Advertisement

The Psychological Record

, Volume 64, Issue 4, pp 671–679 | Cite as

Inter-Method Reliability of Progression Sizes in a Hypothetical Purchase Task: Implications for Empirical Public Policy

  • Derek D. Reed
  • Brent A. Kaplan
  • Peter G. Roma
  • Steven R. Hursh
Original Article

Abstract

Advances in behavioral economic research methodology have generated novel insights into public policy considerations regarding substance use and addiction. A major advancement toward this end was the development of hypothetical purchase tasks (HPTs) that permit modeling of consumption and demand without the need for actual purchases and lengthy human operant studies comprised of real reward deliveries. Psychometric research in the domain of behavioral pharmacology suggests that the HPT has adequate test–retest reliability, as well as construct and convergent/divergent validity. Research to date has exclusively examined pharmacological commodities, however, necessitating the need for technology transfer to other pressing societal issues. In the present study, we examined demand for recreational driving across three groups, each consisting of a different fuel price progression size in the HPT. Findings suggest that behavioral economic models of demand do not differ as a function of progression size, providing support to the inter-method reliability of this procedure.

Keywords

Behavioral economics Demand curve Driving Hypothetical purchase task Reliability 

References

  1. Bickel, W. K., DeGrandpre, R. J., & Higgins, S. T. (1993). Behavioral economics: a novel experimental approach to the study of drug dependence. Drug and Alcohol Dependence, 33, 173–192. doi: 10.1016/0376-8716(93)90059-Y.CrossRefPubMedGoogle Scholar
  2. Bickel, W. K., Jarmolowicz, D. P., MacKillop, J., Epstein, L. H., Carr, K., Mueller, E. T., & Waltz, T. J. (2012). The behavioral economics of reinforcement pathologies: Novel approaches to addictive disorders. In H. J. Shaffer (Ed.), APA addiction syndrome handbook. Washington: APA Books.Google Scholar
  3. Brownell, K. D., & Frieden, T. R. (2009). Ounces of prevention—the public policy case for taxes on sugared beverages. New England Journal of Medicine, 360, 1805–1808. doi: 10.1056/NEJMp0902392.CrossRefPubMedGoogle Scholar
  4. Carter, B. L., & Tiffany, S. T. (1999). Meta-analysis of cue-reactivity in addiction research. Addiction, 94, 327–340. doi: 10.1046/j.1360-0443.1999.9433273.x.CrossRefPubMedGoogle Scholar
  5. Collins, R. L., Parks, G. A., & Marlatt, G. A. (1985). Social determinants of alcohol consumption: the effects of social interaction and model status on the self-administration of alcohol. Journal of Consulting and Clinical Psychology, 53, 189–200. doi: 10.1037/0022-006X.53.2.189.CrossRefPubMedGoogle Scholar
  6. Few, L. R., Acker, J., Murphy, C., & MacKillop, J. (2012). Temporal stability of a cigarette purchase task. Nicotine & Tobacco Research, 14, 761–765. doi: 10.1093/Ntr/Ntr222.CrossRefGoogle Scholar
  7. Green, L., & Freed, D. E. (1993). The substitutability of reinforcers. Journal of the Experimental Analysis of Behavior, 60, 141–158. doi: 10.1901/jeab.1993.60-141.PubMedCentralCrossRefPubMedGoogle Scholar
  8. Havranek, T., Irsova, Z., & Janda, K. (2012). Demand for gasoline is more price-inelastic than commonly thought. Energy Economics, 34, 201–207. doi: 10.1016/j.eneco.2011.09.003.CrossRefGoogle Scholar
  9. Hursh, S. R. (1980). Economic concepts for the analysis of behavior. Journal of the Experimental Analysis of Behavior, 34, 219–238. doi: 10.1901/jeab.1980.34-219.PubMedCentralCrossRefPubMedGoogle Scholar
  10. Hursh, S. R. (1984). Behavioral economics. Journal of the Experimental Analysis of Behavior, 42, 435–452. doi: 10.1901/jeab.1984.42-435.PubMedCentralCrossRefPubMedGoogle Scholar
  11. Hursh, S. R. (in press). Behavioral economics and the analysis of consumption and choice. In F. K. McSweeney& E. S. Murphy (Eds.), Wiley-Blackwell handbook of operant and classical conditioning. Oxford: Wiley-Blackwell.Google Scholar
  12. Hursh, S. R., & Roma, P. G. (2013). Behavioral economics and empirical public policy. Journal of the Experimental Analysis of Behavior, 99, 98–124. doi: 10.1007/s00213-008-1120-0.CrossRefPubMedGoogle Scholar
