Centralized school assignment algorithms must distinguish between applicants with the same preferences and priorities. This is done with randomly assigned lottery numbers, nonlottery tie-breakers like test scores, or both. The New York City public high school match illustrates the latter, using...

Previous research has shown how terrorist attacks attract media attention and influence public opinion and decision-makers. However, we lack a comparative assessment of the extent to which extremist ideologies matter and how they matter. Therefore, this paper compares mass media debates over...

This paper develops a novel method for policy choice in a dynamic setting where the available data is a multi-variate time series. Building on the statistical treatment choice framework, we propose Time-series Empirical Welfare Maximization (T-EWM) methods to estimate an optimal policy rule by...

Using causal graphs, this paper develops a simple check to uncover the direction of the causal link between economic policy uncertainty and stock market volatility. The check is applied to monthly data for 22 countries. The results imply that uncertainty is an instantaneous cause of stock market...

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...

One of the perceived advantages of difference-in-differences (DiD) methods is that they do not explicitly restrict how units select into treatment. However, when justifying DiD, researchers often argue that the treatment is "quasi-randomly" assigned. We investigate what selection mechanisms are...

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...

Decarbonizing the global energy matrix through investments in renewable energy (RE) is considered a pathway to mitigate the effects of global climate change. Auctions have become an increasingly popular policy instrument for this purpose. In the last few years, auctions have been rapidly adopted...

We introduce the package ddml for Double/Debiased Machine Learning (DDML) in Stata. Estimators of causal parameters for five different econometric models are supported, allowing for flexible estimation of causal effects of endogenous variables in settings with unknown functional forms and/or...

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...