* OLS Model for the Earnings Equation
*
* Keywords:
* regression, ols, log-linear, dummy, earnings, age, education, kids, earnings,
* equation, married, women
*
* Description:
* We illustrate how to estimate a log-linear Multiple OLS model for the
* Earnings Equation for women, making use if generated standard and
* dummy variables
*
* Author(s):
* Noel Roy
* Skif Pankov
*
* Source:
* William H. Greene, Econometric Analysis - 7th Edition
* Pearson International Edition, Chapter 5, Example 5.2 (page 156)
* Table F5-1.shd is described as follows:
* LFP "A dummy variable = 1 if woman worked in 1975, else 0";
* WHRS "Wife's hours of work in 1975";
* KL6 "Number of children less than 6 years old in household";
* K618 "Number of children between ages 6 and 18 in household";
* WA "Wife's age";
* WE "Wife's educational attainment, in years";
* WW "Wife's average hourly earnings, in 1975 dollars";
* RPWG "Wife's wage reported at the time of the 1976 interview
* (not the same as the 1975 estimated wage).
*
* To use the subsample with this wage, one needs to select 1975
* workers with LFP=1, then select only those women with non-zero RPWG.
* Only 325 women work in 1975 and have a non-zero RPWG in 1976.";
* HHRS "Husband's hours worked in 1975";
* HA "Husband's age";
* HE "Husband's educational attainment, in years";
* HW "Husband's wage, in 1975 dollars";
* FAMINC "Family income, in 1975 dollars.
* This variable is used to construct the property income variable.";
* MTR "This is the marginal tax rate facing the wife, and is taken from
* published federal tax tables (state and local income taxes are excluded).
* The taxable income on which this tax rate is calculated
* includes Social Security, if applicable to wife.";
* WMED "Wife's mother's educational attainment, in years";
* WFED "Wife's father's educational attainment, in years";
* UN "Unemployment rate in county of residence, in percentage points.
* This taken from bracketed ranges.";
* CIT "Dummy variable = 1 if live in large city (SMSA), else 0";
* AX "Actual years of wife's previous labor market experience";
* Source: 1976 Panel Study of Income Dynamics,
* based on data for the previous year, 1975.
* Of the 753 observations, the first 428 are for women with positive hours
* worked in 1975, while the remaining 325 observations are for women who
* did not work for pay in 1975. A more complete discussion of the data is
* found in Mroz [1987], Appendix 1.
sample 1 753
* Reading the datafile and naming the variables
read (TableF5-1.shd) lfp whrs kl6 k618 age educ ww / skiplines=1
* Instructing not to display a warning when an observation is skipped -
* the model requires us to skip around 300 observations in our data
set nowarnskip
* Instructing to skip an observation if (1-lfp) is equal to 1 (is TRUE) - i.e.,
* when a woman does not work
skipif (1-lfp)
* Generating the natural log of weekly earnings, square of age and the
* dummy indicating whether this woman has kids
genr lnearn=log(ww*whrs)
genr age2=age**2
genr kids=dum(kL6+k618)
* Running an OLS regression of lnearn on age, age2, educ and kids, specifying
* that the model estimated is log-linear and to display a covariance matrix of
* estimated coefficients
ols lnearn age age2 educ kids / pcov loglin
stop