Economics

This course focuses on multivariate linear regression model with OLS (basic notions) and multivariate linear regression model with OLS 2/2 (main issues). Topics include: assumptions, Gauss-Markov theorem, Partialling-out interpretation; endogeneity: the omitted variable problem, instrumental variables, testing endogeneity, testing overidentification restrictions; proxy variable as solution to the omitted variable problem; measurement error in dependent variable; heteroskedasticity.

This course provides students with a basic understanding of the key economic issues involved in the emerging market economies. Students learn to analyze the interaction between economic factors and institutional, political, and social factors in the formulation and implementation of economic policies in emerging economies, including transition economies.

This courses uses ten topics to explore how the global economy emerged in the past and how global trade and global empires changed the world. The first part of the course traces the connection between European colonial empires and the making of the global economy until the Industrial Revolution, and how the rise of the West impacted other world regions. The second part of the course discusses globalization and deglobalization and the shifts of global economic power in the modern age. This is modern economic history in a global context and focuses mainly on non-European regions.

This course explores how labor markets work and analyzes a wide range of labor issues within Japanese and US economies. Each class begins with the theoretical background of labor economics, then students analyze a related research article to understand how and whether the standard, neo-classical model is applied to real economic life. 

The regular version of this course is worth 3.0 UC quarter units. The Q version of this course is worth 4.5 UC quarter units. Students must submit a special study project form which outlines the requirements for the additional units. This is typically an additional paper graded by the instructor of the course.

In this course, students study econometric methods to analyze individual-level data (microdata). The course starts by studying core policy evaluation methods, then covers various extensions, and finally reviews limited dependent variable models. Throughout the course, emphasis is placed on (a) agents’ choice and selection into treatment, and (b) heterogeneities in treatment impact. Related to these keywords, the lectures answer the following questions: What are appropriate econometric techniques to measure policy impact when assignment to the policy (treatment) is not random? What is the econometric framework to measure policy impact when the policy impact is heterogeneous among the individuals?

This course provides a rigorous treatment of the core concepts and skills in security investments and portfolio management. The main focus is on the trade-off between risk and return, which will be analyzed in a mean variance framework. Along this line, two main theories of asset pricing will be explained: the Capital Asset Pricing Model and Arbitrage Pricing Theory. The empirical tests of these two theories will also be discussed.

The course presents an introduction to the economic theory of the public sector. The topics covered include public goods, externalities, education, health care, pensions, redistribution, collective decision making and cost-benefit analysis.  A prerequisite for this course is a basic course in microeconomics.

This graduate-level course prepares students for theoretical research in financial markets and is based on journal articles and working papers. The first part of the course discusses different methods to facilitate transactions. The course introduces secured and unsecured credit, and compares the difference between credit and money. The second part of the course discusses search and matching friction in the financial markets, discussing models applying search and matching friction to study stock markets, housing markets, and bond markets. The last part of the course discusses the current development of fintech, introducing the theory behind cryptocurrencies and analyzing how digital currencies influences the current economy.

This course equips students with fundamental skills and conceptual knowledge essential for investment professionals, including money managers, security analysts, and investment advisors. Students gain a strong foundation in the theoretical principles and practical applications of portfolio investment techniques, with an emphasis on using Python for financial analysis. Additionally, the course incorporates discussions on recent financial news relevant to lecture topics, enhancing students' understanding of real-world investment scenarios.    

The course covers the following topics: The Investment Environment; Portfolio Theory and Practice; Equilibrium in Capital Market; Fixed-Income Securities; Security Analysis, and Options, Futures, and Other Derivatives. 

Recommended prerequisites: Basic knowledge of statistics and understanding of introduction to microeconomics. 

This course provides a mathematical foundation of regression analysis for advanced undergraduate students or graduate students who have studied intermediate-level econometrics and are familiar with probability theory and regression models. This course studies estimation methods for regression models such as ordinary least squares (OLS), generalized least squares (GLS), instrumental variables (IV) estimation, and the generalized method of moments (GMM) in a mathematically rigorous fashion.