Labour Economics

Labour Economics

専門教育科目

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国際商経学部

2年

KCCBG2MCA1

2単位

講義 (Lecture)

2026年度後期

(Fall semester)

横山 由紀子

School of Economics and Management

英語

目標1／目標5／目標8

9:00-10:30, Friday (with an Appointment)
Research Building I, 202

Email address is posted on UNIPA.

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Objective:
Students learn the principles of labour economics and broaden their knowledge about the labour market in the real world.

Targets:
Students will be able to explain regarding the concepts of labor economics, acquire their own insights of the labour market and discuss them with other students.

Subtitle:
A course to acquire your own insights of the labour market and discuss them with other students. 

Keywords:
labour market, human resourse, income, discrimination, decision-making
 

This course provides students with an introduction to labour economics. Students are required to participate in discussion proactively. Students develop critical thinking skills and diverse perspectives through discussion.

【Flow of the class】
1. Learning introductory labor economics theory by reading the handout materials
2. Discussing the content of a TED talk related to the labor market
　(1) Group Discussion
　(2) One-minute presentations as groups
　(3) Discussion in the whole class
※ Everyone needs to speak up in the class discussion as well as in groups!!

【Contents】
1. Introduction to labour economics
2. Labour supply
3. Labour demand
4. Labour market equilibrium
5. Mid-term exam
6. Human capital
7. The wage structure
8. Discussion and Presentation
9. Labour mobility
10. Labour market discrimination
11. Incentive pay
12. Mid-term exam 2
13. Unemployment
14. Labour market in Japan
15. Discussion and Presentation

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

<Limited permission for use>
When using generative AI, please pay attention to the contents described in “Guidelines on the Use of Generative AI in Education at the University of Hyogo (For Students)”.
In this course, the use of generative AI is permitted only within the following scope, and use beyond this scope is prohibited. Students must follow the instructions of the instructor regarding the use of generative AI. If it is found that generative AI has been used beyond the scope approved by the instructor, credits may not be granted or may be revoked. It is important to verify factual accuracy and check/add sources and references for any content generated by AI. Submitting AI-generated output directly as assignments or reports is strictly prohibited.
<Permitted Scope>
Summarizing lecture materials, drafting assignments/reports, translation and proofreading of documents

Supplementary materials are provided in class.

Borjas, G. (2019) Labor Economics, eighth edition, McGraw-Hill Education.

(preparation)
watching TED talks and writing passages about them, 20h
preparation for presentations, 10h
(review)
ｗriting a passages about what you learned in each class and your evaluation of your performance, 30h

discussion, presentation

Students will be graded according to the achievement of the lecture objectives and targets.
Credits will be given if graded S (90-), A(80-89), B(70-79), or C(60-69).

Grading criteria:
Class discussions and comments (including PREPARATION and FEEDBCK for each class): 70%
Mid-term exam : 10%
Final report: 20%

Assignment & presentation: General feedback for the entire class will be provided in the classroom.
Report: General feedback for the entire class will be posted on UNIPA.

(1) Class rules are very strict, so attendance at the first class is strongly recommended. The optimal class size is 35 students.
(2) Students who miss class twice without prior notification will not receive credits.
(3) All students must share their thoughts using the microphone during whole-class discussions. Students who do not speak up during the whole-class discussion will be considered absent.
(4) Students must submit two assignments each week: one for preparation and one for review. The total word count for both assignments is at least 400 words per week.

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