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This thesis examines the macro-finance-fiscal term structure model to incorporate fiscal instability variables and the term spread to understand the impact of the sovereign debt crisis on the evolution of the yield curve. My findings reveal financial instability increases the term spread associated with the expectation of higher sovereign default risk and consequently signals economic agents to reduce their spending, and thus worsens economic activity. Secondly, I also investigate whether the dynamic factor model with nonparametric factor loadings is more accurate relative to other term structure models by employing the dynamic semi-parametric factor model (DSFM). The empirical results indicate that a better in-sample fit is provided by the dynamic semiparametric factor model. However, the overall forecasting results are not encouraging. The dynamic semiparametric factor model provides accurate results in forecasting a persistent trend while the dynamic Nelson-Siegel model is more suitable to fit more volatile series. Thirdly,I use a Sheen-Trueck-Wang business conditions index for term structure modeling and forecasting. I find the cross-sectional yield provides guidance to anchor the yield in the next period. The prediction performance of the model is enhancedby using the index since it includes information on frequently released or more recent available data. The index is significantly related to the slope factor, which suggests the forward-looking information from the index inuences the adjustmentthe in the yield slope. Lastly, I examine the effectiveness of the US quantitative easing (QE) policy with a Bayesian structural vector auto regressive (B-SVAR)model with sign restrictions. I find the transmission mechanism of the Federal Reserve asset purchase effectively expands output and avert deflation through a compression in the yield spread.
Interest rates are directly related to our lives. When interest rates are high, we hold less cash and more interest-bearing assets because we face a high opportunity cost of holding cash. Interest rates are directly related to the economy. When interest rates are high, there are not as many viable opportunities for firms to invest as when they are low, leading to a lower level of investment and a lower level of economic activities. Interest rates are directly related to the objectives of countries' monetary policy. This book, entitled "Interest Rates: Term Structure Models, Monetary Policy and Prediction" sheds light on selected aspects of this multifaceted role of interest rates. Topics discussed include term structure models; policy interest rates and the usefulness of interest rates as a predictor.
Interest rate rules play an important role in the empirical analysis of monetary policy as well as in modern monetary theory. Besides giving a comprehensive insight into this line of research the study incorporates the term structure of interest rates into interest rate rules. This is performed analytically as well as empirically. In doing so, state of the art techniques of modern finance for the analysis of the term structure of interest rates are introduced into the macroeconomic concept of interest rate rules. The study implies that from the theoretical perspective term structure effects are an important extension of interest rate rules. From an empirical perspective it shows that including term structure effects in interest rate reaction functions improves our understanding of the interest rate setting of the Deutsche Bundesbank and the European Central Bank.
Understanding the dynamic evolution of the yield curve is critical to many financial tasks, including pricing financial assets and their derivatives, managing financial risk, allocating portfolios, structuring fiscal debt, conducting monetary policy, and valuing capital goods. Unfortunately, most yield curve models tend to be theoretically rigorous but empirically disappointing, or empirically successful but theoretically lacking. In this book, Francis Diebold and Glenn Rudebusch propose two extensions of the classic yield curve model of Nelson and Siegel that are both theoretically rigorous and empirically successful. The first extension is the dynamic Nelson-Siegel model (DNS), while the second takes this dynamic version and makes it arbitrage-free (AFNS). Diebold and Rudebusch show how these two models are just slightly different implementations of a single unified approach to dynamic yield curve modeling and forecasting. They emphasize both descriptive and efficient-markets aspects, they pay special attention to the links between the yield curve and macroeconomic fundamentals, and they show why DNS and AFNS are likely to remain of lasting appeal even as alternative arbitrage-free models are developed. Based on the Econometric and Tinbergen Institutes Lectures, Yield Curve Modeling and Forecasting contains essential tools with enhanced utility for academics, central banks, governments, and industry.
This paper introduces global factors within a FAVAR framework in an empirical affine term structure model. We apply our method to a panel of international yield curves and show that global factors account for more than 80 percent of term premia in advanced economies. In particular they tend to explain long-term dynamics in yield curves, as opposed to domestic factors which are instead more relevant to short-run movements. We uncover the key role for global curvature in shaping term premia dynamics. We show that this novel factor precedes global economic and financial instability. In particular, it coincides with immediate expectations of permanent expansionary monetary policy during the recent crisis.
This dissertation studies the relationship between the term structure of interest rates, monetary policy, and macroeconomy. The first chapter, A Parsimonious No-Arbitrage Term Structure Model that is Useful for Forecasting, offers a solution to a well-known puzzle in the term structure literature. The puzzle is that while the level, slope and curvature (or the first three principal components of yields) can quite accurately summarize the cross-section of yields at any point in time, different functions of interest rates and other macroeconomic variables appear to be helpful when the goal is to predict future interest rates. My paper proposes a parsimonious representation to capture this feature in a large dataset. In the first step, I run reduced rank regressions of one-year excess returns on a panel of 131 macroeconomic variables and initial forward rates from 1964 to 2007. I find that a single linear combination of macroeconomic variables and forward rates can predict excess returns on two- to five-year maturity bonds with R-squared up to 0.71. The forecasting factor subsumes the tent-shaped linear combination of forward rates constructed by Cochrane and Piazzesi (2003) and explains excess returns better. In the second step, I estimate a restricted Gaussian Affine Term Structure Model (GATSM) with the level, slope and curvature commonly used by most term structure models along with the forecasting factor. Restrictions are derived based on the fact that while cross-sectional information in yields is spanned by the level, slope and curvature, cross-sectional information in expected excess returns is spanned by the forecasting factor. Compared with a conventional GATSM only including the level, slope and curvature, the restricted four-factor GATSM generates plausible countercyclical term premia. The second and third chapter focus on the recent zero lower bound (ZLB) period. In the second chapter, Measuring the Macroeconomic Impact of Monetary Policy at the Zero Lower Bound, coauthored with Cynthia Wu, we employ an approximation that makes a nonlinear shadow rate term structure model (SRTSM) extremely tractable for analysis of an economy operating near the zero lower bound for interest rates. We show that such a model offers a better description of the data compared to the widely used GATSM. Moreover, the model can be used to summarize the macroeconomic effects of unconventional monetary policy at the ZLB. Using a simple factor-augmented vector autoregression (FAVAR), we show that the shadow rate calculated by our model exhibits similar dynamic correlations with macro variables of interest in the period since 2009 as the fed funds rate did in data prior to the Great Recession. This result gives us a tool for measuring the effects of monetary policy under the ZLB, using either historical estimates based on the fed funds rate or less precisely measured estimates inferred solely from the new data for the shadow rate alone. We show that the Fed has used unconventional policy measures to successfully lower the shadow rate. Our estimates imply that the Fed's efforts to stimulate the economy since 2009 have succeeded in lowering the unemployment rate by 0.13% relative to where it would have been in the absence of these measure. The third chapter, Effects of Unconventional Monetary Policies on the Term Structure of Interest Rates, offers a complete characterization of effects of unconventional monetary policies on interest rates by examining policies' impacts on the whole yield curve. I make use of the SRTSM to summarize all interest rates with factors of lower dimension so that I can capture responses of all interest rates in a parsimonious way. By investigating how policy announcements affect the three factors and then the whole forward curve accordingly, I find that during the ZLB period, forward rate with short maturities are constrained, while forward rates with long maturities still respond to policy announcements. Following each easing (tightening) policy announcement, long forward rates would decrease (increase) by 10 basis points on average.