Current Unpublished Working Papers
Monetary Policy Expectations at the Zero Lower Bound
2013-18 | With Rudebusch | August 2013
Obtaining monetary policy expectations from the yield curve is difficult near the zero lower bound (ZLB). Standard dynamic term structure models, which ignore the ZLB, can be misleading. Shadow-rate models are better suited for this purpose, because they account for the distributional asymmetry in projected short rates induced by the ZLB. Besides providing better interest rate fit and forecasts, our shadow-rate models deliver estimates of the future monetary policy liftoff from the ZLB that are closer to survey expectations. We also document significant improvements for inference about monetary policy expectations when macroeconomic factors are included in the term structure model.
International Channels of the Fed’s Unconventional Monetary Policy
2012-12 | With Neely | August 2013
Previous research has established that the Federal Reserve’s large scale asset purchases (LSAPs) significantly influenced international bond yields. We use dynamic term structure models to uncover to what extent signaling and portfolio balance channels caused these declined. For the U.S. and Canada, the evidence supports the view that LSAPs had substantial signaling effects. For Australian and German yields, signaling effects were more moderate and portfolio balance effects likely played a larger role. Both signaling and portfolio balance effects were small for Japanese yields. Our conclusions regarding the empirical importance of LSAP channels are consistent with predictions based on interest rate dynamics during normal times: Signaling effects tend to be large for countries with strong yield responses to conventional U.S. monetary policy surprises, and portfolio balance effects depend on the degree of substitutability across countries, measured using correlation between foreign and U.S. bond returns.
Nominal Interest Rates and the News
2011-20 | September 2013
This paper provides new estimates of the impact of monetary policy actions and macroeconomic news on the term structure of nominal interest rates. The key novelty is to parsimoniously capture the impact of news on all interest rates using a simple no-arbitrage model. The different types of news are analyzed in a common framework by recognizing their heterogeneity, which allows for a systematic comparison of their effects. This approach leads to novel empirical findings: First, the monetary policy substantially affects both short-term and long-term interest rates, and its effects do not die out with maturity. Second, macroeconomic data surprises have small and insignificant effects on far-ahead forward rates, consistent with conventional macroeconomic models. Third, the term-structure response to macroeconomic news is consistent with considerable interest-rate smoothing by the Federal Reserve. Fourth, monetary policy surprises are multidimensional while macroeconomic news is one-dimensional
Bayesian Estimation of Dynamic Term Structure Models under Restrictions on Risk Pricing
2011-03 | November 2011
This paper performs Bayesian estimation of affine Gaussian dynamic term structure models (DTSMs) in which the risk price parameters are restricted. A new econometric framework for DTSM estimation allows the researcher to select plausible constraints from a large set of restrictions, to correctly quantify statistical uncertainty, and to incorporate model uncertainty. The main empirical result is that under the restrictions favored by the data the expectations component, and not the term premium, accounts for the majority of high-frequency movements of long-term interest rates. At lower frequencies, term premia are counter-cyclical and more stable than implied by DTSMs without risk price restrictions.
Published Articles (Refereed Journals and Volumes)
The Signaling Channel for Federal Reserve Bond Purchases
Forthcoming in International Journal of Central Banking | With Rudebusch
Comment on “Term Premia and Inflation Uncertainty: Empirical Evidence from an International Panel Dataset”
Forthcoming in American Economic Review | With Rudebusch and Wu
Term premia implied by maximum likelihood estimates of affine term structure models are misleading because of small-sample bias. We show that accounting for this bias alters the conclusions about the trend, cycle, and macroeconomic determinants of the term premia estimated in Wright (2011). His term premium estimates are essentially acyclical, and often just parallel the secular trend in long-term interest rates. In contrast, bias-corrected term premia show pronounced countercyclical behavior, consistent with theoretical and empirical arguments about movements in risk premia.
Correcting Estimation Bias in Dynamic Term Structure Models
Journal of Business and Economic Statistics 30(3), July 2012, 454-467 | With Rudebusch and Wu
The affine dynamic term structure model (DTSM) is the canonical empirical finance representation of the yield curve. However, the possibility that DTSM estimates may be distorted by small-sample bias has been largely ignored. We show that conventional estimates of DTSM coefficients are indeed severely biased, and this bias results in misleading estimates of expected future short-term interest rates and of long-maturity term premia. We provide a variety of bias-corrected estimates of affine DTSMs, both for maximally-flexible and over-identified specifications. Our estimates imply short rate expectations and term premia that are more plausible from a macro-finance perspective.
Testing for Endogenous Growth
In Master’s Thesis | Germany: VDM Publishing, 2004
Models of endogenous growth have strong empirical predictions about the determinants of technological progress. This thesis details the implications of alternative R&D-based endogenous growth models, and then surveys the empirical literature that tests different aspects of this New Growth Theory. Numerous studies attempt to test the validity of endogenous growth models but come to very different conclusions, since varying hypotheses are considered. There are few rigorous and plausible empirical assessments of whether the determinants of technological progress conform to the predictions of the theory. I provide new evidence on the relevance of R&D intensity for economic growth, using dynamic panel data methods, thereby contributing to the empirical literature that finds support for R&D-based endogenous growth models.