Brazilian Business Cycles Research Articles

Brazilian Business Cycle Analysis in a High-Dimensional and Time-Irregular Span Context

Brazilian Business Cycle Analysis in a High-Dimensional and Time-Irregular Span Context

Flexible markov-switching models with evolving regime-specific parameters: an application to Brazilian business cycles

ABSTRACT This article develops a flexible class of Markov-switching models in which the GDP growth rate is decomposed into a long-run growth trend and evolving regime-dependent means. The models can account for multiple regimes, breaks in the long-run trend, stochastic volatility, and time-varying transition probabilities. They can also handle data outliers that may arise from rare events, such as the COVID-19 crisis. We illustrate our methodology by modelling Brazilian GDP growth, which has exhibited complicated dynamics over the past four decades. Our results suggest two regimes, one long-run trend break, significant time variation in volatility, and the presence of outliers. Moreover, the selected model features time-varying transition probabilities driven by domestic variables (fiscal stance, reserves, and the real interest rate). Significantly, our findings indicate a marked decline in Brazil’s long-run growth in recent years.

Does a Survey Based Capacity Utilization Measure Help Predicting Brazilian Output Gap in Real-Time?

The aim of the paper is to assess the informational content of a survey-based measure of the Brazilian manufacturing capacity utilization rate produced by the Brazilian Institute of Economics from Getulio Vargas Foundation. From a theoretical point of view, the survey-based capacity measure should provide meaningful information with respect to the Brazilian business cycle. In this work, we choose to use the output gap as the most comprehensive and convincing proxy of the cyclical situation (Graff and Sturm in CESifo Econ Stud 58(1):220–251, 2012). More specifically, we will refer to a real-time version of the output gap, using an existing real-time GDP data set produced by the Central Bank of Brazil (Cusinato et al. in Empir Econ, 2012). The information efficiency of the real-time output gap estimates is tested checking whether survey data can help producing real-time estimates that are significantly closer to the latest releases. In this sense, the paper provides a significant contribution to the existing literature, extending analysis already available for OECD countries to the Brazilian economy. Our main result is that survey data can indeed help to produce more efficient estimates of the output gap in real time.

A Study of the Brazilian business cycles (1900 – 2012)

This paper studies the Brazilian business cycles in the period of 1900 to 2012. Since the quarterly series of the actual GDP only starts in 1980 we had to build the series for the period of 1900 to 1979, using the time series structural model with temporal disaggregation for the first period. After that, a Markov switching model is proposed to build a chronology of the business cycles. The chosen model has two separate regimes with different scenarios of expansion and recession, and the dating carried out in this paper is compared with other studies on the theme, and characterizations for the growth phases that can support studies of the economic history in Brazil are proposed.

The role of interest rates in the Brazilian business cycles

This paper offers additional insights on the relationship between interest rates and business cycles in Brazil. First, I document that Brazilian interest rates are very volatile, counter-cyclical and positively correlated with net exports, as observed in other emerging market economies. Next, I present a dynamic stochastic general equilibrium model in which firms face working capital constraints and labor supply is independent of consumption. This parsimonious model, appropriately calibrated to the Brazilian economy, predicts that interest rate shocks can explain about one third of output fluctuations and delivers business cycle regularities consistent with the Brazilian data.

Brazilian business cycles and growth from 1850 to 2000

We study the cyclical and growth properties of Brazilian per capita output from 1850 to 2000. We find that, contrary to some developed countries, Brazil did not experience large changes in the volatility of per capita output. However, we obtained evidence that the oscillations in economic activity became more persistent after World War II.

A Markov Switching Regime Model of the Brazilian Business Cycle

Previous studies have shown that linear models are incapable of capturing business cycle dynamics with accuracy. This has brought interest in non-linear models such as the Markov switching (MS) regime technique, which can distinguish business cycle recession and expansion phases, and is sufficiently flexible to allow different relationships to apply over these phases. This technique can be used to simultaneously estimate the data generating process of real GDP growth and classify each observation into one of two regimes (i.e. low-growth and high-growth regimes). In this study, we investigate the dynamics of the Brazilian business cycle using a Markov regime switching vector autoregressive model (MS-VAR). The study was developed using time-variable transition probabilities (TVTP) and for comparison and validation, fixed transition probabilities (FTP) between regimes. In order to capture cyclical fluctuations of the Brazilian GDP, we use the yield spread as a leading indicator. Most of the results obtained with the MS-VAR-TVTP are according to the expected. We show that the model is adequate to predict short-term cyclical fluctuations in the Brazilian economy. We also estimate an MS-VAR model with FTP in order to validate the TVTP model. We confirm the relevance of the yield spread in the estimation of the model parameters and the transition probabilities.

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.

Ciclos reais brasileiros em dois setores

Construímos um modelo de equilíbrio geral dinâmico de dois setores com o intuito de investigar o comportamento dos ciclos reais brasileiros. Quando os investimentos dos dois setores são agregados de acordo com uma Cobb-Douglas para formação de capital, o modelo é consistente com as volatilidades cíclicas dos componentes das contas nacionais e com a natureza contracíclica das exportações líquidas e do câmbio real. Caso a elasticidade de substituição entre o consumo de comercializáveis e de não comercializáveis seja baixa, o modelo também reproduz a volatilidade observada no câmbio real.

