Investigating the Roles of Income and Net Worth On Academic Achievement: A Latent Growth Curve Model

Background & Purpose: Research consistently demonstrates the importance of household financial variables in predicting academic achievement. Young people whose families have access to greater financial resources frequently achieve higher educational outcomes, such as higher scores on achievement tests, and higher rates of high school graduation, college enrollment, and college completion. Household income is a commonly used measure in predicting these achievement outcomes; however, household assets are used less frequently. As a result, limited research exists that examines the relationship between assets and different types of achievement outcomes. Furthermore, when assets are included, they are often used to predict an achievement outcome at one point in time. This paper extends current knowledge by testing individual variability in academic achievement scores and their rate of change at three different time points predicted by income and net worth using latent growth curve modeling.

Methods: This study used secondary data from the Panel Study of Income Dynamics and its Child Development Supplement. The study included a sample of young people ranging in age from 12 to 18 (N = 861) and included only Blacks and Whites. A latent growth curve model was performed to test the individual variability of young people's academic achievement scores and their rate of change in achievement scores across three time points, 1997, 2002, and 2007. Academic achievement was a composite score of the Woodcock-Johnson standardized Letter-Word scores and standardized Applied Problems scores, which served as proxies for reading and math achievement, respectively. Log of income from 1993 and log of net worth from 1994, which were allowed to correlate, were used as independent variables.

Results: Results indicate that the overall fit for the theoretical model was adequate, CFI = .932, GFI = .977, SRMR = .043. There was not a significant, linear trend in academic achievement, &Beta = -25.80, z = -1.08, p = .28. However, there was significant variability in academic achievement scores in 1997, B = 189.20, z = 55.10, p < .0001, and significant variability around the mean initial score, 189.20 ± 181.08, z = 5.35, p < .0001. Initial scores explained about 11% of this variability, R² = .11. There was a significant prediction in the variability in academic achievement by the log of income, B = 1.06, z = 3.04, p = .002, and the log of net worth, B = 15.66, z = 4.77, p < .0001.

Conclusions & Implications: Evidence suggests that while income remains a consistent, significant predictor of academic achievement, research may also want to consider the role of asset variables, including net worth. In this particular model, net worth is a stronger predictor of academic achievement than income. As a profession that advocates for social and economic opportunity, social work may have a unique ability to support asset accumulation, especially for young people and families with disadvantaged access to financial resources, in order to improve achievement outcomes.