Research Seminar I

Research Seminar I

専門教育科目

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国際商経学部

2年

KCCBG2MCA3

2単位

演習 (Seminar)

2025年度後期

(Fall semester)

Jean-Baptiste M.B. SANFO

国際商経学部

英語

目標9

Before or after class, in the classroom

1◎／2〇／3〇

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【Course Objectives】
This course is designed to equip students with the practical skills needed to apply econometric methods using R. The course will prepare students to analyze real-world data, extract meaningful insights, and effectively communicate results. Students will learn how to manipulate and visualize data, implement econometric models, and interpret the results. The course emphasizes a hands-on approach to ensure that students gain confidence in using R for data-driven decision-making in academic, research, and professional settings.

【Learning Outcome】
By the end of this course, students will be able to:
1. Utilize R to perform data cleaning, visualization, and basic econometric analysis.
2. Interpret and present analyzed results in a clear and actionable manner.
3. Carry out a basic empirical research project

Econometric analysis; applied statistic; R; data analysis; data visualization

This course is designed to be hands-on and interactive, allowing you to actively engage with the material and develop practical skills. As your instructor, I will serve primarily as a facilitator by guiding you through the learning process while encouraging collaboration and exploration. Your participation is key to your success, and together we will create a dynamic learning environment!

Lecture 1:  Introduction to R I
Lecture 2:  Introduction to R II
Lecture 3:  Simple Regression Analysis
Lecture 4:  Multiple Regression Analysis: Estimation
Lecture 5:  Multiple Regression Analysis: Inference
Lecture 6:  Multiple Regression Analysis: OLS asymptotics
Lecture 7: Mid-term test
Lecture 8: Multiple Regression Analysis with Qualitative Regressors
Lecture 9: Regression Analysis with Pooled Cross sections Data
Lecture 10:  Regression Analysis with Panel Data
Lecture 11: Basic Regression Analysis with Time Series Data I
Lecture 12: Basic Regression Analysis with Time Series Data II
Lecture 13: Research project
Lecture 14: Research project
Lecture 15: Research project

Final evaluation

The content of the course may vary depending on the pace of the progress.

Computer Use: Student will use their own computers during almost all lectures (TBA).

Policy on the Use of Generative AI:

Students are expected to follow the instructions of the instructor regarding the use of generative AI. While it is acceptable to use generative AI as a supplementary tool for activities such as writing reports and conducting case searches, it is crucial to verify the accuracy of the content produced. Students should ensure that facts are checked and that sources and references are properly acknowledged. The output from generative AI must not be submitted as an assignment without the necessary changes. If this practice is discovered, credit may be denied or revoked.

Using R for Introductory Econometrics 2nd edition, by  Florian Heiss
Can be accessed for free using this link:  https://www.urfie.net/downloads/PDF/URfIE_web.pdf

Applied Statistics with R, by  David Dalpiaz. https://book.stat420.org/
Introductory Econometrics: A Modern Approach, by Jeffrey M. Wooldridge
H. Stock & M. M. Watson Introduction to Econometrics 4th ed. Pearson

【Pre-Learning】Students will be provided with lecture notes and handouts beforehand. Please read them before the class.

【Post- Learning】Lecture notes and handouts will contain exercises or questions. Please review them after the class.

Students will be asked to share their understanding of given concepts or asked to report orally what they discussed in groups.
Econometric models will be estimated in class using real-world data. We will discuss estimation results together.
Students will estimate econometric models and give presentations on their findings.

Engagement in classroom activities (40%)
Mid-term test (20%)
Research project presentation (40%)

In the classroom

The prerequisite for this course is Introductory Statistics for Economics.

Students should have an understanding of statistics and basic econometrics.

Regular attendance is required.

N/A

Remember that making mistakes is a natural part of the learning process. Don’t fear mistakes; instead, view them as valuable opportunities for growth. Be proactive in your learning by seeking help, asking questions, and sharing your thoughts. Learning is a collaborative effort, and I’m here to support you every step of the way. Just as you are learning, so am I; together, we can create a positive and enriching experience. Let’s engage, explore, and learn from each other!