I need an explanation for this Economics question to help me study.
1) Prepare variables for regression:
i) You’ve been given some code turning the “SEX” variable into a “female” variable that is equal to one when the person is female, and equal to zero if the person is male.
ii) The next part is up to you. Instead of having all the provinces, create indicator variables for four regions: east (PEI, New Brunswick, Nova Scotia, and Newfoundland and Labrador), qc (Quebec), on (Ontario), and west (Alberta, Manitoba, Saskatchewan, BC).
iii) The AGE_12 variable is not a true continuous variable, but rather age divided into twelve categories. Create a new age variable that is set to the midpoint of each age category. i.e., For each person in the AGE_12 category “15 to 19 years,” set their age in your new variable to be 17. For the 70+ category, set observations to be aged 72.
iv) In this lab, we will be examining hourly earnings (HRLYEARN). Create a variable that is equal to zero if somebody has a missing value for their hourly wage, equal to one if they have a non-missing hourly wage, and equal to missing if they are unemployed (use LFSSTAT).
v) Only keep people in the sample if they have a non-missing hourly wage.
2) Run the following regressions. Note that for ln and squared variables, you first have to create the variable before you can use it in a regression.
Note: ln(.) is the natural logarithm function.
a) reg HRLYEARN age female Explain/interpret the meaning of the coefficient on age and female.
b) reg HRLYEARN age female, robust What is the difference between the regression in (a) and that in (b)? Which is preferable? Why?
c) reg ln(HRLYEARN) age female Explain/interpret the meaning of the coefficient on age and female.
d) reg HRLYEARN ln(age) female Explain/interpret the meaning of the coefficient on age.
e) reg ln(HRLYEARN) ln(age) female Explain/interpret the meaning of the coefficient on age.
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