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How Will Machine Learning Impact Economics? (Guido Imbens, Josh Angrist, Isaiah Andrews)

Marginal Revolution University
392K subscribers
25K views 3 years ago
This episode is the most heated of the series! While Nobel laureates Josh Angrist and Guido Imbens agree on most topics, they sharply diverge on the potential of machine learning to impact economics. Host Isaiah Andrews steps in to referee the dispute, adding his own take on how machine learning might change econometrics. Guido Imbens is optimistic about the potential of using machine learning to estimate “personalized casual effects” in large data sets. He laments that econometrics journals have been too rigid in their expectations, turning away many useful insights from machine learning. Josh Angrist has a less rosy view. He has yet to see machine learning make an impact on the work he’s doing. Instead, he’s seen cases where it can be very misleading. More about Guido Imbens: https://www.gsb.stanford.edu/faculty-... More about Joshua Angrist: https://economics.mit.edu/faculty/ang... More about Isaiah Andrews: https://scholar.harvard.edu/iandrews/... 00:00 - Intro 00:18 - Potential for "personalized" causal effects 07:22 - Applications of machine learning 10:17 - Opportunities for publishing in journals 16:12 - Isaiah Andrews referees! ...more
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How Will Machine Learning Impact Economics? (Guido Imbens, Josh Angrist, Isaiah Andrews)
689Likes
25,437Views
2022May 10
This episode is the most heated of the series! While Nobel laureates Josh Angrist and Guido Imbens agree on most topics, they sharply diverge on the potential of machine learning to impact economics. Host Isaiah Andrews steps in to referee the dispute, adding his own take on how machine learning might change econometrics. Guido Imbens is optimistic about the potential of using machine learning to estimate “personalized casual effects” in large data sets. He laments that econometrics journals have been too rigid in their expectations, turning away many useful insights from machine learning. Josh Angrist has a less rosy view. He has yet to see machine learning make an impact on the work he’s doing. Instead, he’s seen cases where it can be very misleading. More about Guido Imbens: https://www.gsb.stanford.edu/faculty-... More about Joshua Angrist: https://economics.mit.edu/faculty/ang... More about Isaiah Andrews: https://scholar.harvard.edu/iandrews/... 00:00 - Intro 00:18 - Potential for "personalized" causal effects 07:22 - Applications of machine learning 10:17 - Opportunities for publishing in journals 16:12 - Isaiah Andrews referees!

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Marginal Revolution University

392K subscribers