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Technology, skills, and performance: the case of robots in surgery

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  • Elena Ashtari Tafti

    (Institute for Fiscal Studies)

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  • Elena Ashtari Tafti, 2022. "Technology, skills, and performance: the case of robots in surgery," IFS Working Papers W22/46, Institute for Fiscal Studies.
  • Handle: RePEc:ifs:ifsewp:22/46
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    File URL: https://ifs.org.uk/sites/default/files/2024-08/WP202246-Technology-skills-and-performance-the-case-of-robots-in-surgery%20%281%29_0.pdf
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    1. Angus Deaton, 2003. "Health, Inequality, and Economic Development," Journal of Economic Literature, American Economic Association, vol. 41(1), pages 113-158, March.
    2. Zack Cooper & Steve Gibbons & Simon Jones & Alistair McGuire, 2010. "Does Hospital Competition Improve Efficiency? An Analysis of the Recent Market-Based Reforms to the English NHS," CEP Discussion Papers dp0988, Centre for Economic Performance, LSE.
    3. David Card & Alessandra Fenizia & David Silver, 2023. "The Health Impacts of Hospital Delivery Practices," American Economic Journal: Economic Policy, American Economic Association, vol. 15(2), pages 42-81, May.
    4. Thomas Cornelissen & Christian Dustmann & Anna Raute & Uta Schönberg, 2018. "Who Benefits from Universal Child Care? Estimating Marginal Returns to Early Child Care Attendance," Journal of Political Economy, University of Chicago Press, vol. 126(6), pages 2356-2409.
    5. James J. Heckman & Edward Vytlacil, 2005. "Structural Equations, Treatment Effects, and Econometric Policy Evaluation," Econometrica, Econometric Society, vol. 73(3), pages 669-738, May.
    6. Cornelissen, Thomas & Dustmann, Christian & Raute, Anna & Schönberg, Uta, 2016. "From LATE to MTE: Alternative methods for the evaluation of policy interventions," Labour Economics, Elsevier, vol. 41(C), pages 47-60.
    7. Pedro Carneiro & James J. Heckman & Edward J. Vytlacil, 2011. "Estimating Marginal Returns to Education," American Economic Review, American Economic Association, vol. 101(6), pages 2754-2781, October.
    8. Edward Vytlacil & James J. Heckman, 2001. "Policy-Relevant Treatment Effects," American Economic Review, American Economic Association, vol. 91(2), pages 107-111, May.
    9. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    10. James J. Heckman & Sergio Urzua & Edward Vytlacil, 2006. "Understanding Instrumental Variables in Models with Essential Heterogeneity," The Review of Economics and Statistics, MIT Press, vol. 88(3), pages 389-432, August.
    11. Amy Finkelstein & Matthew Gentzkow & Heidi Williams, 2016. "Sources of Geographic Variation in Health Care: Evidence From PatientMigration," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1681-1726.
    12. Jonathan T. Kolstad, 2013. "Information and Quality when Motivation is Intrinsic: Evidence from Surgeon Report Cards," NBER Working Papers 18804, National Bureau of Economic Research, Inc.
    13. David Molitor, 2018. "The Evolution of Physician Practice Styles: Evidence from Cardiologist Migration," American Economic Journal: Economic Policy, American Economic Association, vol. 10(1), pages 326-356, February.
    14. Horn, Danea & Sacarny, Adam & Zhou, Annetta, 2022. "Technology adoption and market allocation: The case of robotic surgery," Journal of Health Economics, Elsevier, vol. 86(C).
    15. Daron Acemoglu & Pascual Restrepo, 2020. "Robots and Jobs: Evidence from US Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 128(6), pages 2188-2244.
    16. Maynou, Laia & Pearson, Georgia & McGuire, Alistair & Serra-Sastre, Victoria, 2022. "The diffusion of robotic surgery: examining technology use in the English NHS," LSE Research Online Documents on Economics 114535, London School of Economics and Political Science, LSE Library.
