 411-431, September.
- Kea BARET, 2021. "Fiscal rules’ compliance and Social Welfare," Working Papers of BETA 2021-50, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
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More about this item
Keywords
Fiscal Rules; Fiscal Compliance; Stability and Growth Pact; Machine learning;All these keywords.
JEL classification:
- E62 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Fiscal Policy; Modern Monetary Theory
- H11 - Public Economics - - Structure and Scope of Government - - - Structure and Scope of Government
- H60 - Public Economics - - National Budget, Deficit, and Debt - - - General
- H68 - Public Economics - - National Budget, Deficit, and Debt - - - Forecasts of Budgets, Deficits, and Debt
NEP fields
This paper has been announced in the following NEP Reports:- NEP-BIG-2024-06-17 (Big Data)
- NEP-CMP-2024-06-17 (Computational Economics)
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