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Applied Regression Analysis for Public Policy
Course Description

Elective course

Quantitative Policy Analysis Specialization for DPP

This class 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 course covers the fundamentals of regression analysis. The course begins with a brief review of the necessary ingredients from probability and statistics. From day one, students will learn the basic functionality of the statistical software package Stata, starting with the generation of descriptive statistics and graphics. Coverage of the linear regression model and regression diagnostics constitutes the core of the course. Once a firm understanding of basic models is attained, we move on to some more advanced regression techniques, including, but not limited to, non-linear regression, models with limited dependent variables, panel data analysis, and the evaluation of causal relationships.

Learning Outcomes
  1. Understand the fundamentals of regression analysis.
  2. Acquire basic proficiency in the statistical software Stata, programming, and interpretation of statistical outcomes.
  3. Learn about some advanced techniques in regression analysis.
  4. Discuss econometric output within the context of analytical policy making/evaluation.
  5. Assess the validity of an econometric study/report.
  6. Gain experience conducting independent quantitative research.


Bachelor-level or a master-level course in statistics is an asset.

Course Level
Academic Year
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