Department of Biostatistics
School of Public Health
University of Illinois at Chicago
NBER Working Papers and Publications
|October 2013||Drive More Effective Data-Based Innovations: Enhancing the Utility of Secure Databases|
with Yi Qian: w19586
Databases play a central role in evidence-based innovations in business, economics, social, and health sciences. In modern business and society, there are rapidly growing demands for constructing analytically valid databases that also are secure and protect sensitive information in order to meet customer and public expectations, to minimize financial losses, and to comply with privacy regulations and laws. We propose new data perturbation and shuffling (DPS) procedures, named MORE, for this purpose. As compared with existing DPS methods, MORE can substantially increase the utility of secure databases without increasing disclosure risk. MORE is capable of preserving important nonmonotonic relationships among attributes, such as the inverted-U relationship between competition and innovation....
Published: Yi Qian & Hui Xie, 2015. "Drive More Effective Data-Based Innovations: Enhancing the Utility of Secure Databases," Management Science, vol 61(3), pages 520-541.
|January 2011||Investigating the Dynamic Effects of Counterfeits with a Random Changepoint Simultaneous Equation Model|
with Yi Qian: w16692
Using a unique panel dataset and a new model, this article investigates the dynamic effects of counterfeit sales on authentic-product price dynamics. We propose a Bayesian random-changepoint simultaneous equation model that simultaneously takes into account three important features in empirical studies: (1) Endogeneity of a market entry, (2) Nonstationarity of the entry effects and (3) Heterogeneity of the firms' response behaviors. Besides accounting for the endogeneity of counterfeiting, the proposed methodology improves the estimation of dynamic effects under heterogeneous response times by firms. We identify both a temporary negative short-term effect and a stable positive long-term effect of counterfeit sales on the authentic prices. Such effect estimates are biased in the OLS model a...
|August 2010||A Semiparametric Approach for Analyzing Nonignorable Missing Data|
with Yi Qian, Leming Qu: w16270
In missing data analysis, there is often a need to assess the sensitivity of key inferences to departures from untestable assumptions regarding the missing data process. Such sensitivity analysis often requires specifying a missing data model which commonly assumes parametric functional forms for the predictors of missingness. In this paper, we relax the parametric assumption and investigate the use of a generalized additive missing data model. We also consider the possibility of a non-linear relationship between missingness and the potentially missing outcome, whereas the existing literature commonly assumes a more restricted linear relationship. To avoid the computational complexity, we adopt an index approach for local sensitivity. We derive explicit formulas for the resulting semiparam...
Published: Xie, Hui, Yi Qian and Leming Qu. 2011. A Semiparametric Approach for Analyzing Nonignorable Missing Data. Statistica Sinica. 21: 1881-1899.