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The Continuing Puzzle of Short Horizon Exchange Rate Forecasting
Rogoff, Kenneth S; Stavrakeva, Vania - National Bureau of Economic Research (NBER) - 2008
results that have been found. We find that by allowing for common cross-country shocks in our panel forecasting specification …
Persistent link: https://www.econbiz.de/10005710862
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Can Exchange Rates Forecast Commodity Prices?
Rogoff, Kenneth S; Rossi, Barbara; Chen, Yu-Chin - National Bureau of Economic Research (NBER) - 2008
particular. We also explore the reverse relationship (commodity prices forecasting exchange rates) but find it to be notably less …
Persistent link: https://www.econbiz.de/10005830811
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Can Oil Prices Forecast Exchange Rates?
Rogoff, Kenneth S; Rossi, Barbara; Ferraro, Domenico - National Bureau of Economic Research (NBER) - 2012
This paper investigates whether oil prices have a reliable and stable out-of-sample relationship with the Canadian/U.S dollar nominal exchange rate. Despite state-of-the-art methodologies, we find little systematic relation between oil prices and the exchange rate at the monthly and quarterly...
Persistent link: https://www.econbiz.de/10011227945
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Forecast Evaluation of Small Nested Model Sets
Hubrich, Kirstin; West, Kenneth D. - National Bureau of Economic Research (NBER) - 2008
We propose two new procedures for comparing the mean squared prediction error (MSPE) of a benchmark model to the MSPEs of a small set of alternative models that nest the benchmark. Our procedures compare the benchmark to all the alternative models simultaneously rather than sequentially, and do...
Persistent link: https://www.econbiz.de/10005710819
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DSGE Models in a Data-Rich Environment
Boivin, Jean; Giannoni, Marc P. - National Bureau of Economic Research (NBER) - 2006
Standard practice for the estimation of dynamic stochastic general equilibrium (DSGE) models maintains the assumption that economic variables are properly measured by a single indicator, and that all relevant information for the estimation is summarized by a small number of data series. However,...
Persistent link: https://www.econbiz.de/10005714295
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DSGE Model-Based Forecasting of Non-modelled Variables
Schorfheide, Frank; Sill, Keith; Kryshko, Maxym - National Bureau of Economic Research (NBER) - 2009
This paper develops and illustrates a simple method to generate a DSGE model-based forecast for variables that do not explicitly appear in the model (non-core variables). We use auxiliary regressions that resemble measurement equations in a dynamic factor model to link the non-core variables to...
Persistent link: https://www.econbiz.de/10005718736
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Efficient Prediction of Excess Returns
Faust, Jon; Wright, Jonathan - National Bureau of Economic Research (NBER) - 2008
price movements around macroeconomic news announcements. These "surprises" cannot be used directly in forecasting--they are … not observed at the time that the forecast is made--but can nonetheless improve forecasting accuracy by reducing parameter … of forecasting excess bond and equity returns. We find substantial improvements in out-of-sample forecast accuracy for …
Persistent link: https://www.econbiz.de/10005720382
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Phillips Curve Inflation Forecasts
Stock, James H.; Watson, Mark W. - National Bureau of Economic Research (NBER) - 2008
preliminary evidence characterizing successful forecasting episodes. …
Persistent link: https://www.econbiz.de/10005778755
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DSGE Models in a Data-Rich Environment
Boivin, Jean; Giannoni, Marc P. - National Bureau of Economic Research (NBER) - 2006
Standard practice for the estimation of dynamic stochastic general equilibrium (DSGE) models maintains the assumption that economic variables are properly measured by a single indicator, and that all relevant information for the estimation is summarized by a small number of data series. However,...
Persistent link: https://www.econbiz.de/10005779020
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Using Out-of-Sample Mean Squared Prediction Errors to Test the Martingale Difference
Clark, Todd; West, Kenneth D. - National Bureau of Economic Research (NBER) - 2005
We consider using out-of-sample mean squared prediction errors (MSPEs) to evaluate the null that a given series follows a zero mean martingale difference against the alternative that it is linearly predictable. Under the null of no predictability, the population MSPE of the null "no change"...
Persistent link: https://www.econbiz.de/10005779026