A CLIMATE CHANGE BURDEN SHARING MODEL USING BAYES' THEOREM

Abstract

A simple and straightforward climate change burden sharing model using Bayes’ Theorem is suggested here. However, not everyone would allocate burden responsibility in a Bayesian manner, and five factors are tested in a questionnaire to see which ones will affect respondents’ view of justice towards payment for pollution. These five factors are population size, per capita pollution rate, per capita wealth, the effort to reduce pollution, and the historical pollution record. Bayesian analysis would require that only the first two factors are important but not the others, though different respondents give different amount of considerations to the five factors. Bayesian analysis is also applied to the climate change burden sharing model where the percentage liability of every country towards climate change is determined using real data of population size and per capita greenhouse gases emission rate. However, since the data of the per capita emission of non-greenhouse gases is unavailable, certain assumptions are made but otherwise, Bayes’ Theorem is an elegant method to determine the amount of burden sharing. Finally, it is recommended that a climate change trust fund be set up where all the world governments will make mandatory contributions towards it based on the percentage liability determined from Bayes’ Theorem. This contribution will be used to fund climate change projects in the respective donor’s country.