Please use this identifier to cite or link to this item: https://ric.cps.sp.gov.br/handle/123456789/6716
Title: Forecasting ability and the impacts of monetary policy and exchange rate shocks: comparisons between DSGE and VAR models estimated for Brazil
Other Titles: Capacidade de previsão e os impactos da política monetária e choques de taxa de câmbio: comparações entre modelos DSGE e VAR estimado para o Brasil
Authors: QUEIROZ, Iris Calegare Largura
REIS, Marcello Carvalho dos
MARTINEZ, Maria Elisa Marciano
type of document: Artigo científico
Keywords: Política monetária;Taxa de câmbio;Comércio internacional
Issue Date: 10-Aug-2020
Citation: QUEIROZ, Iris Calegare Largura, REIS, Marcello Carvalho dos, MARTINEZ, Maria Elisa Marciano. Forecasting ability and the impacts of monetary policy and exchange rate shocks: comparisons between DSGE and VAR models estimated for Brazil. Revista Tecnológica da Fatec Americana, Americana, v. 8, n. 1, p. 1-12, ago, 2020. Disponível em: https://fatec.edu.br/revista/index.php/RTecFatecAM/article/view/247. DOI: 10.47283/244670492020080102
Series/Report no.: R.Tec.FatecAM, Americana, v.8, n.1, p.1-12, ago.2020;
Abstract: This article compares the out-of-sample forecasting ability of a new Keynesian DSGE (Dynamic Stochastic General Equilibrium) model, specified and estimated for Brazil, with a Vector Autoregression (VAR). The article innovates in relation to other similar studies made for Brazil (Castro et al. (2011) e Caetano e Moura (2013), by choosing a specification for the DSGE model that, allowing the use of a richer information set, made possible to compute the predictive ability of the DSGE from forecasts that are, truly, out-of-sample forecasts. Moreover, unlike other articles that used Brazilian data, it also verifies to what degree the responses of variables to a monetary and an exchange rate shock. The estimated DSGE model is similar to the ones adopted by Justiniano e Preston (2005) and Alpanda (2009, 2010a, 2010b). The BVAR model was estimated using a Bayesian procedure like those proposed by Sims and Zha (1998) and Rubio-Ramíres, Waggoner and Zha (2005). The results show that the estimated DSGE model is capable of making out-of-sample forecasts, for some variables, that are competitive when compared to a VAR model.
URI: http://ric.cps.sp.gov.br/handle/123456789/6716
ISSN: 2446-7049
Appears in Collections:Artigos de Periódicos do CPS

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