Time Cost and Demand: Implications for Public Policy

Springer Science and Business Media LLC - Tập 46 - Trang 51-66 - 2022
Lindsay P. Schwartz1, Steven R. Hursh1,2
1Applied Behavioral Research, Institutes for Behavior Resources, Baltimore, USA
2Johns Hopkins University School of Medicine, Baltimore, USA

Tóm tắt

The success of policy involves not only good design but a good understanding of how the public will respond behaviorally to the benefits or detriments of that policy. Behavioral science has greatly contributed to how we understand the impact of monetary costs on behavior and has therefore contributed to policy design. Consumption taxes are a direct result of this; for example, cigarette taxes that aim to reduce cigarette consumption. In addition to monetary costs, time may also be conceptualized as a constraint on consumption. Time costs may therefore have policy implications, for example, long waiting times could deter people from accessing certain benefits. Recent data show that behavioral economic demand curve methods used to understand monetary cost may also be used to understand time costs. In this article we discuss how the impact of time cost can be conceptualized as a constraint on demand for public benefits utilization and public health when there are delays to receiving the benefits. Policy examples in which time costs may be relevant and demand curve methods may be useful are discussed in the areas of government benefits, public health, and transportation design.

Tài liệu tham khảo

Abarca, N., & Fantino, E. (1982). Choice and foraging. Journal of the Experimental Analysis of Behavior, 38(2), 117–123. https://doi.org/10.1901/jeab.1982.38-117 Ainslie, G., & Haslam, N. (1992). Hyperbolic discounting. In G. Loewenstein & J. Elster (Eds.), Choice over time (pp. 57–92). Russell Sage Foundation. Allcott, H., Lockwood, B. B., & Taubinsky, D. (2019). Should we tax sugar-sweetened beverages? An overview of theory and evidence. Journal of Economic Perspectives, 33(3), 202–227. https://doi.org/10.1257/jep.33.3.202 Amlung, M., & MacKillop, J. (2015). Further evidence of close correspondence for alcohol demand decision making for hypothetical and incentivized rewards. Behavioural Processes, 113, 187–191. https://doi.org/10.1016/j.beproc.2015.02.012 Amlung, M. T., Acker, J., Stojek, M. K., Murphy, J. G., & MacKillop, J. (2012). Is talk “cheap?” An initial investigation of the equivalence of alcohol purchase task performance for hypothetical and actual rewards. Alcoholism, Clinical and Experimental Research, 36(4), 716–724. https://doi.org/10.1111/j.1530-0277.2011.01656.x Amlung, M., Petker, T., Jackson, J., Balodis, I., & MacKillop, J. (2016). Steep discounting of delayed monetary and food rewards in obesity: A meta-analysis. Psychological Medicine, 46(11), 2423–2434. https://doi.org/10.1017/S0033291716000866 Bauman, R. (1991). An experimental analysis of the cost of food in a closed economy. Journal of the Experimental Analysis of Behavior, 56(1), 33–50. https://doi.org/10.1901/jeab.1991.56-33 Bernstein, M., Murphy, J., MacKillop, J., & Colby, S. (2014). Alcohol demand indices predict outcomes among heavy-drinking young adults receiving a brief intervention. Drug & Alcohol Dependence, 140, e13. https://doi.org/10.1016/j.drugalcdep.2014.02.056 Bettinger, E. P., Long, B. T., Oreopoulos, P., & Sanbonmatsu, L. (2012). The role of application assistance and information in college decisions: Results from the h&h block FAFSA experiment. Quarterly Journal of Economics, 127(3), 1205–1242. https://doi.org/10.1093/qje/qjs017 Bickel, W. K., Landes, R. D., Christensen, D. R., Jackson, L., Jones, B. A., Kurth-Nelson, Z., & Redish, A. D. (2011). Single- and cross-commodity discounting among cocaine addicts: The commodity and its temporal location determine discounting rate. Psychopharmacology, 217(2), 177–187. https://doi.org/10.1007/s00213-011-2272-x Bickel, W. K., Jarmolowicz, D. P., Mueller, E. T., Koffarnus, M. N., & Gatchalian, K. M. (2012). Excessive discounting of delayed