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Explaining the diverse values assigned to environmental benefits across countries

Abstract

One of the key obstacles to building public consensus regarding environmental problems is the fact that environmental benefits are valued differently by different individuals and across different regions. Lack of public consensus has fractured international and domestic agreements, preventing effective system implementation. However, where does the disparity come from? Here, we provide evidence that can help to understand such diversity by analysing large-scale survey data collected across G20 countries. Combining lifecycle impact assessment and economic valuation techniques, our analysis shows that people’s perceptions of environmental benefits are in fact diverse, but are determined by a few social indicators such as life expectancy, income and gender equality, as well as individual conditions such as relative income and subjective well-being. As these social- and individual-level conditions improve, people shift priorities and place more emphasis on less tangible environmental benefits (biodiversity conservation) rather than relatively tangible (health-related) ones. Focusing on such determinants and addressing the problems of inequality and well-being are critical to building public consensus and tackling global environmental issues practically. Our findings can illuminate a feasible step to global consensus and a sustainable society.

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Fig. 1: The framework of this study.
Fig. 2: Comparison of regional averages of social weightings for 19 countries.
Fig. 3: Four distinct preference groups focusing on human health and biodiversity.

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Data availability

Data are available from the corresponding author on request.

Code availability

All data analysis has been performed using the Stata commands. No original code was used.

References

  1. Lange, G. M., Wodon, Q. & Carey, K. The Changing Wealth of Nations 2018: Building a Sustainable Future (World Bank, 2018).

  2. Sterner, T. & Persson, U. M. An even sterner review: introducing relative prices into the discounting debate. Rev. Environ. Econ. Policy 2, 61–76 (2008).

    Article  Google Scholar 

  3. Tol, R. S. The damage costs of climate change: a note on tangibles and intangibles, applied to DICE. Energy Policy 22, 436–438 (1994).

    Article  Google Scholar 

  4. Bateman, I. J. & Mace, G. M. The natural capital framework for sustainably efficient and equitable decision making. Nat. Sustain. 3, 776–783 (2020).

    Article  Google Scholar 

  5. De Civita, P., Filion, F. and Frehs, J. Environmental Valuation Reference Inventory (Environment and Climate Change Canada); Accessed August 22, 2021 https://www.evri.ca/en

  6. Morrison, M., Groenhout, R. & Moore, W. NSW EPA Environmental Valuation Database (ENVALUE) (New South Wales Environmental Protection Authority, 1995).

  7. Söderqvist, T. & Soutukorva, Å. On how to assess the quality of environmental valuation studies. J. For. Econ. 15, 15–36 (2009).

    Google Scholar 

  8. Muthke, T. & Holm-Mueller, K. National and international benefit transfer testing with a rigorous test procedure. Environ. Resour. Econ. 29, 323–336 (2004).

    Article  Google Scholar 

  9. Kristofersson, D. & Navrud, S. Validity tests of benefit transfer—are we performing the wrong tests? Environ. Resour. Econ. 30, 279–286 (2005).

    Article  Google Scholar 

  10. Johnston, R. J., Rolfe, J., Rosenberger, R. S. & Brouwer, R. Benefit Transfer of Environmental and Resource Values: A Guide for Researchers and Practitioners (Springer, 2015).

  11. Inaba, A. & Itsubo, N. Preface. Int. J. Life Cycle Assess. 23, 2271–2275 (2018).

    Article  Google Scholar 

  12. Itsubo, N. et al. Development of weighting factors for G20 countries—explore the difference in environmental awareness between developed and emerging countries. Int. J. Life Cycle Assess. 23, 2311–2326 (2018).

    Article  Google Scholar 

  13. The World by Income and Region (World Bank, 2020); https://datatopics.worldbank.org/world-development-indicators/the-world-by-income-and-region.html

  14. Hofstetter, P. Perspectives in Life Cycle Impact Assessment: A Structured Approach to Combine Models of the Technosphere, Ecosphere and Valuesphere (Springer Science & Business Media, 1998).

