As part of the course requirements you have to undertake an econometric evaluation of an economic issue using data that you have gathered either from the host of data sets now available on the web, or that you have assembled yourself from data published in journals or in official sources.

The data set must contain a minimum of 3 variables, (one dependent variable and at least 2 right hand side variables to be added to a constant term). You should concentrate on estimating a multiple (rather than simple) regression model. You cannot use the data sets used in the problem sets or lectures. You must find your own data (with 2 exceptions see below)
You should have a minimum of 50 observations in your regressions. Anything less will be penalised heavily.
The model should be a causal one, (ie the right hand side variables should explain the dependent variable, not the other way round). This also means, for example, that you should not estimate identities like a national accounts model of the form Y=C+I+G+(X-M). This is an accounting identity and so the coefficients shouldn’t be anything other than one, barring measurement error).
The econometric results should include a thorough statistical evaluation using the full range of (relevant) diagnostic tests highlighted during the course. Do not use tests just for the sake of it. There are no marks to be gained by doing countless irrelevant tests. Only use tests that are relevant to the type of data and economic relationship you are trying to estimate. (For the purposes of the project assume that a sample of 50 or more observations is enough to make any asymptotic tests valid).

In order for the project to be marked at all, you must also provide a disk or USB containing i) the data you have used ii) the Stata output log containing your regression output (any output – including graphs – generated using any other package will be penalised) and iii) a copy of the project