Vaping Vs. Smoking: The Links To Arthritis And Overall Health Using Double Machine Learning
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DOI: 10.22004/ag.econ.360934
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- Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2018.
"Double/debiased machine learning for treatment and structural parameters,"
Econometrics Journal, Royal Economic Society, vol. 21(1), pages 1-68, February.
- Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney K. Newey & James Robins, 2017. "Double/debiased machine learning for treatment and structural parameters," CeMMAP working papers CWP28/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney K. Newey & James Robins, 2017. "Double/debiased machine learning for treatment and structural parameters," CeMMAP working papers 28/17, Institute for Fiscal Studies.
- Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2017. "Double/Debiased Machine Learning for Treatment and Structural Parameters," NBER Working Papers 23564, National Bureau of Economic Research, Inc.
- Christie Cherian & Eugenia Buta & Patricia Simon & Ralitza Gueorguieva & Suchitra Krishnan-Sarin, 2021. "Association of Vaping and Respiratory Health among Youth in the Population Assessment of Tobacco and Health (PATH) Study Wave 3," IJERPH, MDPI, vol. 18(15), pages 1-11, August.
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This paper has been announced in the following NEP Reports:- NEP-BIG-2026-01-26 (Big Data)
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