ÐÓ°ÉÂÛ̳

The problem, for those concerned with social or economic policy, is that we seldom have the luxury of being able to undertake controlled experiments of the type conducted by natural scientists. Instead, we have to draw our inferences from the analysis of non-experimental data. That is the function of econometrics.

The objective of this course is to provide the basic knowledge of econometrics that is essential equipment for any serious economist or social scientist. The course introduces statistical tools including regression analysis and its application using cross-sectional data.

The second week onwards will be focused on how various technical problems inherent in economic analysis, including heteroskedasticity, autocorrelation, and endogeneity should be handled. This section of the course will pay special attention to the application of the regression model to time-series data - both stationary and non-stationary.

Using the theories and their application in economics, you will participate in daily workshops to get hands-on experience implementing the various estimators and testing procedures in Stata using real-world data. As a result, you will consider how the theory can be applied to a wide range of questions of economic interest (For example, modelling long-term relationships between prices and exchange rates).

By the end of the course, you will be able to provide proof of the unbiasedness or biasedness and consistency or inconsistency of least squares, and instrumental variable estimators using simple models.

Prerequisites: At least one semester of mathematical statistics with a serious analytical treatment of estimation and inference, and at least one semester of multivariate calculus, both passed at a respectable standard.

Level: 200 level. Read more information on levels in our FAQs

Fees: Please see Fees and payments

Lectures: 36 hours

Classes: 18 hours

Assessment: Two written examinations and one computer-based exercise

Typical credit: 3-4 credits (US) 7.5 ECTS points (EU)

Please note: Assessment is optional but may be required for credit by your home institution. Your home institution will be able to advise how you can meet their credit requirements. For more information on exams and credit, read Teaching and assessment

This course attracts a diverse range of participants including professionals who have found that the acquisition of econometric skills would be valuable in their work; PhD students, typically in disciplines other than economics, who are including a serious empirical component in their dissertations; and undergraduate students who want to challenge themselves by taking on this highly ambitious course.

If you are interested in developing a practical and sound grounding in the use of econometrics in economics and the social sciences, you should consider taking this course. It is especially useful if you are targeting a role in economic research, government, data science, policy development or consulting.

• Understand foundational econometric theory and how it can be applied using real-world data
• Analyse how statistical tools including regression analysis can be applied using cross-sectional data
• Develop an intuitive understanding of econometrics that allows you to utilise the theory and tools effectively and creatively in a variety of academic settings
• Practice implementing the various estimators and testing procedures in Stata using real-world data

The design of this course is guided by ÐÓ°ÉÂÛ̳ faculty, as well as industry experts, who will share their experience and in-depth knowledge with you throughout the course.