MSc Economics

The aim of this course is to equip students with a firm grounding in the methods and practice of estimation and inference in econometric models.

ECON60901 is a Co-Requisite for ECON61001

The aim of this module is to equip students with a firm grounding in the methods and practice of estimation and inference in econometric models.

On completion of this unit successful students will be able to undertake well-founded empirical, data-based work. This is a skill required in all modern positions for economists. The skills learned here also form the basis for any empirical research activity (in the dissertation or any post-university academic or commercial research activities).

Provisional

1. The Classical Linear Regression Model

2. Large sample analysis of OLS

3. Inference in regression models estimated from cross-section data

4. Inference in regression models estimated from time series data

5. Instrumental Variable estimation

6. Maximum Likelihood and Binary Choice Models

7. Generalized Method of Moments

Lectures, tutorials and practical and guided self-study.

Students will be able to:

• Understand the manipulation and use of matrices and vectors and their application in econometrics
• Understand how to conduct estimation and inference in both time series and cross-section applications of the linear model, employing standard least squares, instrumental variables and robust inferential techniques
• Understand the construction of advanced estimation procedures such as Maximum Likelihood and Generalized Methods of Moments estimators and associated inferential procedures with applications to economic problems

Students will be able to explain the advantages and disadvantages of using particular estimation techniques in economic applications

Knowledge of programming in R.

Analysing data by applying econometric methods in R.

Applying descriptive and inferential statistics.

Statistical modelling.

Data analysis.

Formative Assessment:

Tutorial Exercises

Summative Assessment:

Final exam - 2 hours (60%)

Midterm - 50 minutes (20%)

Pre-Session statistics test (10%)

Computer/analytical assignments (10%)

Lecture notes will be provided.

A secondary source for all aspects of the course is:

William H. Greene, 2017, Econometric Analysis, 8th Edition, Pearson Higher Education Publishing Company.

Please note that the course will involve linear algebra from the start. So for those of you whose undergraduate Econometrics course was based on a text such as Jeff Wooldridge’s “Introductory Econometrics”, the presentation of the mathematical arguments will be more similar to his Appendices D and E than in the main part of his text. The Pre-session Mathematics and Statistics courses will review linear algebra but it is strongly recommended you review this material in advance. Additional resources are available on the ECON61001 Canvas site.