Search Results

View Selected Citations Select and View All Search Citations

Source: Social Indicators Research

Resulting in 8 citations.

1.	Burton, Russell P. D. Rushing, Beth Ritter, Christian Rakocy, Andrea
1.	Roles, Race and Subjective Well-Being: A Longitudinal Analysis of Elderly Men Social Indicators Research 28,2 (February 1993): 137-156 Cohort(s): Older Men Publisher: Springer Keyword(s): Racial Differences; Social Roles; Well-Being Permission to reprint the abstract has not been received from the publisher. Examined the impact of race and social roles on subjective well-being in elderly men, using data from the older male cohort of the National Longitudinal Survey of Labor Market Experience. Data from interviews with 2,285 men (aged 55-69 yrs at Time 1 and 60-74 yrs at Time 2) were analyzed. Contrary to expectations, results did not indicate lower subjective well-being for Black men than for White men. Findings demonstrate that particular role configurations affect happiness and that these effects are different for Blacks and for Whites. (PsycINFO Database Copyright 1993 American Psychological Assn, all rights reserved)
	Bibliography Citation Burton, Russell P. D., Beth Rushing, Christian Ritter and Andrea Rakocy. "Roles, Race and Subjective Well-Being: A Longitudinal Analysis of Elderly Men." Social Indicators Research 28,2 (February 1993): 137-156.

2.	Kaplan, Seth A. Winslow, Carolyn J. Luchman, Joseph N.
2.	What are We Working For? Comparing the Importance of Job Features for Job Satisfaction over the Career Span Social Indicators Research 148 (2020): 1021-1037. Also: https://link.springer.com/article/10.1007/s11205-019-02231-8 Cohort(s): NLSY79 Publisher: Springer Keyword(s): Job Characteristics; Job Satisfaction; Life Course Permission to reprint the abstract has not been received from the publisher. This study examines the impact, relative importance, and unique predictive validity of changes in a host of job features and other relevant factors on job satisfaction over a 35-year period using data from the 1979 National Longitudinal Survey of Youth cohort (12,686 respondents). The design of our analysis eliminated of the impact of established between-person correlates of job satisfaction (e.g., personality, cognitive ability), thereby providing for direct examination of within-person change in the focal variables. Results using a first-difference regression and a relative weights analysis revealed that changes in intrinsic, social, and extrinsic features corresponded to changes in satisfaction, but with differing magnitudes. Specific features (e.g., different dimensions of the Job Characteristics Model) generally were unique predictors when all variables were considered. Findings regarding the importance of various features substantially deviate from employees' reports about contributors to job satisfaction and, in some cases, also differ from findings drawn from cross-sectional data.
	Bibliography Citation Kaplan, Seth A., Carolyn J. Winslow and Joseph N. Luchman. "What are We Working For? Comparing the Importance of Job Features for Job Satisfaction over the Career Span." Social Indicators Research 148 (2020): 1021-1037.

3.	Mullis, Randolph J.
3.	Measures of Economic Well-Being as Predictors of Psychological Well-Being Social Indicators Research 26,2 (March 1992): 119-135 Cohort(s): Older Men Publisher: Springer Keyword(s): Economic Well-Being; GED/General Educational Diploma/General Equivalency Degree/General Educational Development; Income; Income Dynamics/Shocks; Well-Being Permission to reprint the abstract has not been received from the publisher. Uses data from the National Longitudinal Surveys Mature Male cohort for 1976 to explore the relationship between economic well-being (EWB) and psychological well-being (PWB). This research indicates that a comprehensive measure of EWB based on permanent income, annualized net worth, and household economic demands performs better as a predictor of PWB than conventional measures of EWB, particularly current reported income. Statistically, the results are significant, yet the percentage of PWB variance explained by the measures of EWB is very small. The average level of happiness varied only a small amount across quintile categories of each of the measures of EWB (i.e., a substantial number of Ss in the lowest and next lowest quintiles of the measures of EWB expressed as high a level of happiness as Ss in the upper 2 quintiles of EWB). (PsycINFO Database Copyright 1992 American Psychological Assn, all rights reserved).
	Bibliography Citation Mullis, Randolph J. "Measures of Economic Well-Being as Predictors of Psychological Well-Being." Social Indicators Research 26,2 (March 1992): 119-135.

