Difference between revisions of "Quantitative Impact Assessment Workshop/Case Studies II"

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[Français]
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[[Atelier sur l'évaluation quantitative de l'impact/Études de cas II|[Français]]]
  
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=QIA Workshop - Session 3 - Case Studies I=
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=QIA Workshop - Session 4 - Case Studies II=
 
__NOTOC__
 
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<br>
 
<br>
  
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=='''<small>Agenda | March 26 | 9:00am - 12:00pm ET</small>'''==
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=='''<small>Recording</small>''' ==
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[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>'''==
 
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|'''Case Study 1'''
 
|'''Case Study 1'''
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|Propensity score matching (PSM) and difference-in-difference (DID) to study the determinants and effects of cleantech investment on firm growth
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|Propensity score matching (PSM) and entropy balancing for impact assessment of business innovation and growth support (BIGS) on small and medium sized enterprises
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|Michael Willox
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|Ibrahim Bousmah
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|
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|[[:en:images/1/13/Session_4_-_Case_Study_1_(EN).pdf|Presentation <small>[click here]</small>]]
 
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|-
 
|'''Case Study 2'''
 
|'''Case Study 2'''
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|Hierarchical linear modelling using administrative data to study the Triple P – Positive Parenting Program
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|Matching difference-in-difference (MDID) for evaluation of AgriInnovation Stream C and AgriInnovate commercialization programs
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|Rubab Arim
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|Moh Torshizi
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|
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|[[:en:images/d/d0/Session_4_-_Case_Study_2_(EN).pdf|Presentation <small>[click here]</small>]]
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[[:en:images/a/a2/Handout_1_-_Literature.pdf|Handout 1 <small>[click here]</small>]]
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[[: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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|Empirical density design to study labour supply responses to income taxation among older couples
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|Modified Causal Forest (MCF) method to estimate incremental program impacts for different GBA Plus intersecting identity factors
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|Derek Messacar
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|Christiane Arsenault and Yu-Hsien Liu
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|
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|[[:en:images/4/43/Session_4_-_Case_Study_3_(EN).pdf|Presentation <small>[click here]</small>]]
 
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|}
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=='''<small>Questions and Answers</small>'''==
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[[: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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=='''<small>Meet the Presenters!</small>'''==
 
=='''<small>Meet the Presenters!</small>'''==
  
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====Michael Willox====
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====Ibrahim Bousmah====
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Michael Willox is a senior research economist at Statistics Canada, where he specializes in casual inference analysis and productivity and efficiency modeling. His areas of interest include measuring business productivity and efficiency, climate change economics, and developing business intelligence tools. Michael has worked in several federal government departments, including Finance Canada and Health Canada, where he was a program evaluation analyst. He received a Master of Arts degree in economics from McGill University in 2003 and is currently a PhD candidate at Brunel University, London, UK.
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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.
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====Mohammad (Moh) Torshizi====
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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.''
  
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====Rubab Arim====
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====Christiane Arsenault====
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Dr. Rubab Arim received her Ph.D. in Human Development, Learning, and Culture from the University of British Columbia. She is currently Chief in the Social Analysis and Modelling Division at Statistics Canada. Dr. Arim has research expertise in the use of population-based survey and administrative data and advanced statistical techniques to study policy-relevant issues for vulnerable populations, including children and youth with disabilities and their caregivers, with a particular focus on social determinants of health. Dr. Arim’s recent collaborations include measurement of childhood disability and educational outcomes of child and youth with disabilities using population-based linked survey and administrative data.
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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.
  
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====Derek Messacar====
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====Yu-Hsien Liu====
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Dr. Derek Messacar is a Senior Research Analyst in the Social Analysis and Modelling Division at Statistics Canada. In addition, he is an Associate Professor of Economics at Memorial University; Research Fellow of the Retirement and Savings Institute at HEC Montréal; and Board Member of the Canadian Labour Economics Forum. Dr. Messacar is an applied micro-economist with specializations in public finance and labour economics. He has written on numerous topics including gender inequality, returns to schooling, pensions, retirement, and the COVID-19 pandemic. His research has been published in national and international journals including ''Review of Economics and Statistics'', ''Journal of Labor Economics''; ''American Economic Journal: Applied Economics,'' ''American Economic Journal: Economic Policy''; ''National Tax Journal'', ''Canadian Journal of Economics'', and ''Canadian Public Policy/Analyse de politique''. Dr. Messacar received his B.A. from Brock University, M.A. from the University of British Columbia, and Ph.D. from the University of Toronto.
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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.
  
 
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Latest revision as of 11:57, 10 April 2024


[Français]

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]

Handout 1 [click here]

Handout 2 [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.



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