The dynamic effects of monetary policy and government spending shocks on unemployment in the peripheral Euro area countries
Pietro Dallari and
Antonio Ribba ()
Economic Modelling, 2020, vol. 85, issue C, 218-232
In this paper we study the response of unemployment to monetary policy and government spending shocks in the peripheral Euro-area countries. By applying the structural near-VAR methodology, we jointly model area-wide and national variables. Our main finding is that fiscal multipliers vary across countries and the results are consistent with the prediction of the standard New Keynesian model only in Italy and Greece. Instead, in Ireland, Portugal and Spain increases in government spending are recessionary. Thus we find that Keynesian results of fiscal policy seem to prevail in high public-debt countries, whereas non-Keynesian outcomes seem to characterize high private-debt countries. As for the monetary policy shock, we find that it plays an important role, jointly with the other area-wide shocks, as a long-term driver of national unemployment.
Keywords: Business cycles; Fiscal shocks; Unemployment; Euro area; Near-structural VARs (search for similar items in EconPapers)
JEL-codes: C32 E32 E62 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
Working Paper: The Dynamic Effects of Monetary Policy and Government Spending Shocks on Unemployment in the Peripheral Euro Area Countries (2019)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:85:y:2020:i:c:p:218-232
Access Statistics for this article
Economic Modelling is currently edited by S. Hall and P. Pauly
More articles in Economic Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().