Time Series Cross-Sectional (TSCS) Data Analysis (Houston, TX)

Instructor(s):

  • Christopher Wlezien, University of Texas at Austin
  • Tse-min Lin, University of Texas at Austin

Time series cross-sectional (TSCS) data are data with a cross section of units for each of which there are repeated observations over time. TSCS data have been widely used in social sciences and their use is on the rise. The estimation of models for TSCS data is more complicated than either cross-sectional or time-serial analysis, as it must address both unit heterogeneity and temporal dynamics. This course provides an introduction to the techniques of TSCS data analysis. It begins with a consideration of the limits of cross-sectional analysis, the benefits of TSCS, and selected time-serial issues, before turning to estimation of linear models with fixed and random effects. It then addresses issues in modelling the time series in TSCS and special regression models, including logistic, event count, and event history. It concludes with a brief comparison of TSCS and multilevel data analysis.

Financial support of up to $1,000 per workshop is available for eligible students. In order to determine if you qualify for funding, send a personal statement of purpose, letter of recommendation from an advisor/colleague, and a copy of your unofficial transcript to Pablo Pinto (ppinto2@uh.edu), Director of the University of Houston Center for Public Policy, and Scott Mason (smason@uh.edu), Program Manager 2 at the University of Houston Hobby School of Public Affairs. The deadline for submitting this request is Friday, April 19.

Fee: Members = $1700; Non-members = $3200

Tags: time series, cross-sectional data, TSCS

Course Sections

Section 1

Location: University of Houston -- Houston, Texas

Date(s): May 20 - May 24

Time: 9:00 AM - 5:00 PM

Instructor(s):

  • Christopher Wlezien, University of Texas at Austin
  • Tse-min Lin, University of Texas at Austin

Syllabus: