Empirical work to be completed by Resit students as part
of resit requirements
Preamble: If you are a student who is being required to resit ECON212 as a result of
previous performance, you will need to complete and submit the piece of work below. It
will count for 30% of the credit for your resit. The remaining 70% will accrue from the
Resit Examination to be held in August 2019. You will be provided with the time and
place where the resit examination will take place in due course. To pass the course, you
must gain an overall mark of at least 40% (i.e. it is possible to get less than 40% on one
aspect of the resit work as long as this is compensated for by the other component so
that you get a weighted average mark of at least 40).
Details: Your completed piece of work must be submitted by 14.00 on Monday 5th
August 2019 at the latest. It must be submitted electronically using the VITAL course
website for ECON212. On this website you should go to the Assessment part of it.
There you should find a Turnitin submission area where your work should be left. If you
miss this deadline, you will get zero for this part of your re-assessment.
Your submission: You submission should include discussions of your results as
appropriate, together with relevant output from EViews (this latter might include
histograms, scatter diagrams and output from regression analyses etc.). Overall, your
submission may not exceed 8 pages of A4 in total, with a maximum written content
of not more than 1000 words. Any submissions exceeding either of these limits will
be penalized accordingly.
Your task: In the Assessment part of the VITAL website, you will find a folder called
Resit Empirical Work. The folder contains two items; this document; and an EViews
data file called health.WF1. This is the file of data on which you should perform your
analysis and base your submission report. You can access the EViews software needed
to complete this work via the University of Liverpool’s Apps Anywhere facility.
The data: Place yourself in the position of being a Health Econometrician with a charity
concerned with social and environmental effects of smoking during pregnancy and
household income of mothers on the birth weight of babies. In the data file you have
nearly 2000 cross-section observations on the three variables, each of which has an
easily identifiable acronym as its name (e.g. ‘cigs’ for cigarette consumption during
pregnancy and so on).
(i) Use the graphical and statistical capabilities of EViews to describe each of the
three variables in turn.
(ii) Provide any scatter diagrams of these data that you think are useful in your
(iii) Use the data to consider possible relevant simple and multiple regression
models. Provide a discussion of the results from each and choose, with clear
reasons, a preferred model for the prediction of baby birth weight, conditional on
one or both of your explanatory variables.
(iv) Test the hypothesis that the coefficients of the two explanatory variables are
equal in magnitude and opposite in sign in your multiple regression. Provide a
careful account of how you tested the relevant hypothesis and what the results
(v) Provide a prediction of the average birth weight of a baby whose mother smokes
cigarettes at the lower quartile value of smoking in the sample and at the upper
quartile of household income in the sample. Comment briefly on the result.