シラバス情報

授業科目名
Thesis Seminar II
(英語名)
Thesis Seminar II
科目区分
専門教育科目
Major course
対象学生
国際商経学部
学年
4年
ナンバリングコード
KCCBG4MCA3
単位数
2.00単位
ナンバリングコードは授業科目を管理する部局、学科、教養専門の別を表します。詳細は右上の?から別途マニュアルをダウンロードしてご確認ください。
授業の形態
演習 (Seminar)
開講時期
2025年度後期
(Fall semester)
担当教員
Bishnu Kumar Adhikary
所属
School of Economics and Management
授業での使用言語
英語
None
関連するSDGs目標
目標1/目標2/目標3/目標4
オフィスアワー・場所
10:00-17:00
Room A317 (Research Building 1)
School of Economics and Management

連絡先
By appointment (adhikarykobejp@gmail.com)

対応するディプロマ・ポリシー(DP)・教職課程の学修目標
二重丸は最も関連するDP番号を、丸は関連するDPを示します。
学部DP
1◎/3◎/4◎
研究科DP
1◎/2◎/3◎
全学DP
1-1◎/1-2◎/2-1◎
教職課程の学修目標
目標1:磨き続ける力/目標3:協働する力/ー

講義目的・到達目標
This course is a continuation of Thesis Seminar I. This course is designed to acquaint the students with the necessary theoretical and quantitative skills and knowledge required to develop and address a research problem. The students will develop critical core competencies and skills needed to carry out enquires such as finding a research gap and defining research questions and research objectives, reviewing existing literature and outlining hypotheses, designing research methods that incorporate secondary and primary data collection techniques, sampling and analysis methods, and effective reporting of results. A practical demonstration of time series, cross-sectional, and panel data analysis using E-views and Stata will be given.
授業のサブタイトル・キーワード
Data, Research methods, time series, panel, econometric models, Stata
講義内容・授業計画
1: Research definition, types, and finding an exciting topic (research gap).
2: Research questions, objectives, and value addition.
3: Scientific literature review and justification of research questions with hypotheses.
4: Identifying variables and constructs- preparing a conceptual model
5: Quantitative versus qualitative approach
6: Sampling and data collections- primary versus secondary sources of data
7: Econometric modeling
8: Assignment presentation by students
9: Qualitative research- questionnaire design, interview, and content analysis
10: Quantitative researchtime series analysis with advanced models
11: Quantitative researchcross-section analysis with clustering
12: Quantitative research- panel analysis with Fixed effect models and GMM
13: Use of ARDL model in Stata
14:  Assignment presentation by students
15: Final paper.      
教科書
Introductory Econometrics, 7e, 2019, Jeffrey M. Wooldridge, 826 pages, South-Western Pub, ISBN: 978-1337558860
Basic Econometrics, 5e, Damodar N. Gujarati, and Dawn C. Porter, 2008, McGraw Hill Education, ISBN: 978-0073375779
参考文献
Zikmund, Babin, Carr, and Griffin (2013). Business Research Methods, Ninth Edition, South-Western Publishing, ISBN: 978-1-111-82694-9
Using Econometrics- A Practical Guide, 7e, A H. Studenmund, Pearson, 2016. ISBN: 978-0134182742
事前・事後学習(予習・復習)の内容・時間の目安
This is a preparatory course in business research. The primary objectives of this course are to make the students understand the research process and enable them to carry out a research problem individually in a systematic manner. Students must attend every class on time and actively participate in classroom discussions. The instructor will supply all necessary reading materials and PowerPoints. Students must study for 4 hours weekly to do well on the exam. Students should spend at least 60 hours outside the classroom to achieve good grades in this course.
アクティブ・ラーニングの内容
Teaching methods are mainly based on lectures and practical demonstrations using E-views and Stata. Powerpoint slides will be given to the students before delivering each lecture so that they can make the necessary preparations for the forthcoming classes. The instructor will first discuss the concepts and rationales behind each topic to increase the students' theoretical knowledge. Then, the instructor will solve several problems in the class with the help of statistical software. Afterward, students must solve prescribed exercises and problems at home and discuss their solutions in class. Then, the instructor will address all critical issues so that the students can rectify their mistakes.
成績評価の基準・方法
Class contributions 20%
Presentation and assignment 30%
Final paper 50%
課題・試験結果の開示方法
In the classroom
履修上の注意・履修要件
Must have strong motivation to carry out research
実践的教育
備考
This a course for advanced research
英語版と日本語版との間に内容の相違が生じた場合は、日本語版を優先するものとします。