Macroeconomic data are subject to revision over time as later vintages are released, yet the usual way of generating real-time out-of-sample forecasts from models effectively makes no allowance for this form of data uncertainty. We analyse a simple method which has been used in the context of...

The expectations-augmented Phillips curve (PC) is a cornerstone of many macroeconomic models. We consider the extent to which professional forecasters' inflation and unemployment rate forecasts are `theory consistent', and find much heterogeneity. Perceptions about the responsiveness of...

In this paper we consider the value of Google Trends search data for nowcasting (and forecasting) GDP growth for a developed (U.S.) and emerging-market economy (Brazil). Our focus is on the marginal contribution of "Big Data" in the form of Google Trends data over and above that of traditional...

Macro-variables such as consumption, investment and output are expected to move together in the long run. We consider whether survey forecasts of these quantities suggest beliefs about equilibrium relationships play a prominent role in expectations formation. Evidence is brought to bear from an...

A structural break is viewed as a permanent change in the parameter vector of a model. Using taxonomies of all sources of forecast errors for both conditional mean and conditional variance processes, we consider the impacts of breaks and their relevance in forecasting models: (a) where the...