Fondazione GRINS
Growing Resilient,
Inclusive and Sustainable
Galleria Ugo Bassi 1, 40121, Bologna, IT
C.F/P.IVA 91451720378
Finanziato dal Piano Nazionale di Ripresa e Resilienza (PNRR), Missione 4 (Infrastruttura e ricerca), Componente 2 (Dalla Ricerca all’Impresa), Investimento 1.3 (Partnership Estese), Tematica 9 (Sostenibilità economica e finanziaria di sistemi e territori).



Open Access
GRINS THEMATIC AREAS
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We propose a novel measure of fiscal policy divergence based on public budget data. First, we quantify policy similarity across municipalities based on the cosine similarity of their budget allocations, showing strong correlations with geographic proximity and socio-demographic characteristics similarity.
Next, we predict budget similarity out-of-sample using similarities in population composition, defining policy divergence as the deviation between observed and predicted similarities. In an empirical application to 8,000 Italian municipalities (2000–2015), we show that divergence significantly decreases in election years, suggesting politicians strategically set the more expected policies in the lead-up to elections.
KEYWORDS
AKNOWLEDGEMENTS
For helpful comments and suggestions, we thank seminar participants at the University of Pavia, LISER, Bocconi, ETH Zurich (Economics + Data Science series). We also thank participants at the 2023 SIEP Conference (Verona), 5th Swiss Workshop on Local Public Finance and Regional Economics (Lugano), 2nd Workshop on The Political Economy of Municipal Fiscal Policy (Bergamo), 2024 ZEW Public Finance Conference (Mannheim), and 2024 IIPF Annual Congress (Prague). P. Bello and C. Marconi acknowledge that the research is funded by the European Union -Next Generation EU, in the framework of the GRINS - Growing Resilient, Inclusive and Sustainable Project (GRINS PE00000018 – CUPE63C22002140007). The views and opinions expressed are solely those of the authors and do not necessarily reflect those of the European Union, and the European Union cannot be held responsible for them.
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