学部・大学院区分
Undergraduate / Graduate
経済学部
時間割コード
Registration Code
0401250
科目区分
Course Category
経済学科専門科目
科目名 【日本語】
Course Title
労働経済特論
科目名 【英語】
Course Title
Advanced Course of Labor Economics
コースナンバリングコード
Course Numbering Code
担当教員 【日本語】
Instructor
工藤 教孝 ○
担当教員 【英語】
Instructor
KUDOH Noritaka ○
担当教員所属【日本語】
instructor's belongs
大学院経済学研究科
担当教員所属【英語】
instructor's belongs
Graduate School of Economics
単位数
Credits
2
配当年次
dividend Yearly
3年
3
開講期・開講時間帯
Term / Day / Period
春 木曜日 3時限
Spring Thu 3
対象学年(非表示)
Year
授業形態
Course style
講義
Lecture


授業の目的 【日本語】
Goals of the Course(JPN)
This course is designed to build your research ability in the field of macro-labor economics. This course focuses on the long-run labor market issues such as (1) technological progress and unemployment; and (2) wage inequality. The goal is to catch up with the frontier of research on the aggregate labor market.
授業の目的 【英語】
Goals of the Course
This course is designed to build your research ability in the field of macro-labor economics. This course focuses on the long-run labor market issues such as (1) technological progress and unemployment; and (2) wage inequality. The goal is to catch up with the frontier of research on the aggregate labor market.
到達目標 【日本語】
Objectives of the Course(JPN)
After this course, students should be able to (1) understand the frontier of research in the field of growth and inequality; (2) write their own computer codes to replicate existing quantitative results found in professional articles; and (3) design their own research.
授業の内容や構成
Course Content / Plan
1 Overview: Job Search and Optimal Stopping
2 Trade in the Labor Market
3 Job Creation + Maxima
4 Workers + Python
5 Wage Determination
6 Steady-State Equilibrium
7 Numerical Analysis
8 Technological Progress
9 Job Destruction
10 Match-Specific Productivity Dispersion
11 Heterogeneous Jobs
12 Labor Share
13 Heterogeneous Firms
14 Sorting
履修条件・関連する科目
Course Prerequisites and Related Courses
「労働経済」の履修が望ましいが、 未履修でも受講可能。
講義は英語で行います(All lectures will be given in English)。
成績評価の方法と基準
Course Evaluation Method and Criteria
There will be 5 or more assignments, in which students are asked to replicate some results from leading research papers. Many assignments require Python or Maxima. The course grade will be determined by the average of the grades of all assignments. To pass the course, you must earn C (which is about 60 out of 100) or above for each assignment.
教科書・参考書
Textbook/Reference Book
指定なし。学習に必要な論文等をTACTで配布します(All mandatory reading material (professional articles in leading journals) will be distributed at TACT)。
課外学習等(授業時間外学習の指示)
Study Load(Self-directed Learning Outside Course Hours)
Students need to install some (free) computational packages such as Python and Maxima in your computer and learn the languages.
注意事項
Notice for Students
学習内容は大学院2年生向けに設計されており、皆さんにとっては「かなりやりがいのある」内容となりますので、十分な熱意と学習時間の確保が求められます。他方、評価は大学院生とは別の基準で行いますので過度な心配は不要です。課題の大半がコンピューターを用いたシミュレーションになります。
授業開講形態等
Lecture format, etc.
対面授業科目(原則として対面のみ)
遠隔授業(オンデマンド型)で行う場合の追加措置
Additional measures for remote class (on-demand class)
質問への対応方法
Office hour
講義終了後に対面で、またはTACTにて。