For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| ECO3032 | Economics of Education | 3 | 6 | Major | Bachelor | 3-4 | English | Yes | |
| The purpose of this course is to provide an overview of the Economics of Education, reading through main academic papers in economics that have influenced academic thought on key aspects of education. This course will use economic theory, empirical analysis to examine current issues in Korean education. Some of the topics we will cover include an analysis of how people choose their investments in education (human capital theory); how to empirically distinguish the return to education from the return to natural ability; how education and earnings are related in a single person's lifetime; the role of early childhood education; private tutoring; school choice; school bullying; educational inequality; and the issues in higher education. Students will learn econometric methods to analyze micro-level data and will be encouraged to conduct an empirical analysis using Stata. | |||||||||
| ECO3033 | Health Economics | 3 | 6 | Major | Bachelor | 3-4 | - | No | |
| This course is designed to help student understand how basic economic concepts, principles, and theories can be applied to various health care issues including the production and cost of health care, health insurance theory, pharmaceuticals, cost effectiveness analysis, role of government in the health economy, and national health insurance and reform. Instead of focusing on a few current health care problems such as cost and quality of healthcare, attention is directed toward any health related topics. A set of tools including economic theories and methodologies are provided to students to evaluate a theoretical or empirical argument relating to health care and medical industry. | |||||||||
| ECO3034 | Financial Derivatives | 3 | 6 | Major | Bachelor | 4 | Korean | Yes | |
| This advanced course is designed to introduce students majoring economics to the theoretical and practical aspects of futures, options, and other derivatives. Through this course, the students can expand your knowledge and understanding of the financial derivatives and understand their use in investment decision including hedging, speculating, and arbitrage trading and in corporate financial management. The course also provides theoretical and practical methodologies for pricing futures and options. For the option pricing and valuation, basic stochastic processes and stochastic calculus are covered in this course. Examples of topics in the stochastic processes and calculus are Wiener process, Brownian motion, Ito’s Lemma, Black-Sholes process, and Jump processes. The financial markets for the versatile derivatives assets have grown enormously and have generated a profusion of innovative products and ideas, not to mention periodic financial crises. The financial derivatives assets have become one of the most important tools of modern finance, from both the academic and the practical standpoint. However, the subject matter requires relatively greater use of quantitative methods and theoretical reasoning than many other courses, and most students will find it quite challenging. To participate in this class, all students should already understand the basic concepts of mathematics, statistics, and financial economics. | |||||||||
| ECO3036 | Financial Economics | 3 | 6 | Major | Bachelor | 2-3 | English | Yes | |
| This intermediate course develops basic principles of financial management and investment theory. This course is designed for the 2nd-year and 3rd-year students in the department of Global Economics. This course is provided in the spring semester. This course provides a rigorous introduction to the fundamentals of modern financial analysis and applications to business challenges in valuation, risk analysis, corporate investment decisions, and basic security analysis and investment management. This course also deals with the topics related to financial markets and basic concepts of asset pricing such as; the tradeoff between risk and return, efficient diversification, portfolio management, market efficiency, asset pricing models (CAPM; capital asset pricing models, and APT; arbitrage pricing theory), market microstructure, and behavioral finance. During the first half of the semester, we cover the financial management issues. For example, this course helps students to 1) develop an understanding of the tools that are used to value investment projects and companies (Valuation issues), 2) understand the basic issues involved in how firms should raise funds for their real investments (Financing issues), and 3) evaluate how investment and financing decisions are related. During the last half of the semester, we cover the investment theories. For example, we aim at developing key concepts in investment theory from the perspective of a portfolio manager rather than an individ | |||||||||
| ECO3037 | Asset Pricing | 3 | 6 | Major | Bachelor | 3-4 | English | Yes | |
| Asset pricing theory explains the prices or values of claims to uncertain payments. We need to consider the time and the risk of its payments to value an asset. There are two major pricing theories - arbitrage pricing and equilibrium pricing theories - that are complements rather than substitutes. Arbitrage pricing theory is useful for pricing contingent claims, i.e., financial claims whose cash flows depend on other traded securities. One classic example of this approach is Black-Scholes option pricing model. On the other hand, equilibrium pricing theory is useful for pricing the primary traded securities. This theory is common in academic settings, where we explain why prices are what they are, or how prices might change if policy or economic structure changed. An example of this approach is the CAPM. The course is structured as follows. We start with some basic backgrounds of finance, and then explain the conventional CAPM, followed by various concepts of risk measures. Probably one of the most interesting topics developed since early 1980s is behavioural finance. We discuss this in the framework of market efficiency and empirical results that report anomalies. Basic option pric | |||||||||
