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, which may 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. JEL codes: C32,E32, E37
Highlights
Any modern society is concerned with its current “state” of economic activity and what should be that state in the near future
We propose an estimate for real monthly Gross Domestic Product (GDP) in Brazil for the period 1980–2012, which is an interpolation of the quarterly observed series; see Bernanke et al (1997) and Mönch & Uhlig (2005)
Our monthly GDP proxy is based on a state-space representation which imposes the restriction that the monthly proxy adds up to quarterly observed GDP within every single quarter
Summary
Any modern society is concerned with its current “state” of economic activity and what should be that state in the near future. Since the pioneering work of Burns & Mitchell (1946), we have been endowed with coincident and leading indicators of economic activity, which are timely proxies, respectiverly, of the current state of economic activity and what will it be in the near future This suggests that a superior strategy for having timely and more frequent estimates of economic activity is to combine GDP (or NBER dating) with information on these timely proxies. The econometric models used for interpolation ( in nowcasting and forecasting) in this paper employ a state-space approach They have three advantages over other interpolation methods: first, they allow the estimation of the unobserved monthly GDP with aggregation consistency, i.e., they ensure that the sum of three-months unobserved GDP data in a given quarter is equal to the respective quarterly observed GDP data.
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