Parameter heterogeneity, persistence and cross-sectional dependence: new insights on fiscal policy reaction functions for the Euro area

Golinelli, Roberto ; Mammi, Irene ; Musolesi, Antonio (2018) Parameter heterogeneity, persistence and cross-sectional dependence: new insights on fiscal policy reaction functions for the Euro area. Bologna: Dipartimento di Scienze economiche, p. 47. DOI 10.6092/unibo/amsacta/5828. In: Quaderni - Working Paper DSE (1120). ISSN 2282-6483.
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Abstract

A number of novelties have emerged in the study of the discretionary fiscal policy within the Euro area during the last decade. Among the others, the availability of up-to-date information on fiscal indicators for the years following the Great Recession, the introduction of cutting-edge econometric methods, and a renewed interest about the sustainability of fiscal policy and public debt. The aim of this paper is to address the challenges posed by the estimation of the discretionary fiscal reaction function for the Euro area. We exploit recently introduced testing and estimation strategies for heterogeneous dynamic panels with cross-sectional dependence and propose a new parsimonious approach. Using real-time data over the period 1996-2016, we investigate whether the fiscal policy reaction function is still a benchmark after the Great Recession. We find evidence of strong cross-sectional dependence in the panel, and clear support to a valid cointegration relationship among the main determinants of the function. Newly added covariates, such interest rate spreads, come out to play a relevant role in explaining discretionary actions.

Abstract
Document type
Monograph (Working Paper)
Creators
CreatorsAffiliationORCID
Golinelli, RobertoUniversità di Bologna0000-0003-1107-6417
Mammi, IreneUniversità di Venezia0000-0002-3768-1028
Musolesi, AntonioUniversità di Ferrara0000-0002-3956-5434
Keywords
Dynamic panel models, Panel integration and cointegration, Heterogeneous parameters, Common correlated effects, Euro area countries, Fiscal policy reaction functions, real-time data
Subjects
ISSN
2282-6483
DOI
Deposit date
05 Apr 2018 07:42
Last modified
22 May 2019 13:23
URI

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