Hostname: page-component-cd9895bd7-7cvxr Total loading time: 0 Render date: 2024-12-27T19:34:30.556Z Has data issue: false hasContentIssue false
  • English
  • Français

Prospective Evaluation of Health Communication Effects on Market Outcomes

Published online by Cambridge University Press:  08 April 2022

Rosemarie L. Summers ,
Dallas W. Wood ,
Nellie Lew ,
Shawn A. Karns ,
Mary K. Muth ,
Clark Nardinelli ,
Janet G. Peckham Open the ORCID record for Janet G. Peckham [Opens in a new window]  and
Carolyn Wolff
Rosemarie L. Summers
Affiliation:
Unaffiliated
Dallas W. Wood
Affiliation:
Center for Applied Economics and Strategy, RTI International, Research Triangle Park, NC, USA
Nellie Lew
Affiliation:
Office of Aviation Policy and Plans, Federal Aviation Administration, Washington, DC, USA
Shawn A. Karns
Affiliation:
Center for Applied Economics and Strategy, RTI International, Research Triangle Park, NC, USA
Mary K. Muth
Affiliation:
Center for Applied Economics and Strategy, RTI International, Research Triangle Park, NC, USA
Clark Nardinelli
Affiliation:
Unaffiliated
Janet G. Peckham*
Affiliation:
Office of the Commissioner, Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD 20993, USA
Carolyn Wolff
Affiliation:
Office of the Commissioner, Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD 20993, USA
*
*Corresponding author: e-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Partial equilibrium models have been used extensively by policy makers to prospectively determine the consequences of government programs that affect consumer incomes or the prices consumers pay. However, these models have not previously been used to analyze government programs that inform consumers. In this paper, we develop a model that policy makers can use to quantitatively predict how consumers will respond to risk communications that contain new health information. The model combines Bayesian learning with the utility-maximization of consumer choice. We discuss how this model can be used to evaluate information policies; we then test the model by simulating the impacts of the North Dakota Folic Acid Educational Campaign as a validation exercise.

Keywords

information disclosurelabelingprospective evaluationpublic policyrisk communicationC11C54D61
Type
Article
Information
Journal of Benefit-Cost Analysis , Volume 13 , Issue 1 , Spring 2022 , pp. 34 - 56
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of the Society for Benefit-Cost Analysis

