In this online research ethics course, students will engage as independent learners in the CITI training programme to gain in-depth knowledge and understanding of all aspects of ethics as it applies in the social sciences. The CITI training programme comprises the minimal standards to demonstrate ethical competence and to comply with UM policy and Macau governed regulations for research with vulnerable populations, emerging designs, technology, and more. All students need to complete the discipline-specific prescribed units of the CITI training programme with a default score of 80% or more. Prerequisite(s): None

This doctoral level course aims to develop students’ knowledge and skills regarding academic scholarship and research writing within the social sciences. The course includes the discussion of ways in which culture informs academic writing, and the underlying principles of logic, argumentation and reasoning in academic writing practices. Discipline-specific scholarly conventions and technical requirements for quantitative and qualitative research reporting are discussed and applied in preparation for dissertation writing and the writing of research papers for publication in refereed English journals. Students will also engage with relevant primary and secondary source readings, and conduct critical analysis of exemplary texts. Pre-requisite(s): None

This seminar-based course covers a wide range of material derived from a variety of theoretical traditions and bodies of work. It introduces students to, and help them develop an understanding of, complex issues and texts that are now established as the theoretical basis of scholarship in a number of relevant cognate fields, including communication studies, media studies, cultural studies, gender studies, visual culture, 6 postcolonial studies, literary studies, anthropology, education, film studies, sociology and psychology. Topics in this course will vary according to course instructor and student interest, and may include readings of classical and/or contemporary theories in the social sciences.
Pre-requisite(s): None

This doctoral level course aims to develop students’ knowledge and skills of qualitative research methods in social sciences. Students explore different ontological, epistemological and related methodological perspectives of qualitative research in applied contexts, professional practice, and cultural settings. Students also engage with high-level readings of primary sources and apply critical analysis of exemplary qualitative research papers in preparation for designing and implementing qualitative research projects, develop interpretive/hermeneutic skills, and enhance competency in writing research papers for publication in refereed English journals.
Pre-requisite(s): None

The purpose of this seminar-based course is to introduce students to the issues, practices and strategies involved in collaborative and interactive teaching in higher education settings. Through assigned readings and online and in-class discussion, the course focuses on the nature of teaching and learning, the role of student engagement, how student development impacts learning, the use of technology to enhance student learning, course design, learning outcomes, and models of teaching practice. The course further explores strategies for authentic assessment and whole person education, as well as the development of a teaching portfolio through practical application. Pre-requisite: None

This course is a doctoral level seminar designed to develop the students’ knowledge and skills of quantitative methods in social sciences, familiarize them with procedures of designing and implementing quantitative research projects, improve their critical thinking capability, and increase their competency in writing research papers for publication in refereed English journals. It will provide the students with hand-on experiences in data collection through surveys and data analysis using SPSS, the software packages most commonly applied in quantitative research in social sciences.
Pre-requisite: None

This course is organized into 3 parts, covering consumer and producer theories (Part I), market equilibrium and welfare (Part II) and selected topics in applied game theory (including part of behavioral economics) and its applications in the economics of information and incentives (Part III). Prerequisite(s): None

The objective of this course is to provide an overview of some classic topics in macroeconomics, with a view to providing students with the skills required to read and write professional articles. The main focus is on the basic analytical structure of economic models, their empirical and policy implications. Prerequisite(s): None

Further current topics in theoretical and applied econometrics. Topics will vary and reflect current student and faculty’s demand and instructors’ interests. Selected advanced topics may include nonparametric and semi parametric estimation, numerical optimization, simulation methods, time series, spatial, and panel data models. Prerequisite(s): None

Methodological foundations of microeconomics. Theories of production and individual choice. Aspects of decision theory under certainty, risk and uncertainty. Introduction to game theory under complete and incomplete information, with applications to oligopoly. Perfect competition as a limiting case. General competitive equilibrium: existence and Pareto efficiency. Private information in markets. Basic auction theory. General theory of markets with adverse selection. Contract design in the context of moral hazard problems. Prerequisite(s): None

This is the core macroeconomic course of the Master’s programme. The aim of the course is to give an overview of some classic topics in macroeconomics, with a view to providing students with the skills required to read critically recent professional articles. The main focus is on the basic analytical structure of economic models, their empirical implications, and some policy applications. Prerequisite(s): None

Develops research ability of students through intensive discussion for preparing dissertation, individual and group research projects. Critical appraisal of modern economic research. Main techniques of empirical investigation and key issues in applying and testing theoretical models. Prerequisite(s): None

Review of conditional distributions, expectation, regression and principles of inference. Linear regression models, ordinary and generalised least squares, heteroscedasticity. Non-linear least squares. Hypothesis testing and confidence intervals. Maximum likelihood estimation and testing. Introduction to models and methods for discrete and censored data. Simultaneity, exogeneity, instrumental variables methods. Dynamic models: autoregressive and moving average processes, vector autoregressions. Causality, stationarity, unit root tests, and cointegration. Introduction to panel data methods and models. Prerequisite(s): None