Fall 2023 Quantitative Methods: Social Sciences GR5016 section 001

TIME SERIES, PANEL DATA & FORECASTING

TIME SERIES, PANEL DATA &

Call Number 13799
Day & Time
Location
F 9:10am-11:00am
428 Pupin Laboratories
Points 3
Grading Mode Standard
Approvals Required None
Instructor Gregory M Eirich
Type LECTURE
Method of Instruction In-Person
Course Description

This course will introduce students to the main concepts and methods behind regression analysis of temporal processes and highlight the benefits and limitations of using temporally ordered data. Students study the complementary areas of time series data and longitudinal (or panel) data. There are no formal prerequisites for the course, but a solid understanding of the mechanics and interpretation of OLS regression will be assumed (we will briefly review it at the beginning of the course). Topics to be covered include regression with panel data, probit and logit regression of pooled cross-sectional data, difference-in-difference models, time series regression, dynamic causal effects, vector autoregressions, cointegration, and GARCH models. Statistical computing will be carried out in R.

Web Site Vergil
Department Quantitative Methods/Social Sciences
Enrollment 69 students (100 max) as of 4:05PM Wednesday, July 24, 2024
Subject Quantitative Methods: Social Sciences
Number GR5016
Section 001
Division Graduate School of Arts and Sciences
Note PRIORITY QMSS
Section key 20233QMSS5016G001