- PhD students
- Academic Faculty Members
- Master students with good econometric knowledge
- Independent Researchers
GENERALIZED METHOD OF MOMENTS (GMM)
This online course presents the Generalized Method of Moments (GMM) panel data estimation techniques and their applications in STATA. You need this course if:
- your data is dynamic,
- you face fixed effects,
- you face endogeneity problems, and
- you need to enrich your knowledge to teach others (e.g., PhD students)
The course is organized into three modules.
- Module 1 presents dynamic panel data models based on generalized method of moments (GMM) – often used to mitigate endogeneity concerns.
- Module 2 covers advanced GMM models including two-step GMM, robust, orthogonal & other options.
- Module 3 concludes the course with a summary of learning outcomes, ways to export STATA output to MS Word and some useful references for panel data analysis.
Dr. Stephen Zamore is an Associate Professor at NLA University College and a Postdoctoral Research Fellow at University of Agder. His research interests include audit market regulation, sustainability assurance, empirical finance and IFRS. He has published articles in journals such as Journal of Banking and Finance, International Journal of Finance and Economics, Applied Economics, Research in International Business and Finance, Emerging Markets Finance and Trade, Journal of African Business, and International Journal of Emerging Markets, . Follow his research at researchgate.
Participants receives course completion certificate from Research HUB upon finishing all lectures and MCQs within 01 to 30 weeks from the enrollment date. See sample certificate HERE.
THE COURSE INCLUDES
- 13 on-demand lectures.
- Two MCQ tests for assessment (+2 retake).
- Practice datasets.
- Recommended readings.
- STATA do-files.
- Lifetime access to course resources and updates.
The course contents are subject to copyright. Unauthorized distribution of the course contents will lead to legal actions by Research HUB. The enrolled participants will have lifetime access to the course materials and any future updates. For institutional subscription, contact us at email@example.com.
Core GMM Models
Advanced GMM Models