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...

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...

In recent years there has been increasing interest in forecasting methods that utilise large data sets, driven partly by the recognition that policymaking institutions need to process large quantities of information. Factor analysis is a popular way of doing this. Forecast combination is...

The paper assesses the potential for systematic discrepancies between the measured RPI and an 'ideal' cost-of- living which, the paper argues, should be the target variable for monetary policy (note that the RPI does not claim to be a cost-of-living measure and so this discrepancy does not imply...

The main objective of this paper is to offer a critique of the existing literature on the link between wealth and consumption, as captured by the long-run marginal propensity to consume from financial wealth (mpcw). The international evidence suggests that the mpcw varies considerably across...

In this paper a VAR-based analysis of shocks to G7 GDP components during the 2000/01 slowdown is presented. The patterns of shocks across the components and across the G7 countries are documented, and measures provided of their persistence. The shocks during the preceding expansion are also...

'Consumption risk sharing' refers to the ability of agents to insure or protect their consumption against shocks to their income, for example, by borrowing and lending or holding claims on foreign equity. So measuring the extent of risk sharing informs us about how consumption is likely to...

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...

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...

Density forecast combinations are becoming increasingly popular as a means of improving forecast ‘accuracy’, as measured by a scoring rule. In this paper we generalise this literature by letting the combination weights follow more general schemes. Sieve estimation is used to optimise the...