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Does Buddhism have much to offer in terms of reduction in global CO_2 emissions? A panel data analysis

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  • Jungho Suh

    (The University of Adelaide Geography, Environment and Population, Adelaide, Australia)

Abstract

The primary intent of this paper is to statistically test whether Buddhist countries tend to contribute to global warming mitigation in comparison with other religious groups of countries. A sample of 160 countries were classified into seven groups coded as ‘Buddhist’, ‘Hindu’, ‘Muslim’, ‘Catholic’, ‘Protestant’, ‘Christian mixed’ and ‘None of the above’. This study modelled the religious heritage of a nation into the IPAT equation (Environmental Impact = Population × Affluence × Technology), religion being as a cultural proxy of the technology factor. ‘Buddhist’ countries were found likely to emit lower CO_2 compared with ‘Protestant’ and ‘Christian mixed’ countries, although likely to emit higher CO_2 compared than ‘Hindu’, ‘Muslim’ and ‘Catholic’ countries, all other factors being held equal. The relatively low group effect of ‘Buddhist’ countries on CO_2 emissions can be interpreted to support the argument that teaching Buddhist economics and ecology could be a useful ingredient to curb ever-increasing global CO_2 emissions. Thus, further study is warranted as to how teachings from Buddhism can translate into lower CO_2 emissions.

Suggested Citation

  • Jungho Suh, 2013. "Does Buddhism have much to offer in terms of reduction in global CO_2 emissions? A panel data analysis," Society and Economy, Akadémiai Kiadó, Hungary, vol. 35(2), pages 209-225, August.
  • Handle: RePEc:aka:soceco:v:35:y:2013:i:2:p:209-225
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    Cited by:

    1. Squalli, Jay, 2019. "Is religiosity green in the United States?," Economic Analysis and Policy, Elsevier, vol. 63(C), pages 11-23.

    More about this item

    Keywords

    IPAT equation; fixed effects; random effects; panel cointegration;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • N30 - Economic History - - Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy - - - General, International, or Comparative
    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling

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