Skip to main content Accessibility help
×
Home
Hostname: page-component-7ccbd9845f-hl5gf Total loading time: 0.342 Render date: 2023-01-29T13:42:45.531Z Has data issue: true Feature Flags: { "useRatesEcommerce": false } hasContentIssue true

The lure of incredible certitude

Published online by Cambridge University Press:  11 April 2019

Charles F. Manski*
Affiliation:
Department of Economics and Institute for Policy Research, Northwestern University, Evanston, IL, USA

Abstract

Forthright characterization of scientific uncertainty is important in principle and in practice. Nevertheless, economists and other researchers commonly report findings with incredible certitude, reporting point predictions and estimates. To motivate expression of incredible certitude, economists suggest that researchers respond to incentives that make the practice tempting. This temptation is the ‘lure’ of incredible certitude. I appraise some of the rationales that observers may have in mind when they state that incredible certitude responds to incentives. I conclude that scientific expression of incredible certitude at most has appeal in limited contexts. It should not be a general practice.

Type
Article
Copyright
© Cambridge University Press 2019

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Akerlof, G. and Dickens, W. 1982. The economic consequences of cognitive dissonance. American Economic Review 72, 307319.Google Scholar
Aikman, D., Barrett, P., Kapadia, S., King, M., Proudman, J., Taylor, T., de Weymarn, I. and Yates, T. 2011. Uncertainty in macroeconomic policy-making: art or science. Philosophical Transactions of the Royal Society 369, 47984817.CrossRefGoogle ScholarPubMed
Aneja, A., Donohue, J. and Zhang, A. 2011. The impact of right-to-carry laws and the NRC report: lessons for the empirical evaluation of law and policy. American Law and Economic Review 13, 565632.CrossRefGoogle Scholar
Angrist, J., Imbens, G. and Rubin, D. 1996. Identification of causal effects using instrumental variables. Journal of the American Statistical Association 91, 444455.CrossRefGoogle Scholar
Armantier, O., Bruine de Bruin, W., Potter, S., Topa, G., van der Klaauw, W. and Zafar, B. 2013. Measuring inflation expectations. Annual Review of Economics 5, 273301.CrossRefGoogle Scholar
Bar-Anan, Y., Wilson, T. and Gilbert, D. 2009. The feeling of uncertainty intensifies affective reactions. Emotion 9, 123127.CrossRefGoogle ScholarPubMed
Barsky, R. 1998. Noam Chomsky: A Life of Dissent. Cambridge, MA: MIT Press.Google Scholar
Bénabou, R. and Tirole, J. 2016. Mindful economics: the production, consumption, and value of beliefs. Journal of Economic Perspectives 30, 141164.CrossRefGoogle Scholar
Berkson, J. 1958. Smoking and lung cancer: some observations on two recent reports. Journal of the American Statistical Association 53, 2838.CrossRefGoogle Scholar
Black, D. and Nagin, D. 1998. Do right-to-carry laws deter violent crime? Journal of Legal Studies 27, 209219.CrossRefGoogle Scholar
Brief, R. 1975. The accountant’s responsibility in historical perspective. The Accounting Review 50, 285297.Google Scholar
Brunnermeier, M. and Parker, J. 2005. Optimal expectations. American Economic Review 95, 10921118.CrossRefGoogle Scholar
Buhr, K. and Dugas, M. 2009. The role of fear of anxiety and intolerance of uncertainty in worry: an experimental manipulation. Behaviour Research and Therapy 47, 215223.CrossRefGoogle Scholar
Bureau of Labor Statistics 2018. Employment Situation Technical Note. https://www.bls.gov/news.release/empsit.tn.htm.Google Scholar
Campbell, D. 1984. Can we be scientific in applied social science? Evaluation Studies Review Annual 9, 2648.Google Scholar
Campbell, D. and Stanley, J. 1963. Experimental and Quasi-Experimental Designs for Research. Chicago, IL: Rand McNally.Google Scholar
Caplin, A. and Leahy, J. 2001. Psychological expected utility theory and anticipatory feelings. Quarterly Journal of Economics 116, 5580.CrossRefGoogle Scholar
Chen, S. and Parmigiani, G. 2007. Meta-analysis of BRCA1 and BRCA2 penetrance. Journal of Clinical Oncology 25, 13291333.CrossRefGoogle ScholarPubMed
Congressional Budget Office 2017. Cost Estimate. American Health Care Act. https://www.cbo.gov/system/files/115th-congress-2017-2018/costestimate/americanhealthcareact.pdf.Google Scholar
