COVID-19 hit firms by surprise. In a high frequency, representative panel of German firms, the business outlook declined and business uncertainty increased only when the spread of the COVID-19 pandemic led to domestic policy changes: The announcement of nation-wide school closures on March 13...

Using a representative online panel from the US, we examine how individuals' macroeconomic expectations causally affect their personal economic prospects and their behavior. To exogenously vary respondents' expectations we provide them with different professional forecasts about the likelihood...

This paper introduces two co-movement measures based on the Thick Pen Transform into the macroeconomic literature: the Thick Pen Measure of Association (TPMA) as well as Multi-Thickness Thick Pen Measure of Association (MTTPMA). Both measures are non-parametric, time-varying, and flexible....

This paper proposes tests of policy ineffectiveness in the context of macroeconometric rational expectations models. It is assumed that there is a policy intervention that takes the form of changes in the parameters of a policy rule, and that there are sufficient observations before and after...

Macroeconomic uncertainty affects the subjective distribution of individual expectations. Using four panel datasets, we document the effects of macro uncertainty on the mean expectation (first moment) and subjective uncertainty (second moment) of income forecasts. We find that macro uncertainty...

This paper documents the existence of Political Forecast Cycles. In a theoretical model of political selection, we show that governments release overly optimistic GDP growth forecasts ahead of elections to increase the reelection probability. The bias arises from lack of commitment if voters are...

Survey forecasts are prone to entry and exit of forecasters as well as forecasters not contributing every period leading to gaps. These gaps make it difficult to compare individual forecasters to each other and raises the question of how to deal with the missing observations. This is addressed...

We develop novel forecasting methods for panel data with heterogeneous parameters and examine them together with existing approaches. We conduct a systematic comparison of their predictive accuracy in settings with different cross-sectional (N) and time (T) dimensions and varying degrees of...