学部・大学院区分		開・博前

時間割コード		306060a

科目区分		演習 Seminars

科目名　【日本語】		経済開発政策・マネジメント演習Ⅰa

科目名　【英語】		Seminar on Economic Development Policy and Management Ia

コースナンバリングコード

担当教員　【日本語】		MENDEZ GUERRA Carlos albe ○

担当教員　【英語】		MENDEZ GUERRA Carlos alberto ○

単位数		1

開講期・開講時間帯		春金曜日３時限 Spring Fri 3

授業形態

授業の目的　【日本語】

授業の目的　【英語】

In this research seminar, we will exploit the integration of econometrics, data science and machine learning methods to understand and inform the process of economic growth and development of countries, regions, industries, and firms. In particular, our research agenda includes topics such as:

(1) Regional inequality and convergence dynamics beyond GDP
(2) Economic growth and structural change
(3) Firm productivity dynamics and resource misallocation

Students are constantly encouraged to develop further scientific skills and research ideas through the usage of the statistical programming language R and the application of recent developments from the fields of data science and econometrics.

By the end of the seminar, students are expected to develop an understanding and application of the following quantitative research methodologies:

Time series and panel data econometrics
(2) Nonparametric econometrics
(3) Spatial econometrics
(4) Bayesian econometrics
(5) Machine learning econometrics

到達目標　【日本語】

到達目標　【英語】

授業の内容や構成

Structure of the Course / Schedule授業の構成・計画
The seminar schedule is discussed and decided at the start of each semester. To keep our research efforts focused, students are expected to present their research ideas and progress in the context of any of the following topics:
Regional inequality, convergence beyond GDP, and spatial data science
Structural change, economic growth, and industrial productivity dynamics
Firm productivity dynamics and performance: parametric methods, nonparametric methods and stochastic frontier methods
Quantitative decompositions and counterfactual simulations in economic growth and development
Growth and development econometrics 1: Bayesian model averaging and lasso regressions
Growth and development econometrics 2: Synthetic control and interrupted time series
Growth and development econometrics 3: Nonparametric and spatial approaches
Growth and development econometrics 4: Time series and new panel data approaches

履修条件・関連する科目

There is no precondition to take this course

成績評価の方法と基準

Presentations of research papers (40%) and results research progress (60%) are comprehensively evaluated. To receive credit for this course, students are expected to achieve an overall evaluation equal or superior to C- or C (where applicable).

教科書・参考書

This seminar has its own public website at , which includes a series of open learning resources, news for potential seminar members, and summaries of our research outputs.
For internal communication, coordination, and access to protected learning resources, we use the following website: (access credentials will be issued in the first week of each semester)

課外学習等（授業時間外学習の指示）

注意事項

使用言語

English.
To contact the instructor:

授業開講形態等

遠隔授業（オンデマンド型）で行う場合の追加措置