Bayesian Model Averaging and exchange rate forecasts
Exchange rate forecasting is hard and the seminal result of Meese and Rogoff (1983) that the exchange rate is well approximated by a driftless random walk, at least for prediction purposes, has never really been overturned despite much effort at constructing other forecasting models. However, in several other macro and financial forecasting applications, researchers in recent years have considered methods for forecasting that combine the information in a large number of time series. One method that has been found to be remarkably useful for out-of-sample prediction is simple averaging of the ...
The yield curve and predicting recessions
The slope of the Treasury yield curve has often been cited as a leading economic indicator, with inversion of the curve being thought of as a harbinger of a recession. In this paper, I consider a number of probit models using the yield curve to forecast recessions. Models that use both the level of the federal funds rate and the term spread give better in-sample fit, and better out-of-sample predictive performance, than models with the term spread alone. There is some evidence that controlling for a term premium proxy as well may also help. I discuss the implications of the current shape of ...
Forecasting U.S. inflation by Bayesian Model Averaging
Recent empirical work has considered the prediction of inflation by combining the information in a large number of time series. One such method that has been found to give consistently good results consists of simple equal weighted averaging of the forecasts over a large number of different models, each of which is a linear regression model that relates inflation to a single predictor and a lagged dependent variable. In this paper, I consider using Bayesian Model Averaging for pseudo out-of-sample prediction of US inflation, and find that it gives more accurate forecasts than simple equal ...
Long memory in emerging market stock returns
Many authors have investigated the possibility of long memory in asset returns. Generally, very little evidence has been found for long memory in either stock returns or exchange rate returns. This paper applies the log-periodogram regression to a wide range of emerging market stock returns and finds some evidence for positive long memory in 7 of the 17 series considered.
Weather-adjusting employment data
First version: December 18, 2014. This version: January 12, 2015. This paper proposes and implements a statistical methodology for adjusting employment data for the effects of deviation in weather from seasonal norms. This is distinct from seasonal adjustment, which only controls for the normal variation in weather across the year. Unusual weather can distort both the data and the seasonal factors. We control for both of these effects by integrating a weather adjustment step in the seasonal adjustment process. We use several indicators of weather, including temperature, snowfall and ...
Identifying the effects of monetary policy shocks on exchange rates using high frequency data
This paper proposes a new approach to identifying the effects of monetary policy shocks in an international vector autoregression. Using high-frequency data on the prices of Fed Funds futures contracts, we measure the impact of the surprise component of the FOMC-day Federal Reserve policy decision on financial variables, such as the exchange rate and the foreign interest rate. We show how this information can be used to achieve identification without having to make the usual strong assumption of a recursive ordering.
The high-frequency impact of news on long-term yields and forward rates: Is it real?
This paper uses high-frequency intradaily data to estimate the effects of macroeconomic news announcements on yields and forward rates on nominal and index-linked bonds, and on inflation compensation. To our knowledge, it is the first study in the macro announcements literature to use intradaily real yield data, which allow us to parse the effects of news announcements on real rates and inflation compensation far more precisely than we can using daily data. Long-term nominal yields and forward rates are very sensitive to macroeconomic news announcements. We find that inflation compensation is ...
Uncovered interest parity: it works, but not for long
The failure of uncovered interest parity can be ascribed to the existence of a risk premium. The size of this risk premium may shrink to zero over sufficiently small intervals of time. In contrast, because no interest is paid on intradaily positions and interest is instead paid discretely at the point when a position is rolled over from one day to the next, the size of the interest differential remains fixed over any interval that covers the time of the discrete interest payment. This is true no matter how short that interval is. Using a large dataset of high frequency exchange rate data, we ...
Term premiums and inflation uncertainty: empirical evidence from an international panel dataset
This paper provides cross-country empirical evidence on term premia, inflation uncertainty, and their relationship. It has three components. First, I construct a panel of zero-coupon nominal government bond yields spanning ten countries and eighteen years. From these, I construct forward rates and decompose these into expected future short-term interest rates and term premiums, using both statistical methods (an affine term structure model) and using surveys. Second, I construct alternative measures of time-varying inflation uncertainty for these countries, using actual inflation data and ...
Credit spreads as predictors of real-time economic activity: a Bayesian Model-Averaging approach
Employing a large number of financial indicators, we use Bayesian Model Averaging (BMA) to forecast real-time measures of economic activity. The indicators include credit spreads based on portfolios--constructed directly from the secondary market prices of outstanding bonds--sorted by maturity and credit risk. Relative to an autoregressive benchmark, BMA yields consistent improvements in the prediction of the cyclically-sensitive measures of economic activity at horizons from the current quarter out to four quarters hence. The gains in forecast accuracy are statistically significant and ...