In 1980, respondents in the NLSY79 sample were adminstered the Armed Services VocationalAptitude Battery (ASVAB) in a joint e/ort of the U.S. Departments of Defense and MilitaryServices to update the ASVAB norms. In total, 11,914 NLSY79 respondents (94% of the sam-ple) participated in the test. The ASVAB measures di/erent aspects of ability, knowledge andskill in 10 tests, each in one of the following areas: general science, arithmetic reasoning, wordknowledge, paragraph comprehension, numerical operations, coding speed, auto and shop infor-mation, mathematics knowledge, mechanical comprehension and electronics information. Scoreson these tests are used to estimate each respondent°s percentile score in the Armed Forces Qual-ifying Test (AFQT), as well as our measures of knowledge and ability. The AFQT score is afunction of the individual°s score on tests in arithmetic reasoning, word knowledge, paragraphcomprehension and numerical operations. Our measure of innate ability uses these tests plus atest in coding speed, while our measure of acquired knowledge includes tests in general science,auto and shop information, mathematics knowledge, mechanical comprehension and electronicsinformation. Our results are robust to slightly di/erent decompositions.38
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Panel A: Any Investment IncomeYears of schooling3.55 ***2.40 ***(0.01)(0.02)Num of Observations14 727 8794 218 820This table reports results from a regression of investment income on education, gender, race, age (3-year age groups), birth cohort (10 year cohorts), state of birth, state of residence, census year and a cubic polynomial in earned income. Only the education coefficient is reported. The sample comprises individuals reported in the 5% samples of the 1980, 1990, and 2000 census. We include 18-75 year olds (50-75 year olds when considering retirement income). The dependent variable of interest is whether the household receives income from investments or retirement savings (Panel A), the amount (Panel B), and where the household falls in the entire distribution of investment or retirement income (Panel C). Regressions also include state of residence fixed effects interacted with a dummy variable for being born in the South and turning age 14 in 1958 or later to account for the impact of Brown v. Board of Education for blacks. Top-coded individuals (see text) are dropped in panels B and C. Standard errors, corrected for arbitrary correlation within state of birth-year of birth, are in parentheses. (Numbers with *** indicate significance at the 1-percent level.)Table I(2)OLS Estimates of the Effect of Schooling on Income from Various Sources(1)Income from Retirement SavingsIncome from Investments14,727,8794,218,820R-Squared0.1830.177Panel B: Amount of Investment IncomeYears of schooling273.43 ***548.52 ***(5.00)(4.84)Num of Observations14,655,3924,185,100R-Squared0.0900.147Panel C: Percentile of Investment Income in DistributionYears of schooling3.37 ***2.28 ***(0.01)(0.02)Num of Observations13,255,9803,854,646R-Squared0.1680.179