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Poverty and Welfare Measurement on the Basis of Prospect Theory

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  • Jantti, Markus
  • Kanbur, Ravi
  • Nyyssola, Milla
  • Pirttila, Jukka

Abstract

This paper examines the measurement of social welfare, poverty, and inequality, taking into account features that have been found to be important welfare determinants in behavioral economics. Most notably, we incorporate reference-dependence, loss aversion, and diminishing sensitivity—aspects emphasized in Prospect Theory—to social welfare measurement. We suggest a new notion of equivalent income, the income level with which the individual would be as well off, evaluated using a standard concave utility function, as he actually is, evaluated with a reference-dependent utility function. We examine the differences between standard poverty and inequality measures based on observed income and measures that are calculated based on equivalent income. These differences are illustrated using household-level panel data from Russia and Vietnam.
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  • Jantti, Markus & Kanbur, Ravi & Nyyssola, Milla & Pirttila, Jukka, 2013. "Poverty and Welfare Measurement on the Basis of Prospect Theory," Working Papers 180093, Cornell University, Department of Applied Economics and Management.
    • Handle: RePEc:ags:cudawp:180093
    DOI: 10.22004/ag.econ.180093
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    Cited by:

    1. Markus Jäntti & Stephen P. Jenkins, 2013. "Income Mobility," SOEPpapers on Multidisciplinary Panel Data Research 607, DIW Berlin, The German Socio-Economic Panel (SOEP).
    2. Markus Jäntti & Ravi Kanbur & Milla Nyyssölä & Jukka Pirttilä, 2014. "Poverty and Welfare Measurement on the Basis of Prospect Theory," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 60(1), pages 182-205, March.
    3. Gimpelson, V. & Chernina, E., 2020. "How we perceive our place in income distribution and how the perceptions deviate from reality," Journal of the New Economic Association, New Economic Association, vol. 46(2), pages 30-56.
    4. Olga Cantó & David O. Ruiz, 2015. "The Contribution of Income Mobility to Economic Insecurity in the US and Spain during the Great Recession," Research on Economic Inequality, in: Measurement of Poverty, Deprivation, and Economic Mobility, volume 23, pages 109-152, Emerald Group Publishing Limited.
    5. Che-Yuan Liang, 2017. "Optimal inequality behind the veil of ignorance," Theory and Decision, Springer, vol. 83(3), pages 431-455, October.
    6. Elena Bárcena & Olga Cantó, 2018. "A simple subgroup decomposable measure of downward (and upward) income mobility," Working Papers 472, ECINEQ, Society for the Study of Economic Inequality.
    7. Nicolas Herault, 2015. "How Income Mobility and Income Growth Explain Income Inequality Trends," Melbourne Institute Working Paper Series wp2015n14, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    8. Povel, Felix, 2015. "Measuring Exposure to Downside Risk with an Application to Thailand and Vietnam," World Development, Elsevier, vol. 71(C), pages 4-24.
    9. Dominika Czyz & Karolina Safarzynska, 2023. "Catastrophic Damages and the Optimal Carbon Tax Under Loss Aversion," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 85(2), pages 303-340, June.
    10. Florent Bresson & Jean-Yves Duclos & Flaviana Palmisano, 2019. "Intertemporal pro-poorness," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 52(1), pages 65-96, January.
    11. Francesca Subioli & Michele Raitano, 2022. "Differences set in stone: evidence on the inequality-mobility trade off in italy," Working Papers 633, ECINEQ, Society for the Study of Economic Inequality.
    12. Mohd Nayyer Rahman & Nida Rahman & Abdul Turay & Munir Hassan, 2022. "Do Trade and Poverty Cause Each Other? Evidence from BRICS," Global Journal of Emerging Market Economies, Emerging Markets Forum, vol. 14(1), pages 9-31, January.
    13. Heutel, Garth, 2019. "Prospect theory and energy efficiency," Journal of Environmental Economics and Management, Elsevier, vol. 96(C), pages 236-254.
    14. Tobias Dalhaus & Barry J Barnett & Robert Finger, 2020. "Behavioral weather insurance: Applying cumulative prospect theory to agricultural insurance design under narrow framing," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-25, May.
    15. Luis Ayala & Elena Bárcena-Martín, 2020. "Measuring Social Welfare Gains in Social Assistance Programs: An Application to European Countries," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 151(1), pages 205-229, August.
    16. Travis J. Lybbert & Bruce Wydick, 2017. "Hope as Aspirations, Agency, and Pathways: Poverty Dynamics and Microfinance in Oaxaca, Mexico," NBER Chapters, in: The Economics of Poverty Traps, pages 153-177, National Bureau of Economic Research, Inc.
    17. Susanne Elsas, 2021. "Causality in the Link between Income and Satisfaction: IV Estimation with Internal Instruments," SOEPpapers on Multidisciplinary Panel Data Research 1143, DIW Berlin, The German Socio-Economic Panel (SOEP).

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    More about this item

    Keywords

    Political Economy; Production Economics;

    JEL classification:

    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development

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