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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Estimation of DSGE Models: A Monte Carlo Analysis

Motula, Paulo Fernando Nericke 18 June 2013 (has links)
Submitted by Paulo Fernando Nericke Motula (pnericke@fgvmail.br) on 2013-06-29T15:45:20Z No. of bitstreams: 1 Dissertacao - Paulo Motula.pdf: 1492951 bytes, checksum: d60fce8c6165733b9666076aef7e2a75 (MD5) / Approved for entry into archive by Janete de Oliveira Feitosa (janete.feitosa@fgv.br) on 2013-07-03T13:29:49Z (GMT) No. of bitstreams: 1 Dissertacao - Paulo Motula.pdf: 1492951 bytes, checksum: d60fce8c6165733b9666076aef7e2a75 (MD5) / Approved for entry into archive by Marcia Bacha (marcia.bacha@fgv.br) on 2013-07-09T19:35:20Z (GMT) No. of bitstreams: 1 Dissertacao - Paulo Motula.pdf: 1492951 bytes, checksum: d60fce8c6165733b9666076aef7e2a75 (MD5) / Made available in DSpace on 2013-07-09T19:40:59Z (GMT). No. of bitstreams: 1 Dissertacao - Paulo Motula.pdf: 1492951 bytes, checksum: d60fce8c6165733b9666076aef7e2a75 (MD5) Previous issue date: 2013-06-18 / We investigate the small sample properties and robustness of the parameter estimates of DSGE models. Our test ground is the Smets and Wouters (2007)'s model and the estimation procedures we evaluate are the Simulated Method of Moments (SMM) and Maximum Likelihood (ML). We look at the empirical distributions of the parameter estimates and their implications for impulse-response and variance decomposition in the cases of correct specification and two types of misspecification. Our results indicate an overall poor performance of SMM and some patterns of bias in impulse-response and variance decomposition for ML under the types of misspecification studied. / Neste trabalho investigamos as propriedades em pequena amostra e a robustez das estimativas dos parâmetros de modelos DSGE. Tomamos o modelo de Smets and Wouters (2007) como base e avaliamos a performance de dois procedimentos de estimação: Método dos Momentos Simulados (MMS) e Máxima Verossimilhança (MV). Examinamos a distribuição empírica das estimativas dos parâmetros e sua implicação para as análises de impulso-resposta e decomposição de variância nos casos de especificação correta e má especificação. Nossos resultados apontam para um desempenho ruim de MMS e alguns padrões de viés nas análises de impulso-resposta e decomposição de variância com estimativas de MV nos casos de má especificação considerados.

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