Semester

Spring

Date of Graduation

2019

Document Type

Dissertation

Degree Type

PhD

College

College of Business and Economics

Department

Economics

Committee Chair

Feng Yao

Committee Co-Chair

Joshua Hall

Committee Member

Joshua Hall

Committee Member

Arabinda Basistha

Committee Member

Xiaoli Etienne

Abstract

The first chapter studies a varying coefficient panel data model with different smoothing variables and fixed effects using a two-step estimation approach. The first-step pilot estimator is constructed by ap- approximating the varying coefficients with B-spline functions. The pilot estimator is then used to perform a one-step backfitting to obtain the second-step efficient estimator with kernel local linear estimation. The second-step estimator is efficient in the sense of being equivalent to a procedure knowing the other components of the varying coefficient. The asymptotic properties of both the pilot and efficient estimators are obtained. A Monte Carlo simulation indicates that the proposed estimator performs well with finite sample size.

The second chapter investigates the production efficiency of the U.S. coal-burning power plants that are covered under the Acid Rain Program from 2001 to 2005. To account for the influence of the Acid Rain Program on technical efficiency and the impact of environment variables on the marginal product of inputs, I introduce a panel data stochastic production frontier model with fixed effects and varying coefficients. The varying coefficients capture the relationship between power plant characteristics and the marginal return on inputs. Besides, the proposed model allows the inefficiency to depend on the environment variables, such as environmental policies. This set up enables the identification of the existence and magnitude of inefficiency. The proposed model relaxes the functional form assumption on coefficient functions and distribution assumption on the error terms. The empirical results reveal that the Acid Rain Program improves production efficiency for some power plants based on their operation and maintenance costs on sulfur removal equipment per unit of generating capacity. In addition, the marginal return on capital is affected by the years of operation of a power plant.

The third chapter studies the performance of water utilities in China. Water shortage is of great concern in China. Improving water delivery efficiency is the direct and efficient method to alleviate the water crisis. This paper performs an efficiency analysis of 56 water utilities during the period from 2009 to 2013. A semiparametric stochastic production frontier model with smooth coefficient is introduced to evaluate the magnitude of technical inefficiency and to examine the impact of institutional and operational condition, such as customer density, non-household user rate, non-revenue water ratio, average water pressure in pipes, and the percentage of internal staff among all the employees. The discussion focuses on the impact of the internal staff ratio since the benefits of being an internal staff drive the incentives to work. The empirical results reveal that a water utility with higher internal staff ratio has a lower marginal return on the technical staff. The finding supports that the internal staff ratio changes the technical efficiency and a large internal staff ratio reduces technical inefficiency at a decreasing rate.

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