Quantitive Methods Project

Quantitive Methods Project

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

Do NOT use a package other than Stata to do the project. Do NOT use Stata commands unless they were covered in the course. This can often cause confusion that this is your own work. Nor is it necessary. The project is a demonstration that you understand and can implement the (relevant) techniques/tests covered in the course. This includes mastering and understanding relevant Stata commands.

Do NOT write your name on the project – just give your student number
You should aim for a maximum of 2,500 words or around 8 pages of text, 2 to 3 tables of results and 2 or 3 figures (not including the log file)Please provide a word count on your cover page.

Project Objectives
The idea is to choose an economic issue which you find interesting, outline a theory and a set of testable hypotheses that follow on from that. Then test the theory empirically using the tools you have learned during this term’s course. The dissertation should read something like a typical article that you would find in a (non-technical) academic journal like the Journal of Economic Perspectives or the May Papers & Proceedings volumes of the American Economic Review, (the collection of back issues are in the library).
Choosing a Topic
The most important thing is to choose a project that is feasible, that can be finished within one month from start to finish and still allow you time to work on your other subjects. This means confining your topic to a simple issue. Also it is a good idea to choose a topic that you are interested in, rather than one you fell you ought to do. The more you are interested the easier the project will be. Do not write the theoretical part of your project until you know you have data that can be used to test your hypotheses.
One good way to find a topic to study is to read the economic pages of the broadsheet newspapers and/or academic articles summarised in overview journals like the
Journal of Economic Perspectives
both of which are in the library. In addition there are specialist journals, (and therefore more technical), such as the
American Economic Review, Economic Journal, Quarterly Journal of Economics, Journal of Labor Economics, Journal of Industrial Economics, Journal of Development Economics, Journal of Finance
which should all be good sources of current issues concerning academic economists
There are a large variety of data sources on the internet that should meet your needs
Many UK macroeconomic statistics, (inflation, unemployment, gdp etc), can be downloaded from the Office for National Statistics website
UK Regional data can be found here
Journal of Economic Literature

The bized site also contains access to official UK data alongside company account data and some international data. https://www.bized.co.uk/learn/economics/index.htm
You can find stock market data at the Stock Exchange’s web site
or from yahoo https://uk.finance.yahoo.com/q/hp?s=%5EFTSE
or from the Bank of England
A very good source of international data both cross section and time series is given at the Resources for Economists website https://rfe.org/showCat.php?cat_id=2
and also the Statlib website https://lib.stat.cmu.edu The World Bank also has data https://worldbank.org
and there are lots of data and ideas at https://www.economagic.com/ and https://pwt.econ.upenn.edu
The library also has a useful link to some sites
For those of you interested in working with cross section data. I have put 2 different UK cross section data sets on the course web site
Health, Wages: GHS_project.dta – which has information on wages, health, smoking, drinking, education and other socio-demographic characteristics of individuals taken from the General Household Survey
(you can find a codebook giving details of the variables at https://www.esds.ac.uk/findingData/snDescription.asp?sn=5804
Consumption: Food_project.dta – which has information on household spending on various consumer items taken from the Expenditure & Food Survey
(you can find a codebook giving details of the variables at https://www.esds.ac.uk/findingData/snDescription.asp?sn=5375
You will have to choose which variables to model to make sure the data are free of missing values and give economic reasons for your choice.
These are just guides to help you. You may, of course, find your own data.

Ideally your project should look and be structured like an article you can find in any of the economic journals listed above. You are strongly advised to read some articles to get a feel for how they are presented.
(there is an example article on the course moodle page)
So your project should include the following sections:
Theoretical Framework
Set out the economic theory underlying your project and use it to specify a model and the resulting hypotheses to be tested. Set out your prior expectations of the likely signs and magnitudes of the coefficients. Discuss any econometric problems you expect to encounter.
Discuss the sources for your data. Give the exact definition of variables (in a Table in an appendix) and sample period, Describe the main features of the data using a table of sample means and their standard errors. Graph the trends in the dependent and, perhaps, the independent variables. Comment on the main trends/features.
Econometric Method
Outline the econometric techniques used to estimate your model, (eg. ordinary least squares with corrections for heteroskedasticty/autocorrelation). You need to convince the reader that you have made the right choice of estimation technique. Evaluate the model using the set of (relevant) diagnostic tests covered in the lectures. (Eg, Box-Cox, Ramsey Reset, Forecasting). Do NOT report the results of the tests one after another like a shopping list. Report the tests for each model at the bottom of a column of estimates. (Again read a journal article for hints on presentation).
Outline your results in tabular form, (check with a journal if you are unsure as to how to present your results). The Stata command “outreg” will help considerably with you inputting the results in tabular form. State whether your hypotheses are accepted or rejected. Comment on the results and on any diagnostic tests you have used.
Give an overview of your hypotheses and main results