Applied Regression Analysis 2

Course Description: 

Elective Course

This sequence of classes provides an intuitive and practical introduction to applied econometrics – the practice of analyzing quantitative data with statistical methods. The primary objective is to equip students with the quantitative techniques that are essential to “evidence-based policy-making” and necessary for post-graduate academic research in the quantitative social sciences (economics, peace science, political science, sociology, etc).

The second part of the course introduces some advanced topics in regression analysis: models with limited dependent variables, panel data analysis, the evaluation of causal relationships, and generating professional-quality tables. The core of the second part is devoted to reading, analyzing, and discussing quantitative public policy research of interest to class participants. Students make presentations of published research (academic or technical policy reports) that highlights a specific technique of regression analysis and pursue original quantitative research that relates to one of the following: (i) applied policy projects, (ii) research projects for other courses, (iii) MA thesis proposals, or (iv) any independent research interest involving the quantitative evaluation of some contemporary public policy issue.

Learning Outcomes: 
  1. Exposure to some advanced techniques in regression analysis.
  2. Discuss regression output within the context of analytical policy-making.
  3. Learn how to professionally present regression output.
  4. Gain experience conducting independent quantitative research.
Assessment: 
  1. Research project proposal 15% 
  2. Project update 15% 
  3. Project presentation 20% 
  4. Term project 50% 
Prerequisites: 

ARA 1