| ECO3038 | Economics Co-op 1 | 2 | 4 | Major | Bachelor | - | No | ||
| Students taking this course will participate in an internship provided by a pre-approved institution. By doing so, they can enhance their capabilities of applying economics theories and knowledge learned in classrooms. | |||||||||
| ECO3039 | Economics Co-op 2 | 3 | 6 | Major | Bachelor | - | No | ||
| Students taking this course will participate in an internship provided by a pre-approved institution. By doing so, they can enhance their capabilities of applying economics theories and knowledge learned in classrooms. | |||||||||
| ECO3040 | Economics Individual Research 1 | 2 | 4 | Major | Bachelor | - | No | ||
| This is an independent study course for students who have finished an excellent accomplishment of the course requirements. Students will design and study their own research works under guidance of a tutor. | |||||||||
| ECO3041 | Economics Individual Research 2 | 2 | 4 | Major | Bachelor | - | No | ||
| This is an independent study course for students who have finished an excellent accomplishment of the course requirements. Students will design and study their own research works under guidance of a tutor. | |||||||||
| ECO3042 | Quantitative Analysis using Big Healthcare Data | 3 | 6 | Major | Bachelor | 3-4 | - | No | |
| This course covers modern methods for the analysis related to data. Topics include an introduction to the analysis of longitudinal data, response profiles, fitting parametric curves, covariance pattern models, random effects and growth curve models, generalized linear models for longitudinal data. | |||||||||
| ECO3043 | Machine Learning and Forecasting of Economic Financial Time Series | 3 | 6 | Major | Bachelor | 3-4 | Korean | Yes | |
| This course will cover the statistical and econometric techniques needed to conduct forecasting of macroeconomic time series or financial time series, including forecasting procedures, forecast evaluation methods, and useful machine learning methods. In particular, the course will consider various machine learning methods such as shrinkage methods, factor models, tree-based methods such as random forests, neural networks, etc. On completing this course the students will understand the central technical issues in forecasting of economic/financial time series and recent machine learning methods. They will be comfortable with the use of standard econometric software such as R to undertake their own research. | |||||||||
| ECO3044 | Economic Numerical Analysis | 3 | 6 | Major | Bachelor | Korean | Yes | ||
| Scientific and numerical computing is a booming fields in Economics. The revolution in the computer industry over the last several decades has provided new and powerful tools for computational practitioners. Computing is an interdisciplinary activity that requires experience and expertise in both theoretical and practical subject in Economics. A student understanding of mathematics and scientific thinking is a fundamental requirement for effective computational work. Equally important is solid training in computer programming. This course is to bridge these two subjects by introducing how scientific computing can be done using the Python programming language and the computing environment that has appeared around this language. The students will be equipped with basic training in mathematics and numerical methods and basic knowledge about Python program for Economics. | |||||||||
| ECO3045 | Data Science for Labor Economics | 3 | 6 | Major | Bachelor | - | No | ||
| This course aims to deliver how to analyze various types of data, including big data, focusing on the labor market and education-related issues. In this course, students will apply their analytic skills acquired in class to various real-world cases. This course covers data collection, processing, and analysis methods that are widely used throughout social science, especially in economics. Students will learn how to use programming languages such as R and Python and statistical packages specialized in data analysis such as Stata. This course helps students to understand empirical research conducted in labor economics while conducting empirical exercises on various cases focusing on the labor market and education-related issues. | |||||||||
| ECO3046 | Data Science for Industrial Economics | 3 | 6 | Major | Bachelor | 3-4 | Korean | Yes | |
| This course is designed to provide solid understanding of the issues and tools for empirical analyses in Industrial Economics (or Industrial Organization), covering various topics including consumer choices, firms’ decisions/strategies (e.g. pricing, advertising, entry/exti), and antitrust policies. The goal is to study widely used methodologies of econometrics including linear regressions, discrete choice models, panel data analyses, DID, and event studies and to facillitate hand-on experiences of analyzing economic data of real world exaples. To this end, students will learn how to use a programming language and a statistical package such as Python and STATA. | |||||||||
| ECO3047 | Econometric Analysis Using Big Data | 3 | 6 | Major | Bachelor | 3-4 | Korean | Yes | |
| This lecture will introduce the econometric analysis using big data. The course consists of three parts: i) review of econometric methods for traditional form of data, ii) statistical and econometric techniques for big data in economics, iii) applications of traditional econometric methods and big data methods to actual economic problems. On completing this course, the students will understand the central technical issues in the econometric analysis using big data. They will be comfortable with the use of the econometric software R (or others) to undertake their own research. | |||||||||