Vicente Tuesta, Juan F. Rubio-Ramirez, and Mr. Pau Rabanal
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.
Several authors have recently investigated the predictability of exchange rates by fitting a sequence of long-horizon error-correction regressions. By considering the implied vector error-correction model, we show that little is to be gained from estimating such regressions for horizons greater than one time period. We also show that in small to medium samples the long-horizon procedure gives rise to spurious evidence of predictive power. A simulation study demonstrates that even when using this technique on two independent series, estimates, diagnostic statistics and graphical evidence incorrectly suggest a high degree of predictability of the dependent variable.
In this paper, we first introduce investment-specific technology (IST) shocks to an otherwise standard international real business cycle model and show that a thoughtful calibration of them along the lines of Raffo (2009) successfully addresses the "quantity", "international comovement", "Backus-Smith", and "price" puzzles. Second, we use OECD data for the relative price of investment to build and estimate these IST processes across the U.S and a "rest of the world" aggregate, showing that they are cointegrated and well represented by a vector error correction model (VECM). Finally, we demonstrate that when we fit such estimated IST processes in the model instead of the calibrated ones, the shocks are actually not as powerful to explain any of the four montioned puzzles.
In this paper we identify some of the main factors behind systemic risk in a set of international large-scale complex banks using the novel CoVaR approach. We find that short-term wholesale funding is a key determinant in triggering systemic risk episodes. In contrast, we find no evidence that a larger size increases systemic risk within the class of large global banks. We also show that the sensitivity of system-wide risk to an individual bank is asymmetric across episodes of positive and negative asset returns. Since short-term wholesale funding emerges as the most relevant systemic factor, our results support the Basel Committee's proposal to introduce a net stable funding ratio, penalizing excessive exposure to liquidity risk.