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

REFERENCES

Baer, Justin, Kutner, Mark, Sabatini, John, and White, Sheida. 2009. “Basic Reading Skills and the Literacy of America’s Least Literate Adults.” Results from the 2003 National Assessment of Adult Literacy (NAAL) Supplemental Studies. Available at https://nces.ed.gov/pubs2009/2009481.pdf.Google Scholar
Bagwell, Kyle. 2007. “The Economic Analysis of Advertising.” Handbook of Industrial Organization, 3: 1701–1844.CrossRefGoogle Scholar
Bruder, C., Bulliard, J.L., Germann, S., Konzelmann, I., Bochud, M., Leyvraz, M. and Chiolero, A., 2018. Estimating lifetime and 10-year risk of lung cancer. Preventive medicine reports, 11, pp.125–130.CrossRefGoogle ScholarPubMed
Bureau of Labor Statistics. 2018. “Consumer Price Index – All Urban Consumers (Current Series).” All Items in U.S. City Average, All Urban Consumers, Not Seasonally Adjusted. Available at http://data.bls.gov.Google Scholar
Centers for Disease Control and Prevention. 2008. “Use of Supplements Containing Folic Acid among Women of Childbearing Age – United States, 2007.” Morbidity and Mortality Weekly Report, 57(1): 5–8. Available at https://www.cdc.gov/mmwr/preview/mmwrhtml/mm5701a3.htm.Google Scholar
Centers for Disease Control and Prevention. 2009. Folic Acid Now. Available at https://www.cdc.gov/ncbddd/orders/pdfs/ready_brochure508.pdf.Google Scholar
Centers for Disease Control and Prevention. 2016. Fact Sheets – Moderate Drinking. Available at https://www.cdc.gov/alcohol/fact-sheets/moderate-drinking.htm.Google Scholar
Centers for Disease Control and Prevention. 2017. Birth Defects: Data & Statistics. Available at https://www.cdc.gov/ncbddd/birthdefects/data.html.Google Scholar
Centers for Disease Control and Prevention. (2020a). Folic Acid Helps Prevent Some Birth Defects. Available at https://www.cdc.gov/ncbddd/folicacid/features/folic-acid-helps-prevent-some-birth-defects.html.Google Scholar
Centers for Disease Control and Prevention (Producer). 2020b. “Prevent COVID-19 During Air Travel.” [Poster] Available at https://stacks.cdc.gov/view/cdc/87632.Google Scholar
Chang, Hung-Hao, and Just, David R.. 2007. “Health Information Availability and the Consumption of Eggs: Are Consumers Bayesians?” Journal of Agricultural and Resource Economics, 32: 77–92.Google Scholar
Choi, E. Kwan, and Jensen, Helen H.. 1991. “Modeling the Effect of Risk on Food Demand and the Implications for Regulation.” Caswell, J.A. (eds), In Economics of food safety: pp. 29–44. Springer, Dordrecht.CrossRefGoogle Scholar
Du, Dongyi Tony, Zhou, Esther H., Goldsmith, John, Nardinelli, Clark, and Hammad, Tarek A.. 2012. “Atomoxetine Use During a Period of FDA Actions.” Medical Care, 50: 987–992.CrossRefGoogle ScholarPubMed
Dusetzina, Stacie B., Higashi, Ashley S., Dorsey, E. Ray, Conti, Rena, Huskamp, Haiden A., Zhu, Shu, Garfield, Craig F., and Alexander, G. Caleb. 2012. “Impact of FDA Drug Risk Communications on Health Care Utilization and Health Behaviors: A Systematic Review.” Medical Care, 50(6): 466–478.CrossRefGoogle ScholarPubMed
European Chemicals Agency. 2016. “Valuing Selected Health Impacts of Chemicals.” Summary of the Results and a Critical Review of the ECHA study. Available at https://echa.europa.eu/documents/10162/13630/echa_review_wtp_en.pdf/dfc3f035-7aa8-4c7b-90ad-4f7d01b6e0bc.Google Scholar
Garden‐Robinson, Julie, and Beauchamp, Kimberly. 2011. “Folic Acid Every Day: An Educational Intervention for Women of Childbearing Age.” Family and Consumer Sciences Research Journal, 39(3): 246–255.CrossRefGoogle Scholar
Gerber, Alan, and Green, Donald. 1999. “Misperceptions about Perceptual Bias.” Annual Review of Political Science, 2(1): 189–210.CrossRefGoogle Scholar
Golan, Elise, Kuchler, Fred, Mitchell, Lorraine, Greene, Cathy, and Jessup, Amber. 2001. “Economics of Food Labeling.” Journal of Consumer Policy, 24(2): 117–184.CrossRefGoogle Scholar
Goldman, D.P., Joyce, G.F., Escarce, J.J., Pace, J.E., Solomon, M.D., Laouri, M., Landsman, P.B. and Teutsch, S.M., 2004. “Pharmacy benefits and the use of drugs by the chronically ill.” Jama, 291(19), pp. 2344–2350.CrossRefGoogle ScholarPubMed
Internal Revenue Service. 2018. “Yearly Average Currency Exchange Rates.” Available at https://www.irs.gov/individuals/international-taxpayers/yearly-average-currency-exchange-rates.Google Scholar
Jacoby, Jacob, Speller, Donald E., and Kohn, Carol A.. 1974. “Brand Choice Behavior as a Function of Information Load.” Journal of Marketing Research, 11: 63–69.CrossRefGoogle Scholar
