2022/2023 BU5025 Quantitative Methods
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2022/2023 BU5025 Quantitative Methods
Computer Group Assignment (10%)
Submission deadline: Friday 18 November by 12 noon. Late submission is not accepted.
Notes: This assignment will contribute 10% to the final course assessment. Work in a group of three to five people for this assignment to take advantage of synergies between students. To reflect the effort levels of each member of a group to the final mark, fill in a group- assignment evaluation form as a group and upload with the assignment when you submit.
In case you cannot find a minimum of three people to work with, email Dr. Yakubu Abdul-
Salam (y.abdul-salam@abdn.ac.uk) as soon as possible.
Submission method: Only one evaluation form and one soft copy of the assignment per group have to be submitted to MyAberdeen. As long as one member of a group submits via the submission link on MyAberdeen, other group members will automatically be recognised as having submitted. To find the link for the online submission, go to MyAberdeen ➔ Courses ➔ BU5025 Quantitative Methods ➔ Course Content ➔ Assessments ➔ Econometrics: Group Assignment (10%). Submitting assignments via the submission link on MyAberdeen is straightforward.
Report length: The maximum length for this assignment is five pages (1.5 spacing, 12 points, Times New Roman font with 3cm margin all around). Note that it is not mandatory to write five pages. Good answers address questions in a concise manner.
Reporting format: Please refer to the document ‘Mock Computer Assignment 2022 - Questions, Answers and Format.docx’, which outlines the expected reporting format for this assignment.
Preamble
To improve electricity consumption efficiency, the Government of Freedonia, a fictional country, implemented a policy involving distribution of energy-saving light bulbs to households. As an analyst, you have been tasked by the Government of Freedonia to evaluate the success or otherwise of this programme in improving energy efficiency in the country. You have access to data containing the following variables;
ℎℎid |
Unique household ID |
year |
Year |
cons |
Electricity consumption, kWh |
ℎℎsize |
Household size i.e. number of people in a household |
inome |
Household income, $ |
bulb |
Dummy variable = 1 if household receives energy saving bulbs, and = 0 otherwise |
Please find the associated data file ‘energy_efficiency.xls’ on MyAberdeen. Now answer the following questions.
Question 1: You believe the following regression model explains electricity consumption in Freedonia;
cons = F0 + F1 ∙ ℎℎsize + F2 ∙ income + F3 ∙ bulb + u (1)
i. What signs do you expect for F1 , F2 and F3 ?
ii. Estimate the above regression model and briefly interpret the meaning of each coefficient
iii. Based on only the p-values of the coefficients, which variable(s) are not statistically significant at the 5% significance level?
Question 2: Your colleague advises use of an alternative regression model specification as follows;
lncons = F0 + F1 ∙ ℎℎsize + F2 ∙ income + F3 ∙ bulb + u (2)
where
lncons = log(cons)
i. Estimate the above regression model and briefly interpret the meaning of each coefficient.
ii. What does the F-statistic and the p-value of the F-statistic tell you about the model?
Question 3: For ease in interpretation, another colleague advises use of an alternative model specification as follows;
lncons = F0 + F1 ∙ lnℎℎsize + F2 ∙ lnincome + F3 ∙ bulb + u (3)
where
lncons = log (cons)
lnℎℎsize = log (ℎℎsize)
lnincome = log (income)
i. Estimate the above regression model and briefly interpret the meaning of each coefficient
ii. What does the R-squared statistic tell you about the model?
iii. Based on the t-statistic and the standard errors only, test the null hypothesis that F3 = 0 against the alternative hypothesis that F3 ≠ 0. Based on your test, what conclusions can you draw about the success or otherwise of the energy efficiency programme in Freedonia.
(Note: Consider 5% significance level; Show calculations and explain each step of your calculations)
2022-11-18