We study how individuals' perceptions of current and future levels of income inequality change during periods of expansionary fiscal policy. In a randomized controlled trial (RCT), we provide information on fiscal expansion to a representative sample of the German population. Our findings reveal that combining a fact-based (numerical) information treatment with a narrative treatment about fiscal expansion plans reduces inequality expectations among respondents who are ex-ante dissatisfied with the government's economic policy. These effects are more pronounced among respondents without a college degree or with low political interest, highlighting the importance of narrative information for individuals who are likely to benefit most from it. We explore potential mechanisms by examining revisions in macro- and micro-level assessments of future economic conditions and find that respondents primarily update their expectations regarding economic growth and individual layoff risk.

We examine whether combining factual information on inflation levels and forecasts with a narrative can persistently shape consumers’ inflation expectations. In a preregistered randomized controlled trial with a representative sample of 3,000 German consumers, participants received either numerical or textual information about inflation rates, with or without an accompanying narrative. All treatments immediately lower inflation expectations, with numerical information eliciting stronger adjustments. Adding a narrative produces no additional immediate effect, confirming that it conveys no new information. However, only the combination of numerical information with a narrative yields a lasting reduction in inflation expectations and forecast uncertainty still observable after four weeks. Our results suggest that combining precise information with a narrative enhances information retention and can lead to more persistent shifts in consumers’ beliefs. The effects are strongest when respondents perceive the narrative as relatable and emotionally engaging, and among those with low financial literacy and limited knowledge of inflation.

In this study, establishment-level employment effects of investment grants in Germany are estimated. In addition to the quantitative effects, I provide empirical evidence of funding effects on different aspects of employment quality (earnings, qualifications, and job security) for the period 2004 to 2020. The database combines project-level treatment data, establishment-level information on firm characteristics and employee structure, and regional information at the district level. For the estimations, I combine the difference-in-differences approach of Callaway and Sant’Anna (J Econom 2252: 200–230, 2021) with ties matching at the cohort level. The estimations yield positive effects on the number of employees, but point to contradicting effects of investment grants on different aspects of employment quality.

We study how individuals’ views on current and future levels of income inequality change during periods of expansionary fiscal policy. In a randomized controlled trial (RCT), we provide information on fiscal expansion to a representative sample of the German population. Our findings reveal that combining a fact-based (numerical) information treatment with a narrative treatment about fiscal expansion plans reduces inequality expectations among respondents who are ex-ante dissatisfied with the government’s economic policy. These effects are more pronounced among respondents without a college degree or with low political interest, highlighting the importance of narrative information for individuals who are likely to benefit most from it. We explore potential mechanisms by examining revisions in macro- and micro-level assessments of future economic conditions and find that respondents primarily update their expectations regarding economic growth and individual layoff risk.

This study provides new evidence on the impact of the EU Cohesion Policy on income growth in less developed regions. Our panel includes data from all European regions for the years 1989-2020. Using a fuzzy Regression Discontinuity Design, we model treatment dynamics by applying a random effects estimator. Based on digitized historical data, we precisely replicate the policy rule and correctly classify the regions’ eligibility status. Results show that the policy has a moderate positive effect on GDP per capita growth in the targeted regions.

This study estimates the firm-level employment effects of investment grants in Germany. In addition to the average treatment effect on the treated, we examine discrimination in the funding rules as a potential source of effect heterogeneity. We combine a staggered difference-in-differences approach with a matching procedure at the cohort level. The findings reveal a positive effect of investment grants on employment development. The subsample analyses yield strong evidence for heterogeneous effects based on firm characteristics and the economic environment. They highlight the responsibility of the local funding authorities to clarify ex ante which goals of a funding programme are most important in their regions.