ارزیابی تبعات اقتصادی-اجتماعی بیماری کرونا در ایران از منظر اقتصاد رفتاری

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری، گروه علوم اقتصادی، دانشکدۀ مدیریت و اقتصاد، دانشگاه تربیت‌مدرس، تهران، ایران

2 دانشیار، گروه اقتصاد پژوهش، پژوهشکدۀ اقتصاد، دانشگاه تربیت مدرس، تهران، ایران

3 دانشیار، گروه علوم اقتصادی، دانشکدۀ مدیریت و اقتصاد، دانشگاه تربیت مدرس، تهران، ایران

4 دانشیار، گروه اقتصاد کشاورزی، پژوهشکدۀ اقتصاد، دانشگاه تربیت مدرس، تهران، ایران

چکیده

اقتصاد رفتاری یک روش تحلیل اقتصادی است که از بینش روان‌شناختی برای توضیح و تحلیل تصمیم‌گیری‌های اقتصادی استفاده می‌کند. در تحقیقات انجام‌شده تاکنون بیشتر به جنبه‌های اقتصادی بحران کرونا پرداخته شده و ابعاد اجتماعی آن کمتر موردتوجه قرار گرفته است و تحلیل آن از منظر اقتصاد رفتاری مغفول مانده است. در مطالعۀ حاضر به بررسی مهم‌ترین سوگیری‌های رفتاری افراد در دوران پاندمی کرونا پرداخته شده است. به‌منظور بررسی تبعات اجتماعی پاندمی کرونا و برآورد ارتباط متغیرهای اقتصادی و جمعیت‌شناختی با تئوری‌های اقتصاد رفتاری از روش آزمون انتخاب و مدل لاجیت مختلط استفاده شد و با برآورد مدل لاجیت مختلط با اثرات متقابل، حالات گسترده­ای از روابط حاصل­ضربی بین ویژگی­های شخصیتی و صفات مختص آلترناتیوها مورد آزمون قرار گرفت و سرانجام متغیرهای سن، تعداد فرزندان، سطح درآمد و داشتن آگاهی از تبعات بیماری کرونا دارای تأثیر معنی­دار و قدرت توضیح­دهندگی شناخته شدند. به‌عنوان نمونه، مشاهده گردید که افراد مسن­تر تمایل کمتری برای پرداخت بیشتر جهت کاهش تبعات بیماری کرونا دارند و یا داشتن تعداد فرزند بیشتر رابطۀ منفی و معنی­داری با انتخاب و پرداخت اضافی افراد برای کاهش تبعات این بیماری دارد که می‌تواند به‌دلیل پایین بودن درآمد سرانه در خانوارهای پرجمعیت باشد. ازمنظر اقتصاد رفتاری نیز نتایج برآوردها به نوعی «(اثر) رفتار دسته جمعی و تأثیر اجتماعی» و «اثر اکتشافی» را در رفتار مردم تأیید می‌نمایند که به‌ترتیب حکایت از ارجحیت ابعاد اقتصادی نسبت به ابعاد اجتماعی بیماری و اهمیت دادن شدید مردم به مشکلات خانوادگی ناشی از بروز بیماری دارد و در پایان نیز توصیه‌های سیاستی ارائه گردیده است. اجمالاً این‌که هرچه ساختار انتشار و دسترسی به اطلاعات کامل‌تر و آگاهی بخشی به جامعه به‌صورت کاراتر عمل نماید تا برداشت‌های شخصی نادرست و تورش‌های رفتاری کمتر گردد مدیریت بحران ( ازجمله بیماری کرونا) تسهیل می‌گردد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Assessing the Socio-Economic Consequences of Corona in Iran, from the Behavioral Economics Perspective

نویسندگان [English]

  • zahra Mehranfard 1
  • Amirhossein Mozayani 2
  • Abbas Assari Arani 3
  • Lotfali Agheli 4
1 Ph.D. student, Department of Economic Sciences, Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran
2 Associate Professor, Research Economics Department, Economics Research Institute, Tarbiat Modares University, Tehran, Iran
3 Associate Professor, Department of Economics, Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran
4 Associate Professor, Agricultural Economics Department, Economics Research Institute, Tarbiat Modares University, Tehran, Iran
چکیده [English]

