Individuals’ investment and credit management decisions can be affected by their level of education.
What’s Inside?
A robust examination of an extensive sampling of personal financial data leads the authors to the conclusion that more education exerts a positive influence on an individual’s proclivity to save and ability to manage assets and make informed decisions on the use of debt.
How Is This Research Useful to Practitioners?
The greater the level of an individual’s education, the more likely that individual is to invest in assets with higher potential yield and produce greater investment income. Similarly, people with additional education are more likely to make prudent decisions in the management of their personal credit.
The authors compile and study two sets of data to establish the link between greater education and higher-yielding investment. They consider a third dataset to identify the positive effect of more education on sound financial decisions involving such uses of personal credit as lines of credit and home mortgages.
Education leads to sounder financial decisions. These decisions, in turn, reduce the social costs of personal bankruptcy, foreclosure, and credit delinquencies in general. Increased knowledge can often lead to greater financial stability. Increased earnings as well as positive behavioral changes are behind greater levels of financial market participation and prudent use of household credit.
The authors’ findings and conclusions carry important implications for education policymakers as well as financial service providers. Well-informed and educated consumers tend to make more prudent financial decisions that increase wealth and help them avoid bankruptcy.
How Did the Authors Conduct This Research?
In addition to a review of existing literature on the topic, the authors consider three datasets for their research. The objective of the authors’ research is to gauge the effect of educational achievement on individuals’ financial decision-making ability—something that the professional and academic literature has yet to consider. Their challenge is to be able to control for factors that could hinder their ability to isolate the role that education plays. They consider these effects on wealth accumulation, financial market participation, and credit management.
The US census carries the advantage of size and the disadvantage of not collecting information on personal financial wealth. It does collect information on both personal and investment income although not on allocations of the latter. Parsing these data is useful for measuring rates of saving and investment and retirement income.
Whereas the US census measures investment participation rates and investment and retirement income, the much smaller Survey of Income and Program Participation reflects degrees of asset ownership. Initiated by the US Census Bureau in 1984, it uses a series of panel surveys on demographic, income, and asset ownership questions for 14,000–37,000 households for each panel. Surveys occur every four months for four years. For asset accumulation and investing, the authors use an instrumental variable strategy that isolates the impact of changes in compulsory state education laws to reflect educational achievement from such factors as ability and familial circumstances. It controls for age, gender, race, birth state, and state of residence, using both the US census and Survey of Income and Program Participation data. The results of the testing support the perceived effect of more education—that is, more education causes households to invest more in higher-returning assets and to report higher levels of investment income.
With respect to the effect of education on individuals’ ability to manage credit, the authors use the Federal Reserve Bank of New York Consumer Credit Panel/Equifax dataset. Compiled on a quarterly basis, the data contain credit bureau information for individuals similar to what is in a personal credit report—for example, bankruptcy information and the extent and duration of any credit delinquencies. The data represent a national cross section of individuals.
Because credit bureau data do not contain information on education, a conventional instrumental variable strategy does not work. The authors use instead a two-sample instrumental variable approach. They use census data to regress education on compulsory schooling and then credit outcomes on the results of the first regression (prediction of education). The levels of education correlate positively with good credit outcomes.
Abstractor’s Viewpoint
Knowledge is critical. The authors draw this conclusion from a robust research effort that considers extensive data to establish a connection between the extent of an individual’s education and that individual’s investment acumen, propensity to save, and management of personal credit. Controlling for the variables of skill, age, state of birth, and residence, they identify a positive correlation between greater education and increased investment in higher-yielding assets and higher investment-related income and a lower incidence of personal credit mismanagement (delinquencies and bankruptcy). It would be interesting to conduct a similar analysis, to the extent that data would permit, in other advanced global economies to better gauge the effectiveness of education on an international scale and to rank such efforts accordingly.