Examining country level data across 63 countries

MAE356 T2 2014 – Assignment Details
Due Date: 11:59pm Friday Sept 19th 2014
Word Limit: Max. 1500 words excluding appendices, figures and tables.
Weight: 20% of overall final grade.
Details:
This is an INDIVIDUAL Assignment and while we discourage plagiarism, it is not collusion if you discuss the questions with other students but 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.
In this assignment, you will be examining country level data across 63 countries chosen at random. In particular, we are interested in the determinants of a country’s economic wellbeing. You will not need a working knowledge of macro-economics for this assignment but it doesn’t hurt. The assignment will mainly involve quantitatively analysing the data and you may also need to do some research on some questions through your textbook or other online resources.
Data:
The data along with data definitions are provided in the file MAE356_t2_2014_Assign.XLSX which is provided via Cloud Deakin. Where possible, data has been sourced from the World Bank Database (data.worldbank.org) for the year 2011.
Submission Details:
Once completed, you will need to submit the your ‘Microsoft Word’ document via Cloud Deakin. You must submit a single file only and do not need to fill out an assignment attachment sheet but should contain a cover page with your name and student ID.
Please do not submit it as a PDF as we will be doing a word count. Any tables, figures and appendices will not be included in the word count so use them wisely.
We will not be marking your Excel work file so you must ensure the Word document is self-contained (i.e. all your tables and figures should be in the word document

SUB WORK

2A
Run the following simple linear regression function on GDP per Capita and life expectancy. Present your regression table along with the interpretation of the intercept and slope coefficients. Additionally, conduct a hypothesis test to see if having 5 extra year of life expectancy could increase GDP per capita by more than $20,000. Show all steps for the hypothesis test and use
Adjusted R squared is a coefficient of determination, which tells us the variation in the dependent variable due to changes in the independent variable. From the findings in the above table, the value of adjusted R squared was 0.25, an indication that there was variation of 25.1% GDP per Capita due to life expectancy at 95% confidence interval. This shows that 25.1 % changes in GDP can be caused by changes in life expectancy. R is the correlation coefficient, which shows the relationship between the study variables. From the findings shown in the table above, there was a weak relationship between the variables, therefore, at 95%, the hypothesis is rejected as shown by sig. of 0.111, which is beyond 0.005.
R   203
R Square   0.41
Adjusted R   0.25
Stardard Error   2251.71765
Observation   62

ANOVA df ss ms f Sig

Regression   1   1.12111E   1.33E+07   2.617   0.111
Residual   61   3.09111E   5070232.4
Total   62   3.2121E

coefficient   Stardard Error   P value   Lower 95%   Upper 95%
Intercept   -5968.296   4294.492   0.17   0.021   0.081
LIFEEXP   91.344   56.47   0.111   0.412   567

The constant is -5968.296 and the slope of 91.334, therefore, conduct a hypothesis test to see if having 5 extra year of life expectancy could increase GDP per capita by more than $20,000 and using the equation of the line,,, Y = -5968.296 + 91.334(5 years),,which is – 5511.626 and therefore by 5 extra years the GDP will have decreased by – 5511.626 and this in line with the rejection of the hypothesis.

3B
Based on the multiple regression results you had in Part 3a, test the joint significance of the variables INFLATION, ARTICLE and POP on GDP. Show your steps/calculation and use .
R   0.988
R Square   0.975
Adjusted R   0.973
Stardard Error   2251.71765
Observation   372.80081

ANOVA df ss ms f Sig

Regression   5   3.14332   1.33E+07   452.767   0
Residual   57   7921342   5070232.4
Total   62   3.22111

coefficient   Stardard Error   P value   Lower 95%   Upper 95%
Intercept   359.356   130.798   0.008   0.021   0.081
MKTCAP   0.193   0.106   0.74   0.412   567
ENERGY   0.001   0   0.026   0.212   231
IMPORT   -5.496   2.404   0   0.001   0.233
ARTICLE   0.52   0.009   0.001   0.234   0.344
POP   -1.8118   0   0.662   0.234   0.331

Adjusted R squared is a coefficient of determination, which tells us the variation in the dependent variable due to changes in the independent variable. From the findings in the above table, the value of adjusted R squared was 0.988, an indication that there was variation of 98.8% GDP per Capita due to test of the joint significance of the variables INFLATION, ARTICLE and POP on GDP. There is a joint significance of the variables INFLATION, ARTICLE and POP on GDP. The findings in the table above show that there was a strong positive relationship between the joint variables and, therefore, at 95%, the hypothesis is rejected as shown by sig of 0.000, which is less than the prescribed 0.05 of rejecting the null hypothesis at 95% confidence interval.