Author: Jay L. Zagorsky
Published in: Intelligence 35 (2007) 489-501
Source: National Longitudinal Survey of Youth 1979 (NLSY79)
Introduction
Jay L. Zagorsky’s article examines the relationship between intelligence, as measured by IQ scores, and three dimensions of financial success: income, wealth, and financial hardship. Using data from the National Longitudinal Survey of Youth 1979 (NLSY79), which follows young American baby boomers born between 1957 and 1964, the study seeks to determine whether intelligence is essential for accumulating wealth, earning more income, and avoiding financial hardship. Unlike previous studies that have focused on the relationship between IQ and income, this research expands the analysis to include wealth (net worth) and financial hardship, such as late payments, bankruptcy, and overuse of credit cards.
Methodology
Data and Participants
The study used data from 7,403 NLSY79 respondents who participated in the 2004 survey (ages 33–41) and had available IQ scores. The sample was representative of the U.S. population, consisting of 79.5 percent white, 14.2 percent African American, and 6.3 percent Hispanic, with a nearly even split between men (50.7 percent) and women (49.3 percent).
Measures
1. IQ: Calculated from the Armed Forces Qualification Test (AFQT), part of the Armed Services Vocational Aptitude Battery (ASVAB), adjusted for age to standardize scores (mean 100, standard deviation 15).
2. Income: Sum of all sources of income per capita in 2004, including wages, government benefits, private transfers, and others.
3. Wealth: Net worth per capita, calculated as the difference between assets (home, vehicles, investments) and liabilities (mortgages, debts).
4. Financial Difficulty: Three Boolean indicators: (1) credit card at maximum limit (9% of respondents), (2) two months or more late on bills in the past five years (18.2%), and (3) declared bankruptcy (13.4%).
Analysis
The study combined graphical analysis, descriptive statistics, regressions (Ordinary Least Squares, Robust Regression, Trimmed OLS, Two-Stage Least Squares) and logistic regressions. Explanatory variables included age, race, education, marital status, inheritance, food expenditures and psychological factors such as locus of control, self-esteem and mastery scale.
Results
Income and IQ
The results confirm a positive and significant relationship between IQ and income. Each additional point in IQ score is associated with an annual increase in income of between $202 and $616, depending on the regression technique. For example, a 30-point difference in IQ (from 100 to 130) results in an annual income difference of between $6,000 and $18,500. The correlation between IQ and income was 0.297 (p<0.01).
Wealth and IQ
Unlike income, no significant relationship was found between IQ and wealth. Regressions showed coefficients close to zero, ranging from negative (-$435) to positive ($83), but generally indistinguishable from zero. The correlation between IQ and net worth was weaker (0.156, p<0.01). This indicates that intelligence is not a determining factor in accumulating wealth, supporting the view of Stanley and Danko (1996) in The Millionaire Next Door, who argue that wealth does not depend on intelligence.
Financial Hardship and IQ
The relationship between IQ and financial distress is not linear, but quadratic. Individuals with IQs below the average (less than 100) and well above the average (above 120) are more likely to experience financial distress, such as default or bankruptcy. For example, the probability of maxing out a credit card increases from 7.7% for individuals with an IQ ≤ 75 to 12.1% for those with an IQ of 90, but drops to 5.4% for those with an IQ of 115, before increasing again. Logistic regressions with cubic terms of IQ confirmed this nonlinear relationship. Possible explanations include greater distractibility among high IQ individuals or a tendency to live on the financial edge, relying on their ability to manage risk.
Other Factors
Factors such as education, inheritance, and marital status (divorce) significantly influenced income and wealth. Psychological variables such as internal locus of control, self-esteem, and mastery showed positive relationships with wealth and, to a lesser extent, with income. Race also had an impact: African Americans and Hispanics had, on average, less wealth than whites.
Discussion
The study concludes that although intelligence (as measured by IQ) is an important predictor of income, it does not explain wealth accumulation. This suggests that people with lower IQs are not at a disadvantage in achieving wealth, and those with higher IQs do not have an inherent advantage. The quadratic relationship with financial hardship suggests that both less intelligent and highly intelligent individuals may face financial challenges, possibly for different reasons (lack of resources versus overconfidence).
Limitations
– The results apply to a specific cohort (young U.S. baby boomers in 2004) and may not be generalizable to other periods, cohorts, or countries with different economic structures.
– IQ scores, although correlated with general intelligence, may be influenced by factors such as health, motivation, and the context of the test.
– The study does not establish causality, only associations, and other factors such as luck, mate choice, or timing were not controlled.
Implications for Future Research
The author recommends exploring other psychological factors, such as risk tolerance, preference for immediate versus delayed gratification, and social influence, that may influence wealth accumulation. Studies in other countries or cohorts could verify whether the results are broadly applicable.
Conclusion
The article answers the title question—“Do you have to be smart to be rich?”—with a resounding “no.” Although intelligence is associated with higher income, it is not a determinant of wealth or protection against financial hardship. These findings challenge the idea that intelligence is the key to financial success and highlight the relevance of other factors, such as financial behavior and socioeconomic background.
