Relationship between income and education
Socioeconomic status is measured by determining education and income, although education is used measure of SES in epidemiological studies, no investigators have conducted an empirical analysis quantifying the relative impact of each dimension of SES. With view to assess the independent effects of income and education, the need to study cross-sectional randomly selected samples of population (20 years up), independent effects of income and education through logistic regression analyses that controlled for age, ethnicity, household setting and either education or income. The level of education did not influence risk developed region but, in the more developed one, better-educated, strongly associated with income and education. To be able to understand the relationship between income and education, this research will consider household income of the family (parents’ income) and such capacity to send their children to school, to acquire effective education because of stable income.
Although it appears that income and education correlate in studies (1984), debate has focused on whether relationship is relative/absolute, that income helps individuals meet certain universal needs and therefore that income, at least at levels, is cause of education. The relativity argument is based on idea that impact of income or other resources depends on changeable standards such as those derived from expectancies, social comparisons. A longitudinal data in probability sample of 100 adults between income and education but cross relations can be at large.
There is strong as well as independent association between education and income however, income was not associated with prevalence of parental capacity for education spending after adjusting for certain socioeconomic variables. Similar results have been found in other studies but British studies tend to find the opposite, that income but not education is associated with parental capacity. Understanding the impact of socioeconomic factors on capacity ratio requires research in such countries. Research to address major issues in the existing literature: the causal effect of parental education on children, allowing for separate effects of mother’s and father’s education; and the causal effect of household income. To date no study has tried to account for endogeneity of parental education and of income, a crucial distinction since important policy differences hang on their relative effects.
There can be important innovation to controlling for income and education, the need to try to decompose effects of income into permanent and transitory elements and motivation is that a policy might be concerned with providing financial transfers to households holding parental education levels constant for example income support policies aimed at relieving child poverty. The importance of the latter innovation is that we need to distinguish credit constraints at the point of decision to enter post-compulsory schooling from the permanent effects of long term income differences so as to inform policy. The need to address intergeneration transmission of education and investigates the extent to which early school leaving, at age 16 may be due to variations in permanent income, parental education levels, and shocks to income at the age, stronger effects of maternal education than paternal, and stronger effects on sons than daughters.
To find that the education effects remain significant even when household income is included. Moreover, decomposing the income when the child is 16 between a permanent component and shocks to income at age 16 only latter is significant. It would appear that education is an important input even when we control for permanent income but that credit constraints at age 16 also influential. However, when there is use of instrumental variable methods to account for endogeneity of parental education and paternal income, we find that the strong effects of parental education become insignificant and permanent income matters much more, while the effects of shocks to household income at 16 remain important. A similar pattern of results maybe reflected in the main measure of scholastic achievement at age 16.
Anticipated findings have important implications for the design of policies aimed at encouraging pupils to remain in school longer. Research is to examine extent to which the relationship between participation in post-secondary education and family background, namely parental income and parental education changed between 2005 and 2009, support long-standing pattern that university participation rates are highest among youths from high-income families and of highly educated parents. There is no evidence to suggest that this relationship between university participation and family background changed over the period. Although university participation rates generally rise as family incomes increase, there is little difference in participation rates among youths from modest-income and low-income families.
Overall, correlation between university participation and family income changed. Next, when taking account of education and parental income, university participation rates are more strongly associated with parents' level of education than with their income. To discuss significant data gaps and conclude important implications about the relationship between education and family background throughout 2005 to 2008 period.
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