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Exam (elaborations) ECS3706 - Econometrics (ECS3706)
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Exam (elaborations) ECS3706 - Econometrics (ECS3706) EXAM PACK MAYJUNE 2022
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UNIVERSITY EXAMINATIONSMay/June 2022
ECS3706
ECONOMETRICS
100 marks
Duration: 4 hours
EXAMINERS:
FIRST: PROF S NHAMO
SECOND: DR M ZUKA
EXTERNAL: DR L RAPUTSOANE
CONFIDENTIAL
This paper consists of 11 pages, including a formulae sheet (page 8), three pages of statistical
tables (pages 9 to 11), plus the special front page.
Instructions:
(1) This paper consists of two sections.
Section A: Answer all three (3) questions, which together count for 60 marks:
(20 + 20 + 20 ) = 60.
Section B: Answer any two (2) of the three (3) questions. Each question counts
for 20 marks: (2 x 20) = 40.
(2) Once you have completed your answers, submit your answers as a single document
in PDF format using the e-Assessment tool on the myExams portal. It is
preferable for you to type your answers (font: Arial 12) and then convert your
document to PDF for submission. However, if this is not possible, you may also write
your answers down and scan them to a PDF file. Please write legibly.
(3) Start with a cover page stating the module code (ECS3706) and your student
number.
(4) This should be followed by your answers to the questions.
(5) There is no need for a table of contents, an introduction, a conclusion or a list of
references (as was required in your assignments). Simply answer the questions
asked.
(6) Ensure that each question and sub-question is clearly numbered.
(7) While you are not required to cite your sources, this does not mean that you can
simply copy information from any source. You need to answer the questions in your
own words. Plagiarism will not be tolerated and will result in disciplinary action
if detected.
(8) Ensure that your PDF document is NOT encrypted to a “secured” mode and that it is
NOT password protected, as these files cannot be marked. Virus-infected files will
also not be marked.
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, Page 2 of 11 ECS3706
CONFIDENTIAL May/June 2022
INSTRUCTIONS ON THE DAY OF ASSESSMENT:
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After completing invigilation and following all app instructions, you must upload your Invigilation App data. If however
there is a delay in the upload of the app data at the end of the assessment, you should prioritise the upload of your
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Should you encounter any technical difficulty, please WhatsApp The Invigilator Helpdesk on 073 505 8273.
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, Page 3 of 11 ECS3706
CONFIDENTIAL May/June 2022
SECTION A (60 marks)
Answer ALL three (3) questions in section A.
Section A requires brief and to- the- point answers.
In most cases simply list, or briefly explain, what is required.
It may be advantageous to use statistical notations (mathematical symbols) to explain concepts – but
please ensure that you also explain their meaning.
You do not need to re-explain concepts that have been previously dealt with. If required, you may simply
refer to your previous answer/s.
In general, each mark represents one correct fact or correct interpretation.
QUESTION A1 (20 marks)
(a) Distinguish between the following terms (5)
i. Cross- section and time-series data
ii. Categorical and continuous data
iii. Significance tests and confidence intervals
(b) Including the disturbance or stochastic error term in your model implies that one does not have
to worry about specification errors in the model. Discuss. (6)
(c) You estimate two models. The second one has two fewer explanatory variables. You observe
that R-squared decreases in the second model. Does this prove that the first model is better?
(4)
(d) Provide three examples of situations where you would use a one-tailed hypothesis test
rather than a two-tailed hypothesis test. (5)
[20]
QUESTION A2 (20 marks)
(a) State four valid criteria for determining whether a given variable belongs in an equation. (4)
(b) Consider the following Cobb-Douglas production function which relates production to factors of
𝛽 𝛾
production: 𝑄𝑡 = 𝐾𝑡𝛼 𝐿𝑡 𝑆𝑡 𝑒 𝑢 – where Q is production, K is capital, L is labour, and S is other
knowledge-based inputs such as research and development. You have obtained firm-level data
for all the key variables in your model. Explain how you would estimate the production
parameters using regression analysis. (5)
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