G8269200 International Economics

Hiroshima University Syllabus

Japanese

Academic Year 2024Year School/Graduate School School of Economics Economics Evening Course

Lecture Code G8269200 Subject Classification Specialized Education

Subject Name 国際経済学

Subject Name
（Katakana）コクサイケイザイガク

Subject Name in
English International Economics

Instructor YASUTAKE KOUICHI

Instructor
(Katakana) ヤスタケ　コウイチ

Campus Higashi-Senda Semester/Term 2nd-Year,  First Semester,  First Semester

Days, Periods, and Classrooms (1st) Weds13-14：Higashi-Senda Group Work Rm

Lesson Style Lecture Lesson Style
(More Details) 　

The class will be a mix of lectures, exercises, discussions, and student presentations.The class may be conducted online due to the teacher's travel, but this will be announced in advance.

Credits 2.0 Class Hours/Week 　 Language of Instruction J : Japanese

Course Level 2 : Undergraduate Low-Intermediate

Course Area（Area） 24 : Social Sciences

Course Area（Discipline） 03 : Economics

Eligible Students

Keywords Earth observation satellite data, remote sensing, economic growth, economic development, international comparison

Special Subject for Teacher Education 　 Special Subject 　

Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students)
Criterion referenced
Evaluation
(Applicable only to targeted subjects for undergraduate students) Economics and Management
（Knowledge and Understanding）
・Basic knowledge of economic analysis

Class Objectives
/Class Outline This course covers the rudiments of new social science analysis oriented toward data science. Specifically, students will learn about new economic analysis that is currently attracting attention using Earth observation satellite data such as Google Earth Engine. The course will include economic growth analysis (international comparison) using remote sensing data such as nighttime light data. The contents of this course are as follows.

- Learn about completely new economic analysis based on a data science approach.
- Students will be able to master basic Unix operations and become more familiar with computers through hands-on data analysis and management (no prior knowledge or skills are required).
- Students will learn the basics of academic writing by writing a group report on the forecasting of economic variables.

Class Schedule lesson1 Introduction (how to proceed this class, new social science using alternative data such as earth satellite data, grading)
lesson2 Practical Use of Earth Observation Satellite Data (Part 1)
lesson3 Practical Use of Earth Observation Satellite Data (Part 2)
lesson4 Google Earth Engine Basic Training (Part 1)
lesson5 Google Earth Engine Basic Training (Part 2)
lesson6 Google Earth Engine Basic Training (Part 3)
lesson7  Google Earth Engine Application Lab 1 (Let's do an international comparative analysis of the impact of Covid-19 on economic activity! (Report and Presentation Slide Preparation Part 1)
lesson8 lesson7  Google Earth Engine Application Lab 1 (Let's do an international comparative analysis of the impact of Covid-19 on economic activity! (Report and Presentation Slide Preparation Part 2)
lesson9 Google Earth Engine Application Lab 3 (International Comparative Analysis of the Impact of Covid-19 on Economic Activity) Presentations by Groups
lesson10 Google Earth Engine Application Lab 4 (International Comparative Analysis of Economic Development Using Night Light Data (Report and Presentation Slide Preparation Part 1))
lesson11 lesson10 Google Earth Engine Application Lab 4 (International Comparative Analysis of Economic Development Using Night Light Data (Report and Presentation Slide Preparation Part 2))
lesson12 Presentation on Google Earth Engine Application Lab 6 (International Comparative Analysis of Economic Development Using Night Light Data)
lesson13 Google Earth Engine Application Lab 7 (International Comparative Analysis of Economic Development Using Nighttime Light Data (Report and Presentation Slide Preparation Part 1))
lesson14 lesson13 Google Earth Engine Application Lab 7 (International Comparative Analysis of Economic Development Using Nighttime Light Data (Report and Presentation Slide Preparation Part 2))
lesson15  Presentation on Google Earth Engine Application Lab 6 (International Comparative Analysis of Economic Development Using Night Light Data)

In-class assignment reports will be written in groups. Final reports will be written by each student individually.

