WIT Press


Assessment On The Effect Of Pollution Abatement On Environmental Efficiency With Markov Chain Monte Carlo Simulation

Price

Free (open access)

Paper DOI

10.2495/SDP090542

Volume

120

Pages

9

Page Range

581 - 589

Published

2009

Size

234 kb

Author(s)

A. Ding & S. Managi

Abstract

Both environmental economists and policy makers have shown a great deal of interest in the effect of pollution abatement on environmental efficiency. In line with the modern resources available, however, no contribution is brought to the environmental economics field with the Markov chain Monte Carlo (MCMC) application, which enables simulation from a distribution of a Markov chain and simulating from the chain until it approaches equilibrium. The probability density functions gained prominence with the advantages over classical statistical methods in its simultaneous inference and incorporation of any prior information on all model parameters. This paper concentrated on this point with the application of MCMC to the database of China, the largest developing country with rapid economic growth and serious environmental pollution in recent years. The variables cover the economic output and pollution abatement cost from the year 1992 to 2003. We test the causal direction between pollution abatement cost and environmental efficiency with MCMC simulation. We found that the pollution abatement cost causes an increase in environmental efficiency through the algorithm application, which makes it conceivable that the environmental policy makers should make more substantial measures to reduce pollution in the near future. Keywords: environmental efficiency, pollution abatement, Markov chain Monte Carlo, China, environmental productivity, environmental performance.

Keywords

environmental efficiency, pollution abatement, Markov chain Monte Carlo, China, environmental productivity, environmental performance.