Jing Cynthia Wu studies econometrics, monetary economics, and asset pricing. Her research interests include the term structure of interest rates, monetary policy, financial crises, and commodity futures markets. Her work helps unravel complicated term structure models and develops a straightforward framework for identification, estimation and specification testing. Applying term structure models to monetary policy and commodity futures markets, she contributes important insights to the current literature on “quantitative easing” when the policy rate is at the zero lower bound, and the debate between policy makers and academia on the impact of index fund investment on the commodity futures prices.
Her work has been cited by Federal Reserve chairman Ben Bernanke, vice chair Janet Yellen, President of San Francisco Fed John Williams, among academia, media and blogs.
Co-authored with James D. Hamilton, Wu’s most recent publication is titled “Identification and Estimation of Gaussian Affine Term Structure Models,” forthcoming in the Journal of Econometrics
Wu earned her PhD in economics from UC San Diego. She teaches Applied Regression Analysis at Booth.
Selected Publications
With James D. Hamilton, “Identification and Estimation of Gaussian Affine Term Structure Models,” Journal of Econometrics (forthcoming).
With James D. Hamilton, “The Effectiveness of Alternative Monetary Policy Tools in a Zero Lower Bound Environment,” Journal of Money, Credit, and Banking (2012).
For a listing of research publications please visit Jing Cynthia Wu’s
university library listing page.
REVISION: Unbiased Estimation of Dynamic Term Structure Models
Date Posted: Aug 11, 2011
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 e
New: Identification and Estimation of Gaussian Affine Term Structure Models
Date Posted: Aug 11, 2011
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 estim
New: Testable Implications of Affine Term Structure Models
Date Posted: May 13, 2011
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 the
New: The Effectiveness of Alternative Monetary Policy Tools in a Zero Lower Bound Environment
Date Posted: May 13, 2011
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