4.	Nam, Jaehyun
4.	Does Economic Inequality Constrain Intergenerational Economic Mobility? The Association Between Income Inequality During Childhood and Intergenerational Income Persistence in the United States Social Indicators Research published online (3 January 2021): DOI: 10.1007/s11205-020-02579-2. Also: https://link.springer.com/article/10.1007/s11205-020-02579-2 Cohort(s): NLSY79 Publisher: Springer Keyword(s): Geocoded Data; Income; Intergenerational Patterns/Transmission; Mobility, Economic; Socioeconomic Background; State-Level Data/Policy Permission to reprint the abstract has not been received from the publisher. Using the National Longitudinal Study of Youth 1979, I examine the association between income inequality and intergenerational income mobility in the United States. This study finds that rising income inequality is associated with strengthening the importance of parental family income to child's income. Particularly, the evidence that greater income inequality decreases intergenerational income mobility is clearer when interstate migration problems are addressed. This evidence indicates that income inequality matters since it hinders the equal opportunity to succeed, especially for children from low-income families. If equality of opportunity is a value for policymakers, it provides justification for policy interventions and government efforts to reduce income inequality. A number of sensitivity tests confirm that the main results are robust and reliable.
	Bibliography Citation Nam, Jaehyun. "Does Economic Inequality Constrain Intergenerational Economic Mobility? The Association Between Income Inequality During Childhood and Intergenerational Income Persistence in the United States." Social Indicators Research published online (3 January 2021): DOI: 10.1007/s11205-020-02579-2.

5.	Phipps, Shelley
5.	Health Outcomes for Children in Canada, England, Norway and the United States Social Indicators Research 80,1 (January 2007): 179–221. Also: http://springerlink.metapress.com/content/644w3r872888u325/fulltext.pdf Cohort(s): Children of the NLSY79 Publisher: Springer Keyword(s): Accidents; Behavior Problems Index (BPI); Birthweight; Body Mass Index (BMI); Canada, Canadian; Canadian National Longitudinal Survey of Children and Youth (NLSCY); Child Health; Children, Well-Being; Cross-national Analysis; England, English; Health Survey for England (HSE); Health Survey for Norway (NHS); Health/Health Status/SF-12 Scale; Injuries; Norway, Norwegian; Obesity; Parents, Single; Poverty; Weight Permission to reprint the abstract has not been received from the publisher. This paper thus uses nationally representative microdata surveys to provide a broad descriptive over-view of selected health outcomes for children (aged 2–13) living in Canada, England, Norway and the United States in the late 1990s – over-all and for potentially vulnerable children. If there are significant differences in patterns of child health status across similarly affluent countries with different levels and kinds of state spending, this will point to the need for future research directed at better understanding connections between policy and child health. Section "Comparing Child Health Outcomes" of the paper describes the health surveys employed and provides a comparison of over-all health status for children in the four countries. A range of child health outcomes, including aspects of both physical and emotional health are included. While second section compares health status for all children in the four countries, third section compares the health status of potentially 'vulnerable' children in each country (e.g., low-income children, children living in lone-mother or teen-mother families).
	Bibliography Citation Phipps, Shelley. "Health Outcomes for Children in Canada, England, Norway and the United States." Social Indicators Research 80,1 (January 2007): 179–221. A.

6.	Stevans, Lonnie K. Register, Charles A. Sessions, David N.
6.	Simulating Bias in the Estimator of Labor Market Discrimination Social Indicators Research 27,2 (September 1992): 157-168. Also: http://www.springerlink.com/content/t4tlk48l58k3/?p=4052785af0a24384a3b88b761f222aed&pi=183 Cohort(s): NLSY79 Publisher: Springer Keyword(s): Discrimination; Discrimination, Job; Earnings; Schooling Permission to reprint the abstract has not been received from the publisher. The statistical bias in the wage gap method of estimating labor market discrimination is investigated. An algebraic expression for the bias is derived & then simulated for a selected set of explanatory variables & model parameters. When applied to data from the 1988 National Longitudinal Survey (N = 6,403 males & 6,283 females ages 23-32), results indicate that when the variables years of schooling & labor market experience are used in earnings functions, the estimator tends to underestimate the actual or "true" amount of labor market discrimination. 2 Tables, 18 References. Adapted from the source document. (Copyright 1993, Sociological Abstracts, Inc., all rights reserved.)
	Bibliography Citation Stevans, Lonnie K., Charles A. Register and David N. Sessions. "Simulating Bias in the Estimator of Labor Market Discrimination." Social Indicators Research 27,2 (September 1992): 157-168.

