Dual Master’s Degree in
Applied Economics (The Chinese University of Hong Kong) & Social and Economic Policy (Northwestern University)

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.

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 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.

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 ECON5012 and ECON5122 before taking this course.

This course provides an overview of the theory of industrial organization and its applications. Topics include theory of the firm, business integration, supply chain contracting, monopoly, price and non-price business strategies, and case studies.

This course addresses the economic theory and empirics of corporate finance and governance. The goal is to help students understand major research issues in the field and develop their skills to apply theory to corporate finance practices. It focuses on important topics such as capital structure, ownership structure, capital budgeting and corporate governance institutions. The course extensively uses the tools of game theory, information economics and microeconometrics. Students are recommended to take ECON 5012 and ECON 5122 before taking this course.

This course provides an introduction to the theory and empirics of behavioral economics and behavioral finance. In this course, classical assumptions on economic agents such as rationality and time consistency are relaxed, allowing students to analyze investors and financial markets from a non-traditional perspective. The course is therefore a good complement to the mainstream economic and financial theories built upon individual rationality.

This course is an introduction to rigorous and policy‐relevant impact evaluation strategies and techniques for postgraduate students in economics. The course's main emphasis is on empirical strategies to identify the causal effects of public policies and programs. The course has a strong focus on applications, although students will be expected to fully understand the conceptual underpinnings of each strategy. Topics include instrumental variables, fixed effects, differences-in-differences, experiments, and regression discontinuity design for policy evaluation.

This graduate course includes two parts. The first part provides elementary theories of monetary policy and fiscal policy, providing students a general framework for policy analysis. The second part mainly discusses the development of Chinese monetary policy and fiscal policy in the past three decades, the potential policy reform and its implications to the Chinese economy. In addition, how monetary policy and fiscal policy respond to financial crises or public health crises will be widely analyzed and discussed in this course.

This course provides an introduction to contemporary public policies in China. These include economic public policies such as labor, trade, tax and poverty alleviation, as well as social public policies such as environment, population, education, healthcare and social security. This course focuses on using economic concepts and theories to analyze and evaluate such policies.

This is a course on special topics in Economics. The topic may change from one year to another. Some recent topics are international trade, and monetary and financial economics.ECON5822 Special Topic in Economics I : Economic Policies in Aging Societies (Offered in 2023/24)ECON5831 Special Topics in Economics II : China Financial Markets (Offered in 2023/24)

This course introduces the process of using data and data science techniques to explore and examine problems or issues related to social policy. Data science is a new powerful approach or discipline that combines various aspects of statistics, programming, mathematics, computer science, and visualization techniques. In this course, we will learn the fundamentals of methods for harnessing and analyzing the vast quantities of new and heterogeneous data using the Python programming language.

This course provides the foundational tools for analyzing the economics of education. It will provide several different explanations for why people go to school, including both the signaling and human capital models. Methods for estimating the returns to schooling (i.e. income boosts that can be attributed to education) will be applied and covered in detail. These methods include regression, difference-in-difference, regression discontinuity, and instrumental variables. These tools will also be used to analyze other important questions within education, such as the impact of smaller classes and the importance of teachers. Finally, depending on time and student interest other topics will be explored, such as student debt, school accountability, and higher education finance.

This course would introduce students to important basic ideas of ethnographic fieldwork, both from a historical perspective on how ethnographic field studies have been used to understand organizations in the past (and the concepts that have been developed in these studies) and from the perspective of newer, contemporary approaches (e.g., the use of video interaction analysis methods). The course would also locate policy as one among several social scientific conceptions of how organizations change. Finally, the class will consider the role of human learning in how policies are experienced and implemented. The culminating assignment for the class will be a small fieldwork study in which students investigate a context in which a policy has been implemented and seek to understand through ethnographic methods (e.g. interviews, observations) how the policy is experienced and understood by relevant organizational stakeholders.

This course explores economic, social, and environmental determinants of population health and wellbeing, and how health and wellbeing in turn impacts economic productivity and social disparities. In particular, students will learn about the fetal origins hypothesis, historical and recent developments in fertility, health disparities, the role of environmental pollution, trends in mortality, mental health, and subjective wellbeing. Each topic will be paired with the review of a empirical method, deepening the understanding of research techniques and their applications to real-life problems.

This course explores individual, organizational, and social factors that influence how leadership is defined and enacted in organizations. This exploration highlights theories and models of effective leadership, providing opportunities to build knowledge, develop your own perspectives, and practice the leadership skills necessary to face the challenges of leading organizations for positive impact in complex environments. We will explore the concept of leadership as a set of organizational responsibilities that are socially conditioned and shaped by different cultural values, social contexts, and individual identities. Readings and activities will cover leadership issues such as: aligning and articulating connections among organization mission, strategy, and culture; recognizing and countering bias to support evidence-based decisions, inclusion, and equity; modeling emotional intelligence; and, developing and inspiring new, emerging leaders. *This course is jointly offered with the MS in Leadership and Organizational Change (MSLOC) program. MSLOC charges a $400 fee for staffing, technology, and during courses with an on-site component. MSLOC also might charge additional fees for assessments or simulations.