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A puzzle in international macroeconomics is that observed real exchange rates are highly volatile. Standard international real business cycle (IRBC) models cannot reproduce this fact. We show that TFP processes for the U.S. and the "rest of the world," is characterized by a vector error correction (VECM) and that adding cointegrated technology shocks to the standard IRBC model helps explaining the observed high real exchange rate volatility. Also we show that the observed increase of the real exchange rate volatility with respect to output in the last 20 year can be explained by changes in the parameter of the VECM.
A central puzzle in international macroeconomics is that observed real exchange rates are highly volatile. Standard International Real Business Cycle (IRBC) models cannot reproduce this fact when calibrated using conventional parameterizations, and can only generate one fourth of the real exchange rate volatility observed in the data. Typically, IRBC models are solved assuming that total factor productivity (TFP) processes are stationary. In this paper, we first show that TFP processes for the U.S. and the quot;rest of the worldquot; have a unit root, are cointegrated, and can be jointly characterized with a Vector Error Correction Model (VECM). Then, we explore the implications of extending an otherwise standard international real business cycle model that allows for cointegrated technology shocks. We show that the model can account for the high real exchange rate volatility observed in the data without having to rely on any particular nominal or real friction. Also, we show that the increase of relative volatility of the real exchange rate with respect to output in the last 20 years can be explained by changes in the parameter estimates of the VECM.
Real exchange rates exhibit important low-frequency fluctuations. This makes the analysis of real exchange rates at all frequencies a more sound exercise than the typical business cycle one, which compares actual and simulated data after the Hodrick-Prescott filter is applied to both. A simple two-country, two-good model, as described in Heathcote and Perri (2002), can explain the volatility of the real exchange rate when all frequencies are studied. The puzzle is that the model generates too much persistence of the real exchange rate instead of too little, as the business cycle analysis asserts. Finally, we show that the introduction of adjustment costs in production and in portfolio holdings allows us to reconcile theory and this feature of the data.
This book is designed for self study. The reader can apply the theoretical concepts directly within R by following the examples.
In most macroeconomic models, the substitutability between domestic and foreign goods is calibrated using aggregated data. This imposes homogeneous elasticities across goods, and the calibration is only valid under this assumption. If elasticities are heterogeneous, the aggregate substitutability is a weighted average of good-specific elasticities, which in general cannot be inferred from aggregated data. We identify structurally the substitutability in US goods using multilateral trade data. We impose homogeneity, and find an aggregate elasticity similar in value to conventional macroeconomic estimates. It is more than twice larger with sectoral heterogeneity. We discuss the implications in various areas of international economics.
This Selected Issues paper and Statistical Appendix examines Bangladesh’s nonfinancial state-owned enterprises. The paper argues that, given the overall policy environment and external vulnerabilities, the usefulness of the fixed exchange rate system in Bangladesh has run its course. Greater exchange rate flexibility is needed to ensure that the exchange rate sends appropriate market signals, and to enhance the authorities’ ability to address more effectively and timely both domestic imbalances and external real shocks arising from a rapidly changing global environment. The paper also outlines the structure and recent performance of the commercial banking sector.