Quantitative Impact Assessment Workshop
Revision as of 11:36, 6 March 2024 by Matthew.macvicar (talk | contribs)
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Statistics Canada and the Treasury Board of Canada Secretariat invite you to participate in the third Quantitative Impact Assessment (QIA) workshop.
Overview
Statistics Canada (StatCan) and the Treasury Board of Canada Secretariat (TBS) have organized a four-day workshop on using quantitative impact assessment (QIA) methods for program evaluation. Participants should expect to learn the strengths and limitations of QIA methods and how to better leverage data.
Session 1 - Fundamentals
| Title | Date | Description | Language | Agenda and Materials |
|---|---|---|---|---|
| Fundamental concepts of quantitative impact assessment | March 19 | 9am-12pm (ET) | Fundamentals will provide a comprehensive overview of QIA concepts. Participants will learn the difference between program outcomes and program impacts, and be introduced to the common approaches to QIA (such as difference-in-differences, discontinuity estimators, and more). This session will also offer a detailed overview of randomized controlled experiments – the gold standard of QIA. | English with bilingual materials | Session 1 - Agenda and Materials |
Session 2 - Data
| Leveraging data for impact analysis | March 21 | 9am-12pm (ET) | Data will provide an overview of the data environments available through Statistics Canada. Participants will learn about performing custom tabulations and multivariate analysis, with specific emphasis on the availability of gender and diversity data and Quality of Life data. This session will explain how to access existing microdata and overcome data gaps. | English with bilingual materials | Session 2 - Agenda and Materials |
Session 3 - Case Studies I
| Case Studies I: Applying QIA methods to evaluate program performance and impact | March 26 |
9am-12pm (ET) |
Case Studies I will focus on three real-life examples of QIA methods being applied to evaluate program performance and impact. These case studies primarily leverage social data. The methods covered are (1) empirical density design, (2) hierarchical linear modelling, and (3) propensity score matching and difference-in-differences. | English with bilingual materials | Session 3 - Agenda and Materials |
Session 4 - Case Studies II
| Case Studies II: Applying QIA methods to evaluate program performance and impact | March 28 |
9am-12pm (ET) |
Case Studies II will also focus on three real-life examples of QIA methods being applied to evaluate program performance and impact. These case studies primarily leverage business microdata. The methods covered are (1) propensity score matching and entropy balancing, (2) matching difference-in-differences, and (3) modified causal forest. | English with bilingual materials | Session 3 - Agenda and Materials |
Stay connected
- Join the Business Innovation and Growth Support Data Community of Practice
- Contact the Data Science, Research and Development unit