reinforcers as a trans-disease process contributing to addiction and other disease-related vulnerabilities: Emerging evidence. Pharmacology & Therapeutics, 134(3), 287–297. https://doi.org/10.1016/j.pharmthera.2012.02.004 Bird, K. A., Castleman, B. L., Denning, J. T., Goodman, J., Lamberton, C., & Rosinger, K. O. (2021). Nudging at scale: Experimental evidence from FAFSA completion campaigns. Journal of Economic Behavior & Organization, 183, 105–128. https://doi.org/10.1016/j.jebo.2020.12.022 Burris, M., Nelson, S., Kelley, P., Gupta, P., & Cho, Y. (2012). Willingness to pay for high-occupancy toll lanes: Empirical analysis from I-15 and I-394. (No. 2297; Transportation Research Record: Journal of the Transportation Research Board, pp. 47–55). Transportation Research Board of the National Academies. Castrogiovanni, P., Fadda, E., Perboli, G., & Rizzo, A. (2020). Smartphone data classification technique for detecting the usage of public or private transportation modes. IEEE Access, 8, 58377–58391. https://doi.org/10.1109/ACCESS.2020.2982218 Devarasetty, P. C., Burris, M., & Douglass Shaw, W. (2012). The value of travel time and reliability-evidence from a stated preference survey and actual usage. Transportation Research Part A: Policy & Practice, 46(8), 1227–1240. https://doi.org/10.1016/j.tra.2012.05.002 Dynarski, S. M., & Scott-Clayton, J. E. (2006). The cost of complexity in federal student aid: Lessons from optimal tax theory and behavioral economics. National Tax Journal, 59(2), 319–356. https://doi.org/10.17310/ntj.2006.2.07 Gilroy, S. P., Kaplan, B. A., Schwartz, L. P., Reed, D. D., & Hursh, S. R. (2021). A zero-bounded model of operant demand. Journal of the Experimental Analysis of Behavior, 115(3), 729–746. https://doi.org/10.1002/jeab.679 Greenwald, M. K., & Hursh, S. R. (2006). Behavioral economic analysis of opioid consumption in heroin-dependent individuals: Effects of unit price and pre-session drug supply. Drug & Alcohol Dependence, 85(1), 35–48. https://doi.org/10.1016/j.drugalcdep.2006.03.007 Greenwald, M. K., Sarvepalli, S. S., Cohn, J. A., & Lundahl, L. H. (2021). Demand curve analysis of marijuana use among persons living with HIV. Drug & Alcohol Dependence, 220, 108524. https://doi.org/10.1016/j.drugalcdep.2021.108524 Gunawan, T. (2021). Time costs in the demand of cigarettes [Doctoral dissertation, American University]. ProQuest Dissertations and Theses Database. Hursh, S. R. (1984). Behavioral economics. Journal of the Experimental Analysis of Behavior, 42(3), 435–452. https://doi.org/10.1901/jeab.1984.42-435 Hursh, S. R., & Roma, P. G. (2013). Behavioral economics and empirical public policy. Journal of the Experimental Analysis of Behavior, 99(1), 98–124. https://doi.org/10.1002/jeab.7 Hursh, S. R., & Silberberg, A. (2008). Economic demand and essential value. Psychological Review, 115(1), 186–198. https://doi.org/10.1037/0033-295X.115.1.186 Hursh, S. R., Galuska, C. M., Winger, G., & Woods, J. H. (2005). The economics of drug abuse: A quantitative assessment of drug demand. Molecular Interventions, 5(1), 20–28. https://doi.org/10.1124/mi.5.1.6 Hursh, S. R., Madden, G. J., Spiga, R., DeLeon, I. G., & Francisco, M. T. (2013). The translational utility of behavioral economics: The experimental analysis of consumption and choice. In G. J. Madden, W. V. Dube, T. D. Hackenberg, G. P. Hanley, & K. A. Lattal (Eds.), APA handbook of behavior analysis, Vol. 2: Translating principles into practice (pp. 191–224). American Psychological Association. https://doi.org/10.1037/13938-008 Hursh, S. R., Strickland, J. C., Schwartz, L. P., & Reed, D. D. (2020). Quantifying the impact of public perceptions on vaccine acceptance using behavioral economics. Frontiers in Public Health, 8, 608852. https://doi.org/10.3389/fpubh.2020.608852 Ionescu, L. (2019). Towards a sustainable and inclusive low-carbon economy: Why carbon taxes, and not schemes of emission trading, are a cost-effective economic instrument to curb greenhouse gas emission. Journal of Self-Governance & Management