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What does the yield curve tell us about GDP growth?
A lot, including a few things you may not expect. Previous studies find that the term spread forecasts GDP but these regressions are unconstrained and do not model regressor endogeneity. We build a dynamic model for GDP growth and yields that completely characterizes expectations of GDP. The model does not permit arbitrage. Contrary to previous findings, we predict that the short rate has more predictive power than any term spread. We confirm this finding by forecasting GDP out-of-sample. The model also recommends the use of lagged GDP and the longest maturity yield to measure slope. Greater ...
The term structure of real rates and expected inflation
Changes in nominal interest rates must be due to either movements in real interest rates or expected inflation, or both. We develop a term structure model with regime switches, time-varying prices of risk and inflation to identify these components of the nominal yield curve. We find that the unconditional real rate curve is fairly flat at 1.44%, but slightly humped. In one regime, the real term structure is steeply downward sloping. Real rates (nominal rates) are pro-cyclical (counter-cyclical) and inflation is negatively correlated with real rates. An inflation risk premium that increases ...
No-arbitrage Taylor rules
We estimate Taylor (1993) rules and identify monetary policy shocks using no-arbitrage pricing techniques. Long-term interest rates are risk-adjusted expected values of future short rates and thus provide strong over-identifying restrictions about the policy rule used by the Federal Reserve. The no-arbitrage framework also accommodates backward-looking and forward-looking Taylor rules. We find that inflation and GDP growth account for over half of the time-variation of yield levels and we attribute almost all of the movements in the term spread to inflation. Taylor rules estimated with ...
Do macro variables, asset markets, or surveys forecast inflation better?
Surveys do! We examine the forecasting power of four alternative methods of forecasting U.S. inflation out-of-sample: time series ARIMA models; regressions using real activity measures motivated from the Phillips curve; term structure models that include linear, non-linear, and arbitrage-free specifications; and survey-based measures. We also investigate several methods of combining forecasts. Our results show that surveys outperform the other forecasting methods and that the term structure specifications perform relatively poorly. We find little evidence that combining forecasts produces ...