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Erscheinungsjahr: 
2025
Schriftenreihe/Nr.: 
Quaderni - Working Paper DSE No. 1216
Verlag: 
Alma Mater Studiorum - Università di Bologna, Dipartimento di Scienze Economiche (DSE), Bologna
Zusammenfassung: 
This study evaluates the effectiveness of Italian local fiscal policy by estimating regional government spending multipliers at the NUTS-2 and NUTS-1 levels, using annual data from 1995 to 2021. We employ a novel econometric methodology to comprehensively capture the heterogeneous effects of exogenous government spending across regions, disentangling the effects of public investment from those of public consumption. Our analysis is based on Factor-Augmented Vector Autoregressive (FA-VAR) models, where an external instrument is used to indirectly identify fiscal spending shocks. To address the challenge of identifying valid external instruments in a context of limited cross-sectional data, we use factor analysis to construct a non-fiscal instrument capturing the "common" (national) component driving the dynamics of Italian regional output. This instrument is applied across all regions to estimate fiscal reaction functions. We find that while expansionary fiscal shocks induce positive short-term effects - particularly when public regional investment is analyzed separately from public regional consumption - the uncertainty surrounding these effects is remarkably high. This crucial aspect, often overlooked in the existing literature, complicates the empirical assessment of the effectiveness of regional fiscal policy. Based on our bootstrap-based robust confidence intervals, the effects of fiscal spending shocks tend to dissipate in a few years. We also detected significant regional disparities, with fiscal multipliers being larger in the Center-North regions compared to the Southern regions. This pattern persists even when analyzing Italian macro-areas (NUTS-1 level), underscoring the need for tailored regional fiscal policies.
Schlagwörter: 
Fiscal Multipliers
Identification
Instrumental Variables
Structural Vector Autoregressions
JEL: 
C32
C50
E62
R58
Persistent Identifier der Erstveröffentlichung: 
Creative-Commons-Lizenz: 
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Dokumentart: 
Working Paper

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