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You will use data from the fifth wave of the National Income Dynamics Study (NIDS)

INSTRUCTIONS TO CANDIDATES
ANSWER ALL QUESTIONS

Data

You will use data from the fifth wave of the National Income Dynamics Study (NIDS), collected from around 40 000 individuals in South Africa in 2017. The dataset has been uploaded to Moodle, in the Block 1 Assignment Resources folder. The sample has been restricted to adults (aged 18 and older; approx. 22 000 individuals). The questionnaire that NIDS used to collect data from these individuals is provided on Moodle; you may consult with this if you need more information about the variables. Some additional variables have been created for you to use (listed at the end of the dataset, from male onwards). You will need to create other variables for your analysis.

Structure and formatting of the write-up

1. Font: Your answers should use Times New Roman; font size 12pt. You do not need to provide any further discussion or interpretation beyond answering the specified questions.

2. Stata commands and output must use Courier New in a font size small enough to fit onto one line (usually font size 9pt). Alternatively, Stata commands and output may also be pasted as a picture, provided that the image is clear

3. Line spacing and alignment: Line spacing should be set to 1.5 with 6pts after a paragraph.

4. Appendices:

a. Do file: This is the Stata list of all correct commands used in the assignment to produce all variables and all output. The do file should be neatly organised, with well-labelled variables. Delete only any incorrect commands.

b. Log file: This is the Stata output file showing all output. It must be readable with no formatting errors.

 

 

Tasks and questions

1. Creating variables [16 marks]

Generate the following additional variables:

Potential work experience and experience squared, as per the Block 1 practical.

Define married=1 when best_marstt is “Married”, =0 for other marital status, and =missing

if the information about marital status is unknown.

Define urban=1 when geo2011 is “Urban”, =0 for other area types, and =missing for “Not applicable”.

Interaction between male and urban.

Define upward=1 if the person has been upwardly economically mobile, =0 if their economic position has been static or downwardly mobile, and =missing if the information about their economic position is unknown. For this assignment, someone is defined as upwardly mobile if the income step that their household is on now is higher than what it was when they were aged 15. Use the variables step15 and stepnow to create this new dummy variable.

Define English language proficiency dummy engprof=1 if the person can both read and write

 

English very well, =0 if their reading and/or writing level in English is at a lower level, and =missing if their reading and/or writing level is unknown. Use the variables edlitrden and

edlitwrten to create this new dummy variable.

Paste the commands used and their output into your write-up

 

 

2. Education and other determinants of hourly earnings [40 marks]

Research problem: Investigate the role of human capital, demographic factors, and location in determining the earnings of employed individuals in South Africa.

2.1 Estimation

Use OLS to estimate the following model, Model 1, for individuals whose main job is regular work. The dependent variable is:

lnhwage: natural log of hourly earnings from main job

The explanatory factors to be included in the model are as follows:

education: a three-level spline (measuring years of education completed at primary, secondary and tertiary levels), which is estimated by including the three variables yrschool wsecondary and ztertiary

experience: years of potential work experience, and experience squared

race: whether the individual reports being African, coloured, Indian, or white (ref cat = African)

gender: whether the individual reports being male or female (ref cat = female)

marital status: whether the individual is married or not (ref cat = not married)

location: whether the individual lives in an urban area or not (ref cat = not urban)

male*urban: interaction between the dummy variables for gender and location type

Paste the command used and the output from Stata into your write-up. It must be clearly legible. [3]

2.2 Interpretation

Use a 5% significance level in your answers, where applicable.

a) Using the education spline function, interpret the value of the returns to an extra year of primary, secondary and tertiary education. What does your answer imply about the importance of education in the labour market? [8]

b) Discuss the nature of the estimated relationship between work experience and earnings. Use a table of values to assist your answer. Calculate at what point, if any, the direction of the relationship changes. [8]

 

 

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