Cornfield, J. 1951. A method of estimating comparative rates from clinical data. applications to cancer of the lung, breast, and cervix. Journal of the National Cancer Institute 11, 12691275.Google ScholarPubMed
Crane, B., Rivolo, A. and Comfort, G. 1997. An Empirical Examination of Counterdrug Interdiction Program Effectiveness. IDA paper P-3219. Alexandria, VA: Institute for Defense Analyses.Google Scholar
Craske, M. and Stein, M. 2016. Anxiety. Lancet 388, 30483059.CrossRefGoogle ScholarPubMed
Croushore, D. 2011. Frontiers of real-time data analysis. Journal of Economic Literature 49, 72100.CrossRefGoogle Scholar
Deaton, A. 2009. Instruments of Development: Randomization in the Tropics, and the Search for the Elusive Keys to Economic Development. National Bureau of Economic Research Working Paper 14690.Google Scholar
Delavande, A. 2014. Probabilistic expectations in developing countries. Annual Review of Economics 6, 120.CrossRefGoogle Scholar
DerSimonian, R. and Laird, N. 1986. Meta-analysis in clinical trials. Controlled Clinical Trials 7, 177188.CrossRefGoogle ScholarPubMed
DerSimonian, R. and Laird, N. 2015. Meta-analysis in clinical trials revisited. Contemporary Clinical Trials 45, 139145.CrossRefGoogle ScholarPubMed
Duggan, M. 2001. More guns, more crime. Journal of Political Economy 109, 10861114.CrossRefGoogle Scholar
Duignan, B. 2017. Occam’s Razor. Encyclopædia Britannica. https://www.britannica.com/topic/Occams-razor.Google Scholar
Durlauf, S., Navarro, S. and Rivers, D. 2016. Model uncertainty and the effect of shall-issue right-to-carry laws on crime. European Economic Review 81, 3267.CrossRefGoogle Scholar
Elmendorf, D. 2010. Letter to Honorable Nancy Pelosi, Speaker, U.S. House of Representatives, Congressional Budget Office. http://housedocs.house.gov/energycommerce/hr4872_CBO.pdf.Google Scholar
Financial Accounting Standards Board 2010. Statement of Financial Accounting Concepts No. 8. www.fasb.org/jsp/FASB/Document_C/DocumentPage?cid=1176157498129&acceptedDisclaimer=true.Google Scholar
Fischhoff, B. 2012. Communicating uncertainty: fulfilling the duty to inform. Issues in Science and Technology 28, 6370.Google Scholar
Fischhoff, B. and Davis, A. 2014. Communicating scientific uncertainty. Proceedings of the National Academy of Sciences USA 111, 1366413671.CrossRefGoogle ScholarPubMed
Fischhoff, B. and MacGregor, D. 1982. Subjective confidence in forecasts. Journal of Forecasting 1, 155172.CrossRefGoogle Scholar
Fixler, D., Greenaway-McGrevy, R. and Grimm, B. 2011. Revisions to GDP, GDI, and their major components. Survey of Current Business 91, 931.Google Scholar
Fixler, D., Greenaway-McGrevy, R. and Grimm, B. 2014. Revisions to GDP, GDI, and their major components. Survey of Current Business 94, 123.Google Scholar
Fleiss, J. 1981. Statistical Methods for Rates and Proportions. New York, NY: Wiley.Google Scholar
Friedman, M. 1953. Essays in Positive Economics. Chicago, IL: University of Chicago Press.Google Scholar
Gail, M., Brinton, L., Byar, D., Corle, D., Green, S., Shairer, C. and Mulvihill, J. 1989. Projecting individualized probabilities of developing breast cancer for white females who are being examined annually. Journal of the National Cancer Institute 81, 18791886.CrossRefGoogle ScholarPubMed
Gigerenzer, G., Hoffrage, U. and Kleinbölting, H. 1991. Probabilistic mental models: a Brunswikian theory of confidence. Psychological Review 98, 506528.CrossRefGoogle Scholar
Gollier, C. and Muermann, A. 2010. Optimal choice and beliefs with ex ante savoring and ex post disappointment. Management Science 56, 12721284.CrossRefGoogle Scholar
Heckman, J. and Urzua, S. 2009. Comparing IV with structural models: what simple IV can and cannot identify. National Bureau of Economic Research Working Paper 14706.CrossRefGoogle Scholar
Horowitz, J. and Manski, C. 1998. Censoring of outcomes and regressors due to survey nonresponse: identification and estimation using weights and imputations. Journal of Econometrics 84, 3758.CrossRefGoogle Scholar
Hurd, M. 2009. Subjective probabilities in household surveys. Annual Review of Economics 1, 543564.CrossRefGoogle ScholarPubMed
