This paper provides an introduction into the estimation of Marginal Treatment Effects (MTE). Compared to the existing surveys on the subject, our paper is less technical and speaks to the applied economist with a solid basic understanding of econometric techniques who would like to use MTE...

The idea that certain economic variables are roughly constant in the long-run is an old one. Kaldor described them as stylized facts, whereas Klein and Kosobud labelled them great ratios. While such ratios are widely adopted in theoretical models in economics as conditions for balanced growth,...

Structural econometric methods are often criticized for being sensitive to functional form assumptions. We study parametric estimators of the local average treatment effect (LATE) derived from a widely used class of latent threshold crossing models and show they yield LATE estimates...

Trust affects almost all human relationships - in families, organizations, markets and politics. However, identifying the conditions under which trust, defined as people's beliefs in the trustworthiness of others, has a causal effect on the efficiency of human interactions has proven to be...

This paper shows that import exposure affects voting behavior because it affects local labor markets. We develop a new framework for mediation analysis where one instrumental variable is sufficient to identify three causal effects. Using German data from 1987-2009, we find that import exposure...

Establishing causal relationships is a core aspect of empirical economics. Borrowing ideas from the medical sciences, we propose tentative guidelines for reliable causal inferences that cover aspects related to both the study itself and its fit with the existing background knowledge. Moreover,...

This paper develops a machine-learning method that allows researchers to estimate heterogeneous treatment effects with panel data in a setting with many covariates. Our method, which we name the dynamic causal forest (DCF) method, extends the causal-forest method of Wager and Athey (2018) by...

Good decision-making requires understanding the causal impact of our actions. Often, we only have access to correlational data that could stem from multiple causal mechanisms with divergent implications for choice. Our experiments comprehensively characterize choice when subjects face...

We provide evidence that the robust association between cognitive skills and economic growth reflects a causal effect of cognitive skills and supports the economic benefits of effective school policy. We develop a new common metric that allows tracking student achievement across countries, over...

Using bootstrap panel analysis, allowing for cross-country correlation, without the need of pre-testing for unit roots, we study the causality between government spending and revenue for the EU in the period 1960-2006. We find spend-and-tax causality for Italy, France, Spain, Greece, and...