IDEAS home Printed from https://ideas.repec.org/a/ibn/ijefaa/v12y2020i10p57.html
   My bibliography  Save this article

An Assessment of the Applicability of Behavioral Economics’ Tools to Policy Making Process Considering Sustainable Development Goals

Author

Listed:
  • Abeer Mohamed Ali Abd Elkhalek

Abstract

Achieving sustainable development goals in a very dynamic and complicated world requires innovated solutions. As people are in the heart of the developmental process, understanding what motivates people and what drives their behaviors is a must for designing policies targeting the achievement of developmental goals. This paper aims to assess how the behavioral economics’ tools may be applied to directing people’s behaviors toward more sustainable activities and then contributing to achieve sustainable development goals. Using deductive qualitative approach, and a comparative analysis, the study explores and discusses to what extent insights and techniques from behavioral economics may affect and change policy making process and then public policies' outcomes specifically in the context of sustainable development disciplines. The results showed a vital role of behavioral economics tools in developing public policies in accordance to real behaviors of people which -in turn- help in achieving sustainable development goals. Moreover, it was concluded that changing humans' behaviors toward more sustainable patterns of life provides so many opportunities to strengthen the effectiveness of policies for sustainable development in both developed and developing countries. Using behavioral economics tools, policymakers can design more effective policies to achieve Sustainable Development Goals (SDGs).

Suggested Citation

  • Abeer Mohamed Ali Abd Elkhalek, 2020. "An Assessment of the Applicability of Behavioral Economics’ Tools to Policy Making Process Considering Sustainable Development Goals," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 12(10), pages 1-57, October.
    • Handle: RePEc:ibn:ijefaa:v:12:y:2020:i:10:p:57
    as

