Can one single political leader influence macroeconomic expectations on a global scale? We design a large-scale survey experiment among influential economic experts working in more than 100 countries and use the 2020 US presidential election as a quasi-natural experiment to identify the effect...

In discrete manufacturing, the knowledge about causal relationships makes it possible to avoid unforeseen production downtimes by identifying their root causes. Learning causal structures from real-world settings remains challenging due to high-dimensional data, a mix of discrete and continuous...

Binary treatments are often ex-post aggregates of multiple treatments or can be disaggregated into multiple treatment versions. Thus, effects can be heterogeneous due to either effect or treatment heterogeneity. We propose a decomposition method that uncovers masked heterogeneity, avoids...

We propose a general protocol for calibration and validation of complex simulation models by an approach based on discovery and comparison of causal structures. The key idea is that configurations of parameters of a given theoretical model are selected by minimizing a distance index between two...

This paper evaluates the effectiveness of the COVID-19 temporarily led restriction on short selling by the Stock Exchange of Thailand (SET). We investigate the causal effect of short selling restriction on return, volatility and market quality from 2 September 2019 to 30 September 2020....