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...

We argue that in modelling cross-country growth models one should first identify so-called outlying observations. For the data set of Sala-i-Martin, we use the least median of squares (LMS) estimator to identify outliers. As LMS is not suited for inference, we then use reweighted least squares...

We critically assess an almost universal Benefit-Cost Analysis (BCA) practice. In addition to the central Net Present Value (NPV), analysts frequently also report multiple additional values in what is commonly referred to as ‘NPV sensitivity analysis’. This practice is generally justified...

Understanding the mechanisms through which treatment effects come about is crucial for designing effective interventions. The identification of such causal mechanisms is challenging and typically requires strong assumptions. This paper discusses identification and estimation of natural direct...

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...

We investigate how protectionist policies influence economic growth. Our empirical strategy exploits an extraordinary tax scandal that gave rise to an unexpected change of government in Sweden. A free-trade majority in parliament was overturned by a protectionist majority in 1887. We employ the...

We use the US presidential election on 3 November 2020 to examine how the US president influences economic expectations of international experts. We design a large-scale RCT among 843 experts working in 107 countries, asking about their expectations regarding GDP growth, unemployment, inflation,...

We provide a new framework to identify demand elasticities in markets where managers rely on algorithmic recommendations for price setting, and apply it to a dataset containing bookings for a sample of mid-sized hotels in Europe. Using non-binding algorithmic price recommendations and observed...

We analyze over 44,000 economics working papers from 1980–2023 using a custom language model to construct knowledge graphs mapping economic concepts and their relationships, distinguishing between general claims and those supported by causal inference methods. The share of causal claims within...

In recent years, several automated caps, or algorithmic quantity regulations (AQRs), have been deployed to police supply conditions in sharing economy platforms. AQRs constitute a paradigm shift in platform regulation, as they enable exhaustive, and low-cost enforcement, thus comprehensively...