Homework #2 (Due Apr. 7th 2010)
1. Consider the familiar wage regression function,
-----   (1)
where W is the wage rate, D is a dummy variable for gender (1 for female and 0 otherwise), X2 is education (years of schooling), X3 is experience (years of working experience), u is the error term, B’s are parameters, and the subscript i denotes individuals.
Given the data “WAGES” in the learncare, estimate Eq.(1) by OLS, print the results, and interpret the estimated individual coefficients of X2 and X3.

2.Now consider the augmented version of the above function,

    -----   (2)

where (Di*X2i) and (Di*X3i) are the interactive terms, and v is a new error term (other variables are as defined before).
Given the same data, estimate Eq.(2) by OLS, print the results, and interpret the estimated individual coefficients of the interactive terms.

Homework #3 (Due Apr. 7th 2010)
Consider the familiar wage regression function,
-----   (1)
where W is the wage rate, D is a dummy variable for gender (1 for female and 0 otherwise), X2 is education (years of schooling), X3 is experience (years of working experience), u is the error term, B’s are parameters, and the subscript i denotes individuals.
Given the data “WAGES” in the learncare, estimate Eq.(1) by OLS, and conduct the following heteroskedasticity tests: a) the White’s test, and b) the Goldfeld-Quandt test assuming that gender is the variable which is causing heteroskedasticity. Given the results (print them out), is there evidence of heteroskedasticity?
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明早要交哪！！