Difference between revisions of "Quantitative Impact Assessment Workshop/Case Studies II"
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| + | =='''<small>Recording</small>''' == | ||
| + | [https://youtu.be/j4y8vAwyWcs?si=TkmU9BnqV2PEpHdJ Session 4 - Case Studies II / Études de cas II (YouTube)] | ||
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=='''<small>Agenda | March 28 | 9:00am - 12:00pm ET</small>'''== | =='''<small>Agenda | March 28 | 9:00am - 12:00pm ET</small>'''== | ||
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|Moh Torshizi | |Moh Torshizi | ||
|[[:en:images/d/d0/Session_4_-_Case_Study_2_(EN).pdf|Presentation <small>[click here]</small>]] | |[[:en:images/d/d0/Session_4_-_Case_Study_2_(EN).pdf|Presentation <small>[click here]</small>]] | ||
| − | [[:en:images/ | + | [[:en:images/a/a2/Handout_1_-_Literature.pdf|Handout 1 <small>[click here]</small>]] |
| − | [[:en:images/ | + | [[:en:images/8/8c/Handout_2_-_Treatment_effect_heterogeneity.pdf|Handout 2 <small>[click here]</small>]] |
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|'''Case Study 3''' | |'''Case Study 3''' | ||
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|[[:en:images/4/43/Session_4_-_Case_Study_3_(EN).pdf|Presentation <small>[click here]</small>]] | |[[:en:images/4/43/Session_4_-_Case_Study_3_(EN).pdf|Presentation <small>[click here]</small>]] | ||
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| + | =='''<small>Questions and Answers</small>'''== | ||
| + | [[:en:images/0/01/QIA_Workshop_-_Session_4_-_Case_Studies_II_-_Questions_and_Answers.pdf|List of questions and answers <small>[click here]</small>]] | ||
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| + | Questions and answers are recorded in the language in which they were provided. | ||
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Latest revision as of 11:57, 10 April 2024
QIA Workshop - Session 4 - Case Studies II
Recording
Session 4 - Case Studies II / Études de cas II (YouTube)
Agenda | March 28 | 9:00am - 12:00pm ET
| Case Study 1 | Propensity score matching (PSM) and entropy balancing for impact assessment of business innovation and growth support (BIGS) on small and medium sized enterprises | Ibrahim Bousmah | Presentation [click here] |
| Case Study 2 | Matching difference-in-difference (MDID) for evaluation of AgriInnovation Stream C and AgriInnovate commercialization programs | Moh Torshizi | Presentation [click here] |
| Case Study 3 | Modified Causal Forest (MCF) method to estimate incremental program impacts for different GBA Plus intersecting identity factors | Christiane Arsenault and Yu-Hsien Liu | Presentation [click here] |
Questions and Answers
List of questions and answers [click here]
Questions and answers are recorded in the language in which they were provided.
Meet the Presenters!
Ibrahim Bousmah
Ibrahim Bousmah is an economist with the Treasury Board of Canada Secretariat. He received his Ph.D. in Economics from the University of Ottawa. He is particularly interested in research related to applied econometrics. His other research interests include innovation, entrepreneurship, firm performances, wages, and other labor market attributes.
Mohammad (Moh) Torshizi
Moh Torshizi received his PhD in Agricultural Economics at the University of Saskatchewan in 2015. He also hold B.Sc. and M.Sc. degrees in Agricultural Economics. Before joining the Research and Analysis Directorate at AAFC in 2020, he was an assistant professor of Agribusiness at the University of Alberta. Moh’s research interests are program impact assessment; economics of innovation, competition, and interactions of the two in agri-food systems; and grain marketing, handling, and transportation. He has publications in Ecological Economics, American Journal of Agricultural Economics, Canadian Journal of Agricultural Economics, Australian Journal of Agricultural and Resource Economics, Journal of Agricultural and Food Industrial Organization, Antitrust Bulletin, and the Journal of Transportation Research Forum.
Christiane Arsenault
Christiane Arsenault leads a Quantitative Methodology team at ESDC's Evaluation Directorate. She and her team develop advanced analyses to assess the effectiveness of ESDC programs. Before this, she helped other departments to benefit from innovative data analytics and transformation to make business processes more effective, efficient, and productive. She is passionate about improving our work and fostering cross-functional collaboration.
Yu-Hsien Liu
Yu-Hsien Liu is a Senior Data Analyst in the ESDC Evaluation Directorate. Bringing a hands-on approach to data science, she implemented a machine learning method to uncover new insights on program effectiveness from a Gender-Based Analysis Plus perspective. Yu-Hsien excels in leveraging R, Python, and visualization tools to derive meaningful insights, ensuring a comprehensive understanding of complex datasets.
