We show how the Joslin, Singleton, and Zhu (2011) factor extraction approach to estimating the Gaussian term structure model can be modified to handle the interest rate lower bound without the approximations used in other approaches. This drastically reduces the computation time and produces more robust estimates of the lower bound parameter and the shadow rate. It makes feasible the extensive specification search necessary to allow for unspanned factors as in Joslin, Priebsch, and Singleton (2014), allowing the term structure model to be used to better assess the effects of policy on the term premium and market expectations.

This paper argues that first passage time models are likely to better than affine hazard rate models in modelling stressed credit markets and confirms their superior performance in explaining the behavior of Credit Default Swap rates for the major US banking groups over the period of the financial crisis. Affine models find it hard to deal with periods of exceptionally high or low default risk given their assumption of a constant rate of mean reversion in the hazard rate. In contrast, first passage time models are specified in terms of the distance to default rather than the hazard rate. The persistence of shocks varies with the distance to default, allowing the default curve to invert sharply (compress) when the distance to default is low (high). I use an empirical version of the Collin-Dufresne et al. (2003) model, which contains a smoothing parameter that allows it to control the relative effect of these shocks on the short spreads and can be interpreted as an information lag.

This paper develops a macro-finance model of the Brazilian economy and its sovereign debt markets that allows for domestic and international macroeconomic influences as well as swings in investor confidence. It finds significant evidence of common trends in the US and Brazilian economies and bond markets as well as spillover effects from US inflation and business cycles to the Brazilian economy. The US Fed Funds rate influences Brazilian sovereign spreads, as do Brazilian inflation and policy rates. The Brazilian confidence factor dominates the behavior of the spreads during periods of crisis and we find that it also has a powerful effect on the level and volatility of macroeconomic variables. These results suggest that the macro-finance approach could throw light upon the behavior of other economies that are troubled by sovereign risk.

This paper develops a multi-country macro-finance model to study international economic and financial linkages. This approach models the economy and financial markets jointly using both types of data to throw light on such issues. The world economy is modelled using data for the US and aggregate OECD economies as well as the US Treasury bond market using latent variables to represent a common inflation trend and a US real interest rate factor. We find strong evidence of global effects on both the US and UK, calling into question the standard closed economy macro-finance specification. These economic linkages also help to explain the co-movement of yields in the US and UK Treasury bond markets.

We advocate the use of excess returns rather than yields or log prices in analysing the risk neutral dynamics of the term structure. We show that under standard assumptions, excess returns are affine in the risk neutral innovations in the factors. This framework has several important advantages. First, it allows for an easy estimation of models that are more flexible than the AR(1). Indeed, we estimate models with more general dynamics, like ARFIMA(p, d, q), almost as easily as AR(1). Second, within our framework the dimension of the unrestricted model is the same for the AR(1) as it is for the richer models, and does not expand in line with the state vector as it does in a yield or log price framework. This makes it appropriate to test all of these risk neutral dynamic specifications against the same OLS unrestricted alternative. Our results for the US Treasury bond market show that the unrestricted model is preferred to the AR(1) by the Bayesian Information Criterion, but the opposite conclusion is reached for more flexible models. A final advantage of the excess returns framework is that the pricing errors are much lower than for the equivalent log price system.