Autor según el artículo: Lovcha Y; Perez-Laborda A

Departamento: Economia

Autor/es de la URV: Lovcha, Yuliya / Perez Laborda, Alejandro

Palabras clave: Technology shock Svar Rbc model Long-run restrictions Hours worked Frequency domain technology shock rbc model identification hours worked frequency domain employment

Resumen: © Cambridge University Press 2020. In this paper, we identify the technology shock at business cycle frequencies to improve the performance of structural vector autoregression models in small samples. To this end, we propose a new identification method based on the spectral decomposition of the variance, which targets the contributions of the shock in theoretical models. Results from a Monte-Carlo assessment show that the proposed method can deliver a precise estimate of the response of hours in small samples. We illustrate the application of our methodology using US data and a standard Real Business Cycle model. We find a positive response of hours in the short run following a non-significant, near-zero impact. This result is robust to a large set of credible parameterizations of the theoretical model.

Áreas temáticas: Economics and econometrics Economics Economia Ciencias sociales

Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/

ISSN: 13651005

Direcció de correo del autor: alejandro.perez@urv.cat yuliya.lovcha@urv.cat

Identificador del autor: 0000-0003-4247-598X 0000-0002-0481-7785

Fecha de alta del registro: 2023-02-22

Versión del articulo depositado: info:eu-repo/semantics/acceptedVersion

Enlace a la fuente original: https://www.cambridge.org/core/journals/macroeconomic-dynamics/article/abs/identifying-technology-shocks-at-the-business-cycle-via-spectral-variance-decompositions/A53F3F7EF66EAD06EC63A3D909AC30B8

URL Documento de licencia: http://repositori.urv.cat/ca/proteccio-de-dades/

Referencia al articulo segun fuente origial: Macroeconomic Dynamics. 25 (8): 1966-1992

Referencia de l'ítem segons les normes APA: Lovcha Y; Perez-Laborda A (2021). IDENTIFYING TECHNOLOGY SHOCKS at the BUSINESS CYCLE VIA SPECTRAL VARIANCE DECOMPOSITIONS. Macroeconomic Dynamics, 25(8), 1966-1992. DOI: 10.1017/S1365100519000932

DOI del artículo: 10.1017/S1365100519000932

Entidad: Universitat Rovira i Virgili

Año de publicación de la revista: 2021

Tipo de publicación: Journal Publications