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dc.contributor.authorJiménez, Álvaro
dc.contributor.authorRodríguez, Gabriel
dc.date.accessioned2021-05-06T21:29:25Z
dc.date.available2021-05-06T21:29:25Z
dc.date.issued2020-04
dc.identifier.urihttp://repositorio.pucp.edu.pe/index/handle/123456789/176230
dc.descriptionDocumento de trabajo; 489
dc.description.abstractThis paper estimates hybrid TVP-VAR-SV models suggested by Chan and Eisentat (2018a) in order to identify and quantify the impact of fiscal shocks on the GDP growth of Peru during 1995- 2018. According to Bayesian criteria, the best model presents time-varying dynamics but not in all parameters. The results suggest: (i) fiscal shocks are significant according to the calculus of the IRFs, FEVD and HD of the GDP growth; (ii) tax revenue shocks are less important and their impact depends on the selected model and the quarter when the shock occurs; (iii) effect of capital expenditure shocks are the most important drivers of GDP growth; (iv) both fiscal expenditure shocks have been growing over the last 20 years. Finally, we suggest constant revisions of the fiscal multipliers and we think that in the following years, countercyclical fiscal policy in Peru should be mostly driven by capital expenditure.es_ES
dc.language.isoenges_ES
dc.publisherPontificia Universidad Católica del Perú. Departamento de Economíaes_ES
dc.relation.ispartofurn:issn:2079-8466
dc.relation.ispartofurn:issn:2079-8474
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/pe/*
dc.subjectFiscal Multiplierses_ES
dc.subjectFiscal Policyes_ES
dc.subjectHybrid TVP-VAR-SV Modelses_ES
dc.subjectBayesian Methodses_ES
dc.subjectPeruvian Economyes_ES
dc.titleTime-Varying Impact of Fiscal Shocks over GDP Growth in Peru: An Empirical Application using Hybrid TVP-VAR-SV Modelses_ES
dc.typeinfo:eu-repo/semantics/workingPaper
dc.type.otherDocumento de trabajo
dc.subject.ocdehttp://purl.org/pe-repo/ocde/ford#5.02.00
dc.publisher.countryPE
renati.advisor.orcidhttps://orcid.org/0000-0002-1740-6037
renati.advisor.orcidhttps://orcid.org/0000-0003-1174-9642
dc.identifier.doihttp://doi.org/10.18800/2079-8474.0489


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