* 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