T2 2021 MAE256 – Assignment Details
Due Date: 2 September 2021, Thursday, 8:00 pm
Word Limit: 1500 words excluding appendices, figures and tables.
Weight: 20% of overall final grade.
General Details
(1) This is an INDIVIDUAL Assignment. We strongly discourage plagiarism, as it will be penalized as much as possible. However, it is not collusion if you discuss the questions with other students, but you need to submit your own original work. Note that we may request you come in and explain your assignment in person if we feel your assignment is too similar to another students’ work.
(2) This assignment in total has 30 marks that co
espond to 20% of your final grade.
(3) Once completed, you will need to submit your ‘Microsoft Word’ document via CloudDeakin. You must submit a single file only that contains a cover page with your name and student ID.
If you are submitting your assignment as a PDF document, please ensure that you are also submitting as a Word document to enable word counting.
Please ensure the Word document is self-contained (i.e. all your tables and figures should be in the word document). You will not need to submit a hardcopy.
(4) Penalties for late submission: The following marking penalties will apply if you submit an assessment task after the due date without an approved extension: 5% will be deducted from available marks for each day up to five days, and work that is submitted more than five days after the due date will not be marked. You will receive 0% for the task. 'Day' means working day for paper submissions and calendar day for electronic submissions. The Unit Chair may refuse to accept a late submission where it is unreasonable or impracticable to assess the task after the due date.
(5) For more information about academic misconduct, special consideration, extensions, and assessment feedback, please refer to the document Your rights and responsibilities as a student in this Unit in the first folder next to the Unit Guide of the Resources area in the CloudDeakin unit site.
(6) Building evidence of your experiences, skills and knowledge (Portfolio) - Building a portfolio that evidences your skills, knowledge and experience will provide you with a valuable tool to help you prepare for interviews and to showcase to potential employers. There are a number of tools that you can use to build a portfolio. You are provided with cloud space through OneDrive, or through the Portfolio tool in the Cloud Unit Site, but you can use any storage repository system that you like. Remember that a Portfolio is YOUR tool. You should be able to store your assessment work, reflections, achievements and artefacts in YOUR Portfolio. Once you have completed this assessment piece, add it to your personal Portfolio to use and showcase your learning later, when applying for jobs, or further studies. Curate your work by adding meaningful tags to your artefacts that describe what the artefact represents.
(7) Specific Requirements: Please provide your answers in a Word Document where the page format will be single spaced, 1-inch margins everywhere (top, bottom, left, right) and 12-point Times New Roman font. If you would like to provide references, please use the APA style
[https:
www.deakin.edu.au/students/studying/studysupport
eferencing/apa].
References, graphs, figures and tables are not subject to word limit. You are expected to provide at least 4 digits in your answers. You are expected to provide the computer outputs along with your word submissions. You can do this either by adding your excel file as another attachment or simply by copying and pasting the computer outputs in the word file. For the second method, you can either include the computer outputs in the word file directly in each answer or you can create an appendix of computer outputs at the end of your word file and refer to the appendix while answering the questions.
Regression Models using Cross Section Data
Use the data set in DATA_ASSIGNMENT, which includes information on number of medals won by each country in 2012 and 2016 in the Olympic Games held in London and Rio de Janeiro, respectively, and the characteristics of each country. Country ID is the country identifier. Year denotes the year when the Olympics games were held. Real GDP is the Real Gross Domestic Product of country in billions of dollars. Population is the number of people living in country in millions of people. Total Medals in the sum of gold, silver and
onze medals won by country. Host Country is a dummy variable that takes the value 1 if the country is hosting the Olympic Games and takes the value 0 if the country is not hosting the games. Planned Economy is a dummy variable that takes the value 1 if the country is a planned economy (or was a planned economy in the past), and 0 otherwise.
(i) Present the descriptive statistics of the variables RealGDP, Population, Total Medals. Comment on the means and measures of dispersion (standard deviation, skewness, and kurtosis) of the variables.
(ii) Estimate the following simple regression model of total medals and real GDP.
TotalMedals=β0+ β1RealGDP+u
Write down the estimated sample regression function and interpret both coefficient estimates.
(iii) Now estimate the following simple regression model with a level-log specification.
TotalMedals=β0+ β1log(realGDP)+u
Report your regression results in a sample regression function. Interpret the estimated coefficient of log(realGDP). Provide an explanation of the sign of the slope coefficient.
