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Estimating Brazilian monthly GDP: a state-space approach

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Estimating_Brazilian_Monthly_GDP_a_State_Space_Approach.pdf (262.2Kb)
Date
2015-07-10
Author
Issler, João Victor
Notini, Hilton Hostalácio
Metadata
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Abstract
This paper has several original contributions. The rst is to employ a superior interpolation method that enables to estimate, nowcast and forecast monthly Brazilian GDP for 1980-2012 in an integrated way; see Bernanke, Gertler and Watson (1997, Brookings Papers on Economic Activity). Second, along the spirit of Mariano and Murasawa (2003, Journal of Applied Econometrics), we propose and test a myriad of interpolation models and interpolation auxiliary series all coincident with GDP from a business-cycle dating point of view. Based on these results, we nally choose the most appropriate monthly indicator for Brazilian GDP. Third, this monthly GDP estimate is compared to an economic activity indicator widely used by practitioners in Brazil- the Brazilian Economic Activity Index - (IBC-Br). We found that the our monthly GDP tracks economic activity better than IBC-Br. This happens by construction, since our state-space approach imposes the restriction (discipline) that our monthly estimate must add up to the quarterly observed series in any given quarter, whichmay not hold regarding IBC-Br. Moreover, our method has the advantage to be easily implemented: it only requires conditioning on two observed series for estimation, while estimating IBC-Br requires the availability of hundreds of monthly series. Third, in a nowcasting and forecasting exercise, we illustrate the advantages of our integrated approach. Finally, we compare the chronology of recessions of our monthly estimate with those done elsewhere.
URI
http://hdl.handle.net/10438/14072
Collections
  • FGV EPGE - Pesquisa e Conhecimento Aplicado [17]
  • RP - Artigos [1]
Knowledge Areas
Economia
Subject
Teoria da estimativa
Kalman, Filtragem de
Métodos de espaço de estados
Keyword
GDP interpolation
State-space representation
Kalman filter
Composite and leading indicators
Nowcasting
Forecasting

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