Marco Lyrio

Macro Factors and the Term Structure of Interest Rates

This paper presents an essentially affine model of the term structure of interest rates making use of macroeconomic factors and their long-run expectations. The model extends the approach pioneered by Kozicki and Tinsley (2001) by modeling consistently long-run inflation expectations simultaneously with the term structure. Application to the U.S. economy shows the importance of long-run inflation expectations in the modeling of long-term bond yields. The paper also provides a macroeconomic interpretation for the latent factors found in standard finance models of the yield curve: the level factor represents the long-run inflation expectation of agents; the slope factor captures business cycle conditions; and the curvature factor expresses a clear independent monetary policy factor.

The Effect of Monetary Unification on German Bond Markets

We develop a benchmark against which the effects of ECB monetary policy on the German bond market can be evaluated. We first estimate an affine term structure model for the pre-EMU period linking the German yield curve with the Bundesbank monetary policy. The German monetary policy and its implied yield curve are then reprojected onto the EMU period. The reprojected yield curve differs significantly from the observed one. Short-term interest rates during the EMU period are significantly lower than they would have been in case the Bundesbank were still in charge of monetary policy. Furthermore, yield spreads increased substantially during the EMU period.

Estimation of a Joint Model for the Term Structure of Interest Rates and the Macroeconomy

In this paper, we present a stylized continuous time model integrating the macroeconomy and the bond markets. We use this framework to estimate (real) interest rate policy rules using information contained in both macroeconomic variables (i.e. output and inflation) and in the term structure of interest rates. We extend the standard Kalman filter procedure in order to estimate this model efficiently. Application to the U.S. economy shows that this model is able to estimate the macroeconomic dynamics accurately and that the standard feedback rule only in observable factors is not valid within this framework. Moreover, we find that observable macroeconomic variables do not explain much of the term structure. However, (filtered) stochastic central tendencies of these macroeconomic variables do. Finally, both observable and non-observable factors determine the risk premia and hence the excess holding returns of the bonds.

A New-Keynesian Model of the Yield Curve with Learning Dynamics: A Bayesian Evaluation

We estimate a New-Keynesian macro-finance model of the yield curve incorporating learning by private agents with respect to the long-run expectation of inflation and the equilibrium real interest rate. A preliminary analysis shows that some liquidity premia, expressed as some degree of mispricing relative to no-arbitrage restrictions, and time variation in the prices of risk are important features of the data. These features are, therefore, included in our learning model. The model is estimated on U.S. data using Bayesian techniques. The learning model succeeds in explaining the yield curve movements in terms of macroeconomic shocks. The results also show that the introduction of a learning dynamics is not sufficient to explain the rejection of the extended expectations hypothesis. The learning mechanism, however, reveals some interesting points. We observe an important difference between the estimated inflation target of the central bank and the perceived long-run inflation expectation of private agents, implying the latter were weakly anchored. This is especially the case for the period from mid-1970s to mid-1990s. The learning model also allows a new interpretation of the standard level, slope, and curvature factors based on macroeconomic variables. In line with standard macro-finance models, the slope and curvature factors are mainly driven by exogenous monetary policy shocks. Most of the variation in the level factor, however, is due to shocks to the output-neutral real rate, in contrast to the mentioned literature which attributes most of its variation to long-run inflation expectations.

The Predictive Content of the Yield Curve for Inflation

We revisit the common practice of using yield spreads to forecast inflation. We address two main issues. First, we assess the importance of decomposing yield spreads into an expectations and a term premium component in order to predict inflation. Second, we quantify the impact of financial shocks in the dynamics of each of these components. The yield spread decomposition is achieved with the use of a no-arbitrage macro- finance model incorporating both macroeconomic and financial factors. The model is applied to the U.S. economy and estimated with Bayesian techniques. We find that the yield spread decomposition is crucial to forecast inflation for most forecasting horizons. Also, the inclusion of control variables such as the short-term interest rate and lagged dependent variable does not drive out the predictive power of the yield spread decomposition.

Previsão dos preços de commodities por meio das taxas de câmbio

This paper aims to model and predict the behavior of commodity prices using the exchange rates of commodity-exporting countries. Understanding commodity price dynamics is important for a proper control of inflation and planning of production. Our results point to a causality relation between the exchange rate and commodity prices for all countries under study except South Africa and Argentina. For Australia, Brazil, Canada, Chile, Colombia and New Zealand the exchange rate is an important piece of information to forecast commodity prices in-sample. For Australia and Canada, this relation is also significant out-of-sample. Our results confirm those of Chen, Rogoff and Rossi (2010) and extend that work to the cases of Argentina, Brazil, and Colombia.