Jing Peng

Assistant Professor

Operations and Information Management


Education

Ph.D. in Operations, Information and Decisions, University of Pennsylvania

M.E. in Computer Science, Chinese Academy of Sciences

B.S. in Applied Physics, Xi’an Jiaotong University

Areas of Expertise

Econometrics, E-Commerce, Social Media, Gig Economy, Online Healthcare

Featured Publications

    View Jing’s research on Google Scholar and SSRN.

    R Packages

    I have a keen interest in developing novel econometric methods and have contributed three R packages to CRAN.

    • CoxPlus: A fast and highly scalable R package (core code written in C++) estimating Cox model (proportional hazards model) when an event has more than one cause. It also supports random and fixed effects, tied events, and time-varying variables. This package can be used in multi-channel advertising, social influence identification, etc.
    • PanelCount: A fast and scalable R package (speeded up by C++) implementing random effects and/or sample selection models for panel count data. This package can be applied to marketing campaigns with self-selection and repeated observations.
    • endogeneity: A comprehensive package that implements various recursive two-stage models to address the endogeneity issue in the absence of instrumental variables. This package can be used to address the endogeneity of mediators in randomized experiments or treatment variables in observational studies.

    Teaching

    OPIM 6201 – Research Methods for Operations and Information Management (focus on Econometrics)

    OPIM 5671 – Data Mining and Business Intelligence

    OPIM 5512 – Data Science using Python

     

     

    Contact Information
    Emailjing.peng@uconn.edu
    Mailing Address2100 Hillside Road, Unit 1041, Storrs, CT 06269
    Office LocationBUSN 368
    CampusStorrs
    CoursesOPIM6201; OPIM 5671; OPIM 5512
    Download CV