Research Seminar 1

Research Seminar 1

専門教育科目

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国際商経学部

2年

KCCBG2MCA3

2.00単位

演習 (Seminar)

2026年度後期

(Fall semester)

鎌田　伊佐生

School of Economics and Management

英語

該当なし

By appointment.

kamata@em.u-hyogo.ac.jp

1◎／3◎／4◎

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【Course Objectives】
A series of my Research Seminar courses focuses on empirical analyses of topics/issues in international trade (including foreign direct investment, multinational enterprises, and so on) through which students develop the analytical foundation for graduation research to be performed through Thesis Seminars I & II. In this particular course of Research Seminar I, students learn how to identify data in need, how to use/utilize the data for an analysis properly, and how to present the result of the analysis effectively.

【Learning Outcome】
By the end of this course, students are expected to be able to:
- be able to locate proper data and databases for empirical analyses of topics in international trade;
- understand and explain the characteristics (including advantages and disadvantages) of the located data(bases);
- perform a basic analysis of an intended topic or selected issue; and
- make an effective oral and written presentation of the result of the analysis.

【Keywords】 Empirical research on international trade, Data for economic analyses

In the first section of the course, students search and identify data on designated subjects, and make presentations to explain to the class the features of the data including their advantages and disadvantages. In the second (and relatively brief) section, the students propose topics of their own data analyses to the class, and refine them through in-class discussions. In the third section, the students perform the analyses using the data identified in the first section and present the results to the class.
Classes should be led primarily by students’ activities (i.e., presentations and discussions), and the instructor will join the classes as the facilitator and coach.

 1. Introduction to the seminar: guidance and housekeeping
 2. Finding and understanding data (1): International trade
 3. Finding and understanding data (2): Trade policy (tariffs, trade agreements, etc.)
 4. Finding and understanding data (3): Foreign direct investment (FDI)
 5. Finding and understanding data (4): Multinational activities of firms
 6. Finding and understanding data (5): Other general & international economic indicators
 7. Midterm roundup and reflection
 8. Proposing (and reconsidering) the topic of an analysis (1)
 9. Proposing (and reconsidering) the topic of an analysis (2)
10. Presenting the result of the analysis (1)
11. Presenting the result of the analysis (2)
12. Presenting the result of the analysis (3)
13. Presenting the result of the analysis (4)
14. Presenting the result of the analysis (5)
15. Course wrapping-up and preliminary guidance to Research Seminar II

対面

・In-person classes only.
・Not subject to the cap on distance-education credits.

利用する場面を限定し許可

In this course, the use of generative AI is permitted only as an assistant for searching databases and/or for improving English wording or polishing English sentences in presentation materials. If the submitted contents of any assigned work is found to be generated by AI, the assignment will receive a score of zero.  
When using generative AI, students must comply with the “Guidelines on the Use of Generative AI in Education at the University of Hyogo (For Students).”

Required readings and materials will be provided by the instructor as needed.

van Marrewijk, Charles (2017), International Trade, Oxford University Press
(ISBN: 9780198753759).
Feenstra, Robert C., and Alan M. Taylor (2021), International Trade (5th edition), Worth Publishers / Macmillan (ISBN: 9781319382865).
Other recommended readings and resources will be introduced as needed.

・Pre-learning/preparation: Class preparation involves preparation for presentations that include the corresponding assignments of data identification, topic proposals, and data analyses (8 hours/week on average).
・Post-learning/review: Class review involves (re-)organizing the information on identified data and datasets, reexamining the topics of analyses, and improving data analyses (4 hours/week on average).

Students are required to search and find data & databases in need, perform basic data analyses, and make in-class presentations on those assignments.
Students are also expected to be actively involved in every class discussion.

The course evaluation (grades) will be based on the following criteria (and weights):
  - Quality of presentations* (70%)
    (* Presentations involve corresponding assignments such as data identification and data analyses.)
  - Engagement in class activities including comments to and discussions on in-class presentations (30%)
Grades are assigned as follows: S (90 points or higher), A (80 points or higher), B (70 points or higher), and C (60 points or higher).

Feedback on students’ presentations and corresponding work will be given in class and/or individually.

・Basic knowledge of international economics and statistics/econometrics should help you in working on the assignments.
・Students need to come to the classroom on time and participate for the entire class period every time.
・Students are required to search and find data & databases in need, perform basic data analyses, and make in-class presentations on those assignments—“Homework every week” virtually.
・Students are also expected to be actively involved in every class discussion.
・Students are encouraged to come to see the instructor to obtain advice on the assignments.

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