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...

With a novel dataset, we test whether sentiment in TV news can be used as a proxy for consumer sentiment in order to explain changes in private consumption growth in the United States. The University of Michigan Index of Consumer Sentiment is taken to compare its explanatory power with TV...

We perform principal components analyses of the University of Michigan Index of Consumer Sentiment and TV sentiment in order to gain information on their structure and information content. By introducing the new sentiment variable TV sentiment, gathered from sentiment from statements from over...

We evaluate the usefulness of satellite-based data on nighttime lights for the prediction of annual GDP growth across a global sample of countries. Going beyond traditional measures of luminosity, such as the sum of lights within a country's borders, we propose several innovative distribution-...

This paper presents a composite leading indicator for the Swiss business cycle corresponding to the growth rate cycle concept. It is the result of a complete overhaul of the KOF Economic Barometer that has been published by the KOF Swiss Economic Institute on a monthly basis since 1976. In line...

We investigate whether the KOF Barometer - a leading indicator regularly released by the KOF Swiss Economic Institute - can be useful for short-term out-of-sample prediction of year-on-year quarterly real GDP growth rates in Switzerland. We find that the KOF Barometer appears to be useful for...

This paper presents a coincident and a leading composite monthly indicator for the world business cycle - the Global Economic Barometers. Both target the world's output growth rate cycle. The calculation of these indicators comprises two main stages. The first consists of a variable selection...

Adaptive learning introduces persistence in the evolution of agents' beliefs over time. For applied purposes this is a convenient feature to help explain why economies present sluggish adjustments towards equilibrium. The pace of learning is directly determined by the gain parameter, which...

Under adaptive learning, recursive algorithms are proposed to represent how agents update their beliefs over time. For applied purposes these algorithms require initial estimates of agents perceived law of motion. Obtaining appropriate initial estimates can become prohibitive within the usual...