Hsieh, D., Manski, C. and McFadden, D. 1985. Estimation of response probabilities from augmented retrospective observations. Journal of the American Statistical Association 80, 651662.CrossRefGoogle Scholar
Imbens, G. and Angrist, J. 1994. Identification and estimation of local average treatment effects. Econometrica 62, 467476.CrossRefGoogle Scholar
Imbens, G. and Manski, C. 2004. Confidence intervals for partially identified parameters. Econometrica 72, 18451857.CrossRefGoogle Scholar
Kessler, R. and Wittchen, H. 2002. Patterns and correlates of generalized anxiety disorder in community samples. Journal of Clinical Psychiatry 63 (suppl. 8), 410.Google ScholarPubMed
Knutti, R., Furrer, R., Tebaldi, C., Cermak, J. and Meehl, G. 2010. Challenges in combining projections from multiple climate models. Journal of Climate 23, 27392758.CrossRefGoogle Scholar
Kunda, Z. 1990. The case for motivated reasoning. Psychological Bulletin 108, 480498.CrossRefGoogle ScholarPubMed
Lott, J. 2010. More Guns, Less Crime: Understanding Crime and Gun-Control Laws. Chicago, IL: University of Chicago Press.CrossRefGoogle Scholar
Lott, J. and Mustard, D. 1997. Crime, deterrence and right-to-carry concealed handguns. Journal of Legal Studies 26, 168.CrossRefGoogle Scholar
Manski, C. 1989. Anatomy of the selection problem. Journal of Human Resources 24, 343360.CrossRefGoogle Scholar
Manski, C. 1994. The selection problem. In Advances in Econometrics, Sixth World Congress, ed. Sims, C., 143170. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Manski, C. 1995. Identification Problems in the Social Sciences. Cambridge, MA: Harvard University Press.Google Scholar
Manski, C. 1996. Learning about treatment effects from experiments with random assignment of treatments. Journal of Human Resources 31, 707733.Google Scholar
Manski, C. 2003. Partial Identification of Probability Distributions. New York, NY: Springer-Verlag.Google Scholar
Manski, C. 2004. Measuring expectations. Econometrica 72, 13291376.CrossRefGoogle Scholar
Manski, C. 2007. Identification for Prediction and Decision. Cambridge, MA: Harvard University Press.Google Scholar
Manski, C. 2009. Diversified treatment under ambiguity. International Economic Review 50, 10131041.CrossRefGoogle Scholar
Manski, C. 2011. Policy analysis with incredible certitude. The Economic Journal 121, F261F289.CrossRefGoogle Scholar
Manski, C. 2013. Public Policy in an Uncertain World. Cambridge, MA: Harvard University Press.CrossRefGoogle Scholar
Manski, C. 2015. Communicating uncertainty in official economic statistics: an appraisal fifty years after Morgenstern. Journal of Economic Literature 53, 631653.CrossRefGoogle Scholar
Manski, C. 2016. Credible interval estimates for official statistics with survey nonresponse. Journal of Econometrics 191, 293301.CrossRefGoogle Scholar
Manski, C. 2018a. Communicating uncertainty in policy analysis. Proceedings of the National Academy of Sciences USA. https://doi.org/10.1073/pnas.1722389115.Google ScholarPubMed
Manski, C. 2018b. Reasonable patient care under uncertainty. Health Economics 27, 13971421.CrossRefGoogle ScholarPubMed
Manski, C. 2018c. Survey measurement of probabilistic macroeconomic expectations: progress and promise. NBER Macroeconomics Annual 32, 411471.CrossRefGoogle Scholar
Manski, C. and Lerman, S. 1977. The estimation of choice probabilities from choice based samples. Econometrica 45, 19771988.CrossRefGoogle Scholar
Manski, C. and Pepper, J. 2018. How do right-to-carry laws affect crime rates? Coping with ambiguity using bounded-variation assumptions. Review of Economics and Statistics 100, 232244.CrossRefGoogle Scholar
Mastrandrea, M., Field, C., Stocker, T., Edenhofer, O., Ebi, K., Frame, D., Held, H., Kriegler, E., Mach, K., Matschoss, P., Plattner, G., Yohe, G. and Zwiers, F. 2010. Guidance Note for Lead Authors of the IPCC Fifth Assessment Report on Consistent Treatment of Uncertainties. Intergovernmental Panel on Climate Change (IPCC).Google Scholar
McGuffie, K. and Henderson-Sellers, A. 2005. A Climate Modelling Primer (3rd edn). Chichester: Wiley.CrossRefGoogle Scholar
McWilliams, J.C. 2007. Irreducible imprecision in atmospheric and oceanic simulations. Proceedings of the National Academy of Sciences USA 104, 87098713.CrossRefGoogle ScholarPubMed
