This paper studies whether dynamic term structure models for US nominal bond yields should enforce the zero lower bound by a quadratic policy rate or a shadow rate specification. We address the question by estimating quadratic term structure models (QTSMs) and shadow rate models (SRMs) with at...

We use a no-arbitrage shadow rate term structure model to estimate investors' views about the timing of monetary policy ‘lift-off' in the United Kingdom over time. Our estimates show that when the UK policy rate was first cut to 0.5%, in March 2009, investors believed that it would remain at...

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...

We consider time series forecasting in the presence of ongoing structural change where both the time-series dependence and the nature of the structural change are unknown. Methods that downweight older data, such as rolling regressions, forecast averaging over different windows and exponentially...

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...

We study the interaction between monetary policy and labour supply decisions at the household level. We uncover evidence of heterogeneous responses and a strong income effect on labour supply in the left tail of the income distribution, following a monetary policy shock in the US and the UK....

We examine how to forecast after a recent break. We consider monitoring for change and then combining forecasts from models that do and do not use data before the change; and robust methods, namely rolling regressions, forecast averaging over different windows and exponentially weighted moving...

We estimate a Bayesian VAR analogue to the Bank of England's DSGE model (COMPASS) and assess their relative performance in forecasting GDP growth and CPI inflation in real time between 2000 and 2012. We find that the BVAR outperformed COMPASS when forecasting both GDP and its expenditure...

We develop early warning models for financial crisis prediction using machine learning techniques on macrofinancial data for 17 countries over 1870–2016. Machine learning models mostly outperform logistic regression in out-of-sample predictions and forecasting. We identify economic drivers of...

The Bank of England has constructed a 'suite of statistical forecasting models' (the 'Suite') providing judgement-free statistical forecasts of inflation and output growth as one of many inputs into the forecasting process, and to offer measures of relevant news in the data. The Suite combines a...