Jing Cynthia Wu
I am joining Chicago Booth as an Assistant Professor of Econometrics and Statistics.
Testable Implications of Affine Term Structure Models
with James D. Hamilton, forthcoming in Journal of Econometrics.
Affine term structure models have been used to address a wide range of questions in macroeconomics and finance. This paper investigates a number of their testable implications which have not previously been explored. We show that the assumption that certain specified yields are priced without error is testable, and find that the implied measurement or specification error exhibits serial correlation in all of the possible formulations investigated here. We further find that the predictions of these models for the average levels of different interest rates are inconsistent with the observed data, and propose a more general specification that is not rejected by the data.
The Effectiveness of Alternative Monetary Policy Tools in a Zero Lower Bound Environment (Job Market Paper II)
with James D. Hamilton, forthcoming in Journal of Money, Credit, and Banking.
This paper reviews alternative options for monetary policy when the short-term interest rate is at the zero lower bound and develops new empirical estimates of the effects of the maturity structure of publicly held debt on the term structure of interest rates. We use a model of risk-averse arbitrageurs to develop measures of how the maturity structure of debt held by the public might affect the pricing of level, slope and curvature term-structure risk. We find these Treasury factors historically were quite helpful for predicting both yields and excess returns over 1990-2007. The historical correlations are consistent with the claim that if in December of 2006, the Fed were to have sold off all its Treasury holdings of less than one-year maturity (about $400 billion) and use the proceeds to retire Treasury debt from the long end, this might have resulted in a 14-basis-point drop in the 10-year rate and an 11-basis-point increase in the 6-month rate. We also develop a description of how the dynamic behavior of the term structure of interest rates changed after hitting the zero lower bound in 2009. Our estimates imply that at the zero lower bound, such a maturity swap would have the same effects as buying $400 billion in long-term maturities outright with newly created reserves, and could reduce the 10-year rate by 13 basis points without raising short-term yields.Click here to access the database developed for this paper.
Identification and Estimation of Gaussian Affine Term Structure Models (Job Market Paper I)
with James D. Hamilton, under review
This paper develops new results for both identification and estimation of Gaussian affine term structure models. In terms of identification, we establish that three popular canonical representations are each, for different reasons, unidentified. We also demonstrate that a failure of local identification can complicate numerical search for the maximum-likelihood estimate when one uses conventional estimation methods. A separate contribution of the paper is the proposal of minimum-chi-square estimation as an alternative to maximum-likelihood estimation. We show that, although it is asymptotically equivalent or sometimes even identical to MLE, it can be much easier to compute. In some cases, MCSE allows the researcher to recognize with certainty whether a given estimate represents a global maximum of the likelihood function and makes feasible the computation of small-sample standard errors.
Sample code for
- Purely latent example (to reproduce Table 5)
- MF1 example (to reproduce Table 6)
- MF12 example (to reproduce Table 7)
Unbiased Estimation of Dynamic Term Structure Models
with Michael D. Bauer and Glenn D. Rudebusch, under review.
Affine dynamic term structure models (DTSMs) are the canonical finance representation of the yield curve. However, the literature on DTSMs has ignored the coefficient bias that plagues estimated autoregressive models of persistent time series. We introduce new simulation-based methods for reducing or even eliminating small-sample bias in empirical affine Gaussian DTSMs. With these methods, we show that conventional estimates of DTSM coefficients are severely biased, which results in misleading estimates of expected future short-term interest rates and long-maturity term premia. Our unbiased DTSM estimates imply risk-neutral rates and term premia that are more plausible from a macro-finance perspective.