No basic knowledge of programming languages or Unix is required. Even if you are a true beginner, we will guide you responsibly. Please do not worry. In addition to the final final report, we plan to make reports in groups. We will guide you on how to prepare group reports in class, so please do not worry about this point as well.

Text/Reference
Books,etc. As this is a very new field, textbooks and references are basically those available on the web, such as those published on GitHub (there are few references published in Japanese).

PC or AV used in
Class,etc. 　

(More Details) We will also actively use ChatGPT for class activities. Please bring your own laptop computer (notebook computer) to each class. Students are not allowed to use only a smart phone.

Learning techniques to be incorporated 　

Suggestions on
Preparation and
Review No basic knowledge of computers or finance is assumed. Don't worry, even if you don't know how to manipulate a Windows file! Don't worry. If you do your homework in class, or if you do your homework before and after class, you will make friends with computers. Come to class with a dream in mind.

Requirements No basic knowledge of programming languages or remote sensing technology is required. However, basic knowledge is not required, but please make sure you understand the basic operation of cloud services and basic computer concepts (file structure, etc.) that will be explained in the class. You will be happy. Please bring your laptop computer (Note PC) to every class. (You can't do anything with only a smartphone to begin with.)

Grading Method The level of class participation will be determined by a minute paper after class, followed by a group report to be prepared in the second half of the class, and a final report to be prepared by each individual student. Active participation in class is the way to receive a high evaluation.

Practical Experience

Summary of Practical Experience and Class Contents based on it

Message Both the style and content of the classes may be new to the students. Therefore, it is recommended to attend the first guidance session if possible. Basically, the class will revolve around group activities. Groups will be organized randomly. Students are expected to participate in the class with the dream of learning new content and the responsibility of working as a group. We expect responsible and active students to attend the class.

I will repeat this point because it is important. This is a data analysis class, so we will inevitably use computers a lot, but we do not require any current level of knowledge or skill. What is important is whether or not you have dreams and hopes for data analysis and data science. If you do, you do not need to have any knowledge of programming. I will guide you one by one with responsibility. I encourage you to take on this challenge.

Other

Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching.