7.	Stevans, Lonnie K. Register, Charles A. Sessions, David N.
7.	The Abortion Decision: A Qualitative Choice Approach Social Indicators Research 27,4 (December 1992): 327-344. Also: http://www.springerlink.com/content/gw45l50100h28v6w/ Cohort(s): NLSY79 Publisher: Springer Keyword(s): Abortion; Adolescent Fertility; Demography; Educational Attainment; Fertility; Income; Local Area Unemployment; Medicaid/Medicare; Regions; Religious Influences Permission to reprint the abstract has not been received from the publisher. Used data from the National Longitudinal Survey, Youth Cohort to show the impact of various sociodemographic and economic factors on the abortion decision for 1,867 pregnancies occurring between 1983 and 1985 in 12,868 female adolescents (aged 14-21 yrs). The results suggest a profile of an adolescent choosing the abortion decision as being White, unmarried, residing in the Northeast or West, relatively well-educated, and either in school or working. Additionally, the woman is likely to have a relatively high personal income, and, if present, a relatively low spousal income. Being Baptist or Catholic appears to have no significant influence on the abortion decision, and the same is true for Baptists and Catholics who are religious (attend church more than 2 times per month). For low income women, access to Medicaid funding does significantly increase the probability of choosing abortion. (PsycINFO Database Copyright 1993 American Psychological Assn, all rights reserved)
	Bibliography Citation Stevans, Lonnie K., Charles A. Register and David N. Sessions. "The Abortion Decision: A Qualitative Choice Approach." Social Indicators Research 27,4 (December 1992): 327-344.

8.	Wolfe, Joseph D.
8.	The Effects of Socioeconomic Status on Child and Adolescent Physical Health: An Organization and Systematic Comparison of Measures Social Indicators Research 123,1 (August 2015): 39-58. Also: http://link.springer.com/article/10.1007/s11205-014-0733-4 Cohort(s): Children of the NLSY79 Publisher: Springer Keyword(s): Adolescent Health; Child Health; Child Health, Limiting Condition(s); Children, Illness; Children, Poverty; Family Income; Family Resources; Maternal Employment; Mothers, Education; Poverty; Socioeconomic Factors; Socioeconomic Status (SES) Permission to reprint the abstract has not been received from the publisher. Prior research has established a link between SES and early life health without providing clear theoretical or empirical evidence for using any particular conceptualization or operationalization of SES. Researchers refer to almost any combination of variables related to families’ economic, educational, or occupational circumstances as SES. This abundance of operationalizations makes it difficult to determine how exactly SES shapes early life health. Childhood and adolescence are unique periods of life delineated by extensive social, psychological, and physical transitions. Although these changes may make children and adolescents sensitive to different aspects of SES, research has yet to systematically compare an array of SES measures extensive enough to rigorously examine this possibility. To address this gap, I merge the National Longitudinal Survey of Youth 1979 (NLSY79) and the NLSY79 Children and Young Adults datasets. In analyses, I consider multiple operationalizations of SES derived from the distinct components conceptualization of SES. I find that the best model of SES and early life health includes family income, wealth, education, and occupational prestige. Family income and wealth play especially important roles in early life health but also impact child and adolescent health differently. Children’s health is more vulnerable to their families’ wealth, while adolescents’ health is more sensitive to their families’ current income. Together, the countervailing effects of family income and wealth negate one another such that the overall effect of economic conditions on health is the same for children and adolescents. My findings provide evidence that future research should carefully consider multiple measures of SES when studying the relationship between SES and early life health.
	Bibliography Citation Wolfe, Joseph D. "The Effects of Socioeconomic Status on Child and Adolescent Physical Health: An Organization and Systematic Comparison of Measures." Social Indicators Research 123,1 (August 2015): 39-58.

Admin