Title : Fiscal rules’ compliance and Social Welfare
Author(s) : Kea BARET
Abstract : This paper studies the side-effects of fiscal rules’ compliance on social welfare. It considers national Budget Balance Rules’ (BBR) compliance effects on macroeconomic indicators and social welfare proxy indicators in OECD countries between 2004 and 2015. Instead of fiscal rules strength or fiscal rules presence effectiveness, we focus on fiscal rules’ compliance to assess the impact of fiscal rules’ performance on social welfare. The paper shows that governments seem to operate a reallocation of their spending to ensure both BBR’s compliance and economic objectives. Nevertheless, governments choices regarding their public spending composition seem leading to an increase in social inequalities suggesting that governments finally face a trade-off between fiscal rules’ compliance and social objectives. The analysis constitutes the first use of a causal Machine Mearning approach, namely the Double/Debiased Machine Learning recently developed by Chernozhukov et al. [2018], applied to fiscal rules’ performance assessment issues. This method allows us to highlight the key determinants of national BBR’s compliance as well as assessing the compliance’s effect on different macroeconomic and social indicators. We take care of voter preferences by computing a new proxy variable through Latent Factor Analysis approach and show that voter preferences appear as a key determinant for BBR’s compliance, giving an empirical proof that Wyplosz [2012]’s bias may matter when assessing fiscal rules’ performance.
Key-words : Fiscal rules’ compliance; Social Welfare; Fiscal Surveillance; Machine learning.
JEL Classification : E61, H11, H50, H61, H62.
