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ABSTRACT This article develops a new family of Gaussian macro-dynamic term structure models (MTSMs) in which bond yields follow a lowdimensional factor structure and the historical distribution of bond yields and macroeconomic variables is characterized by a vectorautoregression with order p > 1. Most formulations of MTSMs with p > 1 are shown to imply a much higher dimensional factor structure for yields than what is called for by historical data. In contrast, our "asymmetric" arbitrage-free MTSM gives modelers the flexibility to match historical lag distributions with p > 1 while maintaining a parsimonious factor representation of yields. Using our canonical family of MTSMs we revisit: (i) the impact of no-arbitrage restrictions on the joint distribution of bond yields and macro risks, comparing models with and without the restriction that macro risks are spanned by yield-curve information; and (ii) the identification of the policy parameters in Taylor-style monetary policy rules within MTSMs with macro risk factors and lags. ( JEL: G12,E43, C58, E58) KEYWORDS: Macro-finance term structure model, Lags, Taylor Rule Identification Dynamic term structure models in which a subset of the pricing factors are macroeconomic variables (MTSMs) often have bond yields depending on lags of these factors. 1 As typically parameterized, such MTSMs imply that the cross-section

This paper provides cross-country empirical evidence on bond risk premia. I construct a panel of zero-coupon nominal government bond yields spanning ten industrialized countries and nearly two decades. I hence compute forward rates and then use two different methods to decompose these forward rates into expected future short-term interest rates and term premiums. The first method uses an affine term structure model with macroeconomic variables as unspanned risk factors; the second method uses surveys. I find that term premium estimates declined across countries over the sample period, especially in countries that appear to have reduced inflation uncertainty by making substantial changes in the monetary policy frameworks of their central banks. During the recent financial crisis, term premiums have remained flat and even declined further in some countries, perhaps reflecting the effects of quantitative easing actions by many central banks.

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We develop a class of dynamic term structure models that accommodates arbitrarily many interest-rate factors with very few parameters. The model builds on a cascade interest-rate dynamics that naturally ranks the factors by their rates of mean reversion, with each revolving around the next lower-frequency factor. The model further achieves dimension invariance by parameterizing the distributions of coefficients of the different frequency components. The net result is a class of term structure models with merely five parameters regardless of the number of factors. Using a panel of 15 LIBOR and swap rates, we estimate 15 models with one to 15 factors. The extensive estimation exercise shows that the 15-factor model significantly outperforms the other lower-dimensional specifications. The high-dimensional specification generates root mean squared pricing errors less than one basis point, thus making it an ideal candidate as a basis for forward rate curve stripping. The model also overcomes several known limitations of low-dimensional specifications by matching the observed low cross-correlations between changes in different interest rate series and by

We develop a class of dynamic term structure models that accommodates arbitrarily many interest-rate factors with very few parameters. The model builds on a short-rate cascade, a parsimonious recursive structure that naturally ranks the latent state variables by their rates of mean reversion, each revolving around the next lowest-frequency factor. With appropriate assumptions on volatilities and risk premia, the model overcomes the curse of dimensionality associated with general affine models. Using a panel of 15 LIBOR and swap rates, we estimate models using from one to 15 factors and only five parameters. The in-sample fit of high-dimensional specifications is near exact, with absolute pricing errors averaging less than one basis point, permitting yield-curve stripping in an arbitrage-free, dynamically consistent en-vironment. Cross-maturity correlations accurately reflect empirical evidence, and out-of-sample interest

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Yield curve models within the Nelson and Siegel (1987, hereafter NS) class have proven very popular in …nance and macro…nance, but they lack a theoretical foundation. In this article, I show how the Level, Slope, and Curvature components common to all NS models arise explicitly from low-order Taylor expansions around central measures of the eigenvalues for the generic Gaussian a ¢ ne term structure model outlined in Dai and Singleton (2002). That theoretical foundation provides an assurance that NS models correspond to a well-accepted framework for yield curve modeling. It further suggests that any yield curve from the GATSM class can be represented parsimoniously by a two-factor arbitrage-free NS model. I derive such a model and apply it to investigating changes in United States yield curve dynamics over the period from 1971 to 2010. The results provide evidence for material changes in the data-generating process for the yield curve between the periods 1971-1987, 1988-2002, and 2003-2010.

The yield curve and the macro-economy across time and frequencies

yield curve and the macro-economy across time and frequencies