(iv) Now estimate a model that relates the total number of medals to the real GDP and population:
TotalMedals=β0+ β1realGDP+ β2population+u
Report your results in a sample regression function. Everything else constant, what happens to the total medals if a country’s population increases by 10 million (ignore statistical significance for now)? What can you conclude regarding the comparison of the goodness of fit of this regression model versus the regression model in part (ii)?
(v) Now re-estimate the equation in (iv) but using the log of independent variables. That is, estimate the model,
TotalMedals=β0+ β1log(realGDP)+ β2log(population)+u
Interpret the coefficient of log(population). Test whether log(population) is statistically significant at 1% level.
(vi) Using the estimated model in (v), test whether the coefficient of log(realGDP) is greater than 3 at 5% level of significance.
(vii) Add the variable planned economy to the level-log equation in (v) and estimate the following model.
TotalMedals=β0+ β1log(realGDP)+ β2log(population)+ β3plannedeconomy+ u
Interpret the coefficient of planned economy variable. Test whether the coefficient of plannedeconomy is less than 20 at 1% level of significance.
(viii) Test the overall significance of the model you estimated in part (vii) at 5% level of significance.
(ix) Suppose you want to test whether Host countries win more medals than other countries. Specify a regression model that will enable you to test such a hypothesis using the model in (vii) as a base. Test whether Host countries win more medals than non-host countries at the 5% level of significance.
(x) Using the estimated model in (ix), test whether planned economy and host country variables are jointly significant at the 1% level of significance.
[ XXXXXXXXXX XXXXXXXXXX = 30 Marks]
END OF ASSIGNMENT
Sheet1
Country Year Real GDP (Billions of Dollars) Population (Millions of People) Total Medals Host Country Planned Economy
Afghanistan 2012 20.34 34.39 1 0 0
Albania 2012 12.96 3.21 0 0 0
Algeria 2012 188.68 35.47 1 0 0
American Samoa 2012 0.54 0.07 0 0 0
Ando
a 2012 3.49 0.08 0 0 0
Angola 2012 100.99 19.08 0 0 0
Antigua and Ba
uda 2012 1.13 0.09 0 0 0
Argentina 2012 445.99 40.41 4 0 0
Armenia 2012 10.25 3.09 3 0 0
Aruba 2012 2.46 0.11 0 0 0
Australia 2012 1,371.76 22.30 35 0 0
Austria 2012 418.48 8.39 0 0 0
Aze
aijan 2012 63.40 9.05 10 0 0
Bahamas 2012 7.79 0.34 1 0 0
Bahrain 2012 22.95 1.26 1 0 0
Bangladesh 2012 110.61 148.69 0 0 0
Ba
ados 2012 3.69 0.27 0 0 0
Belarus 2012 55.14 9.49 12 0 1
Belgium 2012 511.53 10.90 3 0 0
Belize 2012 1.47 0.35 0 0 0
Benin 2012 7.29 8.85 0 0 0
Bermuda 2012 6.02 0.06 0 0 0
Bhutan 2012 1.69 0.73 0 0 0
Bolivia 2012 24.43 9.93 0 0 0
