Chapter 7: Causal Direction Between Pollution Abatement and Environmental Efficiency
INTRODUCTION 1 Society faces an important tradeoff between economic output and environmental policy. Both environmental economists and public policy makers in developed and developing countries alike have shown a great deal of interest in the effect of pollution abatement on environmental efficiency. In line with the modern resources available nowadays, there has been a large amount of recent research, but no contribution to the environmental economics field with the Markov chain Monte Carlo (MCMC) application. MCMC techniques enable simulation from a distribution of a Markov chain and simulating from the chain until it approaches equilibrium. This simulation approach of probability density functions gained prominence through the practice of Bayesian statistics, which has the advantage over classical statistical methods in its simultaneous inference and incorporation of any prior information on all model parameters. The work we carried out concentrated on this point. In this chapter, we apply a Bayesian approach via MCMC simulation to the database of China, the largest developing country. China is the world’s third-largest consumer of coal and oil, but much of its energy-producing and -using equipment is both inefficient and highly polluting. As a result, China experiences severe urban air pollution which has a significant impact throughout the region. It is also the world’s second-largest source of greenhouse gas emissions. Improving energy efficiency and accelerating the development and application of new and renewable energy and clean coal technologies are therefore very urgent sustainable development and environmental priorities. Public policy makers are facing tradeoffs between economic growth and...
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