Real interest rates and Brazilian business cycles

We construct a dynamic general equilibrium model to assess the quantitative relationship between real interest rates and output fluctuations in the Brazilian economy from 1980 to 2001. When firms are subject to working capital restrictions, the model is consistent with both the cyclical volatilities of national income components and the countercyclical character of real interest rates. Simulations indicate that output fluctuations are quite sensitive to the persistence of interest rate oscillations. Non-structural econometric estimations of the dynamic IS curve are, therefore, susceptible to the Lucas' critique, and may misguide the Central Bank's policymaking.

Forecasting Brazilian Output 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 proposed by Lam (1991) 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 ability of each model in forecasting out-of-sample the growth rates of GDP is examined. The forecasting ability of the two models is also compared with linear specifications. The authors find that nonlinear models display the best forecasting performance and that specifications including the presence of structural breaks are important in obtaining a representation of the Brazilian business cycle.

The Brazilian business and growth cycles

This paper uses several produceres to date and analyse the Brazilian business and growth cycles. In particular, a Markov switching model is fitted to quarterly and annual real production data. The smoothed probabilities of the Markov states are used as predictive rules to define different phases of cyclical fluctuations of real Brazilian production. The results are compared with different non-parametric rules. All methods implemented yield similar dating and reveal asymmetries across the different states of the Brazilian business and growth cycles, in which slowdowns and recessions are short and abrupt, while high growth phases and expansions are longer and less steep. The resulting dating of the Brazilian economic cycles can be used as a reference point for construction and evaluation of the predictive performance of coincident, leading, or lagging indicators of economic activity. In addition, the filtered probabilities obtained from the Markov switching model allow early recognition of the transition to a new business cycle phase, wich can be used, for example, for evaluation of the adequate strength and timing of countercyclical policies, for reassessment of projected sales or profits by businesses and investors, or for monitoring of inflation pressures.

A Monthly Indicator of Brazilian GDP

This paper constructs an indicator of Brazilian GDP at the monthly frequency. The peculiar instability and abrupt changes of regimes in the dynamic behavior of the Brazilian business cycle are explicitly modeled within nonlinear frameworks. In particular, a Markov switching dynamic factor model is used to combine several macroeconomic variables that display simultaneous comovements with aggregate economic activity. The model generates as output a monthly indicator of the Brazilian GDP and real time probabilities of the current phase of the Brazilian business cycle. The monthly indicator shows a remarkable historical conformity with cyclical movements of GDP. In addition, the estimated filtered probabilities predict all recessions in sample and out-of-sample. The ability of the indicator in linear forecasting growth rates of GDP is also examined within and out-of-sample. In both cases the estimated indicator displays a better predictive performance compared to a linear autoregressive model for GDP. In particular, the inclusion of lags of the indicator improves substantially forecasts of the severity of recessions and strength of expansions, as measured by the volatility of changes in GDP. These results suggest that the estimated monthly indicator can be used to forecast GDP and to monitor the state of the Brazilian economy in real time.

A Monthly Indicator of Brazilian GDP

This paper constructs an indicator of Brazilian GDP at the monthly frequency. The peculiar instability and abrupt changes of regimes in the dynamic behavior of the Brazilian business cycle were explicitly modeled within nonlinear frameworks. In particular, a Markov switching dynamic factor model was used to combine several macroeconomic variables that display simultaneous comovements with aggregate economic activity. The model generates as output a monthly indicator of the Brazilian GDP and real time probabilities of the current phase of the Brazilian business cycle. The monthly indicator shows a remarkable historical conformity with cyclical movements of GDP. In addition, the estimated filtered probabilities predict all recessions in sample and out-of-sample. The ability of the indicator in linear forecasting growth rates of GDP is also examined. The estimated indicator displays a better in-sample and out-of-sample predictive performance in forecasting growth rates of real GDP, compared to a linear autoregressive model for GDP. These results suggest that the estimated monthly indicator can be used to forecast GDP and to monitor the state of the Brazilian economy in real time.

The Brazilian Business Cycle and Growth Cycle

This paper uses several procedures to date and analyze the Brazilian business cycle and growth cycle. In particular, a Markov switching model is fitted to quarterly and annual real production data. The smoothed probabilities of the Markov states are used as predictive rules to define different phases of cyclical fluctuations of real Brazilian production. The results are compared with different non-parametric rules. All methods implemented yield similar dating and reveal asymmetries across the different states of the Brazilian business and growth cycle, in which slowdowns and recessions are short and abrupt, while high growth phases and expansions are longer and less steep. The resulting dating of the Brazilian economic cycles can be used as a reference point for construction and evaluation of the predictive performance of coincident, leading, or lagging indicators of economic activity. In addition, the filtered probabilities obtained from the Markov switching model allow early recognition of the transition to a new business cycle phase, which can be used, for example, for evaluation of the adequate strength and timing of counter cyclical policies, for reassessment of projected sales or profits by businesses and investors, or for monitoring of inflation pressures.