Using double-debiased machine learning to estimate the impact of Covid-19 vaccination on mortality and staff absences in elderly care homes
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DOI: 10.1016/j.euroecorev.2024.104882
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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 Newey & James Robins, 2017. "Double/Debiased Machine Learning for Treatment and Structural Parameters," NBER Working Papers 23564, National Bureau of Economic Research, Inc.
- 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.
- Achim Ahrens & Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann, 2024.
"ddml: Double/debiased machine learning in Stata,"
Stata Journal, StataCorp LP, vol. 24(1), pages 3-45, March.
- Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann & Achim Ahrens, 2022. "ddml: Double/debiased machine learning in Stata," Swiss Stata Conference 2022 02, Stata Users Group.
- Ahrens, Achim & Hansen, Christian B. & Schaffer, Mark E & Wiemann, Thomas, 2023. "ddml: Double/Debiased Machine Learning in Stata," IZA Discussion Papers 15963, Institute of Labor Economics (IZA).
- Achim Ahrens & Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann, 2023. "ddml: Double/debiased machine learning in Stata," Papers 2301.09397, arXiv.org, revised Jan 2024.
- Virat Agrawal & Neeraj Sood & Christopher M. Whaley, 2023. "The Impact of the Global COVID-19 Vaccination Campaign on All-Cause Mortality," NBER Working Papers 31812, National Bureau of Economic Research, Inc.
- John Gibson, 2023.
"Jabbing the economy back to life?,"
Applied Economics Letters, Taylor & Francis Journals, vol. 30(21), pages 2999-3005, December.
- John Gibson, 2021. "Jabbing the Economy Back to Life?," Working Papers in Economics 21/11, University of Waikato.
- Alexander Karaivanov & Dongwoo Kim & Shih En Lu & Hitoshi Shigeoka, 2022.
"COVID-19 vaccination mandates and vaccine uptake,"
Nature Human Behaviour, Nature, vol. 6(12), pages 1615-1624, December.
- Alexander Karaivanov & Dongwoo Kim & Shih En Lu & Hitoshi Shigeoka, 2021. "COVID-19 Vaccination Mandates and Vaccine Uptake," NBER Working Papers 29563, National Bureau of Economic Research, Inc.
- Alexander Karaivanov & Dongwoo Kim & Shih En Lu & Hitoshi Shigeoka, 2021. "COVID-19 Vaccination Mandates and Vaccine Uptake," Discussion Papers dp21-13, Department of Economics, Simon Fraser University.
- Karaivanov, Alexander & Kim, Dongwoo & Lu, Shih En & Shigeoka, Hitoshi, 2021. "COVID-19 Vaccination Mandates and Vaccine Uptake," IZA Discussion Papers 14946, Institute of Labor Economics (IZA).
- Markus B Bjoerkheim & Alex Tabarrok, 2022. "Covid in the nursing homes: the US experience," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 38(4), pages 887-911.
- M. Keith Chen & Judith A. Chevalier & Elisa F. Long, 2021.
"Nursing home staff networks and COVID-19,"
Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 118(1), pages 2015455118-, January.
- M. Keith Chen & Judith A. Chevalier & Elisa F. Long, 2020. "Nursing Home Staff Networks and COVID-19," NBER Working Papers 27608, National Bureau of Economic Research, Inc.
- M. Keith Chen & Judith A. Chevalier & Elisa F. Long, 2020. "Nursing Home Staff Networks and COVID-19," Papers 2007.11789, arXiv.org, revised Jul 2020.
- Victor Chernozhukov & Mert Demirer & Esther Duflo & Iv'an Fern'andez-Val, 2017.
"Fisher-Schultz Lecture: Generic Machine Learning Inference on Heterogenous Treatment Effects in Randomized Experiments, with an Application to Immunization in India,"
Papers
1712.04802, arXiv.org, revised Oct 2023.
- Victor Chernozhukov & Mert Demirer & Esther Duflo & Iván Fernández-Val, 2023. "Fischer-Schultz Lecture: Generic Machine Learning Inference on Heterogenous Treatment Effects in Randomized Experiments, with an Application to Immunization in India," Working Papers hal-04238425, HAL.
- Newton C. A. da Costa & Francisco Antonio Doria & Jaqueline Vianna & Vitor Rodrigues, 2022. "On the Existence of Universal Vaccines," Review of Behavioral Economics, now publishers, vol. 9(4), pages 379–381-3, November.
- John Gibson, 2022. "The Rollout of COVID-19 Booster Vaccines is Associated With Rising Excess Mortality in New Zealand," Working Papers in Economics 22/11, University of Waikato.
- Rahi Abouk & John S. Earle & Johanna Catherine Maclean & Sungbin Park, 2024. "Promoting Public Health with Blunt Instruments: Evidence from Vaccine Mandates," NBER Working Papers 32286, National Bureau of Economic Research, Inc.
- Butler, David & Butler, Robert & Farnell, Alex & Simmons, Robert, 2024. "COVID-19 infections and short-run worker performance: Evidence from European football," European Journal of Operational Research, Elsevier, vol. 315(2), pages 750-763.
- Elizabeth B. Pathak & Janelle M. Menard & Rebecca B. Garcia & Jason L. Salemi, 2022. "Joint Effects of Socioeconomic Position, Race/Ethnicity, and Gender on COVID-19 Mortality among Working-Age Adults in the United States," IJERPH, MDPI, vol. 19(9), pages 1-15, April.
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- Coco, Giuseppe & Monturano, Gianluca & Resce, Giuliano, 2025. "Predicting Delays in Cohesion Infrastructure Projects," Economics & Statistics Discussion Papers esdp25099, University of Molise, Department of Economics.
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More about this item
Keywords
Machine learning; Vaccines; Care homes; Covid-19;All these keywords.
JEL classification:
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
- I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
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