We evaluate nowcasts and one- to four-quarter-ahead forecasts of Swiss full time equivalent jobs from 1998-2011, comparing forecasts of the KOF Swiss Economic Institute and of the State Secretariat for Economic Affairs with the outcome of the reference series. Both forecasts are biased downward,...

In this paper we suggest an approach to comparison of models' forecasting performance in unstable environments. Our approach is based on combination of the Cumulated Sum of Squared Forecast Error Differential (CSSFED) suggested earlier in Welch and Goyal (2008) and the Bayesian change point...

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...

GDP forecasters face tough choices over which leading indicators to follow and which forecasting models to use. To help resolve these issues, we examine a range of monthly indicators to forecast quarterly GDP growth in a major emerging economy, Russia. Numerous useful indicators are identified...

We evaluate nowcasts and one- to four-quarter-ahead forecasts of Swiss full time equivalent jobs from 1998q1–2011q4, comparing forecasts of the KOF Swiss Economic Institute and of the State Secretariat for Economic Affairs with the outcome of the reference series. Both forecasts are biased...

We compare forecasts from different adaptive learning algorithms and calibrations applied to US real-time data on inflation and growth. We find that the Least Squares with constant gains adjusted to match (past) survey forecasts provides the best overall performance both in terms of forecasting...

This paper assesses the probability method for quantifying EU consumer survey data on perceived and expected inflation. Based on household level data from the Swedish consumer survey that asks for both qualitative and quantitative responses, it is found that the theoretical assumptions of the...

This article re-examines the findings of Stock and Watson (2012b) who assessed the predictive performance of dynamic factor models (DFM) over autoregressive (AR) bench-marks for hundreds of target variables by focusing on possible business cycle performance asymmetries in the spirit of Chauvet...

We examine the information content of a newly created news sentiment index from over 300,000 articles from some of the most widely read newspapers in the US to explain changes in the University of Michigan Index of Consumer Sentiment from 1995 to 2009. Using ARMA-models, we show that consumer...