Browsing by Author "Xiaoyong Zheng, Committee Member"

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Alarming Behavior: Crime Displacement and Observable Private Precaution
(2008-07-31) Collett-Schmitt, Kristen Elizabeth; Charles R. Knoeber, Committee Chair; Xiaoyong Zheng, Committee Member; Walter N. Thurman, Committee Member; Stephen E. Margolis, Committee Member
Essays in Nonmarket Valuation with Applications to Environmental Economics
(2010-04-22) Domanski, Adam Matthew; Roger H. von Haefen, Committee Co-Chair; Raymond B. Palmquist, Committee Co-Chair; Xiaoyong Zheng, Committee Member; Laura O. Taylor, Committee Member
Non-market valuation techniques are vital instruments of policy. Providing quantitative welfare estimates validates public policy decisions. This research independently addresses three aspects of nonmarket valuation. Hedonic valuation of industrial accidents, limitations in recreational demand discrete choice modeling, and opportunities to expand urban planning research techniques. A hedonic estimation of the 2006 Apex, NC chemical fire finds that this unexpected event impacted public welfare, but only mildly and for a limited time period after the accident. Important factors seemed to be the lack of long-term contamination and the zero chance of future contamination. A mixed logit latent class estimation of recreational fishing trips in Wisconsin demonstrates the welfare implications of the random sampling of alternatives. This technique strategically reduces estimation time, but is difficult to implement in models where the independence of irrelevant alternatives (IIA) hypothesis is not present. By estimating a multi-class model using the EM algorithm, IIA is reintroduced in the model. This research evaluates the impact of various sample sizes on welfare estimates. The final research chapter applies the mixed logit model in the context of housing demand and urban planning. An exploratory estimation of a multi-class model using past research as a guide for choice set construction shows promise for this method's applicability to practitioners.
Modeling Dependence in the Design of Crop Insurance Contracts
(2010-03-24) Zhu, Ying; David A. Dickey, Committee Member; Peter Bloomfield, Committee Member; Sujit K. Ghosh, Committee Co-Chair; Xiaoyong Zheng, Committee Member; Barry K. Goodwin, Committee Chair
A Multi-Channel Wireless Implantable Neural Recording System
(2009-04-27) Yin, Ming; Paul Franzon, Committee Member; Gianluca Lazzi, Committee Co-Chair; Maysam Ghovanloo, Committee Co-Chair; Kevin Gard, Committee Member; Xiaoyong Zheng, Committee Member; Donald Woodward, Committee Member
ABSTRACT YIN, MING. A Multi-Channel Wireless Implantable Neural Recording System. (Under the direction of Dr. Maysam Ghovanloo). This dissertation presents a multi-channel implantable wireless neural recording (WINeR) system for electrophysiology and behavioral neuroscience research applications. This system consists of two units: a system-on-a-chip (SoC) transmitter unit and a receiver unit built with off-the-shelf components. A novelty of the WINeR system is in its utilization of a wireless single-slope ADC technique by inserting a wireless link in between a pulse width modulator and a time-to-digital converter (TDC). This technique not only offers the WINeR system the benefit of a single-slope ADC, but also makes the WINeR transmitter unit very simple, low power, and small in regards to chip area. In addition, by directly transmitting pulse width modulation (PWM) signal, the pulse rate over the wireless link is reduced to the sampling rate, while a moderate system resolution can still be achieved. Another novelty of this system is that its transmitter uses an asynchronous (clockless) topology and achieves very low noise levels by eliminating the on-chip clock. Some of the other features of this system are the wideband FSK demodulator and FPGA-based TDC in the receiver unit capable of achieving high resolution, low noise, low power, low cost, and ease of implementation. A 32-channel WINeR transmitter prototype is implemented in a standard CMOS technology, and operates in the 900MHz ISM band. A prototype WINeR receiver is also built using off-the-shelf components with up to 75MHz bandwidth. A custom developed VC++ GUI running on a PC interface with the receiver unit through a USB port and facilitates data storage and visualization. In addition, detailed noise analysis is conducted both theoretically and experimentally to further characterize the performance of the system. Finally, the full functionality of the entire WINeR system has been validated from bench-top, and through in vivo experiments on rats.
Three Essays on Dynamic Panel Data Estimation
(2009-12-01) Eryuruk, Gunce; Mehmet Caner, Committee Chair; Xiaoyong Zheng, Committee Member; Atsushi Inoue, Committee Member; A. Ronald Gallant, Committee Member
This dissertation consists of three essays, first two of which consider a new estimation method of dynamic panel data models and the last one considers an application of these models. The first essay (Chapter 1) offers empirical likelihood (EL) estimation of dynamic panel data models, which provide great flexibility to empirical researchers. EL estimation method is shown to have great advantages in usual settings, however little is known on the relative merits of these estimators in panel data models. With this essay, we try to fill that gap by establishing the asymptotic properties of the EL estimator for a dynamic panel model with individual effects when both the time and the cross-section dimensions tend to infinity. We give the conditions under which this estimator is consistent and asymptotically normal. In the second essay (Chapter 2), via a Monte Carlo study, we assess the relative finite sample performances of EL, generalized method of moments, and limited information maximum likelihood estimators for an autoregressive panel data model when there are many moment conditions. We also extend our results to the many weak moments settings. Our results suggest that when the overall performances are concerned, in terms of median, interquartile range and median absolute error of the estimators, in both strong and weak moments settings, EL is more reliable. In the final essay (Chapter 3) we consider an application of dynamic panel data models to examine the determinants of the allocation of state highway funds using panel data for North Carolina's 100 counties for the years 1990 to 2005. We make two main contributions with this essay. First, although there have been numerous studies of highway funding at the state level, to our knowledge, there is no analysis at the sub-state or county levels. Second, by using dynamic panel data models and sophisticated methods to estimate them, we account for any potential persistence in the process of adjustment toward an equilibrium, besides, unlike most of the previous studies, we control for the unobserved county heterogeneity and time effects that explain spatial differences, which may cause omitted variable problem if ignored.