[go: up one dir, main page]

IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/30345.html
   My bibliography  Save this paper

Overconfidence and Technology Adoption in Health Care

Author

Listed:
  • Diego A. Comin
  • Jonathan S. Skinner
  • Douglas O. Staiger
Abstract
Variation in technology adoption is a key driver of differences in productivity. Previous studies sought to explain variations in technology adoption by heterogeneity in profitability, costs of adoption, or other factors. Less is known about how adoption is affected by bias in the perceived skill to implement the technology. We develop a Bayesian framework in which the use of the technology depends on perceived skill, while the outcomes from using it depend on actual skill. We study the determinants of adoption in the case of implantable cardiac defibrillators (ICDs) for which we document large differences across hospitals in the rate of adoption between 2002-2006, and a strong reversal from 2006-2013. We find that perception bias explains two-thirds of the cross-hospital variation in ICD use. A dynamic version of the model with learning about bias predicts accurately the subsequent decline in ICD use between 2006-2013. These results suggest an important role for misperception in explaining the wide variation in the adoption of new technologies.

Suggested Citation

  • Diego A. Comin & Jonathan S. Skinner & Douglas O. Staiger, 2022. "Overconfidence and Technology Adoption in Health Care," NBER Working Papers 30345, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:30345
    Note: AG EH PR
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w30345.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Foster, Andrew D & Rosenzweig, Mark R, 1995. "Learning by Doing and Learning from Others: Human Capital and Technical Change in Agriculture," Journal of Political Economy, University of Chicago Press, vol. 103(6), pages 1176-1209, December.
    2. Diego Comin & Bart Hobijn, 2007. "Implementing Technology," NBER Working Papers 12886, National Bureau of Economic Research, Inc.
    3. Diego Comin & Bart Hobijn, 2010. "An Exploration of Technology Diffusion," American Economic Review, American Economic Association, vol. 100(5), pages 2031-2059, December.
    4. Leila Agha & David Molitor, 2018. "The Local Influence of Pioneer Investigators on Technology Adoption: Evidence from New Cancer Drugs," The Review of Economics and Statistics, MIT Press, vol. 100(1), pages 29-44, March.
    5. Olley, G Steven & Pakes, Ariel, 1996. "The Dynamics of Productivity in the Telecommunications Equipment Industry," Econometrica, Econometric Society, vol. 64(6), pages 1263-1297, November.
    6. Wu, Bingxiao & David, Guy, 2022. "Information, relative skill, and technology abandonment," Journal of Health Economics, Elsevier, vol. 83(C).
    7. Wennberg, David E. & Sharp, Sandra M. & Bevan, Gwyn & Skinner, Jonathan S. & Gottlieb, Daniel J. & Wennberg, John E., 2014. "A population health approach to reducing observational intensity bias in health risk adjustment: cross sectional analysis of insurance claims," LSE Research Online Documents on Economics 56671, London School of Economics and Political Science, LSE Library.
    8. 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.
    9. Ulrike Malmendier & Geoffrey Tate, 2015. "Behavioral CEOs: The Role of Managerial Overconfidence," Journal of Economic Perspectives, American Economic Association, vol. 29(4), pages 37-60, Fall.
    10. Diego Comin & Martí Mestieri, 2018. "If Technology Has Arrived Everywhere, Why Has Income Diverged?," American Economic Journal: Macroeconomics, American Economic Association, vol. 10(3), pages 137-178, July.
    11. 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.
    12. Esther Duflo & Michael Kremer & Jonathan Robinson, 2011. "Nudging Farmers to Use Fertilizer: Theory and Experimental Evidence from Kenya," American Economic Review, American Economic Association, vol. 101(6), pages 2350-2390, October.
    13. Timothy G. Conley & Christopher R. Udry, 2010. "Learning about a New Technology: Pineapple in Ghana," American Economic Review, American Economic Association, vol. 100(1), pages 35-69, March.
    14. Dan Lovallo & Colin Camerer, 1999. "Overconfidence and Excess Entry: An Experimental Approach," American Economic Review, American Economic Association, vol. 89(1), pages 306-318, March.
    15. Boyan Jovanovic & Yaw Nyarko, 1995. "A Bayesian Learning Model Fitted to a Variety of Empirical Learning Curves," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 26(1995 Micr), pages 247-305.
    16. 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.
    17. Amitabh Chandra & Douglas O. Staiger, 2010. "Identifying Provider Prejudice in Healthcare," NBER Working Papers 16382, National Bureau of Economic Research, Inc.
    18. Tavneet Suri, 2011. "Selection and Comparative Advantage in Technology Adoption," Econometrica, Econometric Society, vol. 79(1), pages 159-209, January.
    19. Markus Glaser & Martin Weber, 2007. "Overconfidence and trading volume," The Geneva Papers on Risk and Insurance Theory, Springer;International Association for the Study of Insurance Economics (The Geneva Association), vol. 32(1), pages 1-36, June.
    20. Brad M. Barber & Terrance Odean, 2001. "Boys will be Boys: Gender, Overconfidence, and Common Stock Investment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 116(1), pages 261-292.
    21. 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.
    22. David Cutler & Jonathan S. Skinner & Ariel Dora Stern & David Wennberg, 2019. "Physician Beliefs and Patient Preferences: A New Look at Regional Variation in Health Care Spending," American Economic Journal: Economic Policy, American Economic Association, vol. 11(1), pages 192-221, February.
