Changes in the shape of the yield curve have traditionally been one of the key macroeconomic indicators of a likely change in economic outlook. However, the recent financial crises have created a challenge to the management of monetary policy, demanding a revision in the way that policymakers model expected changes in the economy. This volume brings together central bank economists and leading academic monetary economists to propose new methods for modelling the behaviour of interest rates. Topics covered include: the analysis and extraction of expectations of future monetary policy and inflation; the analysis of the short-term dynamics of money market interest rates; the reliability of existing models in periods of extreme market volatility and how to adjust them accordingly; and the role of government debt and deficits in affecting sovereign bond yields and spreads. This book will interest financial researchers and practitioners as well as academic and central bank economists.

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.

State-of-the-art research from academics and policymakers on the role of and challenges to monetary policy during the ongoing financial crisis.

This Element is intended for students and practitioners as a gentle and intuitive introduction to the field of discrete-time yield curve modelling. I strive to be as comprehensive as possible, while still adhering to the overall premise of putting a strong focus on practical applications. In addition to a thorough description of the Nelson-Siegel family of model, the Element contains a section on the intuitive relationship between P and Q measures, one on how the structure of a Nelson-Siegel model can be retained in the arbitrage-free framework, and a dedicated section that provides a detailed explanation for the Joslin, Singleton, and Zhu (2011) model.

Macroeconomic concepts such as in ation and real economic activity are not directly observed. Researchers often use factor models in order to measure these unobserved concepts. The underlying view is that a small number of factors exist which represent the concept and drive many related variables. Consequently, the U.S. economy is often modeled as an a ne function of some factors. If indeed there is such a factor structure for the U.S. economy, then it can be represented by a generalized dynamic factor model (GDFM). In the rst chapter, I describe and summarize the literature on GDFMs. In the second chapter, I investigate the interactions and mutually independent dynamics of changes in in ation and real growth by applying the GDFM to a block of real growth variables, a block of in ation variables, and to their joint panel. In this manner, an empirical decomposition of the U.S. economy is obtained and this allows the reconcilitaion of forward and backward looking Phillips curves. In the third chapter, I build and study a discrete time generalized dynamic a ne term structure model. This is characterized by three main features that are conceptually important for a ne yield curve models. I allow: (a) for state vector dynamics beyond Markovian types; (b) that all yields may contain an idiosyncratic component to re ect measurement-errors in the data; and (c) that idiosyncratic components may be crosssectional as well as time-serial correlated. It is possible to directly compare this model with the version that is restricted by Du e-Kan's no-arbitrage conditions. Chapter four addresses whether or not changes in yields can be explained by changes to the latent dynamic factors which underlie the macroeconomic concepts of in ation and real growth. As such, I contribute to the debate about whether or not monetary policy should react to real activity measures.