AuthorSam, Abdoul Gadiry
AdvisorKer, Alan P.
Committee ChairKer, Alan P.
MetadataShow full item record
PublisherThe University of Arizona.
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
AbstractThe first essay of this dissertation studies the determinants and effects of firms' participation in a voluntary pollution reduction program (VPR) initiated by government regulators. This research presents empirical evidence in support of the "enforcement theory" for VPRs, which predicts that (1) participation is rewarded by relaxed regulatory scrutiny; (2) the anticipation of this reward spurs firms to participate in the program; and (3) the program rewards regulators with reduced pollution. The results also indicate that firms' VPR participation, and pollutant reductions themselves, were prompted by a firm's likelihood of becoming a boycott target and/or being subject to environmental interest group lobbying for tighter standards.In the second essay, a nonparametric regression estimator which can accommodate two empirically relevant data environments is proposed. The first data environment assumes that at least one of the explanatory variables is discrete. In such an environment, a "cell" approach which estimates a separate regression for each discrete cell, has generally been employed. The second data environment assumes that one needs to estimate a set of regression functions that belong to different individuals. In both environments the proposed estimator attempts to reduce estimation error by incorporating extraneous data from the other individuals or "cells" when estimating the regression function for a given individual or "cell". The simulation results for the proposed estimator demonstrate a strong potential in empirical applications.In the third essay, the nonparametric approach proposed in the second essay is used to estimate the parameters of the short-term interest rate diffusion. The nonparametric estimators of the drift of the short rate proposed by Stanton (1997) and Jiang (1998) can produce spurious nonlinearities due to the persistent dependence and limited sampling period of interest rates. The simulations show that the proposed estimator significantly attenuates the spurious nonlinearities of Stanton's nonparametric estimator. An empirical study of the US term structure of interest rates is presented based on the proposed estimator and two other competing models. The results suggest that the estimation of the short rate diffusion parameters using additional data from yields of different maturities has significant economic implications on the valuation interest rate derivatives.