The Relationship between Income and Education
This paper will focus on the role of family incomes and the influence of such incomes on educational achievement of a child. The study used data collected by the National Longitudinal Survey of Youth (NLSY) that uses information collected on educational performance and family incomes of more than 4000 children in the United States. The study incorporates various measures and tests relevant towards illustrating the correlation between family incomes, parental education and the educational achievement of children drawn from poor and rich backgrounds in the United States and the United Kingdom. There is a high positive correlation between family incomes and educational achievement as per the results collected from the study.
The Relationship between Income and Education
The economic background of a child has been termed as one of the primary determinants towards the achievements of a child in academia. Research indicates that a majority of children from poor socioeconomic backgrounds score poor results as compared to children drawn from stable socioeconomic backgrounds. In the year 1966, he Coleman Report illustrated the relationship that existed between the achievements of students in educational institutions and the socioeconomic wellbeing family. Some initiatives such as the Federal Head Start program that was established in the 1960s as a means of poverty eradication have been effective in reducing poverty levels. In addition, the aim of such was to weaken the linkages that exist between poverty among families and the social and cognitive development of children. The linkages between family poverty levels and overall student achievement are a significant pattern that has been seen across the world in the field of education. On the other hand, the causes of the relationship between family poverty and achievement of students in educational institutions have been a source of significant disagreement among scholars.
The relationship between family poverty and achievements of students is viewed as part of a sociological necessity instead of being a product of a set of conditions in society, educational practices and policy choices. Majority of research conducted on the relationship between student achievement and family poverty has focused on mechanisms such as attainment of education by parents, family incomes, family structure, school quality, neighborhood conditions and choices. This paper largely focuses on the trends towards income inequality among families and the resulting gap in student achievement between children drawn from both rich and poor families.
Statement of Hypothesis
It is assumed that the economic status of a family is a primary determinant of student achievement. Previous research indicates that children from low-income backgrounds are susceptible to poor educational performance due to a variety of factors such as inappropriate environment and lack of funds to access quality education. In addition, it is also assumed that parental education plays a critical role in child development given that it determines parental levels of income and subsequent access to quality education.
To provide an elaborate comparison of the student achievements across the income gaps, test scores will be used to provide a comparison on achievements of students from low and high-income families using standard deviation units. This is a standard practice and has been used in other studies such as studies by Fryer and Levitt (2004), Grissmer, Flanagan, and Williamson (1998), and Reardon and Galindo (2009). Actual variances of student achievement are constant over the time of study to provide validity of comparisons used across the income gaps. Two key measures of the socioeconomic statuses of the families are used in this study namely the family incomes and parental educational attainment levels. The two are used as the dependent variables of this test whereas the student achievement is used as the independent variable.
A majority of similar studies has employed regressions of the outcome variables, which is usually the educational achievement of students drawn from both rich and poor families. Other measures to be used include observable family, the neighborhood and child abilities. A majority of studies using such approaches indicate a correlation between the educational outcomes of children and family incomes despite lacking direct estimates based on a causal relationship.
A variety of studies conducted on the relationship between family incomes and student educational achievements indicate the presence of a strong linkage between the two. In addition, the studies indicate a strong correlation between the education levels of their parents and the educational attainment of the children. The correlation in earnings between parents and their children has been provided as between 0.4-0.5 in the United States and 0.60 in the United Kingdom as per studies by Lorraine Dearden et al. (1997) for the figures on the United Kingdom and Gary Solon (1999) and Casey Mulligan (1999) for the US. Additionally, the studies conducted by these authors indicate that the mobility in education, in the United States is between 0.14-0.45 and 0.25-0.40 for the United Kingdom to indicate a strong relationship between parental educational levels and the educational achievements of their children.
Heckman & Masterov (2004) point out that children who are brought up under poor conditions are prone to lower standards of education despite the promise of extensive financial gains from education. However, the mechanisms that are used to highlight such intergenerational correlations are ambiguous. Krueger (2004) also notes that the presence of financial constraints in a majority of families has significant negative impacts on the educational achievement of students. On the other hand, Carneiro and Heckman (2003) provide in their study that a current level of parental income does not have a correlation towards the educational choices of a child. However, factors such as parental education have large influences on the permanent income accruable to a family. This, in turn, determines the overall quality of education accessible by the offspring within such a family.
