[Solved]You are asked to work on a project on wage inequality and the determinants of wage rates in city X in Y province in China.

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[Solved]You are asked to work on a project on wage inequality and the determinants of wage rates in city X in Y province in China.

T13301 Advanced Quantitative Methods and IT Skills for Business

Data: Download the datasets wage.xls from “Coursework” folder on Moodle.

Word Limit: 2000 words (excluding tables, figures, footnotes and references).

The Task: You are asked to work on a project on wage inequality and the determinants of wage rates in city X in Y province in China.

You have been provided with the data from a survey of 359 employees in this city from three sectors, manufacturing, construction and other. The dataset provides information of the following characteristics: monthly wage rates, age, education, sex, occupation, Party member status, working experience, marital status, hukou, etc.

You are asked to address the following issues:

(1)  Given the complex data set, explain how you will proceed in order to provide evidence on wage inequality. (15%)

(2)  Provide the evidence of wage inequality you have found and comment on the evidence. (30%)

(3)  Explain how you will investigate determinants of wage rates of city X in province Y in China. (15%)

(4)  Present the determinants of the wage rates and interpret your results. (30%)

(5)  Draw sensible conclusions and provide policy suggestions to the local government. (10%)

You should use MS-Excel or a similar package to carry out statistical and graphical data analysis.

List of Variables:

ID: identifier for the employee

WAGE: monthly wage (1000 RMB)

EDUCATION: number of years of education

SEX: indicator variable for sex, (1=Female, 0=Male)

EXPERIENCE: number of years of working experience

AGE: age of the employee (years)

PARTY MEMBER: indicator variable for Communist Party Member status (1= Party member, 0=not Party member)/

SECTOR: sector of the employment (1=Manufacture, 2= Construction, 0= others)

MARR: Marital Status (0 = unmarried, 1=married)

OCCUPATION: occupational category (1=Management, 2=sales, 3=clerical, 4=service. 5=professional, 6=others)

HUKOU: indicator variable of Hukou (i.e. household registration) (1= local hukou, 0= hukou not in X city)