Social Metrics II: Further Topics on Structural Analysis in the Social Sciences
The spring semester class is a seminar and builds on the fall class by introducing students to advanced topics in social metrics. We will study autoregressive dependent lag (ARDL) models, co-integration, and error correction models involving non-stationary time series. We will investigate simultaneous equations systems, vector error correction (VEC), and vector autoregressive (VAR) models. The final part of the seminar will involve the study of panel data, as well as logit/probit models. As with the fall class, the spring class will also be very “hands on” in that students will get ample exposure to concrete issues. Mathematical derivations will be kept to a minimum, as the goal is to train students to do practical work in social metrics. Also like the fall semester class, students will have to do joint collaborative projects in addition to conference work. Finally, methodological issues will be discussed throughout the semester. The spring semester is particularly relevant to students who wish to pursue graduate studies in a social science discipline, although it will be equally relevant for those seeking other types of graduate degrees that involve knowledge of intermediate-level quantitative analysis. Prerequisite: Social Metrics I.