  13. Hursh, S. R., & Silberberg, A. (2008). Economic demand and essential value. Psychological Review, 115, 186–198. doi: 10.1037/0033-295x115.1.186.CrossRefPubMedGoogle Scholar
  14. Hursh, S. R., & Winger, G. (1995). Normalized demand for drugs and other reinforcers. Journal of the Experimental Analysis of Behavior, 64, 373–384. doi: 10.1901/jeab.1995.64-373.PubMedCentralCrossRefPubMedGoogle Scholar
  15. Hursh, S. R., Raslear, T. G., Shurtleff, D., Bauman, R., & Simmons, L. (1988). A cost-benefit-analysis of demand for food. Journal of the Experimental Analysis of Behavior, 50, 419–440. doi: 10.1901/jeab.1988.50-419.PubMedCentralCrossRefPubMedGoogle Scholar
  16. Hursh, S. R., Raslear, T. G., Bauman, R., & Black, H. (1989). The quantitative analysis of economic behavior with laboratory animals. In K. G. Grunert & F. Olander (Eds.), Understanding economic behavior (pp. 117–165). New York: Kluwer Academic Publishers, Theory and Decision Library.Google Scholar
  17. Hursh, S. R., Madden, G. J., Spiga, R., DeLeon, I. G., & Francisco, M. T. (2012). The translational utility of behavioral economics: The experimental analysis of consumption and choice. Washington: American Psychological Association.Google Scholar
  18. 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, 412–426. doi: 10.1037/1064-1297.7.4.412.CrossRefPubMedGoogle Scholar
  19. Jain, N., Rademaker, A., & Robinson, J. K. (2012). Implementation of the federal excise tax on indoor tanning services in Illinois. Archives of Dermatology, 148, 122–124. doi: 10.1001/archderm.148.1.122.CrossRefPubMedGoogle Scholar
  20. Johnson, M. W., & Bickel, W. K. (2006). Replacing relative reinforcing efficacy with behavioral economic demand curves. Journal of the Experimental Analysis of Behavior, 85, 73–93. doi: 10.1901/jeab.2006.102-04.PubMedCentralCrossRefPubMedGoogle Scholar
  21. Ko, M. C., Terner, J., Hursh, S., Woods, J. H., & Winger, G. (2002). Relative reinforcing effects of three opioids with different durations of action. Journal of Pharmacology and Experimental Therapeutics, 301, 698–704. doi: 10.1124/jpet.301.2.698.CrossRefPubMedGoogle Scholar
  22. Laibson, D. (2001). A cue-theory of consumption. Quarterly Journal of Economics, 116, 81–119. doi: 10.1162/003355301556356.CrossRefGoogle Scholar
  23. MacKillop, J., & Murphy, J. G. (2007). A behavioral economic measure of demand for alcohol predicts brief intervention outcomes. Drug and Alcohol Dependence, 89, 227–233. doi: 10.1016/j.drugalcdep.2007.01.002.CrossRefPubMedGoogle Scholar
  24. MacKillop, J., Murphy, J. G., Ray, L. A., Eisenberg, D. T. A., Lisman, S. A., Lum, J. K., & Wilson, D. S. (2008). Further validation of a cigarette purchase task for assessing the relative reinforcing efficacy of nicotine in college smokers. Experimental and Clinical Psychopharmacology, 16, 57–65. doi: 10.1037/1064-1297.16.1.57.CrossRefPubMedGoogle Scholar
  25. MacKillop, J., O'Hagen, S., Lisman, S. A., Murphy, J. G., Ray, L. A., Tidey, J. W., & Monti, P. M. (2010). Behavioral economic analysis of cue-elicited craving for alcohol. Addiction, 105, 1599–1607. doi: 10.1111/j.1360-0443.2010.03004.x.CrossRefPubMedGoogle Scholar
  26. MacKillop, J., Brown, C. L., Stojek, M. K., Murphy, C. M., Sweet, L., & Niaura, R. S. (2012a). Behavioral economic analysis of withdrawal- and cue-elicited craving for tobacco: an initial investigation. Nicotine & Tobacco Research, 14, 1426–1434. doi: 10.1093/Ntr/Nts006.CrossRefGoogle Scholar
  27. MacKillop, J., Few, L. R., Murphy, J. G., Wier, L. M., Acker, J., Murphy, C., & Chaloupka, F. (2012b). High-resolution behavioral economic analysis of cigarette demand to inform tax policy. Addiction, 107, 2191–2200. doi: 10.1111/j.1360-0443.2012.03991.x.PubMedCentralCrossRefPubMedGoogle Scholar
  28. Madden, G. J., & Hartman, E. C. (2006). A steady-state test of the demand curve analysis of relative reinforcer efficacy. Experimental and Clinical Psychopharmacology, 14, 79–86. doi: 10.1037/1064-1297.14.1.79.CrossRefPubMedGoogle Scholar
  29. Madden, G. J., & Kalman, D. (2010). Effects of bupropion on simulated demand for cigarettes and the subjective effects of smoking. Nicotine & Tobacco Research, 12, 416–422. doi: 10.1093/Ntr/Ntq018.CrossRefGoogle Scholar
