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"This paper demonstrates that "commodity currency" exchange rates have remarkably robust power in predicting future global commodity prices, both in-sample and out-of-sample. A critical element of our in-sample approach is to allow for structural breaks, endemic to empirical exchange rate models, by implementing the approach of Rossi (2005b). Aside from its practical implications, our forecasting results provide perhaps the most convincing evidence to date that the exchange rate depends on the present value of identifiable exogenous fundamentals. We also find that the reverse relationship holds; that is, that commodity prices Granger-cause exchange rates. However, consistent with the vast post-Meese-Rogoff (1983a,b) literature on forecasting exchange rates, we find that the reverse forecasting regression does not survive out-of-sample testing. We argue, however, that it is quite plausible that exchange rates will be better predictors of exogenous commodity prices than vice-versa, because the exchange rate is fundamentally forward looking. Therefore, following Campbell and Shiller (1987) and Engel and West (2005), the exchange rate is likely to embody important information about future commodity price movements well beyond what econometricians can capture with simple time series models. In contrast, prices for most commodities are extremely sensitive to small shocks to current demand and supply, and are therefore likely to be less forward looking"--National Bureau of Economic Research web site

The new high-speed rail (HSR) service, the most important intercity mode in Taiwan in this decade, started formally in January 2007. To be able to predict the intercity mode market more accurately, it is necessary to collect data relating to passengers' choice behavior. Thus, this
note explains the merits of combining data sources and addresses the framework of modeling dynamic choice behavior (See Figure 1).

Abstract.  Motivated by Japan's economic experiences in recent decades, we incorporate adaptive learning into an open economy dynamic stochastic general equilibrium model to examine the volatility and welfare impact of alternative monetary policies. Comparing four Taylor‐styled policy rules that reflect Japan's monetary policy debates, we first show that imperfect knowledge and the associated learning process induce higher volatility in the economy and that explicit exchange rate stabilization is unwarranted. Moreover, contrary to results under the rational expectation paradigm, we find that while tight inflation controls raise output volatility, they can improve overall welfare under learning by smoothing inflation fluctuations.