Behavioral economics is a method of economic analysis that uses psychological insights to explain and analyze economic decisions. In the researches done so far, more attention has been paid to the economic aspects of the current crisis and less attention has been paid to the social dimensions and the issue of behavioral economics has been neglected. In the present study, we examine the most important behavioral biases of individuals during the corona pandemic. In order to investigate the social consequences of the corona pandemic and to estimate the relationship between economic and demographic variables with behavioral economics theories, the choice experiment was selected and the mixed logit model was used and by estimating the mixed logit model with interactions a wide range of multiplicative states between personality traits and traits specific to the alternatives were tested. Finally, the variables of age, number of children, income level and awareness of the consequences of corona disease were multiplied by the price with a significant effect and explanatory power. For example, it was observed that older people are less willing to pay more to reduce the consequences of corona disease or having more children has a negative and significant relationship with the selection and additional payment of people to reduce the consequences of this disease. From the perspective of behavioral economics. the result of the estimates confirms a kind of “(effect) of collective behavior and social impact” and “exploratory effect” in people’s behavior, which indicates the preference of economic dimensions over the social dimensions of the disease and the great importance of people to family problems caused by the disease, respectively.

کلیدواژه‌ها [English]

  • Behavioral Economics
  • Preferences
  • Covid-19
  • Health Economics
- انصاری‌سامانی، حبیب؛ و همکاران، (1394). «مقدمه‌ای بر اقتصاد رفتاری: مفهوم، روش‌شناسی و شیوه‌های استخراج ترجیحات». اقتصاد تطبیقی، 2 (1): 37-69.
 - تیموری، عباد؛ و همکاران، (1396). «نقد انتخاب عقلانی از منظر رویکردهای رقیب: اقتصاد رفتاری، آزمایشگاهی و علوم مغزی». پژوهش‌های اقتصادی ایران، 22 (7): 43-1.
- رهبر، فرهاد؛ و همکاران، (1392). «اقتصاددانان رفتاری و نظریه‌های آن‌ها». برنامه‌ریزی و بودجه، 18 (1): 165-133.
- Ariely, D., (2008). Predictably irrational. New York: Harper Audio New York.
- Ansari Samani, H. et al., (2014). “An Introduction to Behavioral Economics: Concept, Methodology and Methods of Extracting Preferences”. Comparative Economics, 2(1): 37-69. (In Persian)
- Aysola, J.; Tahirovic, E.; Troxel, A.B.; Asch, D.A.; Gangemi, K.; Hodlofski, A. T. et al., (2018). “A randomized controlled trial of opt-in versus opt-out enrollment into a diabetes behavioral intervention”. Am J Health Promot, 32(3): 745–52.
- Biddle, N., (2021). “Behavioral economics and the covid-induced education crisis”. OECD education working paper, 254 (11): 1-45.
- Bickel, W. K.; Moody, L. & Higgins, S. T., (2016). Some current dimensions of the behavioral economics of health-related behavior change. Prev Med.
- Biran, A.; Schmidt, W-P.; Varadharajan, KS.; Rajaraman. D.; Kumar, R.; Greenland, K. et al., (2014). “Effect of a behaviour-change intervention on handwashing with soap in India (SuperAmma): a cluster-randomised trial”. Lancet Glob Health, 2(3): e145–e154154.
- Chapman, G. B.; Li, M.; Colby, H., & Yoon, H., (2010). “Opting in vs opting out of influenza vaccination”. JAMA, 304(1): 43–4.
- Cifuentes, F. J., (2020). “The importance of behavioral economics during covid-19”. Journal of economics and behavioral studies, 12(3): 70-74.
- Coleman, S., (2007). “The Minnesota income tax compliance experiment: replication of the social norms experiment”. Available at SSRN 1393292.
