Building on a mixed data sampling (MIDAS) model we evaluate the predictive power of a variety of monthly macroeconomic indicators for forecasting quarterly Chinese GDP growth. We iterate the evaluation over forecast horizons from 370 days to 1 day prior to GDP release and track the release days...

This paper presents a MIDAS type mixed frequency VAR forecasting model. First, we propose a general and compact mixed frequency VAR framework using a stacked vector approach. Second, we integrate the mixed frequency VAR with a MIDAS type Almon lag polynomial scheme which is designed to reduce...

In this study we introduce a new monthly indicator for private consumption in Germany based on search query time series provided by Google Trends. The indicator is based on unobserved factors extracted from a set of consumption-related search categories of the Google Trends application Insights...

This paper evaluates the forecast performance of boosting, a variable selection device, and compares it with the forecast combination schemes and dynamic factor models presented in Stock and Watson (2006). Using the same data set and comparison methodology, we find that boosting is a serious...

In any dataset with individual forecasts of economic variables, some forecasters will perform better than others. However, it is possible that these ex post differences reflect sampling variation and thus overstate the ex ante differences between forecasters. In this paper, we present a simple...

Practitioners do not always use research findings, as the research is not always conducted in a manner relevant to real-world practice. This survey seeks to close the gap between research and practice in respect of short-term forecasting in real time. To this end, we review the most relevant...

The use of large-dimensional factor models in forecasting has received much attention in the literature with the consensus being that improvements on forecasts can be achieved when comparing with standard models. However, recent contributions in the literature have demonstrated that care needs...

We use the results of business tendency surveys (BTS) to forecast private investment growth in Peru, exploring the possible non-linear link between the BTS and private investment for forecasting purposes. We find that business confidence indices extracted from BTS, in particular the one...

We show that growth and unemployment forecasts submitted by individual FOMC members do not exhibit herding behavior, while the inflation forecasts show strong evidence of anti-herding. Interestingly, anti-herding is more important for non-voting members than for voters.

In this paper, we develop methods for estimation and forecasting in large time-varying parameter vector autoregressive models (TVP-VARs). To overcome computational constraints, we draw on ideas from the dynamic model averaging literature which achieve reductions in the computational burden...