Econometrics

Econometrics

専門教育科目

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国際商経学部

2年

KCCBG2MCA7

2単位

講義・演習 (Lecture/Seminar)

2026年度前期

(Spring semester)

Jean-Baptiste M.B. SANFO

国際商経学部

日本語

目標9

Before or after class, in the classroom.

Office: Research Building I Room A 204

sanfo@em.u-hyogo.ac.jp

1◎／2〇／3〇

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【Course Objectives】

This course provides an introduction to basic econometric methods used in applied economic analysis. Students will learn how to use data to estimate and interpret empirical models. The course combines theoretical foundations with hands-on applications using the R programming language and real-world datasets, enabling students to develop practical skills for empirical research and evidence-based policy analysis.

【Learning Outcomes】

By the end of this course, students will be able to:

1. Demonstrate understanding of the foundations of econometrics.
2. Apply econometric methods to real-world economic data.
3. Conduct hypothesis tests and interpret the results.
4. Utilize R software to analyze data.
5. Critically evaluate and interpret empirical research results

Ordinary least square, hypothesis testing, causality, policy analysis

【Course Overview】

This course provides an introduction to basic econometric methods used in applied economic analysis. Students will learn how to use data to estimate and interpret empirical models, with an emphasis on understanding assumptions, results, and limitations. The course combines theoretical foundations with hands-on applications using real-world data and the R programming language, and it will enable students to develop practical skills for empirical research and evidence-based policy analysis. Topics are introduced theoretically and then applied using real-world data in R, followed by an interpretation of the results.

【Schedule】

Lecture 1: Guidance and Review of Basic Statistical Concepts
Lectures 2 - 3: The 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 evaluation
Lecture 8-9: Regression Analysis with Binary or Dummy variables
Lectures 10-11:   Regression Analysis with Pooled Cross sections Data
Lectures 12 - 13:  Regression Analysis with Panel Data
Lectures 14- 15:   Basic Regression Analysis with Time Series Data

Final evaluation

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

ハイブリッド（対面）

Each topic is first introduced theoretically to ensure a solid understanding of fundamental concepts and terminology. Students then apply these concepts using real-world data by estimating models in R, followed by interpretation and discussion of the results.

For sessions conducted remotely, students must have the necessary equipment and internet access (e.g., a computer and a stable Wi-Fi connection) to attend classes from home or other locations. Sessions to be conducted remotely will be determined and communicated after course registration.

利用する場面を限定し許可

Students are required to comply with the University of Hyogo's policy regarding the use of generative AI tools. Generative AI may be used as a supplementary aid for learning activities such as drafting reports or conducting preliminary research, provided that students critically assess the content produced. Students are responsible for verifying the accuracy of all information, properly acknowledging sources and references, and ensuring that submitted work reflects their own understanding and independent effort. Assignments generated primarily by generative AI, or submitted without appropriate revision and original contribution, are not permitted.

If inappropriate use of generative AI is identified, the assignment may receive no credit or other academic measures may be taken in accordance with university regulations.

Introductory Econometrics: A Modern Approach, by Jeffrey M. Wooldridge

Basic Econometrics, by Damodar N.Gujarati

Introduction to Econometrics with R by Christoph Hanck, Martin Arnold, Alexander Gerber, and Martin Schmelzer
https://www.econometrics-with-r.org/

H. Stock & M. M. Watson Introduction to Econometrics 4th ed. Pearson

Econometrics for Business Analytics by Jose Fernandez
https://bookdown.org/cuborican/RE_STAT/

【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.

Engagement in classroom activities (20%)
Assignments (20%)  
Mid-term Evaluation (30%)
Final evaluation (30%)

In the classroom

The maximum number of students is 60. If the number of applicants exceeds 60, students will be selected by lottery. Students who wish to take the course must register for the lottery via the Universal Passport. After the lottery results have been announced, please register for the winning course on your own.

While not required, prior completion of a statistics class (e.g., Introductory Statistics for Economics) is strongly recommended to ensure familiarity with key statistical concepts used in this course.

Regular attendance is required. Students are expected to attend ALL sessions. Absences must be supported by official documentation (e.g., medical or official administrative reasons).

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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!