Who gets caught for corruption when corruption is pervasive? Evidence from China’s anti-bribery blacklist

© 2016 Informa UK Limited, trading as Taylor & Francis Group. This article empirically investigates why in a corruption-pervasive country only a minority of the firms get caught for bribery while the majority get away with it. By matching manufacturing firms to a blacklist of bribers in the healthcare sector of a province in China, we show that the government-led blacklisting is selective: while economically more visible firms are slightly more likely to be blacklisted, state-controlled firms are the most protected compared to their private and foreign competitors. Our finding points to the fact that a government can use regulations to impose its preferences when the rule of law is weak and the rule of government is strong

Large Deviations for Stochastic Generalized Porous Media Equations

The large deviation principle is established for the distributions of a class of generalized stochastic porous media equations for both small noise and short time.Comment: 15 pages; BiBoS-Preprint No. 05-11-196; publication in preparatio

Explore Regional Variation in the Effects of Built Environment on Driving with High Resolution U.S. Nationwide Data

There have been numerous studies on the relationship between travel behavior and built environment over the last few decades. Prior studies have mostly focused on producing point estimates of model coefficients and ended up with a wide range of estimates for the built environment elasticity of travel behavior, including household Vehicle Miles Traveled. With few exceptions, previous studies use data from a single region or a small number of regions, and thus are not able to sufficiently investigate the regional variation in built environment elasticity. On the other hand, a few papers have addressed the heterogeneity of elasticity among different population groups and neighborhood types, but so far have paid little attention to regional variation of elasticity. In his latest research project, Liming Wang uses the 2009 U.S. National Household Travel Survey and high resolution built environment measures in the Smart Location Database to investigate the Urbanized Area-level variation in the effect of built environment with multi-level mixed effect models. He found that there exist regional variations in the relationship between built environment and household VMT, and, as a matter of fact, there is no significant fixed effect of major built environment factors on VMT after considering urbanized area-level random effect. This presentation will conclude with a discussion of the implications of this research.https://pdxscholar.library.pdx.edu/trec_seminar/1240/thumbnail.jp