Morgan, M. and Henrion, M. 1990. Uncertainty: A Guide to Dealing with Uncertainty in Quantitative Risk and Policy Analysis. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Morgenstern, O. 1963. On the Accuracy of Economic Observations (2nd edn). Princeton, NJ: Princeton University Press.Google Scholar
National Cancer Institute 2011. Breast Cancer Risk Assessment Tool. http://www.cancer.gov/bcrisktool/.Google Scholar
National Comprehensive Cancer Network 2017. Breast Cancer Screening and Diagnosis. Version 1.2017. www.nccn.org/professionals/physician_gls/pdf/breast-screening.pdf.Google Scholar
National Research Council 1999. Assessment of Two Cost-Effectiveness Studies on Cocaine Control Policy, ed. Manski, C. F., Pepper, J. V. and Thomas, Y.. Committee on Data and Research for Policy on Illegal Drugs, Committee on Law and Justice and Committee on National Statistics, Commission on Behavioral and Social Sciences and Education. Washington, DC: National Academy Press.Google Scholar
National Research Council 2005. Firearms and Violence: A Critical Review, ed. Wellford, C., Pepper, J. and Petrie, C.. Washington, DC: National Academy Press.Google Scholar
Palmer, T., Shutts, G., Hagedorn, R., Doblas-Reyes, F., Jung, T. and Leutbecher, M.. 2005. Representing model uncertainty in weather and climate prediction. Annual Review of Earth and Planetary Sciences 33, 163193.CrossRefGoogle Scholar
Parker, W. 2006. Understanding pluralism in climate modeling. Foundations of Science 11, 349368.CrossRefGoogle Scholar
Parker, W. 2013. Ensemble modeling, uncertainty and robust predictions. WIRES Climate Change 4, 213223.CrossRefGoogle Scholar
Rydell, C. and Everingham, S. 1994. Controlling Cocaine. Report prepared for the Office of National Drug Control Policy and the U.S. Army. Santa Monica, CA: RAND Corporation.Google Scholar
Schotter, A. and Trevino, I. 2014. Belief elicitation in the laboratory. Annual Review of Economics 6, 103128.CrossRefGoogle Scholar
Seeskin, Z. and Spencer, B. 2015. Effects of Census Accuracy on Apportionment of Congress and Allocations of Federal Funds. Institute for Policy Research Working Paper 15-05, Northwestern University.Google Scholar
Simon, H. 1955. A behavioral model of rational choice. Quarterly Journal of Economics 69, 99118.CrossRefGoogle Scholar
Swinburne, R. 1997. Simplicity as Evidence for Truth. Milwaukee, WI: Marquette University Press.Google Scholar
Stainforth, D., Allen, M., Tredger, E. and Smith, L. 2007. Confidence, uncertainty and decision-support in climate predictions. Philosophical Transactions of the Royal Society 365, 21452161.CrossRefGoogle ScholarPubMed
Tukey, J. 1962. The future of data analysis. Annals of Mathematical Statistics 33, 167.CrossRefGoogle Scholar
Tversky, A. and Kahneman, D. 1974. Judgement under uncertainty: heuristics and biases. Science 185, 11241131.CrossRefGoogle ScholarPubMed
Van der Heiden, C., Muris, P. and van der Molen, H. 2012. Randomized controlled trial on the effectiveness of metacognitive therapy and intolerance-of-uncertainty therapy for generalized anxiety disorder. Behaviour Research and Therapy 50, 100109.CrossRefGoogle ScholarPubMed
Whitchurch, E., Wilson, T. and Gilbert, D. 2011. He loves me, he loves me not …: uncertainty can increase romantic attraction. Psychological Science 22, 172175.CrossRefGoogle ScholarPubMed
Wilson, T., Centerbar, D., Kermer, D. and Gilbert, D. 2005. The pleasures of uncertainty: prolonging positive moods in ways people do not anticipate. Journal of Personality and Social Psychology 88, 521.CrossRefGoogle Scholar
9
Cited by

Save article to Kindle

To save this article to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

The lure of incredible certitude
Available formats
×

Save article to Dropbox

To save this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Dropbox account. Find out more about saving content to Dropbox.

The lure of incredible certitude
Available formats
×

Save article to Google Drive

To save this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Google Drive account. Find out more about saving content to Google Drive.

The lure of incredible certitude
Available formats
×
×

Reply to: Submit a response

Please enter your response.

Your details

Please enter a valid email address.

Conflicting interests

Do you have any conflicting interests? *