Quasisymmetric Embeddability of Weak Tangents

In this paper, we study the quasisymmetric embeddability of weak tangents of metric spaces. We first show that quasisymmetric embeddability is hereditary, i.e., if $X$ can be quasisymmetrically embedded into $Y$, then every weak tangent of $X$ can be quasisymmetrically embedded into some weak tangent of $Y$, given that $X$ is proper and doubling. However, the converse is not true in general; we will illustrate this with several counterexamples. In special situations, we are able to show that the embeddability of weak tangents implies global or local embeddability of the ambient space. Finally, we apply our results to expanding dynamics and establish several results on Gromov hyperbolic groups and visual spheres of expanding Thurston maps.Comment: 35 pages, 6 figure

Fiscal Policy, Regional Disparity and Poverty in China: a General Equilibrium Approach

The main objective of this research is to analyze the effects of the fiscal dimension of China’s government transfer and preferential tax policy on regional income disparity and poverty reduction. Using a computable general equilibrium model with a three-region component, we find that the preferential tax policy on the eastern coastal region of China has a significant effect on household income, as well as on the FGT indicator. The simulation results suggest that tax policy is a more effective tool to counter against China’s regional disparity than government transfer.China, Regional Disparity, Fiscal Policy, Government Transfer, Preferential Policy, Poverty, CGE, FGT

High Dimensional Probability

About forty years ago it was realized by several researchers that the essential features of certain objects of Probability theory, notably Gaussian processes and limit theorems, may be better understood if they are considered in settings that do not impose structures extraneous to the problems at hand. For instance, in the case of sample continuity and boundedness of Gaussian processes, the essential feature is the metric or pseudometric structure induced on the index set by the covariance structure of the process, regardless of what the index set may be. This point of view ultimately led to the Fernique-Talagrand majorizing measure characterization of sample boundedness and continuity of Gaussian processes, thus solving an important problem posed by Kolmogorov. Similarly, separable Banach spaces provided a minimal setting for the law of large numbers, the central limit theorem and the law of the iterated logarithm, and this led to the elucidation of the minimal (necessary and/or sufficient) geometric properties of the space under which different forms of these theorems hold. However, in light of renewed interest in Empirical processes, a subject that has considerably influenced modern Statistics, one had to deal with a non-separable Banach space, namely $\mathcal{L}_{\infty}$. With separability discarded, the techniques developed for Gaussian processes and for limit theorems and inequalities in separable Banach spaces, together with combinatorial techniques, led to powerful inequalities and limit theorems for sums of independent bounded processes over general index sets, or, in other words, for general empirical processes.Comment: Published at http://dx.doi.org/10.1214/074921706000000905 in the IMS Lecture Notes Monograph Series (http://www.imstat.org/publications/lecnotes.htm) by the Institute of Mathematical Statistics (http://www.imstat.org