Cameron & Heckman (1998) and Chevalier & Lanot (2002) using United States data and the united kingdom National Child Development Study respectively come to similar conclusions that family incomes determine the access to quality education. Thus, in the end, poor families are unable to provide their children with quality education, which results in poor student achievement. Chevalier (2004) uses data from the Family Resources Survey to provide that the income of a father determine the schooling options available to a child. They also provide that if the incomes of parents are endogenously correlated to education; thus the education coefficients are biased.
Researchers have sought different explanations for the correlation between family incomes and child educational achievement. The first explanation is that poverty in families is usually associated with depression, stress and deterioration of health. Such may negatively influence the ability of parents to provide their children with the support that they might need for educational excellence or achievement. Child Trends and Center for Child Health Research (2004) provides that, in the year 1998, an estimated 27% of children enrolled in kindergarten living under poverty condition were under the care of parents at risk of depression as compared to 14% of children in kindergarten with parents who had stable incomes. Children from poor families are likely to have underdeveloped speech and high levels of irritability and hostility in the classroom because of the influences of frustration and aggravation exhibited by their parents.
Data Set and Measures
Data used in this study is derived from National Longitudinal Survey of Youth (NLSY) that makes up for 4500 children in the United States. The data within this survey is made up of a various income and demographic measures that are essential to illustrate the correlation between incomes and educational achievements. In addition, the data sets are inclusive of five consecutive measures of the cognitive test scores for each child taken on an annual basis. The main variable namely the income of the family is seen to have significant educational achievement in reading and mathematics. The survey indicates that an increase of $1000 in family incomes is seen to enhance child performance in mathematics and reading outcomes by 6% of the standard deviation. Such effects are higher for children who are drawn from extremely poor backgrounds and those at younger ages.
The instrumental variables in this test are bigger than the Standard Fixed Effects (FE) estimates or Ordinary Least Squares (OLS) estimates. This has been attributed to the fact that an attenuation bias occurs in the measurement of the incomes resulting in distorted standard fixed effects (FE) and ordinary least squares (OLS) estimates. In addition, incomes are of higher importance to the most disadvantaged families as compared to families that have lower levels of poverty. Furthermore, the differences are also brought about by the expectations of future incomes towards future child outcomes.
The NLSY provides a rich source of information in relation to child achievements and their mothers. In addition, it also provides for the evaluation of family incomes and educational achievements among children over a long period. Data provided is relative to the different biennial measures of the backgrounds and cognitive achievements of children from the year 1986 to 2000. The NLSY survey provides diverse components that are relative to family incomes namely unearned income, nontaxable income and earned income. The Internal Revenue Service (IRS) (2002) estimates that 80-87% of households receive Earned Income Tax Credit.
|Year||No. of Children||Median Family income(lagged)||Fraction of children in EITC eligible families||Median EITC payments||EITC payment as a fraction of family income (1child family)||EITC payment as a fraction of family income (2+ child families)|
|Entire Sample||Eligible for EITC||Not Eligible for EITC||Difference between Eligible and not-eligible groups|
|Panel A: Baseline Variables|
|Two or more siblings||0.50||0.52||0.50||0.02|
In essence, an understanding of the effects of growing in poverty is essential towards this research. This is a difficult question to answer given that family income is endogenous. Such an understanding is essential for policymakers to understand given that it provides the basis for the establishment of different income support initiatives and programs such as the (EITC) that has a significant effect in the improvement of the quality of life for children living in poverty conditions. Previous estimates on the effects of family incomes on the achievements in child education have been marred by the omission variables and the respective biases.
In essence, the study indicates that children who are brought up in poor households are bound to face numerous challenges that may take the form of difficult home environments despite the increase in family incomes. Such challenges would ensure continued impediments towards the healthy development of a child and thus reflect on their overall educational achievements. 4,412 children with relation to their mothers provide this research with an avenue to observe the effect of income shocks on families and educational achievement of the children. EITC changes highlighted the changes in incomes between the years 1993 and 1997 to indicate increases of $2100 in incomes as per dollar value in year 2000. EITC payments to families increased by $1,670 between 1987 and the year 2000.
