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http://hdl.handle.net/2445/187600
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DC Field | Value | Language |
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dc.contributor.author | Sorić, Petar | - |
dc.contributor.author | Monte Moreno, Enric | - |
dc.contributor.author | Torra Porras, Salvador | - |
dc.contributor.author | Clavería González, Óscar | - |
dc.date.accessioned | 2022-07-12T09:46:12Z | - |
dc.date.available | 2022-07-12T09:46:12Z | - |
dc.date.issued | 2022 | - |
dc.identifier.uri | http://hdl.handle.net/2445/187600 | - |
dc.description.abstract | The present study uses Gaussian Process regression models for generating density forecasts of inflation within the New Keynesian Phillips curve (NKPC) framework. The NKPC is a structural model of inflation dynamics in which we include the output gap, inflation expectations, fuel world prices and money market interest rates as predictors. We estimate country-specific time series models for the 19 Euro Area (EA) countries. As opposed to other machine learning models, Gaussian Process regression allows estimating confidence intervals for the predictions. The performance of the proposed model is assessed in a one-step-ahead forecasting exercise. The results obtained point out the recent inflationary pressures and show the potential of Gaussian Process regression for forecasting purposes. | ca |
dc.format.extent | 24 p. | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | eng | ca |
dc.publisher | Universitat de Barcelona. Facultat d'Economia i Empresa | ca |
dc.relation.isformatof | Reproducció del document publicat a: http://www.ub.edu/irea/working_papers/2022/202210.pdf | - |
dc.relation.ispartof | IREA – Working Papers, 2022, IR22/10 | - |
dc.relation.ispartof | AQR – Working Papers, 2022, AQR22/07 | - |
dc.relation.ispartofseries | [WP E-IR22/10] | ca |
dc.relation.ispartofseries | [WP E-AQR22/07] | - |
dc.rights | cc-by-nc-nd, (c) Sorić et al., 2022 | - |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ | * |
dc.source | Documents de treball (Institut de Recerca en Economia Aplicada Regional i Pública (IREA)) | - |
dc.subject.classification | Aprenentatge automàtic | - |
dc.subject.classification | Anàlisi de sèries temporals | - |
dc.subject.classification | Previsió econòmica | - |
dc.subject.classification | Corba de Phillips | cat |
dc.subject.other | Machine learning | - |
dc.subject.other | Time-series analysis | - |
dc.subject.other | Economic forecasting | - |
dc.subject.other | Phillips curve | eng |
dc.title | Density forecasts of inflation using Gaussian process regression models | ca |
dc.type | info:eu-repo/semantics/workingPaper | ca |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | ca |
Appears in Collections: | AQR (Grup d’Anàlisi Quantitativa Regional) – Working Papers Documents de treball (Institut de Recerca en Economia Aplicada Regional i Pública (IREA)) |
Files in This Item:
File | Description | Size | Format | |
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IR22_010_Soric+Monte+Torre+Claveria.pdf | 1.79 MB | Adobe PDF | View/Open |
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