Bosnia and Herzegovina 2012 18.09 3.76 0 0 0
Botswana 2012 17.63 2.01 1 0 0
Brazil 2012 2,476.65 194.95 17 0 0
British Virgin Islands 2012 0.91 0.09 0 0 0
Brunei 2012 13.02 0.40 0 0 0
Bulgaria 2012 53.51 7.53 2 0 0
Burkina Faso 2012 10.19 16.47 0 0 0
Burma 2012 50.20 47.96 0 0 0
Burundi 2012 2.33 8.38 0 0 0
Cambodia 2012 12.88 14.14 0 0 0
Cameroon 2012 25.46 19.60 0 0 0
Canada 2012 1,736.05 34.13 18 0 0
Cape Verde 2012 1.90 0.50 0 0 0
Cayman Islands 2012 3.21 0.06 0 0 0
Central African Republic 2012 2.17 4.40 0 0 0
Chad 2012 9.49 11.23 0 0 0
Chile 2012 248.59 17.11 0 0 0
China 2012 7,298.10 1338.30 88 0 1
Colombia 2012 331.66 46.30 8 0 0
Comoros 2012 0.61 0.74 0 0 0
Congo-Brazzaville 2012 14.75 4.04 0 0 0
Cook Islands 2012 0.25 0.02 0 0 0
Costa Rica 2012 41.01 4.66 0 0 0
Croatia 2012 63.85 4.42 6 0 0
Cuba 2012 64.10 11.26 14 0 1
Cyprus 2012 24.69 0.66 1 0 0
Czech Republic 2012 215.22 10.52 10 0 0
Democratic Republic of Congo 2012 15.64 65.97 0 0 0
Denmark 2012 332.68 5.55 9 0 0
Djibouti 2012 1.14 0.89 0 0 0
Dominica 2012 0.48 0.07 0 0 0
Dominican Republic 2012 55.61 9.93 2 0 0
East Timor 2012 1.05 1.12 0 0 0
Ecuador 2012 67.00 14.47 0 0 0
Egypt 2012 229.53 81.12 2 0 0
El Salvador 2012 23.05 6.19 0 0 0
Equatorial Guinea 2012 19.79 0.70 0 0 0
Eritrea 2012 2.61 5.25 0 0 0
Estonia 2012 22.18 1.34 2 0 0
Ethiopia 2012 31.71 82.95 7 0 0
Fiji 2012 3.81 0.86 0 0 0
Finland 2012 266.07 5.36 3 0 0
France 2012 2,773.03 64.90 34 0 0
Gabon 2012 17.05 1.51 1 0 0
Gambia 2012 1.11 1.73 0 0 0
Georgia 2012 14.37 4.45 7 0 0
Germany 2012 3,570.56 81.78 44 0 0
Ghana 2012 39.20 24.39 0 0 0
Greece 2012 298.73 11.32 2 0 0
Grenada 2012 0.82 0.10 1 0 0
Guam 2012 2.77 0.18 0 0 0
Guatemala 2012 46.90 14.39 1 0 0
Guinea 2012 5.13 9.98 0 0 0
Guinea-Bissau 2012 0.97 1.52 0 0 0
Guyana 2012 2.26 0.76 0 0 0
Haiti 2012 7.35 9.99 0 0 0
Honduras 2012 17.26 7.60 0 0 0
Hong Kong 2012 243.67 7.07 1 0 0
Hungary 2012 140.03 10.00 17 0 0
Iceland 2012 14.06 0.32 0 0 0
India 2012 1,847.98 1224.62 6 0 0
Indonesia 2012 846.83 239.87 2 0 0
Iran 2012 386.67 73.97 12 0 1
Iraq 2012 115.39 32.03 0 0 0
Ireland 2012 217.28 4.48 5 0 0
Israel 2012 242.93 7.62 0 0 0
Italy 2012 2,194.75 60.48 28 0 0
Ivory Coast 2012 24.07 19.74 0 0 0
Jamaica 2012 15.07 2.70 12 0 0
Japan 2012 5,867.15 127.45 38 0 0
Jordan 2012 28.84 6.05 0 0 0
Kazakhstan 2012 186.20 16.32 13 0 0
Kenya 2012 33.62 40.51 11 0 0
Kiribati 2012 0.18 0.10 0 0 0
Kuwait 2012 176.59 2.74 1 0 0
Kyrgyzstan 2012 5.92 5.45 0 0 0
Laos 2012 8.30 6.20 0 0 0
Latvia 2012 28.25 2.24 2 0 0
Lebanon 2012 42.19 4.23 0 0 0
Lesotho 2012 2.43 2.17 0 0 0
Liberia 2012 1.16 3.99 0 0 0
Libya 2012 71.95 6.36 0 0 1
Liechtenstein 2012 5.15 0.04 0 0 0
Lithuania 2012 42.73 3.29 5 0 0
Luxembourg 2012 59.47 0.51 0 0 0
Macedonia 2012 10.17 2.06 0 0 0