In conclusion, the estimates from this study indicate that children who are exposed to increased incomes achieve positive results in the form of better educational achievements. This is because higher incomes provide better environments in their homes, as well as provide them with access to quality education. There is a need for additional research to highlight the presence of essential variables and factors such as challenging home environments that determine the development of a child. In addition, the studies indicate an express correlation between the incomes accruable to a family and the educational achievements of children. The improvements in family incomes have a general positive impact on the overall educational achievements of a child despite the presence of other factors that may negatively influence overall development. Parental income from the study is correlated to the parental education level that in turn determines the access to quality education.
Blau, David M. “The Effect of Income on Child Development.” Review of Economics and Statistics 81, No.2 (1999): 261–76.
Black, Sandra E., Paul J. Devereux, and Kjell G. Salvanes. “Why the Apple Doesn’t Fall Far: Understanding Intergenerational Transmission of Human Capital.” American Economic Review 95 No.1 (2005): 437–49.
Dahl, Gordon B. and Lance Lochner. “The Impact of Family Income on Child Achievement: Evidence from the Earned Income Tax Credit.” American Economic Review 102, No.5 (2012): 1927–1956.
Evans, Williams, and Craig Garthwaite. 2010. “Giving Mom a Break: The Impact of Higher EITC Payments on Maternal Health.” National Bureau of Economic Research Working Paper 16296.
Goodman-Bacon, Andrew, and Leslie McGranahan. “How Do EITC Recipients Spend Their Refunds?” Federal Reserve Bank of Chicago Economic Perspectives 32, No.2 (2008): 17–32.
Lockwood, J. R., Daniel McCaffrey, Louis
Mariano, and Claude Stodgy. “Bayesian Methods for Scalable Multivariate
Value-Added Assessment.” Journal of Educational and Behavioral Statistics
32 No.2 (2007.): 125–50.
 David M. Blau, “The Effect of Income on Child Development,” Review of Economics and Statistics 81, no.2 (1999): 277.
 Gordon B. Dahl, and Lance Lochner, “The Impact of Family Income on Child Achievement: Evidence from the Earned Income Tax Credit,” American Economic Review 102, no.5 (2012):1930.
 Gordon B. Dahl, and Lance Lochner. “The Impact of Family Income on Child Achievement: Evidence from the Earned Income Tax Credit,” American Economic Review 102, no.5 (2012):1930.
 Gordon B. Dahl and Lance Lochner, “The Impact of Family Income on Child Achievement: Evidence from the Earned Income Tax Credit,” American Economic Review 102, no.5 (2012):1933
 Gordon B. Dahl and Lance Lochner, “The Impact of Family Income on Child Achievement: Evidence from the Earned Income Tax Credit,” American Economic Review 102, no.5 (2012):1939
 J. R. Lockwood, Daniel McCaffrey, Louis Mariano, and Claude Setodji,“Bayesian Methods for Scalable Multivariate Value-Added Assessment,” Journal of Educational and Behavioral Statistics 32, no.2 (2007): 127.
 J. R. Lockwood, Daniel McCaffrey, Louis Mariano, and Claude Setodji, “Bayesian Methods for Scalable Multivariate Value-Added Assessment,” Journal of Educational and Behavioral Statistics 32, no.2 (2007): 130.
 J. R. Lockwood, Daniel McCaffrey, Louis Mariano, and Claude Setodji, “Bayesian Methods for Scalable Multivariate Value-Added Assessment,” Journal of Educational and Behavioral Statistics 32, no.2 (2007): 137.
 Williams Evans and Craig Garthwaite.. “Giving Mom a Break: The Impact of Higher EITC Payments on Maternal Health,” National Bureau of Economic Research Working Paper 1629, (2010): 31.
 Andrew Goodman-Bacon and Leslie McGranahan.. “How Do EITC Recipients Spend Their Refunds?” Federal Reserve Bank of Chicago Economic Perspectives 32, no.2 (2008): 23.