Academic Year	2024Year	School/Graduate School	School of Economics Economics Evening Course
Lecture Code	G8269200	Subject Classification	Specialized Education
Subject Name	国際経済学
Subject Name （Katakana）	コクサイケイザイガク
Subject Name in English	International Economics
Instructor	YASUTAKE KOUICHI
Instructor (Katakana)	ヤスタケ　コウイチ
Campus	Higashi-Senda	Semester/Term	2nd-Year, First Semester, First Semester
Days, Periods, and Classrooms	(1st) Weds13-14：Higashi-Senda Group Work Rm
Lesson Style	Lecture	Lesson Style (More Details)
The class will be a mix of lectures, exercises, discussions, and student presentations.The class may be conducted online due to the teacher's travel, but this will be announced in advance.
Credits	2.0	Class Hours/Week		Language of Instruction	J : Japanese
Course Level	2 : Undergraduate Low-Intermediate
Course Area（Area）	24 : Social Sciences
Course Area（Discipline）	03 : Economics
Eligible Students
Keywords	Earth observation satellite data, remote sensing, economic growth, economic development, international comparison
Special Subject for Teacher Education		Special Subject
Class Status within Educational Program (Applicable only to targeted subjects for undergraduate students)
Criterion referenced Evaluation (Applicable only to targeted subjects for undergraduate students)	Economics and Management （Knowledge and Understanding）・Basic knowledge of economic analysis
Class Objectives /Class Outline	This course covers the rudiments of new social science analysis oriented toward data science. Specifically, students will learn about new economic analysis that is currently attracting attention using Earth observation satellite data such as Google Earth Engine. The course will include economic growth analysis (international comparison) using remote sensing data such as nighttime light data. The contents of this course are as follows. - Learn about completely new economic analysis based on a data science approach. - Students will be able to master basic Unix operations and become more familiar with computers through hands-on data analysis and management (no prior knowledge or skills are required). - Students will learn the basics of academic writing by writing a group report on the forecasting of economic variables.
Class Schedule	lesson1 Introduction (how to proceed this class, new social science using alternative data such as earth satellite data, grading) lesson2 Practical Use of Earth Observation Satellite Data (Part 1) lesson3 Practical Use of Earth Observation Satellite Data (Part 2) lesson4 Google Earth Engine Basic Training (Part 1) lesson5 Google Earth Engine Basic Training (Part 2) lesson6 Google Earth Engine Basic Training (Part 3) lesson7 Google Earth Engine Application Lab 1 (Let's do an international comparative analysis of the impact of Covid-19 on economic activity! (Report and Presentation Slide Preparation Part 1) lesson8 lesson7 Google Earth Engine Application Lab 1 (Let's do an international comparative analysis of the impact of Covid-19 on economic activity! (Report and Presentation Slide Preparation Part 2) lesson9 Google Earth Engine Application Lab 3 (International Comparative Analysis of the Impact of Covid-19 on Economic Activity) Presentations by Groups lesson10 Google Earth Engine Application Lab 4 (International Comparative Analysis of Economic Development Using Night Light Data (Report and Presentation Slide Preparation Part 1)) lesson11 lesson10 Google Earth Engine Application Lab 4 (International Comparative Analysis of Economic Development Using Night Light Data (Report and Presentation Slide Preparation Part 2)) lesson12 Presentation on Google Earth Engine Application Lab 6 (International Comparative Analysis of Economic Development Using Night Light Data) lesson13 Google Earth Engine Application Lab 7 (International Comparative Analysis of Economic Development Using Nighttime Light Data (Report and Presentation Slide Preparation Part 1)) lesson14 lesson13 Google Earth Engine Application Lab 7 (International Comparative Analysis of Economic Development Using Nighttime Light Data (Report and Presentation Slide Preparation Part 2)) lesson15 Presentation on Google Earth Engine Application Lab 6 (International Comparative Analysis of Economic Development Using Night Light Data) In-class assignment reports will be written in groups. Final reports will be written by each student individually. No basic knowledge of programming languages or Unix is required. Even if you are a true beginner, we will guide you responsibly. Please do not worry. In addition to the final final report, we plan to make reports in groups. We will guide you on how to prepare group reports in class, so please do not worry about this point as well.
Text/Reference Books,etc.	As this is a very new field, textbooks and references are basically those available on the web, such as those published on GitHub (there are few references published in Japanese).
PC or AV used in Class,etc.
(More Details)	We will also actively use ChatGPT for class activities. Please bring your own laptop computer (notebook computer) to each class. Students are not allowed to use only a smart phone.
Learning techniques to be incorporated
Suggestions on Preparation and Review	No basic knowledge of computers or finance is assumed. Don't worry, even if you don't know how to manipulate a Windows file! Don't worry. If you do your homework in class, or if you do your homework before and after class, you will make friends with computers. Come to class with a dream in mind.
Requirements	No basic knowledge of programming languages or remote sensing technology is required. However, basic knowledge is not required, but please make sure you understand the basic operation of cloud services and basic computer concepts (file structure, etc.) that will be explained in the class. You will be happy. Please bring your laptop computer (Note PC) to every class. (You can't do anything with only a smartphone to begin with.)
Grading Method	The level of class participation will be determined by a minute paper after class, followed by a group report to be prepared in the second half of the class, and a final report to be prepared by each individual student. Active participation in class is the way to receive a high evaluation.
Practical Experience
Summary of Practical Experience and Class Contents based on it
Message	Both the style and content of the classes may be new to the students. Therefore, it is recommended to attend the first guidance session if possible. Basically, the class will revolve around group activities. Groups will be organized randomly. Students are expected to participate in the class with the dream of learning new content and the responsibility of working as a group. We expect responsible and active students to attend the class. I will repeat this point because it is important. This is a data analysis class, so we will inevitably use computers a lot, but we do not require any current level of knowledge or skill. What is important is whether or not you have dreams and hopes for data analysis and data science. If you do, you do not need to have any knowledge of programming. I will guide you one by one with responsibility. I encourage you to take on this challenge.
Other
Please fill in the class improvement questionnaire which is carried out on all classes. Instructors will reflect on your feedback and utilize the information for improving their teaching.

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