  30. Murphy, J. G., & MacKillop, J. (2006). Relative reinforcing efficacy of alcohol among college student drinkers. Experimental and Clinical Psychopharmacology, 14, 219–227. doi: 10.1037/1064-1397.14.2.219.CrossRefPubMedGoogle Scholar
  31. Murphy, J. G., MacKillop, J., Skidmore, J. R., & Pederson, A. A. (2009). Reliability and validity of a demand curve measure of alcohol reinforcement. Experimental and Clinical Psychopharmacology, 17, 396–404. doi: 10.1037/a0017684.CrossRefPubMedGoogle Scholar
  32. Murphy, J. G., MacKillop, J., Tidey, J. W., Brazil, L. A., & Colby, S. M. (2011). Validity of a demand curve measure of nicotine reinforcement with adolescent smokers. Drug and Alcohol Dependence, 113, 207–214. doi: 10.1016/j.drugalcdep.2010.08.004.PubMedCentralCrossRefPubMedGoogle Scholar
  33. Patient Protection and Affordable Care Act, Pub. L. No. 111-148, §2702, 124 Stat. 119, 318–319 (2010).Google Scholar
  34. Powell, L. M., Chriqui, J., & Chaloupka, F. J. (2009). Associations between state-level soda taxes and adolescent body mass index. Journal of Adolescent Health, 45, S57–S63. doi: 10.1016/j.jadohealth.2009.03.003.CrossRefPubMedGoogle Scholar
  35. Pritchard, J. (2010). Virtual rewards for driving green. Behavior Analyst, 33, 185–187.PubMedCentralPubMedGoogle Scholar
  36. Rachlin, H., Green, L., Kagel, J. H., & Battalio, R. C. (1976). Economic demand theory and psychological studies of choice. In G. Bower (Ed.), The psychology of learning and motivation (vol. 10, pp. 129–154). New York, NY: Academic Press.Google Scholar
  37. Reed, D. D., Luiselli, J. K., Magnuson, J. D., Fillers, S., Vieira, S., & Rue, H. C. (2009). A comparison between traditional economical and demand curve analyses of relative reinforcer efficacy in the validation of preference assessment predictions. Developmental Neurorehabilitation, 12, 164–169. doi: 10.1080/17518420902858983.CrossRefPubMedGoogle Scholar
  38. Reed, D. D., Niileksela, C., & Kaplan, B. A. (2013a). Behavioral economics: a tutorial for behavior analysts in practice. Behavior Analysis in Practice, 6, 34–54.PubMedCentralPubMedGoogle Scholar
  39. Reed, D. D., Partington, S. W., Kaplan, B. A., Roma, P., & Hursh, S. (2013b). Behavioral economic analyses of demand for fuel in North American transportation. Journal of Applied Behavior Analysis, 46, 651–655. doi: 10.1002/jaba.64.CrossRefPubMedGoogle Scholar
  40. Roane, H. S., Lerman, D. C., & Vorndran, C. M. (2001). Assessing reinforcers under progressive schedule requirements. Journal of Applied Behavior Analysis, 34, 145–166. doi: 10.1901/jaba.2001.34-145.PubMedCentralCrossRefPubMedGoogle Scholar
  41. Shafir, E. (2013). The behavioral foundations of public policy. Princeton: Princeton University Press.Google Scholar
  42. Shahan, T. A., Bickel, W. K., Madden, G. J., & Badger, G. J. (1999). Comparing the reinforcing efficacy of nicotine containing and de-nicotinized cigarettes: a behavioral economic analysis. Psychopharmacology, 147, 210–216. doi: 10.1007/s002130051162.CrossRefPubMedGoogle Scholar
  43. 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, 223–231. doi: 10.1007/s00213-004-2020-6.CrossRefPubMedGoogle Scholar
  44. Sturm, R., Powell, L. M., Chriqui, J. F., & Chaloupka, F. J. (2010). Soda taxes, soft drink consumption, and children’s body mass index. Health Affairs, 29, 1052–1058. doi: 10.1377/hlthaff.2009.0061.PubMedCentralCrossRefPubMedGoogle Scholar
  45. Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving decisions about health, wealth, and happiness. New Haven: Yale University Press.Google Scholar
  46. White, H. R., & Labouvie, E. W. (1989). Towards the assessment of adolescent problem drinking. Journal of Studies on Alcohol, 50, 30–37.CrossRefPubMedGoogle Scholar
  47. Williams, S. N. (2012). A tax on indoor tanning would reduce demand in europe. British Medical Journal, 345, e6550. doi: 10.1136/bmj.e6550.CrossRefPubMedGoogle Scholar

Copyright information

© Association of Behavior Analysis International 2014

Authors and Affiliations

  • Derek D. Reed
    • 1
  • Brent A. Kaplan
    • 1
  • Peter G. Roma
    • 2
    • 3
  • Steven R. Hursh
    • 2
    • 3
  1. 1.Department of Applied Behavioral ScienceUniversity of KansasLawrenceUSA
  2. 2.Institutes for Behavior ResourcesBaltimoreUSA
  3. 3.Department of Psychiatry and Behavioral SciencesJohns Hopkins University School of MedicineBaltimoreUSA

Personalised recommendations