Forecasting Brazilian output and its turning points in the presence of breaks: a comparison of linear and nonlinear models

This paper compares the forecasting performance of linear and nonlinear models under the presence of structural breaks for the Brazilian real GDP growth. The Markov switching models proposed by Hamilton (1989) and its generalized version by Lam (1990) are applied to quarterly GDP from 1975:1 to 2000:2 allowing for breaks at the Collor Plans. The probabilities of recessions are used to analyze the Brazilian business cycle. The in-sample and out-of-sample forecasting ability of growth rates of GDP of each model is compared with linear specifications and with a non-parametric rule. We find that the nonlinear models display a better forecasting performance than linear models. The specifications with the presence of structural breaks are important in obtaining a representation of the Brazilian business cycle and their inclusion improves considerably the models forecasting performance within and out-of-sample.<br>Este artigo compara as habilidades preditivas de modelos lineares e não-lineares, com quebras estruturais, nas previsões da taxa de crescimento do PIB real do Brasil. Os modelos com mudanças de regime markovianas, propostos por Hamilton (1989) e generalizados por Lam (1990), são estimados para dados trimestrais de 1975:1 a 2000:2. Os modelos são estimados permitindo quebras estruturais durante os planos Collor. As probabilidades de recessão dos modelos são utilizadas para analisar o ciclo de negócios brasileiro. A capacidade de previsão da taxa de crescimento do PIB fora e dentro da amostra desses modelos é comparada com modelos lineares e com uma regra não-parametrizada. Os resultados indicam que os modelos não-lineares são os que apresentam o melhor desempenho preditivo quando comparados com modelos lineares. A inclusão de quebras estruturais é importante para a representação do ciclo de negócios no Brasil, além de levar a um desempenho de previsão consideravelmente melhor do que os modelos sem intervenção, dentro e fora de amostra

Monetary Policy, Inflation and the Level of Economic Activity in Brasil After the Real Plan: Stylized Facts From SVAR Models

This article investigates the stochastic and dynamic relationship of a group ofBrazilian macroeconomic variables (price and industrial production indexes, nominalexchange rate, short and medium-run nominal interest rates) for the period after theReal Plan (1996-2004). We adopt, as has become usual in the literature, severalSVAR (structural VAR) models to uncover stylized facts for the short-run impacts ofthe identified exogenous sources of fluctuations of this selected set of variables.A distinctive feature of this article is the employment of Directed Acyclic Graphs(DAG) to obtain the contemporaneous causal order of the variables used to identifythe SVAR models. Another distinguishing characteristic is the careful attention paidto monetary policy developments after the Real Plan when splitting our sample intwo subsamples (1996/07-1998/08 and 1999/03-2004/12).The main results are: a) in response to a positive short run interest rate innovation,during the 1999-2004 subperiod, the output and the price level decrease?however, theoutput response is faster and the price level responds with a lag of near four months; b)for the 1996-1998 subperiod, the most likely effect of a positive short run interest rateinnovation is the reduction of the price level (also with a four months lag), even thoughthere is a large uncertainty in this response, and the reduction of output; c)short runinterest rate innovations are one of the most important sources of temporary fluctuationsin the level of economic activity for both subsamples; and d) exogenous shocks to theexchange rate and to the medium term interest rate are for the 1999-2004 period, themost important sources of inflation rate fluctuation.

Measuring Monetary Policy Stance in Brazil

In this article we use the theory of conditional forecasts to develop a new MonetaryConditions Index (MCI) for Brazil and compare it to the ones constructed using themethodologies suggested by Bernanke and Mihov (1998) and Batini and Turnbull(2002). We use Sims and Zha (1999) and Waggoner and Zha (1999) approaches todevelop and compute Bayesian error bands for the MCIs.The new indicator we develop is called the Conditional Monetary Conditions Index(CMCI) and is constructed using, alternatively, Structural Vector Autoregressions(SVARs) and Forward-Looking (FL) models. The CMCI is the forecasted output gap,conditioned on observed values of the nominal interest rate (the Selic rate) and of the realexchange rate. We show that the CMCI, when compared to the MCI developed byBatini and Turnbull (2002), is a better measure of monetary policy stance because ittakes into account the endogeneity of variables involved in the analysis.The CMCI and the Bernanke and Mihov MCI (BMCI), despite conceptualdifferences, show similarities in their chronology of the stance of monetary policy inBrazil. The CMCI is a smoother version of the BMCI, possibly because the impact ofchanges in the observed values of the Selic rate is partially compensated by changes inthe value of the real exchange rate. The Brazilian monetary policy, in the 2000:9-2005:4 period and according to the last two indicators, has been expansionary nearelection months.