  15. Goedkoop, M. J. & Spriensma, R. The Eco-indicator 99: A Damage Oriented Method for Life Cycle Impact Assessment Methodology (PRé Consultants, 1999).

  16. Environmental Priority Strategies in Product Design (EPS) (Swedish Life Cycle Center, 2015); https://www.lifecyclecenter.se/projects/environmental-priority-strategies-in-product-design-eps/

  17. ExternE - Publications Office of the EU (europa.eu); https://op.europa.eu/en/publication-detail/-/publication/91c4b9d0-5775-4bc4-9c2c-184804739041

  18. Bielecki, A. et al. The externalities of energy production in the context of development of clean energy generation. Environ. Sci. Pollut. Res. 27, 11506–11530 (2020).

    Article  Google Scholar 

  19. Murakami, K. et al. Development of weighting factors for G20 countries. Part 2: estimation of willingness to pay and annual global damage cost. Int. J. Life Cycle Assess. 23, 2349–2364 (2018).

    Article  Google Scholar 

  20. Eichengreen, B., Donghyun, P. & Kwanho, S. When fast-growing economies slow down: international evidence and implications for China. Asian Econ. Pap. 11, 42–87 (2012).

    Article  Google Scholar 

  21. Gill, I. & Kharas, H. An East Asian Renaissance: Ideas for Economic Growth (World Bank, 2007).

  22. Gill, I. S. & Kharas, H. The Middle-Income Trap Turns Ten (English) Policy Research Working Paper No. WPS 7403 (World Bank Group, 2015).

  23. Felipe, J., Kumar, U. & Galope, R. Middle-Income Transitions: Trap or Myth? ADB Economics Working Paper Series No. 421 (Asian Development Bank, 2014).

  24. Solow, R. A contribution to the theory of economic growth. Q. J. Econ. 70, 65–94 (1956).

    Article  Google Scholar 

  25. Lin, J. Y. & Treichel, V. Learning from China’s Rise to Escape the Middle-Income Trap: A New Structural Economics Approach to Latin America Policy Research Working Paper No. 6165 (World Bank, 2012).

  26. Eichengreen, B., Park, D. & Shin, K. Growth slowdowns redux. Japan World Econ. 32, 65–84 (2014).

    Article  Google Scholar 

  27. Barro, R. Economic growth in a cross section of countries. Q. J. Econ. 106, 407–443 (1991).

    Article  Google Scholar 

  28. Mauro, P. Corruption and growth. Q. J. Econ. 110, 681–712 (1995).

    Article  Google Scholar 

  29. Knack, S. & Keefer, P. Institutions and economic performance: cross-country tests using alternative institutional measures. Econ. Politics 7, 207–227 (1995).

    Article  Google Scholar 

  30. Isham, J., Pritchett, L., Woolcock, M. & Busby, G. The varieties of resource experience: natural resource export structures and the political economy of economic growth. World Bank Econ. Rev. 19, 141–174 (2005).

    Article  Google Scholar 

  31. Boxall, P. C. & Adamowicz, W. L. Understanding heterogeneous preferences in random utility models: a latent class approach. Environ. Resour. Econ. 23, 421–446 (2002).

    Article  Google Scholar 

  32. Kuriyama, K., Hanemann, W. M. & Hilger, J. R. A latent segmentation approach to a Kuhn–Tucker model: an application to recreation demand. J. Environ. Econ. Manage. 60, 209–220 (2010).

    Article  Google Scholar 

  33. Konow, J. & Earley, J. The hedonistic paradox: is homo economicus happier? J. Public Econ. 92, 1–33 (2008).

    Article  Google Scholar 

  34. Nickerson, C., Schwarz, N., Diener, E. & Kahneman, D. Zeroing in on the dark side of the American dream: a closer look at the negative consequences of the goal for financial success. Psychol. Sci. 14, 531–536 (2003).

    Article  Google Scholar 

  35. Bertrand, M. & Mullainathan, S. Do people mean what they say? Implications for subjective survey data. Am. Econ. Rev. 91, 67–72 (2001).

