The major contributions of twentieth century econometrics to knowledge were the definition of causal parameters when agents are constrained by resources and markets and causes are interrelated, the analysis of what is required to recover causal parameters from data (the identification problem),...

Education and income are strong predictors of health and longevity. In the last 20 years many efforts have been made to understand if these relationships are causal and what the possible role of policy should be as a result. The evidence from various studies is ambiguous: the effects of...

This paper explores methods for inferring the causal effects of treatments on choices by combining data on real choices with hypothetical evaluations. We propose a class of estimators, identify conditions under which they yield consistent estimates, and derive their asymptotic distributions. The...

In this paper we intend to survey and suggest the theoretical framework of the important aspects of causality detection with the purpose of conveying to the reader the essential features and the different forms in which inferences may be drawn from given data. Section II presents the basic...

This paper proposes strategies for defining, identifying, and estimating features of treatment-effect distributions in contexts where multiple outcomes are of interest. After describing existing empirical approaches used in such settings, the paper develops a notion of treatment preference that...

We describe a framework for empirical welfare analysis that uses the causal estimates of a policy's impact on net government spending. This framework provides guidance for which causal effects are (and are not) needed for empirical welfare analysis of public policies.The key ingredient is the...

What is the impact of granular credit risk on banks and on the economy? We provide the first causal identification of single-name counterparty exposure risk in bank portfolios by applying a new empirical approach on an administrative matched bank-firm dataset from Norway. Exploiting the fat tail...

Marginal outcome tests compare the expected effects of a decision on individuals who are of different races but at the same indifference point of the decision-maker. I present a simple formalization of how such tests can detect racial bias, defined as a deviation from accurate statistical...

Consider a rational expectations (RE) model that includes a relationship between variables `x_t` and `z_(t+1)`. To be considered structural and potentially useful as a guide to actual behavior, this model must specify whether `x_t` is influenced by the expectation at t of `z_(t+1)` or,...