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PPG 1004: Quantitative Methods for Policy Analysis

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University of Toronto - School of Public Policy and Governance

PPG-1004: Quantitative Methods for Policy Analysis

Description: The central objective of this course is to equip students with the tools necessary to tackle issues that involve the empirical analysis of public policy problems of the sort they might encounter in a professional environment. It will cover probability theory and statistics, with a focus on the sensible application of methods to deal with empirical problems using appropriate data.

The course is designed with twin objectives in mind. The first is to provide students with the ability to analyze critically the empirical analysis done by others at a level sufficient to make intelligent decisions about how to use that analysis in the design of public policy. The second is to provide students with the skills necessary to perform empirical policy analysis on their own or to participate on a team involved in such an empirical analysis. The second objective is really a subset of the first.

Faculty: Garth Frazer (Fall 2012)

 

Teaching Topics Addressed in this Course, Organized by Public Management Subject

 Democratic Institutions and the Policy Process

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 Decision Sciences for Public Management

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 Evaluation and Performance Measurement

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 Human Resources Management

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 Leadership for Public Management

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Commentary by the Atlas Editors: This landmark course aims to provide students with the ability to understand and critically assess quantitative research that sheds light on public policy issues. In order to further their practical understanding of quantitative research methods, students learn how to use statistical software (in this case STATA) to conduct their own basic quantitative research.

Students use STATA to perform regression analysis and other types of quantitative research throughout this course. Course evaluation is based largely on series of nine assignments (eight minor assignments and one major assignment) for which students are required to use their knowledge of STATA to analyze data and assess the public policy implications. In addition to these assignments, students take a final written exam that tests knowledge of all course material.

The material taught in this course can be divided into the following broad topics:

1.)    Confidence Intervals and Hypothesis Testing (weeks one and two)

2.)    Linear Regression (weeks 3, 4 and 5)

3.)    Multiple Regression: (weeks 6 and 7. Includes learning about: dummy variables, least squares assumptions, omitted variables bias, binary dependent variables and internal validity).

4.)    Randomized Experiments and Difference-in-Differences studies.

5.)    Panel Data.

Page created by: Ben Eisen and Matthew Seddon, last updated 28 April 2013. The content presented on this page, except in the Commentary, is drawn directly from the source(s) cited above, and consists of direct quotations or close paraphrases.

 Syllabus

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© University of Toronto 2008
School of Public Policy and Governance