The DOI matches its Crossref record.
UNCERTAINTY AND THE WELFARE ECONOMICS OF MEDICAL CARE
Abstract
This chapter focuses on the way in which the operation of the medical-care industry and the efficacy with which it satisfies the needs of society differ from a norm. The term norm that the economist usually uses for the purposes of such comparisons is the operation of a competitive model, that is, the flows of services that would be offered and purchased and the prices that would be paid for them. The interest in the competitive model stems partly from its presumed descriptive power and partly from its implications for economic efficiency. If a competitive equilibrium exists at all and if all commodities relevant to costs or utilities are in fact priced in the market, then the equilibrium is necessarily optimal. There is no other allocation of resources to services that will make all participants in the market better off. The most obvious distinguishing characteristics of an individual's demand for medical services is that it is not steady in origin as, for example, for food or clothing but is irregular and unpredictable. Medical services, apart from preventive services, afford satisfaction only in the event of illness, a departure from the normal state of affairs.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Pavlou, P. A., Liang, H., & Xue, Y. (2007) · MIS Quarterly · doi:10.2307/25148783 · Cited by 2,646
(1988) · Cited by 1,379
Product fit uncertainty in online markets: nature, effects, and antecedents
Hong, Y. (., & Pavlou, P. A. (2014) · Information Systems Research · doi:10.1287/isre.2014.0520 · Cited by 453
Health Insurance for “Humans”: Information Frictions, Plan Choice, and Consumer Welfare
Handel, B. R., & Kolstad, J. T. (2015) · American Economic Review · doi:10.1257/aer.20131126 · Cited by 427
Thau, S., & Mitchell, M. S. (2010) · Journal of Applied Psychology · doi:10.1037/a0020540 · Cited by 367
The Nature of Risk Preferences: Evidence from Insurance Choices
Barseghyan, L., Molinari, F., O'Donoghue, T., & Teitelbaum, J. C. (2013) · American Economic Review · doi:10.1257/aer.103.6.2499 · Cited by 348
Prejudice, clinical uncertainty and stereotyping as sources of health disparities
Balsa, A. I., & McGuire, T. G. (2003) · Journal of Health Economics · doi:10.1016/s0167-6296(02)00098-x · Cited by 333
Behavioral Hazard in Health Insurance *
Baicker, K., Mullainathan, S., & Schwartzstein, J. (2015) · The Quarterly Journal of Economics · doi:10.1093/qje/qjv029 · Cited by 247
Relaxing Occupational Licensing Requirements: Analyzing Wages and Prices for a Medical Service
Kleiner, M. M., Marier, A., Park, K. W., & Wing, C. (2016) · The Journal of Law and Economics · doi:10.1086/688093 · Cited by 181
Does Diversity Matter for Health? Experimental Evidence from Oakland
Alsan, M., Garrick, O., & Graziani, G. (2018) · doi:10.3386/w24787 · Cited by 160
Effects of Occupational Licensing Laws on Minorities: Evidence from the Progressive Era
Law, M. T., & Marks, M. S. (2009) · The Journal of Law and Economics · doi:10.1086/596714 · Cited by 117
Health Economics at the Crossroads of Centuries – From the Past to the Future
Jakovljevic, M. (., & Ogura, S. (2016) · Frontiers in Public Health · doi:10.3389/fpubh.2016.00115 · Cited by 103
Kyriopoulos, I.-I., Zavras, D., Skroumpelos, A., Mylona, K., Athanasakis, K., & Kyriopoulos, J. (2014) · International Journal for Equity in Health · doi:10.1186/1475-9276-13-54 · Cited by 95
How Fair Is Actuarial Fairness?
Landes, X. (2015) · Journal of Business Ethics · doi:10.1007/s10551-014-2120-0 · Cited by 66
Standardization and the costs of assessing quality
Jones, P., & Hudson, J. (1996) · European Journal of Political Economy · doi:10.1016/0176-2680(95)00021-6 · Cited by 65
Curbing shopping cart abandonment in C2C markets — an uncertainty reduction approach
Tang, H., & Lin, X. (2019) · Electronic Markets · doi:10.1007/s12525-018-0313-6 · Cited by 56
The benefits and costs of the section 8 existing housing program
Reeder, W. J. (1985) · Journal of Public Economics · doi:10.1016/0047-2727(85)90014-3 · Cited by 55
From moral hazard to risk-response feedback
Jebari, J., Táíwò, O. O., Andrews, T. M., Aquila, V., Beckage, B., Belaia, M., Clifford, M., Fuhrman, J., Keller, D. P., Mach, K. J., et al. (2021) · Climate Risk Management · doi:10.1016/j.crm.2021.100324 · Cited by 55
Economic Effects of Risk Classification Bans
Dionne, G., & Rothschild, C. (2014) · The Geneva Risk and Insurance Review · doi:10.1057/grir.2014.15 · Cited by 52
Gerhardt, R., & Hackethal, A. (2009) · doi:10.2139/ssrn.1343607 · Cited by 52
Service Design Attributes Affecting Diabetic Patient Preferences of Telemedicine in South Korea
Park, H., Chon, Y., Lee, J., Choi, I.-J., & Yoon, K.-H. (2011) · Telemedicine and e-Health · doi:10.1089/tmj.2010.0201 · Cited by 38
Macro-level efficiency of health expenditure: estimates for 15 major economies
Chen, S., Kuhn, M., Prettner, K., Bloom, D. E., & Wang, C. (2021) · Social Science & Medicine · doi:10.1016/j.socscimed.2021.114270 · Cited by 36
Evaluating the administration costs of biologic drugs: development of a cost algorithm
Tetteh, E. K., & Morris, S. (2014) · Health Economics Review · doi:10.1186/s13561-014-0026-2 · Cited by 34
Krieger, M., & Felder, S. (2013) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph10062560 · Cited by 31
A discrimination-free premium under a causal framework
Araiza Iturria, C. A., Hardy, M., & Marriott, P. (2024) · North American Actuarial Journal · doi:10.1080/10920277.2023.2291524 · Cited by 20
A Discrimination-Free Premium Under a Causal Framework
Araiza Iturria, C. A., Hardy, M., & Marriott, P. (2022) · doi:10.2139/ssrn.4079068 · Cited by 20
Metadata
- Authors
- Arrow, K. J.
- Venue
- Uncertain Times
- Publisher
- Duke University Press
- Published
- 2003-12-08
- Pages
- 1-34
- OpenAlex
- W3035509303
- Cited by
- 4,078
- References
- 0
- FWCI
- 359.91
- Type
- book chapter
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.