Jorgenson, Dale W., Ho, Mun S., and Samuels, Jon D.. 2012. “A Prototype Industry‐Level Production Account for the United States, 1947–2010.” From Second World KLEMS Conference, Harvard University. Available at http://www.worldklems.net/data.htm.Google Scholar
Martin, Joyce A., Hamilton, Brady E., Ventura, Stephanie J., Osterman, Michelle J. K., Wilson, Elizabeth C., and Mathews, T. J.. 2012. “Births: Final Data for 2010.” National Vital Statistics Reports, 61(1): 1–72.Available at https://www.cdc.gov/nchs/data/nvsr/nvsr61/nvsr61_01.pdf.Google ScholarPubMed
Muhammad, Andrew, Seale, James L. Jr, Meade, Birgit, and Regmi, Anita. 2011. International Evidence on Food Consumption Patterns: An Update Using 2005 International Comparison Program Data. TB-1929. U.S. Dept. of Agriculture, Econ. Res. Serv. March 2011. Revised February 2013.Google Scholar
Muth, Mary, Okrent, Abigail, Zhen, Chen, and Karns, Shawn. 2019. Using Scanner Data for Food Policy Research. Academic Press, Cambridge, MA.Google Scholar
North Dakota State University Extension Service. 2008. “N.D. Receives Folic Acid Awareness Grant.” Available at https://www.ag.ndsu.edu/news/newsreleases/2008/jan-3-2008/n-d-receives-folic-acid-awareness-grant/.Google Scholar
Rutherford, Thomas F. 1998. “CES Preferences and Technology: A Practical Introduction.” In Economic Equilibrium Modeling with GAMS: An Introduction to GAMS/MCP and GAMS/MPSGE. Washington, DC: GAMS Development Corporation.Google Scholar
Ščasný, Milan, and Zvěřinová, Iva. 2016. “Stated-Preference Study to Examine the Economic Value of Benefits of Avoiding Selected Adverse Human Health Outcomes Due to Exposure to Chemicals in the European Union.” FD7.Final Report Part II: Fertility and Developmental Toxicity. Available at https://echa.europa.eu/documents/10162/13630/study_economic_benefits_avoiding_adverse_health_outcomes_2_en.pdf/face3f5e-25b9-4602-bdd5-79b6a230eef9.Google Scholar
Shimshack, Jay P., Ward, Michael B., and Beatty, Timothy K. M.. 2007. “Mercury Advisories: Information, Education, and Fish Consumption.” Journal of Environmental Economics and Management, 53(2): 158–179.CrossRefGoogle Scholar
Smith, V. Kerry, Desvousges, William H., Johnson, F. Reed, and Fisher, Ann. 1990. “Can Public Information Programs Affect Risk Perceptions?” Journal of Policy Analysis and Management, 9(1): 41–59.CrossRefGoogle Scholar
Teisl, Mario F., and Roe, Brian. 1998. “The Economics of Labeling: An Overview of Issues for Health and Environmental Disclosure.” Agricultural and Resource Economics Review, 27: 140–150.CrossRefGoogle Scholar
The World Bank. 2018. “World Development Indicator.” World Bank, International Comparison Program database. Available at http://databank.worldbank.org/data/reports.aspx?source=world-development-indicators.Google Scholar
U.S. Census Bureau. 2015. “2012 Economic Census of the United States.” EC1231SG1 – Manufacturing: Summary Series: General Summary: Detailed Statistics by Subsectors and Industries: 2012. Available at https://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?src=bkmk.Google Scholar
U.S. Census Bureau. 2016. Annual Estimates of the Resident Population by Sex, Age, Race, and Hispanic Origin: 1 April 2010 to 1 July 2016. Available at https://www.census.gov/data/datasets/2016/demo/popest/state-detail.html#tables.Google Scholar
Viscusi, W. Kip, and Hersch, Joni. 2008. “The Mortality Cost to Smokers.” Journal of Health Economics, 27(4): 943–958.CrossRefGoogle ScholarPubMed
Witte, K. and Allen, M., 2000. A meta-analysis of fear appeals: Implications for effective public health campaigns. Health education & behavior, 27(5), pp.591–615.CrossRefGoogle ScholarPubMed
Wohlgenant, Michael K. 2011. “Consumer Demand and Welfare in Equilibrium Displacement Models.” edited by Lusk, Jayson L., Roosen, Juttta, Shogren, Jason. In The Oxford Handbook of the Economics of Food Consumption and Policy: 0–44. Oxford University Press, NY, NY.CrossRefGoogle Scholar
Young, A.T., 2013. US elasticities of substitution and factor augmentation at the industry level. Macroeconomic Dynamics, 17(4), pp.861–897.CrossRefGoogle Scholar
Supplementary material: File

Summers et al. supplementary material

Appendix B

Download Summers et al. supplementary material(File)
File 40.3 KB
Supplementary material: File

Summers et al. supplementary material

Appendix A

Download Summers et al. supplementary material(File)
File 39.3 KB