Project Description:
The report should describes the question/s of interest, how you used your data set to analyze these question/s with details on the steps you used in your analysis, your findings about your question of interest. Specifically, your report should contain the following:
1. Cover page (Title, names, IDs of the group members, Course number)
2. Abstract: A one paragraph summary of what you set out to learn, and what you ended up finding. It should summarize the entire report.
3. Introduction: A discussion of what question/s you are interested in.
4. Description of your used data set: give details about how the data set was collected and the variables in the data set.
5. Provide descriptive statistics of each variable in the report (mean, median, variance, standard deviation, maximum, minimum,... etc.).
6. Write your regression model and define your variables.
7. Run the estimation of the regression model using Excel to get the coefficients and the standard errors of each coefficient and plot the necessary graphs to check the required conditions about the error terms.
8. Analyze the Excel output: Test for each coefficient of the regression model and for the regression model as a whole. Assess the regression model: how well does it fit the data? Are the required conditions about the errors satisfied?
9. Results: Provide inferences about the questions of interest and discussion.
10. Conclusion: provide brief conclusions about the results of your study
Instructions: you must do the following:
1- Collect data related to the topic that has been chosen. A soft copy of the data must be sent to the instructor (Excel File). The document will be part of the evaluation process.
2- Plot the data for the three series and include the graphs in the report.
3- Run the estimation of the regression model using Excel to get the coefficients and the standard errors of each coefficient (as shown in class) and plot the necessary graphs to check the required conditions about the error terms.
4- Analyze the Excel output: Test for each coefficient of the regression model and for the regression model as a whole. Assess the regression model: how well does it fit the data? Are the required conditions about the errors satisfied?
Examples of questions of interest are as follows:
Estimating a Multiple Regression Model for GCC countries:
1- The impact of Exports and FDI (Foreign Direct investment) on GDP in Qatar (1990 - 2015)
2- The impact of Consumption and Investment on the GDP in Qatar (1990 - 2015)
3- The impact of Exports and FDI (Foreign Direct investment) on GDP in Country (Y) (1990- 2015)
4- The impact of Consumption and Investment on the GDP in Country (Y) (1990 - 2015)
5- Is the unemployment rate in Country (Y) is related to economic measures such as interest rates, stock returns, and the inflation rate?
The data set should preferably contain at least 30-60 observations, and ideally, but not restricted to, 3 variables.
Below are a few potential sources of data:
a. The website of the Central Banks of Qatar, Saudi Arabia, Bahrain, UAE, Oman and Kuwait (check the statistical reports of the central banks).
b. Bloomberg
https://www.sama.gov.sa/en-US/EconomicReports/Pages/YearlyStatistics.aspx.