Understanding North Korea's Economic System and Transition (in Korean)
This course provides an in-depth examination of the contemporary North Korean economy, focusing on its unique economic system and challenges associated with transition economics. Given the scarcity of reliable information and credible macroeconomic data, the course offers a comprehensive and systematic analysis of the subject matter, structured into three distinct modules: (1) theoretical foundations, which explore socialist economic systems from a broad perspective; (2) characteristics of the North Korean economy, delving into key features and implications; and (3) transition dynamics and economic integration, investigating potential economic integration between North and South Korea. Suitable for students from diverse academic backgrounds, no prior expertise in North Korean studies or economics is necessary, although foundational understanding of these fields may prove advantageous in comprehending complex concepts presented throughout the course.
Economic Development (in English)
This course explores why some countries achieve sustained economic growth while others remain stagnant. It examines how capital accumulation, education, and demographic factors contribute to income differences, how technological progress and institutional efficiency drive productivity, and how political, cultural, and geographical factors shape long-term development. A key focus is South Korea, a striking example of rapid economic transformation, where investment in human capital, industrialization, and export-driven policies enabled a transition from poverty to prosperity within a generation. By integrating theory with real-world cases, including Korea’s growth and contemporary challenges like geopolitical risks and global trade tensions, this course provides a comprehensive understanding of economic development.
Statistics for Economics (in English)
This course offers an introduction to statistics, focusing on the essential skill of extracting information from data, which is crucial in everyday life and various academic disciplines. The objective is for students to develop an intuitive understanding of statistical concepts and reasoning, enabling them to apply elementary techniques and critically assess others' statistical work. Topics include descriptive and inferential statistics, with course learning outcomes consisting of organizing and analyzing data using descriptive statistics (histogram, mean, median, mode, and standard deviation), understanding probability theory, and applying hypothesis tests to means, proportions, and variances. The course delivery method includes 3 hours of weekly lectures, supplemented by lab sessions that provide hands-on experience with Microsoft Excel for assignments. By the end of the course, students will be better equipped to handle advanced courses requiring data analysis skills.
Econometrics 2 (in English)
This course serves as an application-focused extension to the core econometrics courses, concentrating on the empirical applications of econometrics and the use of the statistical software STATA. Students will develop an understanding of econometric models, learning to estimate and test economic relationships using real datasets and an econometric software package. The course also explores the emerging field of deep learning, expanding the types of data that can be analyzed, such as images and text. Google COLAB will be utilized for practicing deep learning programs. Upon successful completion of the course, students will be able to interpret statistical results, conduct appropriate data analysis, understand the basics of neural network operations, and implement deep learning programs for natural language processing. The course comprises 3 hours of weekly lectures and lab sessions, during which students will work in small groups on STATA and COLAB assignments and research projects. Active participation in lab sessions is crucial for success in the course.