In this book, Andrew Harvey sets out to provide a unified and comprehensive theory of structural time series models. Unlike the traditional ARIMA models, structural time series models consist explicitly of unobserved components, such as trends and seasonals, which have a direct interpretation. As a result the model selection methodology associated with structural models is much closer to econometric methodology. The link with econometrics is made even closer by the natural way in which the models can be extended to include explanatory variables and to cope with multivariate time series. From the technical point of view, state space models and the Kalman filter play a key role in the statistical treatment of structural time series models. The book includes a detailed treatment of the Kalman filter. This technique was originally developed in control engineering, but is becoming increasingly important in fields such as economics and operations research. This book is concerned primarily with modelling economic and social time series, and with addressing the special problems which the treatment of such series poses. The properties of the models and the methodological techniques used to select them are illustrated with various applications. These range from the modellling of trends and cycles in US macroeconomic time series to to an evaluation of the effects of seat belt legislation in the UK.

Forecasting, Structural Time Series Models and the Kalman Filter

This paper employs an approximation that makes a nonlinear term structure model extremely tractable for analysis of an economy operating near the zero lower bound for interest rates. We show that such a model oers an excellent description of the data and can be used to summarize the macroeconomic eects of unconventional monetary policy at the zero lower bound. Our estimates imply that the eorts by the Federal Reserve to stimulate the economy since 2009 succeeded in making the unemployment rate in May 2013 0.23% lower than it otherwise would have been.

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Measuring the Macroeconomic Impact of Monetary Policy at the Zero Lower Bound

This paper employs an approximation that makes a nonlinear term structure model extremely tractable for analysis of an economy operating near the zero lower bound for interest rates. We show that such a model offers an excellent description of the data compared to the benchmark model and can be used to summarize the macroeconomic effects of unconventional monetary policy. Our estimates imply that the efforts by the Federal Reserve to stimulate the economy since July 2009 succeeded in making the unemployment rate in December 2013 1% lower, which is 0.13% more compared to the historical behavior of the Fed.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID2469299_code753937.pdf?abstractid=2321323&mirid=4

https://www.federalreserve.gov/pubs/ifdp/2013/1081/ifdp1081.pdf

Capital flows to emerging market economies: A brave new world?

/pdf/methods-of-policy-accommodation-at-the-interest-rate-lower-5d59gvepsi.pdf

Methods of Policy Accommodation at the Interest-Rate Lower Bound

Previous research has emphasized the portfolio balance effects of Federal Reserve bond purchases, in which a reduced bond supply lowers term premia. In contrast, we find that such purchases have important signaling effects that lower expected future short-term interest rates. Our evidence comes from a model-free analysis and from dynamic term structure models that decompose declines in yields following Fed announcements into changes in risk premia and expected short rates. To overcome problems in measuring term premia, we consider bias-corrected model estimation and restricted risk price estimation. In comparison with other studies, our estimates of signaling effects are larger in magnitude and statistical significance.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID2334518_code1037079.pdf?abstractid=2334518&mirid=1&type=2

The Signaling Channel for Federal Reserve Bond Purchases

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, for both maximally flexible and overidentified specifications. Our estimates imply interest rate expectations and term premia that are more plausible from a macrofinance perspective. This article has supplementary material online.

/pdf/correcting-estimation-bias-in-dynamic-term-structure-models-1pxemm39yw.pdf

Correcting Estimation Bias in Dynamic Term Structure Models

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 declines. 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 present but likely more moderate, and portfolio balance effects appear to have played a relatively larger role than in the U.S. and Canada. Portfolio balance effects were small for Japanese yields and signaling effects basically nonexistent. These findings about 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 are consistent with the degree of substitutability across nternational bonds, as measured by the covariance between foreign and U.S. bond returns.

/pdf/international-channels-of-the-fed-s-unconventional-monetary-2tygq2a4ac.pdf

International Channels of the Fed’s Unconventional Monetary Policy

We show that conventional dynamic term structure models (DTSMs) estimated on recent U.S. data severely violate the zero lower bound (ZLB) on nominal interest rates and deliver poor forecasts of future short rates. In contrast, shadow-rate DTSMs account for the ZLB by construction, capture the resulting distributional asymmetry of future short rates, and achieve good forecast performance. These models provide more accurate estimates of the most likely path for future monetary policy --- including the timing of policy liftoff from the ZLB and the pace of subsequent policy tightening. We also demonstrate the benefits of including macroeconomic factors in a shadow-rate DTSM when yields are constrained near the ZLB.

/pdf/monetary-policy-expectations-at-the-zero-lower-bound-5drjgz30nt.pdf

Monetary Policy Expectations at the Zero Lower Bound

https://www.frbsf.org/economic-research/files/wp12-12bk.pdf

Michael D. Bauer

Papers

The Signaling Channel for Federal Reserve Bond Purchases

Correcting Estimation Bias in Dynamic Term Structure Models

International Channels of the Fed’s Unconventional Monetary Policy

Monetary Policy Expectations at the Zero Lower Bound

International channels of the Fed's unconventional monetary policy