ECMT1020 Written Assignment
Due 12am Friday June 7, 2013
Instructions
? In order to complete this assignment, you will need the data set
‘Film data.xls’.
? This assignment must be done alone and is worth 10% of your final
mark.
? You will be marked on the correctness of your answers as well as
presentation.
? The assignment must be submitted both electronically and by
hard-copy. The hard-copy version
is to be submitted into the assignment boxes on level 2 of the
Merewether Building. The
electronic version must be submitted via the University Learning
Management System (see 3
minute online tutorial for further details).
? Please submit only one single MS Word (or PDF) file. Do not submit
multiple files. In
particular, DO NOT submit MS Excel files.
? Late assignments will be penalised 20% of full marks per day and must
be sent directly to the
lecturer.
? You should familiarise yourself with the University’s policies
a) To get a sense of the data, provide two well labeled
scatter-plots of 1) revenue vs. budget, and 2) revenue vs. screens. Also,
provide a correlation matrix of these three variables
b) After speaking to an industry expert, they tell you that
budget and screens are the most important determinants of film success at the
box office (advertising is important too, the expert tells you, but you don’t have data on that). Produce a
regression with ‘revenue’ as the dependent variable and ‘budget’ and ‘screens’
as the independent variables. Interpret the regression coefficients.
c) With your regression results of part b), provide residual
plots vs. each independent variable. Also, provide a histogram of the
(standardised) residuals. Comment on the nature of the residuals based upon
these three plots.
d) You show your results and plots to your econometrics
professor at university and he tells you that you may have an issue with
non-normal errors caused by outliers. He suggests you transform the revenue,
screens, and budget data into natural logarithms and re-estimate the equation, which
you do. Provide results of the new
regression and interpret the regression coefficients [Hint: d lnY/d lnX =
(dY/dX)*(X/Y) = (dY/Y)/(dX/X)].
e) With your new regression results of part d), provide
residual plots vs. each independent variable. Also, provide a histogram of the
(standardised) residuals. Comment on the nature of the new residuals based upon
these three plots.
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