    Download full text from publisher

    File URL: http://www.ccsenet.org/journal/index.php/ijef/article/download/0/0/43749/45972
    Download Restriction: no
    File URL: http://www.ccsenet.org/journal/index.php/ijef/article/view/0/43749
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Esther-Mirjam Sent, 2004. "Behavioral Economics: How Psychology Made Its (Limited) Way Back Into Economics," History of Political Economy, Duke University Press, vol. 36(4), pages 735-760, Winter.
    2. Robert Jensen, 2012. "Do Labor Market Opportunities Affect Young Women's Work and Family Decisions? Experimental Evidence from India," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 127(2), pages 753-792.
    3. Abhijit V. Banerjee & Sendhil Mullainathan, 2008. "Limited Attention and Income Distribution," American Economic Review, American Economic Association, vol. 98(2), pages 489-493, May.
    4. Habyarimana, James & Jack, William, 2011. "Heckle and Chide: Results of a randomized road safety intervention in Kenya," Journal of Public Economics, Elsevier, vol. 95(11), pages 1438-1446.
    5. Allcott, Hunt, 2011. "Social norms and energy conservation," Journal of Public Economics, Elsevier, vol. 95(9-10), pages 1082-1095, October.
    6. Allcott, Hunt, 2011. "Social norms and energy conservation," Journal of Public Economics, Elsevier, vol. 95(9), pages 1082-1095.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Peters, Jörg & Langbein, Jörg & Roberts, Gareth, 2016. "Policy evaluation, randomized controlled trials, and external validity—A systematic review," Economics Letters, Elsevier, vol. 147(C), pages 51-54.
    2. Chen, Yan & Lu, Fangwen & Zhang, Jinan, 2017. "Social comparisons, status and driving behavior," Journal of Public Economics, Elsevier, vol. 155(C), pages 11-20.
    3. Quinn Keefer & Galib Rustamov, 2018. "Limited attention in residential energy markets: a regression discontinuity approach," Empirical Economics, Springer, vol. 55(3), pages 993-1017, November.
    4. Lillemo, Shuling Chen, 2014. "Measuring the effect of procrastination and environmental awareness on households' energy-saving behaviours: An empirical approach," Energy Policy, Elsevier, vol. 66(C), pages 249-256.
    5. Peter Bergman, 2020. "Nudging Technology Use: Descriptive and Experimental Evidence from School Information Systems," Education Finance and Policy, MIT Press, vol. 15(4), pages 623-647, Fall.
    6. Todd D. Gerarden & Richard G. Newell & Robert N. Stavins, 2017. "Assessing the Energy-Efficiency Gap," Journal of Economic Literature, American Economic Association, vol. 55(4), pages 1486-1525, December.
    7. Schleich, Joachim & Faure, Corinne & Guetlein, Marie-Charlotte & Tu, Gengyang, 2020. "Conveyance, envy, and homeowner choice of appliances," Energy Economics, Elsevier, vol. 89(C).
    8. Damgaard, Mette Trier & Nielsen, Helena Skyt, 2018. "Nudging in education," Economics of Education Review, Elsevier, vol. 64(C), pages 313-342.
    9. Chatzigeorgiou, I.M. & Andreou, G.T., 2021. "A systematic review on feedback research for residential energy behavior change through mobile and web interfaces," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    10. Beatty, Timothy K.M. & Katare, Bhagyashree, 2018. "Low-cost approaches to increasing gym attendance," Journal of Health Economics, Elsevier, vol. 61(C), pages 63-76.
    11. Fischbacher, Urs & Schudy, Simeon & Teyssier, Sabrina, 2021. "Heterogeneous preferences and investments in energy saving measures," Resource and Energy Economics, Elsevier, vol. 63(C).
    12. Elena Claire Ricci, 2013. "Smart-Grids and Climate Change. Consumer adoption of smart energy behaviour: a system dynamics approach to evaluate the mitigation potential," Working Papers 2013.71, Fondazione Eni Enrico Mattei.
    13. Ajla Cosic & Hana Cosic & Sebastian Ille, 2018. "Can nudges affect students' green behaviour? A field experiment," Journal of Behavioral Economics for Policy, Society for the Advancement of Behavioral Economics (SABE), vol. 2(1), pages 107-111, March.
    14. Anna Kowalska-Pyzalska & Katarzyna Maciejowska & Katarzyna Sznajd-Weron & Rafal Weron, 2014. "Diffusion and adoption of dynamic electricity tariffs: An agent-based modeling approach," HSC Research Reports HSC/14/01, Hugo Steinhaus Center, Wroclaw University of Technology.
    15. Bartels, Lara & Kesternich, Martin, 2022. "Motivate the crowd or crowd- them out? The impact of local government spending on the voluntary provision of a green public good," ZEW Discussion Papers 22-040, ZEW - Leibniz Centre for European Economic Research.
    16. Kowalska-Pyzalska, Anna & Maciejowska, Katarzyna & Suszczyński, Karol & Sznajd-Weron, Katarzyna & Weron, Rafał, 2014. "Turning green: Agent-based modeling of the adoption of dynamic electricity tariffs," Energy Policy, Elsevier, vol. 72(C), pages 164-174.
    17. Cristiano Codagnone & Giuseppe Alessandro Veltri & Francesco Bogliacino & Francisco Lupiáñez-Villanueva & George Gaskell & Andriy Ivchenko & Pietro Ortoleva & Francesco Mureddu, 2016. "Labels as nudges? An experimental study of car eco-labels," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 33(3), pages 403-432, December.
    18. Jihyo Kim & Suhyeon Nam, 2021. "Do Household Time, Risk, and Social Preferences Affect Home Energy Retrofit Decisions in Korea?," Sustainability, MDPI, vol. 13(8), pages 1-18, April.
    19. Maccarrone, Giovanni & Marini, Marco A. & Tarola, Ornella, 2023. "Shop Until You Drop: the Unexpected Effects of Anticonsumerism and Environmentalism," FEEM Working Papers 330384, Fondazione Eni Enrico Mattei (FEEM).
    20. Hinker, Jonas & Hemkendreis, Christian & Drewing, Emily & März, Steven & Hidalgo Rodríguez, Diego I. & Myrzik, Johanna M.A., 2017. "A novel conceptual model facilitating the derivation of agent-based models for analyzing socio-technical optimality gaps in the energy domain," Energy, Elsevier, vol. 137(C), pages 1219-1230.

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ibn:ijefaa:v:12:y:2020:i:10:p:57. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Canadian Center of Science and Education (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.