New statistical method eliminates AI estimation bias in econometrics
A new research paper describes a statistical framework that resolves significant calculation biases caused by artificial intelligence in econometric models. The method, two-step extraction, removes estimation bias when researchers measure the business or economic effects of variables extracted using...
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A new research paper describes a statistical framework that resolves significant calculation biases caused by artificial intelligence in econometric models. The method, two-step extraction, removes estimation bias when researchers measure the business or economic effects of variables extracted using machine learning algorithms from unstructured data such as photos and consumer text.
Originally published at Phys.org
