BAA1024 Global Competitiveness Analysis Assignment: Determinants, Human Development Impact & Business Performance Insights
Background
Examining ‘Global Competitiveness’ across nations is a complex yet profoundly important endeavor to assess business sector performance. How competitive are businesses? What makes it different across countries? Do human development differences contribute? Most importantly, what are the underlying factors that determine our business competitiveness levels?
These questions are undoubtedly relevant as studying Global Competitiveness is crucial in research areas in economics and social science.
For this Group Assignment, your task is to investigate the determinants of business competitiveness across countries. Using the data spanning from 2013 to 2023, you will analyze data across at most 161 countries, depending on the NA cases for some countries in some variables.
Data
Download the data file from eLearn. The data file contains the following variables:

Data Presentation
The dataset contains 1771 observations from the year 2013 to 2023. For this Group Assignment, you are required to conduct data analysis based on the year and variable names assigned to your group.
Refer to the Data file (Excel) and look at the sheet named “group numbers” to identify data for your group.
Refer to the sheet named “WEF Data” and filter the data based on the specific year assigned to your group and select the variable columns (e.g. if the year assigned is 2018, filter observations for the year 2018, and keep the pillar number mentioned in the group information).
The observations across years are the same, equaling 161 before the removal of NAs. You have to report the after-NA removal sample and the sample reported by regression, which should be the same and will be checked in the cleaned data file.
Once you have filtered your data, copy and paste the data into a new Excel sheet. This Excel sheet should be labelled according to the group number (e.g. if the group number is 10, you name it Group10). Your analysis should be based on the data in this new Excel sheet.
For the various analyses that you may need to conduct, ensure that it is properly labelled if the results are stored in different Excel sheets and add their description in the report.
Ensure that your analyses are conducted in a single Excel file. This is the Excel file that you will need to submit for marking.
Independent Variables

Assignment Task
You are required to produce a research report based on the following guidelines:
1. Introduction[10 marks]
- Include a problem statement and the motivation of the study that links why improving the dependent variable is important and how the pillars are relevant.
- Ensure that you include appropriate citations, and each unique citation should have its APA-formatted reference.
- Your introduction should not be more than 1 page.
2. Data Preparation and Exploratory Data Analysis [30 marks]
- For each step, add a heading using heading numbers like 2.1, 2.2, etc if there is any output, show and interpret; if no output, then only briefly mention how it was done.
- Replace the NAs with empty cells. Do not remove rows.
- Add a code for development level using the appropriate LOOKUP formula from the sheet name ‘development categories’ to match ‘Level name’ and ‘Level code’, and insert them into your data file.
- Construct a table in a separate sheet that groups the data across the ‘Level name’ category. Ensure that you present the mean value of your dependent and independent variables for each Level name. Make an appropriate chart and interpret the output.
- Generate and report suitable summary statistics for your dependent variable and your explanatory variable. Interpret the output of at least two variables.
- Produce two (2) appropriate charts to visualise the data. These two chart types must be different. Ensure that the results are appropriately described. Interpret the chart.
3. Empirical Analysis[30 marks]
- Briefly explain each test’s method used in empirical analysis below, along with the outputs. You can use heading numbers like 3.1, 3.2, etc, for each analysis done in this section.
- Identify and conduct an appropriate test to investigate whether there are significant differences in the mean ‘Global Competitiveness Index’ across Development Levels.
- Specify and estimate an appropriate model to predict the ‘Global Competitiveness Index’.
- Make a correlation matrix of the dependent and provided explanatory variables
- Regress the dependent variable against the provided explanatory variables and the ‘Level code’.
- Based on your results, which variables significantly influence the ‘Global Competitiveness Index’? by populating the following table.
- The interpretation of variables must include clarifying the direction, magnitude, and significance of the variables.
Report and explain the tests result accordingly.

4. Discussion and Implications[10 marks]
- Based on the analysis you have conducted, summarise the key findings and provide some implications/recommendations to policymakers and key stakeholders.
- This section should not be more than 1 page.
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