THREE ESSAYS IN URBAN AND REGIONAL ECONOMICS

This dissertation comprises three chapters that are related to the research topics in Urban and Regional Economics. The first chapter examines whether economic self-interest associated with homeownership motivates homeowners to vote more than renters in U.S. local elections. To control for the self-selection of homeownership, I use national election turnout as the counterfactual outcome. Since policy discussions in national elections are targeted more at the national level, the disparity in political participation between homeowners and renters should be reduced. Results based on election data from three U.S. cities confirm these hypothesis, which suggest that local policies may tend to cater to the tastes of homeowners over renters. The second chapter develops a new method to identify and control for selection when estimating the productivity effects of city size. For single peaked factor return distributions, selecting out low-performing agents has limited effect on modal productivity but reduces the CDF evaluated at the mode. Spillovers from agglomeration have the reverse effect. Estimates based on law firm productivity, wages for married women and wages for full-time men all confirm that selection contributes to urban productivity and that doubling city size causes productivity to increase by 1-2.5 percent. The last chapter uses border discontinuity design to study the long-run effect of British colonial rule on the state building in Africa. British colonial legacy is featured with ethnic segregation and stronger executive constraints, which may have undermined state centralisation. Using micro-data from anglophone and francophone countries in sub-Saharan Africa, we find that anglophone citizens are less likely to identify themselves in national terms (relative to ethnic terms). Evidence on taxation, security and the power of chiefs also suggests weaker state capacity in anglophone countries. These results highlight the legacy of colonial rule on state-building

Impact Dynamics of Droplet Containing Particle Suspensions on Deep Liquid Pool

Droplet impact on surfaces is ubiquitous in many natural and industrial processes. While the impact dynamics of droplets composed of simple fluids have been studied extensively, droplets containing particles are less explored, but are more application relevant. The non-Newtonian behavior of particle suspension introduces new physics affecting the impact dynamics. Here, we investigated the impact dynamics of droplets containing cornstarch particles on a deep water pool and systematically characterized the impact outcomes with various Weber number and particle volume fractions. Distinctive phenomena compared to Newtonian droplet impact have been observed. A regime map of the impact outcomes is unveiled and the transition boundaries are quantified with scaling analysis. Rheology of the suspension is found to play a pivotal role in giving rise to distinct impact outcomes. The results lay the foundation for further characterization of the dynamics of suspension droplet impacting on liquid surfaces and can be translated to other suspension fluids

A class of BVPS for first order impulsive functional integro-differential equations with a parameter

This paper is concerned with a class of boundary value problems for the nonlinear impulsive functional integro-differential equations with a parameter by establishing new comparison principles and using the method of upper and lower solutions together with monotone iterative technique. Sufficient conditions are established for the existence of extremal system of solutions for the given problem. Finally, we give an example that illustrates our results

Influence Robustness of Nodes in Multiplex Networks against Attacks

Recent advances have focused mainly on the resilience of the monoplex network in attacks targeting random nodes or links, as well as the robustness of the network against cascading attacks. However, very little research has been done to investigate the robustness of nodes in multiplex networks against targeted attacks. In this paper, we first propose a new measure, MultiCoreRank, to calculate the global influence of nodes in a multiplex network. The measure models the influence propagation on the core lattice of a multiplex network after the core decomposition. Then, to study how the structural features can affect the influence robustness of nodes, we compare the dynamics of node influence on three types of multiplex networks: assortative, neutral, and disassortative, where the assortativity is measured by the correlation coefficient of the degrees of nodes across different layers. We found that assortative networks have higher resilience against attack than neutral and disassortative networks. The structure of disassortative networks tends to break down quicker under attack

Bayesian Repulsive Mixture Modeling with Mat\'ern Point Processes

Mixture models are a standard tool in statistical analysis, widely used for density modeling and model-based clustering. Current approaches typically model the parameters of the mixture components as independent variables. This can result in overlapping or poorly separated clusters when either the number of clusters or the form of the mixture components is misspecified. Such model misspecification can undermine the interpretability and simplicity of these mixture models. To address this problem, we propose a Bayesian mixture model with repulsion between mixture components. The repulsion is induced by a generalized Mat\'ern type-III repulsive point process model, obtained through a dependent sequential thinning scheme on a primary Poisson point process. We derive a novel and efficient Gibbs sampler for posterior inference, and demonstrate the utility of the proposed method on a number of synthetic and real-world problems

Fabrication of low loss silicon waveguides by ion irradiation and electrochemical etching

Ph.DDOCTOR OF PHILOSOPH