ANL551 Data Analytics for Decision Makers Report, SUSS, Singapore: In a theoretically ‘ideal’ labor market, applicants with the same product attributes should be equally
Instructions
Part A
- Statistical Analysis
Part B
- B-1 Professional Report
- B-2 Ministerial Report
Problem Description
In a theoretically ‘ideal’ labor market, applicants with the same product attributes should be equally paid when hired by any organization. The existence of private-MNC and private-SME pay gap for individuals with similar productive characteristics thus has implications for efficiency and equity in the labor market. For instance, this implies that employees in the private-MNC sector receive rents at the cost of taxpayers, and the private-SME sector activities may be crowded out as it becomes hard to retain talents.
You have been appointed by the Ministry of Manpower to analyze the private-MNC and private-SME pay gap in Singapore/Malaysia. The data are drawn from the 2018/2019 survey. Using the tools learned in your current Business Statistics course provide the ministry with an analysis of the MNC-SME pay gap. You may assume the officers at the ministry have a good understanding of basic statistics. In addition, the ministry would like you to prepare a ministerial brief to illustrate the key findings of your analysis to the Minister for Manpower.
Answer each of the following questions, showing your analysis in detail (Excel), and use it in your report. Use the 5% significance level and the 95% confidence level where relevant.
1. Focusing on the variable wage for the MNC sector employees only for this question: as shown in several lectures there are two distinct methods of calculating summary or descriptive statistics using Excel. This question requires you to use both methods. First, use Excel Data Analysis Tool Pack (the descriptive statistics option) to calculate and interpret the summary statistics. Second use Excel to calculate all descriptive statistics documented in your report. These calculations should be carefully laid out in Excel and should NOT use any hard-wired Excel statistical functions e.g., Average, Median, Mode, STDEV et al. You can use the Excel sort command, the sum command, and any other non-statistical Excel commands.
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2. Repeat step 1 above for the variable wage for the SME sector employees.
3. Draw a histogram of the wage distribution for the MNC and SME sector employees respectively. Interpret the graphs carefully.
4. What are the main differences in demographic and social-economic characteristics between employees in the MNC and SME sector? Aid your answer with appropriate tables/graphs.
5. Propose a statistical method to estimate the mean hourly wage rate for all MNC sector employees and all SME sector employees, respectively. Clearly label your diagram and indicate any assumptions made and explain carefully.
6. A media report claims that the mean hourly wage rate for all MNC sector employees was $ 49. Do you agree? Perform a hypothesis test at the 5% significance level. Clearly label your diagram and indicate any assumptions made. Explain carefully any potential errors in your decision-making.
7. Since the answer to Question 5 above suggests a higher mean hourly wage rate in the MNC/SME sector, an office in the ministry hence concludes that the population mean hourly wage rates are not equal between the two sectors. Do you agree? Propose a statistical method to examine if the population mean hourly wage rates are equal for the MNC and SME sector. Clearly indicate any assumptions made.
8. Should the Minister be concerned if the population mean hourly wage rate is higher in the MNC sector? Propose at least two (2) policies for the ministry to address this issue.
Part B: Write a ministerial brief of no more than 200 words containing no more than 3 graphs on the MNC-SME pay gap and any other interesting findings that would be of policy relevance to the Minister. Draw on the relevant evidence you have gathered from your analysis, as well as other information/evidence not covered here but you believe is useful. Your brief should summarize your results from part A in a non-technical way and provide relevant conclusions.
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