Question

# Hi, I'm stuck on the following lobor economics question, and don't know what regressions I should use to answer

it:

Suppose you obtain data on a sample of working adult individuals in the U.S. (indexed by i = 1, ..., N ), who self-reported the following variables:

• labinci = annual wage and salary income from labor (after taxes)• nonlabinci = annual non-labor income (after taxes)

• hoursi = annual hours worked

• educi = total years of completed schooling

• agei = age in years

• malei = a dummy variable equal to 1 for males, 0 for females

Using these data, how would you **estimate the wage elasticity of labor supply**? Write down a specific regression, and feel free to define any new variables using the ones you already have, if you think they would be relevant. Make sure to mention what your **coefficient of interest** is.

How would you test each of the following three hypotheses:

A) the substitution effect dominates the income effect.

B) leisure is a normal good.

C) all else equal, men work significantly more hours than women.

**Write down specific null (H0) and alternative (H1) hypotheses using parameters from the regression equation you wrote down above. **

Suppose you estimate an elasticity of −0.2. How would you **interpret** this?

Suppose you are particularly worried about people misreporting their an- nual work hours. Do you think the **true labor supply elasticity would be larger or smaller than −0.2?**

Besides measurement error, what other **potential concerns do you have about this regression** approach (e.g. with respect to the key OLS assumptions being potentially violated)? **Which slope coefficients do you think may be biased**? Explain.

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