In a year or so, Master students are going to graduate and work in government offices, public or private enterprises, research centers, and even startups. In these institutions, you are going to be given tasks to understand real-world economic phenomena. To able to accept these tasks, it is important for students to learn a very important tool in economics: econometrics.

In this course, Master students are going to learn the fundamentals of econometrics at an intermediate level. The goal of this course is to introduce students to basics of econometrics, such as estimating causal effects and inference statistics. Students will also learn introduction to applied econometrics techniques—such as microeconometrics and microeconometrics—used in government, business, and academic research. Such tools prepare students who wish to continue to a doctorate degree. The tools are useful for students intending to become quantitative business and economic analysts, and for those interested in knowing how economics is applied to real-world problems. The instructor designs the lectures to achieve a balance between theoretical foundations and applications.

The range of topics covered in this course include, but not limited to, inference statistics, ordinary least square (OLS) estimation method, probability distributions, hypothesis testing, classical assumptions, basic econometric modeling, multivariate regressions, an introduction to limited dependent variable models, an introduction to panel data, and time-series estimation methods.

The course is quite technical and rigorous. You are expected to attend all lectures and tutorials, complete problem sets, and review relevant book chapters before each meeting. You must have a self-discipline to complete this course. Given the 3 credit hours, you must allocate at least 7.5 hours each week for the course.