Using a model of deterministic structural change, we revisit several topics in inflation dynamics explored previously using stochastic, time - varying parameter models. We document significant reductions in inflation persistence and predictability. We estimate that changes in the volatility of...

This paper uses kernel methods to estimate a seven variable time-varying (TV) vector autoregressive (VAR) model on the US data set constructed by Smets and Wouters. We use an indirect inference method to map from this TV VAR to time variation in implied Dynamic Stochastic General Equilibrium...

Why is inflation so much lower and at the same time more stable in developed economies in the 1990s, compared with the 1970s? This paper suggests that the United Kingdom, United States and other countries may have escaped from a volatile inflation equilibrium. Our argument builds on the story...

We identify a 'risk news' shock in a vector autoregression (VAR), modifying Barsky and Sims's procedure, while incorporating sign restrictions to simultaneously identify monetary policy, technology and demand shocks. The VAR-identifed risk news shock is estimated to account for around 2%-12% of...

This paper undertakes a Bayesian analysis of optimal monetary policy for the United Kingdom. We estimate a suite of monetary policy models that include both forward and backward-looking representations as well as large and small-scale models. We find an optimal simple Taylor-type rule that...

We show that interest rate rules that feed back on the growth rates of target variables (such as output or asset prices) may induce recessions in the presence of a zero lower bound, through purely self-fulfilling dynamics. This pathology is illustrated in a small New Keynesian model with...

The volatility of inflation and output has fallen in most advanced economies in the 1990s and 2000s. We use a monetary overlapping generations model to discuss the cause and durability of this macroeconomic change. In that model, agents' decision rules require them to make forecasts of future...

Most macroeconomic data are uncertain - they are estimates rather than perfect measures. Use of these uncertain data to form an assessment of current activity can be viewed as a problem of signal extraction. One symptom of that uncertainty is the propensity of statistical agencies to revise...

We estimate a time varying parameter structural macroeconomic model of the UK economy, using a Bayesian local likelihood methodology. This enables us to estimate a large open-economy DSGE model over a sample that comprises several different regimes and an incomplete set of data. Our estimation...

By employing large panels of survey data for the UK economy, we aim at reviewing linear approaches for regularisation and dimension reduction combined with techniques from the machine learning literature, like Random Forests, Support Vector Regressions and Neural Networks for forecasting GDP...