    23. Jonathan Skinner & Douglas Staiger, 2015. "Technology Diffusion and Productivity Growth in Health Care," The Review of Economics and Statistics, MIT Press, vol. 97(5), pages 951-964, December.
    24. Diego A. Comin & Martí Mestieri, 2010. "An Intensive Exploration of Technology Diffusion," NBER Working Papers 16379, National Bureau of Economic Research, Inc.
    25. Sendhil Mullainathan & Ziad Obermeyer, 2022. "Diagnosing Physician Error: A Machine Learning Approach to Low-Value Health Care [“The Determinants of Productivity in Medical Testing: Intensity and Allocation of Care,”]," The Quarterly Journal of Economics, Oxford University Press, vol. 137(2), pages 679-727.
    26. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Comin, Diego & Mestieri, Martí, 2014. "Technology Diffusion: Measurement, Causes, and Consequences," Handbook of Economic Growth, in: Philippe Aghion & Steven Durlauf (ed.), Handbook of Economic Growth, edition 1, volume 2, chapter 2, pages 565-622, Elsevier.
    2. Sebastian Calónico & Rafael Di Tella & Juan Cruz Lopez del Valle, 2023. "The Political Economy of a “Miracle Cure”: The Case of Nebulized Ibuprofen and its Diffusion in Argentina," NBER Working Papers 31781, National Bureau of Economic Research, Inc.
    3. Tafti, Elena Ashtari, 2023. "Technology, Skills, and Performance: The Case of Robots in Surgery," CINCH Working Paper Series (since 2020) 78746, Duisburg-Essen University Library, DuEPublico.
    4. Edward D. Perry & David A. Hennessy & GianCarlo Moschini, 2022. "Uncertainty and learning in a technologically dynamic industry: Seed density in U.S. maize," American Journal of Agricultural Economics, John Wiley & Sons, vol. 104(4), pages 1388-1410, August.
    5. Barham, Bradford L. & Chavas, Jean-Paul & Fitz, Dylan & Schechter, Laura, 2018. "Receptiveness to advice, cognitive ability, and technology adoption," Journal of Economic Behavior & Organization, Elsevier, vol. 149(C), pages 239-268.
    6. Apoorv Gupta & Jacopo Ponticelli & Andrea Tesei, 2020. "Language Barriers, Technology Adoption and Productivity: Evidence from Agriculture in India," NBER Working Papers 27192, National Bureau of Economic Research, Inc.
    7. Attema, Arthur E. & Galizzi, Matteo M. & Groß, Mona & Hennig-Schmidt, Heike & Karay, Yassin & L’Haridon, Olivier & Wiesen, Daniel, 2023. "The formation of physician altruism," Journal of Health Economics, Elsevier, vol. 87(C).
    8. Frankovic, Ivan & Kuhn, Michael & Wrzaczek, Stefan, 2020. "Medical innovation and its diffusion: Implications for economic performance and welfare," Journal of Macroeconomics, Elsevier, vol. 66(C).
    9. Avdic, Daniel & Ivets, Maryna & Lagerqvist, Bo & Sriubaite, Ieva, 2023. "Providers, peers and patients. How do physicians’ practice environments affect patient outcomes?," Journal of Health Economics, Elsevier, vol. 89(C).
    10. Elena Ashtari Tafti, 2022. "Technology, skills, and performance: the case of robots in surgery," IFS Working Papers W22/46, Institute for Fiscal Studies.
    11. Hannes Ullrich & Michael Allan Ribers, 2023. "Machine predictions and human decisions with variation in payoffs and skill: the case of antibiotic prescribing," Berlin School of Economics Discussion Papers 0027, Berlin School of Economics.
    12. Pablo Celhay & Paul Gertler & Paula Giavagnoli & Christel Vermeersch, 2016. "Nudging Medical Providers to Adopt and Sustain Better Quality Care Practices," Natural Field Experiments 00537, The Field Experiments Website.
    13. Terrance Hurley & Jawoo Koo & Kindie Tesfaye, 2018. "Weather risk: how does it change the yield benefits of nitrogen fertilizer and improved maize varieties in sub‐Saharan Africa?," Agricultural Economics, International Association of Agricultural Economists, vol. 49(6), pages 711-723, November.
    14. Michelson, Hope & Fairbairn, Anna & Ellison, Brenna & Maertens, Annemie & Manyong, Victor, 2021. "Misperceived quality: Fertilizer in Tanzania," Journal of Development Economics, Elsevier, vol. 148(C).
    15. William F. Maloney & Felipe Valencia Caicedo, 2014. "Engineers, Innovative Capacity and Development in the Americas," Documentos CEDE 11948, Universidad de los Andes, Facultad de Economía, CEDE.
    16. Ram Fishman & Stephen C. Smith & Vida Bobic & Munshi Sulaiman, 2022. "Can Agricultural Extension and Input Support Be Discontinued? Evidence from a Randomized Phaseout in Uganda," The Review of Economics and Statistics, MIT Press, vol. 104(6), pages 1273-1288, November.
    17. Helen X. H. Bao & Steven Haotong Li, 2016. "Overconfidence And Real Estate Research: A Survey Of The Literature," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 61(04), pages 1-24, September.
    18. Niu, Chiyu & Ragasa, Catherine, 2018. "Selective attention and information loss in the lab-to-farm knowledge chain: The case of Malawian agricultural extension programs," Agricultural Systems, Elsevier, vol. 165(C), pages 147-163.
    19. Xavier Cirera & Diego A. Comin & Marcio Cruz & Kyung Min Lee, 2020. "Anatomy of Technology in the Firm," NBER Working Papers 28080, National Bureau of Economic Research, Inc.
    20. Bird, Samuel S. & Carter, Michael R. & Lybbert, Travis J. & Mathenge, Mary & Njagi, Timothy & Tjernström, Emilia, 2022. "Filling a niche? The maize productivity impacts of adaptive breeding by a local seed company in Kenya," Journal of Development Economics, Elsevier, vol. 157(C).

    More about this item

    JEL classification:

    • I1 - Health, Education, and Welfare - - Health
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:30345. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.