Master of Philosophy (MPhil) in
ECONOMICS

This course is the second part of a sequence of two courses on microeconomic theory for M.Phil and PhD students. It covers applied game theory and its applications: principal-agent problems, economics of information, auctions, bargaining, public goods provision, mechanism design, and market design. This module aims to provide students rigorous and accessible explanations. The objective is to focus on classic results. If time permits, we will also take the students to the frontiers of research in selected areas.

This course covers state-of-art core materials of modern macroeconomics including both theories and applications. It is the second course of a sequence of two courses on macroeconomic theory for M.Phil and PhD students. In the theory section, topics featured include: (1) Structural change and unified growth models, (2) Microfoundation of economic growth including misallocation, innovation and production network etc., and (3) Business cycle theories including Real Business Cycles and the New Keynesian frameworks. The application section of the course emphasizes the use of firm-level or aggregate data in the conduct of macroeconomic research using the above theories.

This is a graduate level course in applied econometrics. Both microeconometric theory and empirical strategies for applied econometric research will be discussed. Modern causal inference including machine learning tools and big data analysis will be introduced. This course will discuss instrumental variable methods, treatment effect, matching, panel data models, differences-in-differences, regression discontinuity designs, binary response model, censored data, and modern causal inference topics including machine learning in causal inference, and so on. Students are advised to take ECON5120/ ECON5121/ ECON5122 before taking this course.

This is an advanced course on game theory. We will cover topics in strategic games, extensive games of complete and incomplete information, epistemic foundations of game theory, repeated games, bargaining theory, coalitional games and matching theory. We will also discuss various applications of game theory in Economics.

In modern economic research, computers enhance our capacity of solving complex problems. Computation is particularly important in fields involving massive data. The objective of this course is to introduce graduate students to computational approaches to solve economic models, with an emphasis on dynamic programming and simulation-based econometric methods. We will formulate economic problems in computationally tractable form and use techniques of numerical analysis to solve them. Substantive applications will cover a wide range of problems including labor, industrial organization, macroeconomics, and international trade.

This graduate-level course studies advanced monetary economics. Its focus will be on models and theories of money and financial intermediation, but relevant empirical literature will be incorporated as well. The topics include ISLM model in open economies, OLG monetary model, flexible price monetary model, such as MIU and CIA model and new Keynesian sticky price model. China's monetary policies will also be discussed in the course.

This course offers theoretical, empirical and current topics in international trade. It covers studies of positive issues, such as: Why do countries trade? What goods do countries trade? How does openness to trade shape countries' industrial structure and global production sharing? The course also concerns the normative issues, such as: Is trade beneficial to everyone, or are there winners and losers? What is the impact of trade on economic growth, wage inequality and poverty? All these issues will be discussed both from theories and empirics, as well as at country, industry and firm level. In particular, we will also discuss the ongoing US-China trade war.

The course provides an overview of selected topics in industrial organization. Both theories and empirical approaches will be used. Court cases and legal materials will be used to illustrate the applications of various concepts in industrial organization.

Large-scale data set has become increasingly available in many fields of economics. This presents challenges to statistical inference and even merely "understanding" the data. Meanwhile, it offers abundant opportunities for new inquiries and answers. In this course, we introduce the core statistical methods to work with big data (structured and unstructured) and show how these techniques can be combined with econometric tools in economics research. While we cover major machine learning tools, including supervised learning methods, unsupervised learning and dimensionality reduction, we will focus on their concrete applications in current empirical research. Examples will be drawn from various lines of research, including text as data, relevant prediction problems in economics, and causal inference.

Using the Chinese economy as a context, the course is designed to guide and train students to think courageously, creatively, and critically. Students are required to find "puzzles" in the contemporary Chinese economy, to develop economic issues of general relevance from these "puzzles", to frame these issues into theoretical or empirical questions, and finally to draft papers based on these questions. The course relies heavily on class discussion. Students are required to present at each stage of their thinking process. Students are advised to take ECON5010/5011/5012, 5020/5021/5022 and 5120/5121/5122 before taking this course.

This course provides the economic foundation of modern asset pricing theory. It serves as an introduction to the functioning of the financial market as an efficient venue for financing investment activities. Various issues on risk measurement, risk assessment, managing risk, investors' psychological attitudes towards risk, and its implications on consumption and portfolio decision making in an uncertain world will be introduced and discussed. In-depth treatment will be given to the classical Markowitz's mean-variance analysis, CAPM, multi-factor asset pricing theory and no-arbitrage asset pricing theory as cornerstones of modern finance.

This is a graduate-level international finance course. It aims to provide students with a solid understanding of the modern theories and empirics of international finance. Topics covered in this course include: exchange rate determination theories, exchange rate regimes, capital flows, currency crises, international monetary policy spillovers and coordination, among others.

The goal of this course is to understand the economic problems of developing countries by using economic theories and their applications. The course will cover both macroeconomic and microeconomic approaches to development economics. We will first overview the theories of growth and discuss their potential in explaining income differences across countries, and then study the different facets of human development: market, institution, and culture.

The course provides a theoretical and empirical foundation for the analysis of labor market. Topics to be covered include: labor supply and demand, minimum wages, migration, human capital and education production, labor market incentives, efficiency wage, and skill investment. Students should preferably have finished graduate level Microeconomic theory and Econometric Theory and Applications before taking this course.