Economics, 7(4), 35–41. Jacobs, E. A., & Bickel, W. K. (1999). Modeling drug consumption in the clinic using simulation procedures: Demand for heroin and cigarettes in opioid-dependent outpatients. Experimental and Clinical Psychopharmacology, 7(4), 412–426. https://doi.org/10.1037/1064-1297.7.4.412 Jones, B., & Rachlin, H. (2006). Social discounting. Psychological Science, 17(4), 283–286. https://doi.org/10.1111/j.1467-9280.2006.01699.x Kassler, W. J., Dillon, B. A., Haley, C., Jones, W. K., & Goldman, A. (1997). On-site, rapid HIV testing with same-day results and counseling. AIDS, 11(8), 1045–1051. Killeen, P. R. (2015). The arithmetic of discounting. Journal of the Experimental Analysis of Behavior, 103(1), 249–259. https://doi.org/10.1002/jeab.130 Kim, B. K., & Zauberman, G. (2019). Psychological time and intertemporal preference. Current Opinion in Psychology, 26, 90–93. https://doi.org/10.1016/j.copsyc.2018.06.005 Koffarnus, M. N., Franck, C. T., Stein, J. S., & Bickel, W. K. (2015). A modified exponential behavioral economic demand model to better describe consumption data. Experimental and Clinical Psychopharmacology, 23(6), 504–512. https://doi.org/10.1037/pha0000045 Kofoed, M. S. (2017). To apply or not to apply: FAFSA completion and financial aid gaps. Research in Higher Education, 58(1), 1–39. https://doi.org/10.1007/s11162-016-9418-y Liang, T. S., Erbelding, E., Jacob, C. A., Wicker, H., Christmyer, C., Brunson, S., Richardson, D., & Ellen, J. M. (2005). Rapid HIV testing of clients of a mobile STD/HIV clinic. AIDS Patient Care and STDs, 19(4), 253–257. https://doi.org/10.1089/apc.2005.19.253 Lu, Y., Musalem, A., Olivares, M., & Schilkrut, A. (2013). Measuring the effect of queues on customer purchases. Management Science, 59(8), 1743–1763. https://doi.org/10.1287/mnsc.1120.1686 MacKillop, J., Few, L. R., Murphy, J. G., Wier, L. M., Acker, J., Murphy, C., Stojek, M., Carrigan, M., & Chaloupka, F. (2012). High-resolution behavioral economic analysis of cigarette demand to inform tax policy: High-resolution analysis of cigarette demand. Addiction, 107(12), 2191–2200. https://doi.org/10.1111/j.1360-0443.2012.03991.x MacKillop, J., Murphy, C. M., Martin, R. A., Stojek, M., Tidey, J. W., Colby, S. M., & Rohsenow, D. J. (2016). Predictive validity of a cigarette purchase task in a randomized controlled trial of contingent vouchers for smoking in individuals with substance use disorders. Nicotine & Tobacco Research, 18(5), 531–537. https://doi.org/10.1093/ntr/ntv233 Nighbor, T. D., Barrows, A. J., Bunn, J. Y., DeSarno, M. J., Oliver, A. C., Coleman, S. R. M., Davis, D. R., Streck, J. M., Reed, E. N., Reed, D. D., & Higgins, S. T. (2020). Comparing participant estimated demand intensity on the cigarette purchase task to consumption when usual-brand cigarettes were provided free. Preventive Medicine, 140, 106221. https://doi.org/10.1016/j.ypmed.2020.106221 Page, L. C., Castleman, B. L., & Meyer, K. (2020). Customized nudging to improve FAFSA completion and income verification. Educational Evaluation and Policy Analysis, 42(1), 3–21. https://doi.org/10.3102/0162373719876916 Paniati, J. (2004). Operational solutions to traffic congestion. Public Roads, Federal Highway Administration, 68(3), 2–8. Pritschmann, R. K., Yurasek, A. M., & Yi, R. (2021). A review of cross-commodity delay discounting research with relevance to addiction. Behavioural Processes, 186, 104339. https://doi.org/10.1016/j.beproc.2021.104339 Roma, P. G., Hursh, S. R., & Hudja, S. (2016). Hypothetical purchase task questionnaires for behavioral economic assessments of value and motivation. Managerial and Decision Economics, 37(4–5), 306–323. https://doi.org/10.1002/mde.2718 Reed, D. D., Kaplan, B. A., Becirevic, A., Roma, P. G., & Hursh, S. R. (2016). Toward quantifying the abuse liability of ultraviolet tanning: A behavioral economic approach to tanning addiction. Journal of the Experimental Analysis of Behavior, 106(1), 93–106. https://doi.org/10.1002/jeab.216 Schwartz, L. P., Blank, L., & Hursh, S. R. (2021). Behavioral