This course is an introduction for economics graduate students to the techniques of econometrics. The emphasis is on the essential ideas and the applications of econometric methods rather than on technical and theoretical details. However the results are not just presented but instead are derived using a mixture of rigour and intuition so as to leave as few loose ends as possible. We recognise that available economic data are either cross sectional (observations on several economic units - usually countries, firms or households - at a single point in time) or time series (observations one economic unit over time), or panel (observations on several economic units followed through time), and each type of data may need its special set of tools. We start with the linear regression model, which is the simplest model for explaining one variable using several explanatory variables, and then move to an introduction to ‘micro-econometrics', i.e., methods most useful for the analysis of cross sectional data, and an introduction to ‘macro-econometrics', i.e., methods most useful for the analysis of aggregate data over time.

On completion of the course you should be able to understand most of the econometric results that are presented in the applied economics literature and make critical assessments of those results. You should also be able to produce good estimates in fairly simple situations and provide coherent interpretation of those results, including any caveats on their use. Particular skills include:

• interpret regression coefficients in linear and nonlinear regression models
• assess the fit and statistical significance of econometric relationships
• construct interval estimates and hypothesis tests of interesting economic hypotheses, including those involving several parameters
• distinguish different forms of data and the models appropriate for them: cross section, time series and panel data
• critically assess choices of functional form
• understand the assumptions in the statistical model, the consequences of failure and methods of detection
• use the statistical package Stata.

The assessment scheme is as follows:

      Mid-semester examination               20%

      Assignments                                   15%

      Final examination                            65%

The mid-semester exam will be redeemable, in the sense that all of the weighting for that component will be placed onto the final exam if doing so improves your overall mark. Both examinations will be in the standard closed-book format. Your final grade from the course will generally not be the exact result of the calculation, as scaling of scores is often necessary after the raw score is calculated. The scaling, if needed, will preserve the order and the scaling may be up or down.

Contact of 4 hours and a total 10 hours total a week (masters students) or 13 hours a week (graduate diploma students).

Students should have a background with at least undergraduate study of economics, including courses in basic mathematics and statistics for economics.

This course is similar to EMET8005 Economic Models and Introductory Econometrics offered by the School of Economics. The two courses are incompatible, but each can be used to satisfy a prerequisite that specifies the other.

Marno Verbeek, A Guide to Modern Econometrics, Wiley, 2nd edition 2004, ISBN 0-470-85773-1.

Jeffrey M. Wooldridge, Introductory Econometrics: A Modern Approach, South-Western, 3rd edition 2006, ISBN 0-324-28978-2

Any introductory textbooks in (i) mathematical techniques for economics and (ii) statistics for economists.

Delivery Mode: On-Campus.  3 hours of lectures (usually arranged as 1 hour + 2 hours) and one, 1-hour, tutorial a week for a 13 week semester.