    17. Maynou, Laia & Pearson, Georgia & McGuire, Alistair & Serra-Sastre, Victoria, 2022. "The diffusion of robotic surgery: Examining technology use in the English NHS," Health Policy, Elsevier, vol. 126(4), pages 325-336.
    18. Jason Abaluck & Leila Agha & Chris Kabrhel & Ali Raja & Arjun Venkatesh, 2016. "The Determinants of Productivity in Medical Testing: Intensity and Allocation of Care," American Economic Review, American Economic Association, vol. 106(12), pages 3730-3764, December.
    19. Gowrisankaran, Gautam & Town, Robert J., 1999. "Estimating the quality of care in hospitals using instrumental variables," Journal of Health Economics, Elsevier, vol. 18(6), pages 747-767, December.
    20. Janet Currie & W. Bentley MacLeod, 2017. "Diagnosing Expertise: Human Capital, Decision Making, and Performance among Physicians," Journal of Labor Economics, University of Chicago Press, vol. 35(1), pages 1-43.
    21. McClellan, Mark & Newhouse, Joseph P., 1997. "The marginal cost-effectiveness of medical technology: A panel instrumental-variables approach," Journal of Econometrics, Elsevier, vol. 77(1), pages 39-64, March.
    22. Amitabh Chandra & Douglas O. Staiger, 2007. "Productivity Spillovers in Health Care: Evidence from the Treatment of Heart Attacks," Journal of Political Economy, University of Chicago Press, vol. 115(1), pages 103-140.
    23. Tavneet Suri, 2011. "Selection and Comparative Advantage in Technology Adoption," Econometrica, Econometric Society, vol. 79(1), pages 159-209, January.
    24. Martin Eckhoff Andresen, 2018. "Exploring marginal treatment effects: Flexible estimation using Stata," Stata Journal, StataCorp LP, vol. 18(1), pages 118-158, March.
    25. Christian N. Brinch & Magne Mogstad & Matthew Wiswall, 2017. "Beyond LATE with a Discrete Instrument," Journal of Political Economy, University of Chicago Press, vol. 125(4), pages 985-1039.
    26. Xiang Zhou & Yu Xie, 2019. "Marginal Treatment Effects from a Propensity Score Perspective," Journal of Political Economy, University of Chicago Press, vol. 127(6), pages 3070-3084.
    27. Jonathan T. Kolstad, 2013. "Information and Quality When Motivation Is Intrinsic: Evidence from Surgeon Report Cards," American Economic Review, American Economic Association, vol. 103(7), pages 2875-2910, December.
    28. Amitabh Chandra & Douglas O Staiger, 2020. "Identifying Sources of Inefficiency in Healthcare [“The Determinants of Productivity in Medical Testing: Intensity and Allocation of Care,”]," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 135(2), pages 785-843.
    29. David C Chan & Matthew Gentzkow & Chuan Yu, 2022. "Selection with Variation in Diagnostic Skill: Evidence from Radiologists [The Determinants of Productivity in Medical Testing: Intensity and Allocation of Care]," The Quarterly Journal of Economics, Oxford University Press, vol. 137(2), pages 729-783.
    30. Borghans, Lex & Green, Francis & Mayhew, Ken, 2001. "Skills Measurement and Economic Analysis: An Introduction," Oxford Economic Papers, Oxford University Press, vol. 53(3), pages 375-384, July.
    31. Souvik Banerjee & Anirban Basu, 2021. "Estimating Endogenous Treatment Effects Using Latent Factor Models with and without Instrumental Variables," Econometrics, MDPI, vol. 9(1), pages 1-25, March.
    32. Skinner, Jonathan, 2011. "Causes and Consequences of Regional Variations in Health Care," Handbook of Health Economics, in: Mark V. Pauly & Thomas G. Mcguire & Pedro P. Barros (ed.), Handbook of Health Economics, volume 2, chapter 0, pages 45-93, Elsevier.
    33. Guido W. Imbens & Donald B. Rubin, 1997. "Estimating Outcome Distributions for Compliers in Instrumental Variables Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 555-574.
    34. Bjorklund, Anders & Moffitt, Robert, 1987. "The Estimation of Wage Gains and Welfare Gains in Self-selection," The Review of Economics and Statistics, MIT Press, vol. 69(1), pages 42-49, February.
    35. Edward Vytlacil, 2002. "Independence, Monotonicity, and Latent Index Models: An Equivalence Result," Econometrica, Econometric Society, vol. 70(1), pages 331-341, January.
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