A nonparametric method to estimate a technical change effect on marginal abatement costs of U.S. coal power plants, published in Energy Economics

     Emission at coal fired power plants

This paper develops a method to investigate the effects of technical change on marginal abatement costs (MAC). This was the second chapter of Maethee Mekaroonreung Ph.D. dissertation. The research was motivated by a paper by Erin Baker that suggested that technical change does not always reduce MAC. In their analysis they made parametric assumptions to investigate a variety of models relating technical change and MAC. In this paper we used nonparametric methods to investigate this question for boilers in coal fired power plants. We find that while technical change reduces MAC, non-technical change related to changes in abatement input costs, production input levels, and pollutant level change is a larger effect. So the investment and installation pollution abatement equipment has lead to larger MACs.

The literature usually assumes that technical change reduces marginal abatement cost; however, recent results suggest that precisely the opposite occurs. This paper proposes a nonparametric method to determine the effect of technical change on marginal abatement cost. The method decomposes NOx marginal abatement cost changes in 2000–2004 and in 2004–2008 for 325 boilers operating in 134 U.S. bituminous coal power plant into technical and non-technical change effects. We find that technical change reduces the NOx marginal cost about 28.3% in 2000–2004 and 26.5% in 2004–2008. However, more stringent regulations enacted the NOx budget program results in lower NOx emission levels as plant operators install more advanced NOx abatement equipment which in turn causes an overall increase in marginal abatement cost.

Nonparametric measurement of productivity and efficiency in education, published in Annals of Operations Research


This paper was written in 2010 and appeared on-line in 2011. It has taken Annals of Operations Research more than 3 years to publish the paper. This paper combines a deterministic contextual variables model with a Malmquist productivity analysis. The methods are applied to Ohio school data. See the abstract below for more details.

This paper was written with John Ruggiero one of the most widely cited researchers in the area of DEA. John and I have written several papers over the years and he has acted as a mention to me. He is generally considered to be the life of the conference as most academic conferences he attends.

Nondiscretionary environmental inputs are critical in explaining relative efficiency differences and productivity changes in public sector applications. For example, the literature on education production shows that school districts perform better when student poverty is lower. In this paper, we extend the nonparametric approach to decompose the Malmquist Productivity Index suggested by Färe et al. (American Economic Rewiew 84:66–83, 1994) into efficiency, technological and environmental changes. The approach is applied to analyze educational production of Ohio school districts. Applying the extended approach in an analysis of the educational production of 604 school districts in Ohio, we find changes in environmental harshness are the primary drivers in productivity changes of underperforming school districts, while technical progress drives the performance of top performing school districts.