The past decade has witnessed significant advances in causal inference and Bayesian network learning, two intertwined disciplines that allow researchers to discern underlying cause‐and‐effect ...
Our foray into causal analysis is not yet complete. Until we define the methods of causal inference, we can't get to the deeper insights that causal analysis can provide. This article details many of ...
Machine learning algorithms are widely used for decision making in societally high-stakes settings from child welfare and criminal justice to healthcare and consumer lending. Recent history has ...
In the quest to unravel the underlying mechanisms of natural systems, accurately identifying causal interactions is of paramount importance. Leveraging the advancements in time-series data collection ...
The surge in enterprise AI has fueled interest in causal analysis. In this piece, I explore the threads that bind cause and effect - and how they can be applied across a range of industry scenarios.
We know that correlation does not imply causation, but careful analyses of correlations are often our only way to quantify cause and effect in domains ranging from healthcare to education. This ...
Joshua Angrist GS ’89 was awarded the 2021 Nobel Prize in Economics. He won half of the prize jointly with Guido Imbens “for their methodological contributions to the analysis of causal relationships.
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Citations: Waisman, Caio, Harikesh Nair, Carlos Carrion. 2025. Online Causal Inference for Advertising in Real-Time Bidding Auctions. Marketing Science. (1)176-195.
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