    Article  Google Scholar 

  36. Kristensen, N. & Johansson, E. New evidence on cross-country differences in job satisfaction using anchoring vignettes. Labour Econ. 15, 96–117 (2008).

    Article  Google Scholar 

  37. Tella, R. D., MacCulloch, R. J. & Oswald, A. J. The macroeconomics of happiness. Rev. Econ. Stat. 85, 809–827 (2003).

    Article  Google Scholar 

  38. Layard, R. Measuring subjective well-being. Science 327, 534–535 (2010).

    Article  CAS  Google Scholar 

  39. Graham, C. Happiness Around the World: The Paradox of Happy Peasants and Miserable Millionaires (Oxford Univ. Press, 2012); https://doi.org/10.1093/acprof:osobl/9780199549054.001.0001

  40. Murray, C. J. & Lopez, A. D. The Global Burden of Disease Global Burden of Disease and Injury Series, Vol. 1 (World Health Organization, World Bank, Harvard School of Public Health, 1996).

  41. Tang, L. et al. Development of human health damage factors related to CO2 emissions by considering future socioeconomic scenarios. Int. J. Life Cycle Assess. 23, 2288–2299 (2018).

    Article  CAS  Google Scholar 

  42. Tang, L. et al. Development of human health damage factors for PM2.5 based on a global chemical transport model. Int. J. Life Cycle Assess. 23, 2300–2310 (2018).

    Article  CAS  Google Scholar 

  43. Lande, R. Risks of population extinction from demographic and environmental stochasticity and random catastrophes. Am. Nat. 142, 911–927 (1993).

    Article  Google Scholar 

  44. Yamaguchi, K., Ii, R. & Itsubo, N. Ecosystem damage assessment of land transformation using species loss. Int. J. Life Cycle Assess. 23, 2327–2338 (2018).

    Article  Google Scholar 

  45. El Serafy, S. in Environmental Accounting for Sustainable Development (World Bank, 1989).

  46. Whittaker, R. H. Communities and Ecosystems 2nd edn (MacMillan, 1975).

  47. World Bank Open Data (World Bank, accessed 22 July 2019).

  48. Arrow, K. et al. Report of the NOAA panel on contingent valuation. Fed. Regist. 58, 4601–4614 (1993).

    Google Scholar 

  49. Olsen, S. B. Choosing between internet and mail survey modes for choice experiment surveys considering non-market goods. Environ. Resour. Econ. 44, 591–610 (2009).

    Article  Google Scholar 

  50. Meyerhoff, J., Mørkbak, M. R. & Olsen, S. B. A meta-study investigating the sources of protest behaviour in stated preference surveys. Environ. Resour. Econ. 58, 35–57 (2014).

    Article  Google Scholar 

  51. Andreoni, J. Giving with impure altruism: applications to charity and Ricardian equivalence. J. Polit. Econ. 97, 1447–1458 (1989).

    Article  Google Scholar 

  52. Train, K. Discrete Choice Methods with Simulation, 2nd edn (Cambridge Univ. Press, 2009).

  53. Freeman, A. M. III, Herriges, J. A. & Kling, C. L. The Measurement of Environmental and Resource Values. Theory and Methods, 3rd edn (Routledge, 2014).

  54. Hensher, D., Rose, J. & Greene, W. Applied Choice Analysis, 2nd edn (Cambridge Univ. Press, 2015).

  55. Kamakura, W. & Russell, G. A probabilistic choice model for market segmentation and elasticity structure. J. Mark. Res. 26, 379–390 (1989).

    Article  Google Scholar 

  56. Diener, E. Subjective well-being. Psychol. Bull. 95, 542–575 (1984).

    Article  CAS  Google Scholar 

  57. Stiglitz, J., Sen, A. & Fitoussi, J.-P. Report by the Commission on the Measurement of Economic Performance and Social Progress (European Commission, 2009).

  58. Self, A., Thomas, J. M. & Randall, C. Measuring National Well-being: Life in the UK (Office for National Statistics, 2012).

