Developed Advanced Econometric Questions for Teaching
- Day: 2024-09-06
- Time: 15:35 to 16:20
- Project: Teaching
- Workspace: WP 1: Strategic / Growth & Development
- Status: Completed
- Priority: MEDIUM
- Assignee: Matías Nehuen Iglesias
- Tags: Econometrics, Nested Logit, Education, Binary Models, Python
Description
Session Goal
The goal of the session was to develop advanced econometric questions suitable for graduate and post-graduate level studies, with a focus on binary outcome models and nested logit models.
Key Activities
- Question Development: Created a series of question ideas inspired by econometric exercises, focusing on binary outcome models such as probit and logit. These questions are designed to challenge graduate-level students and encourage a deeper understanding of econometric concepts.
- Advanced Question Outline: Outlined advanced questions aimed at post-graduate or PhD students, focusing on complex calculations and theoretical proofs, including likelihood ratio tests and maximum likelihood estimation.
- Nested Logit Model Analysis: Reviewed and corrected probability computations and elasticity calculations for transportation alternatives using a nested logit model. Updated Python code to derive cross-price elasticities and choice probabilities.
Achievements
- Developed a comprehensive set of advanced econometric questions for educational purposes.
- Successfully reviewed and improved the nested logit model analysis, ensuring accurate probability and elasticity calculations.
Pending Tasks
- Further refinement of questions to ensure clarity and alignment with educational objectives.
- Validation of Python code implementations for accuracy and efficiency.
Evidence
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