- Congdon, W. J., & Shankar, M., (2018). “The role of behavioral economics in evidence-based policymaking”. The ANNALS of the American Academy of Political and Social Science, 678(1): 81–92.
- Dillard, A. J.; McCaul, K. D. & Klein, W. M., (2006). “Unrealistic optimism in smokers: Implications for smoking myth endorsement and selfprotective motivation”. J Health Commun, 11(S1): 93–102. doi: 10.1001/jamanetworkopen.2020.10185.
- Finucane, M.L.; Alhakami, A.; Slovic, P. & Johnson, S. M., (2000). “The affect heuristic in judgments of risks and benefits”. J Behav Decis Mak, 13(1): 1–17.
- Fogg, B., (2009). “A behavior model for persuasive design”. In: Proceedings of the 4th international Conference on Persuasive Technology: 40. ACM.
- Gallagher, S., (2020). “Coronavirus: How to Ensure your Relationships Survive Self-Isolation”. Digital News Brand Independent. Information website: https://www.independent.co.uk (accessed April 13, 2020).
- Halpern, S. D.; French, B.; Small, D. S.; Saulsgiver, K.; Harhay, M. O. & Audrain-McGovern, J. et al., (2015). “Randomized trial of four financialincentive programs for smoking cessation”. N Engl J Med, 372: 2108–17.
- Haushofer, J. y. & Metcalf, J., (2020). “Combining behavioral economics and infectious disease epidemiology to mitigate the COVID-19 outbreak”.
- Hearne, R. R. & Salinas, Z. M., (2002). “The use of choice experiments in the analysis of tourist preferences for ecotourism development in Costa rica”. Journal of environmental management, 65(2): 153-163.
- Hensher, D. A.; Rose, J. & Bertoia, T., (2007). “The implications on willingness to pay of a stochastic treatment of attribute processing in stated choice studies”. Transportation Research, 43(2): 73–89. doi:10.1016/j.tre.2005.07.006.
- Hussam, R.; Rabbani, A.; Reggiani, G. & Rigol, N., (2017). “Habit formation and rational addiction: a field experiment in handwashing”. Harvard Business School BGIE Unit working: 18-30.
- John, L. K.; Loewenstein, G.; Troxel, A. B.; Norton, L.; Fassbender, J. E. & Volpp, K. G.,  (2011). “Financial incentives for extended weight loss: a randomized”. Controlled trial. J Gen Intern Med,  26(6): 621–6.
- Kahneman, D.; Slovic, S. P. Slovic, P. & Tversky, A., (1982). Judgment under uncertainty: heuristics and biases. Cambridge University Press.
- Kliger, D., (2020). Economic behavior and behavioral economics at times of covid-19 pandemic, mind and society. Springer: 1-8.
- Kumar, B., (2020). “Covid-19 pandemic and the role of behavioral economics”. MPRA: 1-12.
- Kunu, S. & Duran, S., (2021). “Understanding covid-19 virus pandemic in terms of behavioral economics in terms of how people think and learn”. Economi: 111-118.
- Kwok, Y. L. A.; Gralton, J. & McLaws, M. L., (2015). “Face touching: A frequent habit that has implications for hand hygiene”. American Journal of Infection Control, 43(2): 112–114.
- Laibson, D., (1997). “Golden eggs and hyperbolic discounting”. Q J Econ. 112(2): 443–78.
- Linnemayr, S.; Stecher, C. & Mukasa, B., (2017), “Behavioral economic incentives to improve adherence to antiretroviral medication”. AIDS (London, England), 31(5): 719.
- Loewenstein, G.; Asch, D. A.; Friedman, J. Y., Melichar, L. A. & Volpp, K. G., (2012). “Can behavioural economics make us healthier?”. BMJ, 344: e3482.
- Loewenstein, G.; Brennan, T. & Volpp, K. G., (2007). “Asymmetric paternalism to improve health behaviors”. JAMA, 298(20): 2415–7.
- Luoto, J. & Carman, K. G., (2014). Behavioral economics guidelines with applications for health interventions. Washington: Inter American Development Bank.
- Matjasko, J. L. Cawley, J. H.; Baker-Goering, M. M. & Yokum, D. V., (2016). “Applying behavioral economics to public health policy: illustrative examples and promising directions”. Am J Prev Med., 50(5): S13–S1919.
- McFadden, D., (1973). Conditional logit analysis of qualitative choice behavior. New York: Academic Press.
