In density forecasts, respondents are asked to assign probabilities to pre-specifted ranges of inflation. We show in two large-scale experiments that responses vary when we modify the response scale. Asking an identical question with modifted response scales induces different answers: Shifting,...

The approach by Engelberg, Manski, and Williams (2009) to convert probabilistic survey responses into continuous probability distributions implicitly assumes that the question intervals are equally wide. Almost all recently established household surveys have intervals of varying widths. Applying...

In density forecasts, respondents are asked to assign probabilities to a response scale with pre-specified ranges of inflation. In two large-scale experiments, one conducted in the US and one in Germany, we show how the specifics of the response scale determine the responses: Shifting,...

In density forecasts, respondents are asked to assign probabilities to pre-specified ranges of inflation. We show in two large-scale experiments that responses vary when we modify the response scale. Asking an identical question with modified response scales induces different answers: Shifting,...

We present the results of an experiment where a random subset of the participants in the Bundesbank's household panel receive personalized response scales, centered at each participant's point forecast. Personalized response scales offer two advantages over the standard scale which is centered...

We investigate the question whether macroeconomic variables contain information about future stock volatility beyond that contained in past volatility. We show that forecasts of GDP and industrial production growth from the Federal Reserve's Survey of Professional Forecasters predict volatility...

We examine the properties and forecast performance of multiplicative volatility specifications that belong to the class of GARCH-MIDAS models suggested in Engle et al. (2013). In those models volatility is decomposed into a short-term GARCH component and a long-term component that is driven by...

We investigate the relationship between long-term U.S. stock market risks and the macroeconomic environment using a two component GARCH-MIDAS model. Our results show that macroeconomic variables are important determinants of the secular component of stock market volatility. Among the various...

We investigate the relationship between long-term U.S. stock market risks and the macroeconomic environment using a two component GARCH-MIDAS model. Our results provide strong evidence in favor of counter-cyclical behavior of long-term stock market volatility. Among the various macro variables...