  59. Staff Working Document on “Progress on ‘GDP and Beyond’ Actions” (European Commission, 2013).

  60. OECD Guidelines on Measuring Subjective Well-being (OECD, 2013); https://doi.org/10.1787/9789264191655-en

  61. Krueger, A. & Stone, A. Progress in measuring subjective well-being. Science 346, 42–44 (2014).

    Article  CAS  Google Scholar 

  62. Schimmack, U. & Oishi, S. The influence of chronically and temporarily accessible information on life satisfaction judgments. J. Pers. Soc. Psychol. 89, 395–406 (2005).

    Article  Google Scholar 

  63. Layard, R., Clark, A. & Senik, C. in World Happiness Report (eds Helliwell, J. et al.) 89 (United Nations, 2012).

  64. Diener, E., Oishi, S. & Tay, L. Advances in subjective well-being research. Nat. Hum. Behav. 2, 253–260 (2018).

    Article  Google Scholar 

  65. The UK Health & Wellbeing Report 2020. https://www.askattest.com/reports-guides/uk-health-wellbeing-report-2020 (Attest, 2020).

  66. Measures of National Well-being Dashboard. https://www.ons.gov.uk/peoplepopulationandcommunity/wellbeing/articles/measuresofnationalwellbeingdashboard/2018-04-25 (Office for National Statistics UK, 23 October 2019).

  67. Subjective well-being statistics. EU Statistics on Income and Living Conditions (EU-SILC). https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Subjective_well-being_-_statistics#Overall_life_satisfaction_in_the_EUhttps://ec.europa.eu/eurostat/statistics-explained/index.php?title=Glossary:EU_statistics_on_income_and_living_conditions_(EU-SILC). (Eurostat statistics explained, October 2019.)

  68. Oishi, S. Culture and well-being: Conceptual and methodological issues. In International Differences in Well-being. 34-69 (eds Diener, E. et al.) (Oxford Univ. Press, 2010).

  69. Bhatnagar, T. Subjective Well-being in the Indian Context: Concept, Measure and Index. PhD thesis, Indian Institute of Technology Bombay (2010).

  70. Clark, A. E. & Oswald, A. J. Satisfaction and comparison income. J. Public Econ. 61, 359–381 (1996).

    Article  Google Scholar 

  71. Caporale, G. M., Georgellis, Y., Tsitsianis, N. & Yin, Y. P. Income and happiness across Europe: do reference values matter? J. Econ. Psychol. 30, 42–51 (2009).

    Article  Google Scholar 

  72. McCarthy, D. P. et al. Financial costs of meeting global biodiversity conservation targets: current spending and unmet needs. Science 338, 946–949 (2012).

    Article  CAS  Google Scholar 

  73. ISO14044 Environmental Management—Life Cycle Assessment—Requirements and Guidelines (ISO, 2006).

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Acknowledgements

We thank Y. Mitani (Kyoto University), H. Sakamoto (Kobe University) and K. Takeuchi (Kyoto University) for their helpful comments, the International Research Unit of Nikkei Research for its valuable support in conducting the social survey across various regions accompanied by local research companies, and seminar participants at the Annual Conference of the Society for Environmental Economics and Policy Studies (SEEPS) and the Conference on Advanced Studies in Economics (CASE) for their valuable discussions and feedback. This work was supported by JSPS Grants-in-Aid for Scientific Research (grant no. JP18J40180, K.M.). This large-scale simultaneous social survey has been supported financially by the Cabinet Office of the Japan Government (Funding Program for Next Generation World-Leading Researchers (NEXT Program), grant no. GZ006, N.I.).

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All authors contributed to the design and methodology of this study. K.M. led the survey design, statistical analysis, writing and revisions of the manuscript, with input from all other authors. K.K. provided the code for the latent class logit model with the EM algorithm. The initial concept for LIME was developed by N.I. and K.K.

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Correspondence to Kayo Murakami.

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Murakami, K., Itsubo, N. & Kuriyama, K. Explaining the diverse values assigned to environmental benefits across countries. Nat Sustain 5, 753–761 (2022). https://doi.org/10.1038/s41893-022-00914-8

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