- O’Donoghue, T. & Rabin, M., (1999). “Doing it now or later”. Am Econ Rev., 89(1): 103–24.
- Ortega, D. L.; Wang, H. H.; Wu, L. & Olynk, N. J., (2011). “Modeling heterogeneity in consumer preferences for select food safety attributes in China”. Food Policy, 36(2): 318–324. doi:10.1016/j.foodpol.2010.11.030.
- Peters, E.; Lipkus, I. & Diefenbach, M. A., (2006). “The functions of affect in health communications and in the construction of health preferences”. J Commun, 56: S140–S162162.
- Raafat, R. M.; Chater, N. & Frith, C., (2009). “Herding in humans”. Trends Cognit Sci., 13(10): 420–8.
- Rahbar, F. et al., (2012). “Behavioral economists and their theories”. Planning and Budgeting, 18(1): 133-165, (In Persian)
- Samuelson, W. & Zeckhauser, R., (1988). “Status quo bias in decision making”. J Risk Uncertain, 1(1): 7–59.
- Schwarz, N., (2011). “Feelings-as-information theory”. In: Van Lange P, Kruglanski A, Higgins ET, editors. Handbook of theories of social psychology, Thousand Oaks: Sage: 289–308.
- Slovic, P. & Peters, E., (2006). “Risk perception and affect”. Curr Dir Psychol Sci., 15(6): 322–5.
- Taymoori, E. et al., (2016). “Criticism of rational choice from the perspective of competing approaches: behavioral economics, laboratory and brain science”. Iran's economic research, 22(73): 1-43, (In Persian).
- Thaler, R. H. & Sunstein, C. R., (2008). “Nudge: improving decisions about health, wealth and happiness”. The Social Science, New Haven: Yale University Press.
- Thaler, R. H., (2016). “Behavioral economics: past, present, and future”. American Economic Review, 106(7).
- Thaler, R. H., (2018). “From cashews to nudges: The evolution of behavioral economics”. American Economic Review, 108(6).
- Train, K., (2003). Discrete choice methods with simulation. Cambridge, UK: Cambridge University Press.
-  Tversky, A. & Kahneman, D., (1979). “Prospect theory: an analysis of decision under risk”. Econometrica, 47(2): 263–91.
-Tversky, A. & Kahneman, D., (1974). “Judgment under uncertainty: heuristics and biases”. Science, 185(4157).
- Van der Pol, M. & Cairns, J., (2011). “Descriptive validity of alternative intertemporal models for health outcomes: an axiomatic test”. Health Econ., 20(7): 770–82.
- Van Der Pol, M.; Hennessy, D. & Manns, B., (2017). “The role of time and risk preferences in adherence to physician advice on health behavior change”. Eur J Health Econ., 18(3): 373–86.
- Voj-a-cek, O. & Pec-akov-a, I., (2010). “Comparison of discrete choice models for economic environmental research”. Prague Economic Papers, 1: 35–53. doi: 10.18267/j.pep.363.
- Watson, J.; Dreibelbis, R.; Aunger, R.; Deola, C.; King, K. & Long, S. et al., (2019). “Child’s play: harnessing play and curiosity motives to improve child handwashing in a humanitarian setting”. Int J Hyg Environ Health., 222(2): 177–82.
- Weinstein, N. D.; Marcus, S. E. & Moser, R. P., (2005). “Smokers’ unrealistic optimism about their risk”. Tob control, 14(1): 55–9.
- Weinstein, N. D., (1980). “Unrealistic optimism about future life events”. J Pers Soc Psychol, 39(5): 806.
- Weinstein, N. D., (1987). “Unrealistic optimism about susceptibility to health problems: conclusions from a community-wide sample”. J Behav Med., 10(5): 481–500.
- White, J. S. & Dow, W. H., (2015). “Intertemporal choices for health”. In: Roberto Ch A, Kawachi I, editors, Behavioral economics and public health, Oxford: Oxford University Press; 27: 62.
- Wilder-Smith, A. & Freedman, D., (2020). “Isolation, quarantine, social distancing and community containment: pivotal role for old style public health measures in the novel coronavirus (2019-nCoV) outbreak”. J Travel Med., 27(2).
- Wu, C. et al., (2020). “The dynamics of trust before, during and after the covid-19 outbreak”. Canadian institutes of health research, Information website: https://www.csa-scs.ca/.