Econometrics

About the major

The major in Econometrics focuses on the application of mathematical and statistical techniques to the analysis of social, financial, business and economic data, which is available in ever-increasing quantity and complexity. It blends the essentials of economics with a balanced and rigorous training in modern econometric theory and associated empirical methods. This major is training for an area of high employer demand, with employers increasingly looking for graduates with highly sophisticated quantitative skills.

Requirements for completion

A major in Econometrics requires 48 credit points from the Unit of Study table including:
(i) 12 credit points of 1000-level units of study
(ii) 12 credit points of 2000-level core units of study
(iii) 24 credit points of 3000-level selective units of study; which includes 6 credit points of 3000-level Interdisciplinary Project unit

A minor in Econometrics requires 36 credit points from the Unit of Study table including:
(i) 12 credit points of 1000-level units of study
(ii) 12 credit points of 2000-level core units of study
(iii) 12 credit points of 3000-level selective units of study

First Year

ECMT1010 Introduction to Economic Statistics introduces the basic statistical tools of analysis and how to manipulate economic data.

ECMT1020 Introduction to Econometrics introduces regression analysis, the most important tool in econometrics. Students work with both macroeconomic and microeconomic data as a way to introduce interpretation of economic phenomena using statistical analysis. In this unit, the difference between correlation and causation is also introduced.

Second Year

The tools of microeconomic analysis are further developed in ECMT2150. This unit outlines many of the common issues that arise using economic and financial data (autocorrelation in macroeconomic and financial time-series data, multicollinearity, heteroscedasticity, endogeneity, and sample selection bias), and potential solutions. This is further developed in ECMT2160. This unit emphasizes endogeneity issues and introduces students to new estimation techniques (GMM). Time is also taken to help students understand the particular issues relating to discrete-choice problems, with applications to consumer choice and labour market decisions and policies.

Third Year

In their third year, students apply the econometric skills learnt in the four preceding theory units. In their selective units students develop their own models to analyse economic data. This requires a high-level of statistical understanding. It also requires that these are informed by economic theory. The culminating unit for the major is the combined interdisciplinary project. This unit will require students to demonstrate that they can choose the appropriate model to critically analyse and to provide advice. Students will also need to be able to demonstrate they understand the limitations of the models used.

Honours

If you commenced your degree prior to 2018: Admission to Honours requires a major in Econometrics with an average of 70 percent or above.

If you commenced your degree in 2018: Admission to Honours is via the Bachelor of Advanced Studies and requires the completion of a major in Econometrics with an average of 70 percent or above. You will need to ensure you have completed all other requirements of the Bachelor of Advanced Studies, including Open Learning Environment (OLE) units and a second major, prior to commencing Honours.

The Honours year requires 48 credit points including:
(i) 24 credit points of 4000-level Honours thesis units of study
(ii) 24 credit points of 4000-level Honours seminar units of study.

Contact/further information

School of Economics
sydney.edu.au/arts/economics
Room 370, Merewether H04
Email:

Example Pathways

Econometrics pathway to major

Econometrics pathways to minor

Learning Outcomes

1. Demonstrate an understanding of basic econometric tools of analysis.
2. Demonstrate abilities to use empirical evidence to evaluate the validity of an economic argument, to use statistical methodology, interpret statistical results and to conduct appropriate econometric and statistical analysis of data.
3. Demonstrate the ability to analyse and interpret economic events and policies using econometric models that are informed by econometric theory, showing an understanding of the difference between correlation and causation.
4. Demonstrate an understanding of particular statistical issues that arise when dealing with economic data, and use appropriate techniques to deal with these issues and to communicate their findings.
5. Demonstrate an understanding of endogeneity and potential solutions.
6. Apply econometric analysis to work and research in other relevant disciplinary communities.
7. Clearly communicate the results and implications of informed and sophisticated econometric analysis.