Educational_Attainment {bqror}

Educational Attainment study based on data from the National Longitudinal Study of Youth (NLSY, 1979) survey.

Description

Educational Attainment study based on data from the National Longitudinal Study of Youth (NLSY, 1979) survey.

Usage

data(Educational_Attainment)

Details

This data is taken from the National Longitudinal Study of Youth (NLSY, 1979) survey and corresponds to 3,923 individuals. The objective is to study the effect of family background, individual, and school level variables on the quantiles of educational attainment conditional on the covariates. The dependent variable i.e. the educational degree, has four categories given as less than high school, high school degree, some college or associate's degree, and college or graduate degree. The independent variables include intercept, square root of family income, mother's education, father's education, mother's working status, gender, race, and whether the youth lived in an urban area at the age of 14, and indicator variables to control for age-cohort effects.

Value

Returns data with components

mother_work:

Indicator for working female at the age of 14.

urban:

Indicator for the youth living in urban area at the age of 14.

south:

Indicator for the youth living in South at the age of 14.

father_educ:

Number of years of father's education.

mother_educ:

Number of years of mother's education.

fam_income:

Family income of the household in $1000.

female:

Indicator for individual's gender.

black:

Indicator for black race.

age_cohort_2:

Indicator variable for age 15.

age_cohort_3:

Indicator variable for age 16.

age_cohort_4:

Indicator variable for age 17.

dep_edu_level:

Four categories of educational attainment: less than high school, high school degree, some college or associate's degree, and college or graduate degree.

References

Rahman, M. A. (2016). '"Bayesian Quantile Regression for Ordinal Models."' Bayesian Analysis, 11(1): 1-24. DOI: 10.1214/15-BA939

Jeliazkov, I., Graves, J., and Kutzbach, M. (2008). '"Fitting and Comparison of Models for Multivariate Ordinal Outcomes."' Advances in Econometrics: Bayesian Econometrics, 23: 115'-'156. DOI: 10.1016/S0731-9053(08)23004-5

Jeliazkov, I., and Rahman, M. A. (2012). '"Binary and Ordinal Data Analysis in Economics: Modeling and Estimation"' in Mathematical Modeling with Multidisciplinary Applications, edited by X.S. Yang, 123-150. John Wiley '&' Sons Inc, Hoboken, New Jersey. DOI: 10.1002/9781118462706.ch6

See Also

Survey Process.