This paper shows how particle filtering allows us to undertake likelihood-based inference in dynamic macroeconomic models. The models can be nonlinear and/or non-normal. We describe how to use the output from the particle filter to estimate the structural parameters of the model, those...

This paper shows how changes in the volatility of the real interest rate at which small open emerging economies borrow have a quantitatively important effect on real variables like output, consumption, investment, and hours worked. To motivate our investigation, we document the strong evidence...

This paper provides first and second-order approximation methods for the solution of non-linear dynamic stochastic models in which the exogenous state variables follow conditionally-linear stochastic processes displaying time-varying risk. The first-order approximation is consistent with a...

We conduct an extensive empirical analysis of VIX derivative valuation models over the 2004-2007 bull market and the subsequent financial crisis. We show that existing models yield large distortions during the crisis because of their restrictive volatility mean reverting assumptions. We propose...

A model of profits switches between four regimes with fixed probabilities; the rationally expected profits stream implies the stock market value. This efficient market model is not rejected by UK post-war time-series behaviour of either profits or the FTSE index.

The paper analyses the transmission of liquidity shocks and risk shocks to global financial markets. Using a Global VAR methodology, the findings reveal fundamental differences in the transmission strength and pattern between the 2007-08 financial crisis and the 2010-11 sovereign debt crisis....

The dynamic behavior of the term structure of interest rates is difficult to replicate with models, and even models with a proven track record of empirical performance have underperformed since the early 2000s. On the other hand, survey expectations are accurate predictors of yields, but only...

This paper is concerned with methods for analysing spatial data. After initial discussion on the nature of spatial data, including the concept of randomness, we focus most of our attention on linear regression models that involve interactions between agents across space. The introduction of...

This paper provides an overview of the panel VAR models used in macroeconomics and finance. It discusses what are their distinctive features, what they are used for, and how they can be derived from economic theory. It also describes how they are estimated and how shock identification is...

We find that forecasts from DSGE models are not more accurate than either times series models or official forecasts, but neither are they any worse. We also find that all three types of forecast failed to predict the recession that started in 2007 and continued to forecast poorly even after the...