Uncovering regimes in out of sample forecast errors from predictive regressions

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dc.contributor.author Da Silva Neto, Anibal Emiliano
dc.contributor.author Gonzalo, Jesús
dc.contributor.author Pitarakis, Jean-Yves
dc.contributor.editor Universidad Carlos III de Madrid. Departamento de Economía
dc.date.accessioned 2020-12-09T18:12:32Z
dc.date.available 2020-12-09T18:12:32Z
dc.date.issued 2020-12-09
dc.identifier.issn 2340-5031
dc.identifier.uri http://hdl.handle.net/10016/31555
dc.description.abstract We introduce a set of test statistics for assessing the presence of regimes in out of sample forecast errors produced by recursively estimated linear predictive regressions that can accommodate multiple highly persistent predictors. Our tests statistics are designed to be robust to the chosen starting window size and are shown to be both consistent and locally powerful. Their limiting none distributionsare also free of nuisance parameters and hence robust to the degree of persistence of the predictors.Our methods are subsequently applied to the predictability of the value premium whose dynamics are shown to be characterised by state dependence.
dc.description.sponsorship Gonzalo gratefully acknowledges financial support from the Spanish Ministerio de Economia y Competitividad (grants ECO2016-78652, PID2019-104960GB-I00, and Maria de Maeztu MDM 2014- 0431), and MadEco-CM (grant S205/HUM-3444). Pitarakis thanks the British Academy for financial support through grant SRG170220.
dc.language.iso eng
dc.relation.ispartofseries Working paper. Economics
dc.relation.ispartofseries 20-14
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other Predictive Regressions
dc.subject.other Predictability
dc.subject.other Out Of Sample Forecast Errors
dc.subject.other Cusum
dc.subject.other Thresholds
dc.title Uncovering regimes in out of sample forecast errors from predictive regressions
dc.type workingPaper
dc.subject.jel C12
dc.subject.jel C22
dc.subject.jel C53
dc.subject.jel C58
dc.relation.projectID Gobierno de España. ECO2016-78652-P
dc.relation.projectID Gobierno de España. PID2019-104960GB-I00
dc.relation.projectID Gobierno de España. MDM 2014- 0431
dc.identifier.uxxi DT/0000001857
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