Madagascar 2012 9.95 20.71 0 0 0
Malawi 2012 5.70 14.90 0 0 0
Malaysia 2012 278.67 28.40 2 0 0
Maldives 2012 2.05 0.32 0 0 0
Mali 2012 10.59 15.37 0 0 0
Malta 2012 8.89 0.42 0 0 0
Marshall Islands 2012 0.17 0.05 0 0 0
Mauritania 2012 4.08 3.46 0 0 0
Mauritius 2012 11.31 1.28 0 0 0
Mexico 2012 1,155.32 113.42 7 0 0
Micronesia 2012 0.32 0.11 0 0 0
Moldova 2012 7.00 3.56 2 0 0
Monaco 2012 5.42 0.04 0 0 0
Mongolia 2012 8.56 2.76 5 0 0
Montenegro 2012 4.55 0.63 1 0 0
Morocco 2012 100.22 31.95 1 0 0
Mozambique 2012 12.80 23.39 0 0 0
Namibia 2012 12.30 2.28 0 0 0
Nauru 2012 0.06 0.01 0 0 0
Nepal 2012 18.88 29.96 0 0 0
Netherlands 2012 836.26 16.62 20 0 0
New Zealand 2012 141.41 4.37 13 0 0
Nicaragua 2012 7.30 5.79 0 0 0
Niger 2012 6.02 15.51 0 0 0
Nigeria 2012 235.92 158.42 0 0 0
North Korea 2012 12.28 24.59 6 0 1
Norway 2012 485.80 4.89 4 0 0
Oman 2012 71.78 2.78 0 0 0
Pakistan 2012 211.09 173.59 0 0 0
Palau 2012 0.18 0.02 0 0 0
Palestine 2012 4.00 4.15 0 0 0
Panama 2012 30.68 3.52 0 0 0
Papua New Guinea 2012 12.94 6.86 0 0 0
Paraguay 2012 23.88 6.45 0 0 0
Peru 2012 176.66 29.08 0 0 0
Philippines 2012 224.75 93.26 0 0 0
Poland 2012 514.50 38.18 10 0 0
Portugal 2012 237.52 10.64 1 0 0
Puerto Rico 2012 99.20 3.98 2 0 0
Qatar 2012 172.98 1.76 2 0 0
Romania 2012 179.79 21.44 9 0 0
Russia 2012 1,857.77 141.75 82 0 1
Rwanda 2012 6.38 10.62 0 0 0
Saint Kitts and Nevis 2012 0.71 0.05 0 0 0
Saint Lucia 2012 1.23 0.17 0 0 0
Saint Vincent and the Grenadines 2012 0.69 0.11 0 0 0
Samoa 2012 0.65 0.18 0 0 0
San Marino 2012 1.49 0.03 0 0 0
Sao Tome and Principe 2012 0.25 0.17 0 0 0
Saudi Arabia 2012 576.82 27.45 1 0 0
Senegal 2012 14.29 12.43 0 0 0
Se
ia 2012 45.04 7.29 4 0 0
Seychelles 2012 1.01 0.09 0 0 0
Sie
a Leone 2012 2.24 5.87 0 0 0
Singapore 2012 239.70 5.08 2 0 0
Slovakia 2012 95.99 5.43 4 0 0
Slovenia 2012 49.54 2.05 4 0 0
Solomon Islands 2012 0.84 0.54 0 0 0
Somalia 2012 1.07 9.33 0 0 0
South Africa 2012 408.24 49.99 6 0 0
South Korea 2012 1,116.25 48.88 28 0 0
Spain 2012 1,490.81 46.07 17 0 0
Sri Lanka 2012 59.17 20.86 0 0 0
Sudan 2012 55.10 43.55 0 0 0
Surinam 2012 3.79 0.53 0 0 0
Swaziland 2012 3.98 1.06 0 0 0
Sweden 2012 538.13 9.38 8 0 0
Switzerland 2012 635.65 7.83 4 0 0
Syria 2012 59.83 20.45 0 0 0
Taiwan 2012 876.04 23.17 2 0 0
Tajikistan 2012 6.52 6.88 1 0 0
Tanzania 2012 23.71 44.84 0 0 0
Thailand 2012 345.65 69.12 3 0 0
Togo 2012 3.59 6.03 0 0 0
Tonga 2012 0.44 0.10 0 0 0
Trinidad and Tobago 2012 22.48 1.34 4 0 0
Tunisia 2012 45.86 10.55 3 0 0
Turkey 2012 773.09 72.75 5 0 0
Turkmenistan 2012 24.11 5.04 0 0 0
Tuvalu 2012 0.04 0.01 0 0 0
Uganda 2012 16.81 33.42 1 0 0
United Kingdom 2012 2,431.59 62.23 65 1 0
Ukraine 2012 165.25 45.87 20 0 0
United Arab Emirates 2012 360.25 7