economic demand in opioid treatment: Predictive validity of hypothetical purchase tasks for heroin, cocaine, and benzodiazepines. Drug & Alcohol Dependence, 221, 108562. https://doi.org/10.1016/j.drugalcdep.2021.108562 Sheikh, A., Misra, A., & Guensler, R. (2015). High-occupancy toll lane decision making: Income effects on I-85 express lanes, Atlanta Georgia. Transportation Research Record: Journal of the Transportation Research Board, 2531(1), 45–53. Spiga, R., Martinetti, M. P., Meisch, R. A., Cowan, K., & Hursh, S. (2005). Methadone and nicotine self-administration in humans: A behavioral economic analysis. Psychopharmacology, 178(2–3), 223–231. https://doi.org/10.1007/s00213-004-2020-6 Stein, J. S., Koffarnus, M. N., Snider, S. E., Quisenberry, A. J., & Bickel, W. K. (2015). Identification and management of nonsystematic purchase task data: Toward best practice. Experimental and Clinical Psychopharmacology, 23(5), 377–386. https://doi.org/10.1037/pha0000020 Strickland, J. C., Reed, D. D., Hursh, S. R., Schwartz, L. P., Foster, R. N. S., Gelino, B. W., LeComte, R. S., Oda, F. S., Salzer, A. R., Schneider, T. D., Dayton, L., Latkin, C., & Johnson, M. W. (2022). Behavioral economic methods to inform infectious disease response: Prevention, testing, and vaccination in the COVID-19 pandemic. PLoS One, 17(1), e0258828. https://doi.org/10.1371/journal.pone.0258828 Tarnoff, P. (2004). Traffic signal clearance intervals. Institute of Transportation Engineers Journal, 74(4), 20–24. Tarnoff, P. (2005). Customer-focused performance measures. Institute of Transportation Engineers Journal, 75(5), 33–36. Tiboni, M., Rossetti, S., Vetturi, D., Torrisi, V., Botticini, F., & Schaefer, M. D. (2021). Urban policies and planning approaches for a safer and climate friendlier mobility in cities: Strategies, initiatives and some analysis. Sustainability, 13(4), 1778. https://doi.org/10.3390/su13041778 Tsunematsu, S. (2001). Effort- and time-cost effects on demand curves for food by pigeons under short session closed economies. Behavioural Processes, 53(1–2), 47–56. https://doi.org/10.1016/S0376-6357(00)00147-9 U.S. Department of Health & Human Services. (2022, January 10). Biden-Harris administration requires insurance companies and group health plans to cover the cost of at-home COVID-19 tests, increasing access to free tests. Valdiserri, R. O., Moore, M., Gerber, A. R., Campbell, C. H., Dillon, B. A., & West, G. R. (1993). A study of clients returning for counseling after HIV testing: Implications for improving rates of return. Public Health Reports (Washington, D.C.: 1974), 108(1), 12–18. Wilson, A. G., Franck, C. T., Koffarnus, M. N., & Bickel, W. K. (2016). Behavioral economics of cigarette purchase tasks: Within-subject comparison of real, potentially real, and hypothetical cigarettes. Nicotine & Tobacco Research, 18(5), 524–530. https://doi.org/10.1093/ntr/ntv154 World Health Organization. (2014). Report of the sage working group on vaccine hesitancy. https://www.who.int/immunization/sage/meetings/2014/october/1_Report_WORKING_GROUP_vaccine_hesitancy_final.pdf. Accessed 25 Sept 2021. Yoon, J. H., Suchting, R., McKay, S. A., San Miguel, G. G., Vujanovic, A. A., Stotts, A. L., Lane, S. D., Vincent, J. N., Weaver, M. F., Lin, A., & Schmitz, J. M. (2020). Baseline cocaine demand predicts contingency management treatment outcomes for cocaine-use disorder. Psychology of Addictive Behaviors, 34(1), 164–174. https://doi.org/10.1037/adb0000475 Zauberman, G., Kim, B. K., Malkoc, S. A., & Bettman, J. R. (2009). Discounting time and time discounting: Subjective time perception and intertemporal preferences. Journal of Marketing Research, 46(4), 543–556. https://doi.org/10.1509/jmkr.46.4.543 Zvorsky, I., Nighbor, T. D., Kurti, A. N., DeSarno, M., Naudé, G., Reed, D. D., & Higgins, S. T. (2019). Sensitivity of hypothetical purchase task indices when studying substance use: A systematic literature review. Preventive Medicine, 128, 105789. https://doi.org/10.1016/j.ypmed.2019.105789