People with higher IQs make significantly more accurate predictions about uncertain future events, leading to better decision-making throughout their lives.
A University of Bath study found that individuals with low IQ make forecasting errors more than twice as large as those with high IQ, providing new insight into why intelligence correlates with better health, wealth, and life outcomes.
The research, published in the Journal of Personality and Social Psychology, analyzed data from 3,946 people over 50 in England who were asked to predict their own life expectancy. These predictions were then compared against official mortality statistics to measure forecasting accuracy.
The Probability Assessment Gap
Using genetic markers linked to intelligence alongside cognitive test scores, researchers discovered that smarter individuals consistently make more realistic probability assessments. People in the lowest 2.5% of IQ distribution showed forecast errors that were substantially larger than those in the top 2.5%.
“Accurately assessing the probability of good and bad things happening to us is central to good decision-making,” explains Professor Chris Dawson of the University of Bath’s School of Management. “Almost all decisions we make, whether it’s starting a business, investing, crossing the road, choosing who to date, all require probabilistic assessments.”
Why Smart People Make Better Choices
The study revealed several key patterns in how intelligence affects decision-making:
- Higher IQ individuals show 16% better forecasting accuracy compared to lower IQ groups
- Smart people make fewer both positive and negative errors, showing more consistent judgment
- Low IQ individuals display greater “noise” in their predictions—more random variation when asked repeatedly about the same event
- The relationship held even after controlling for education, wealth, and family background
The researchers used an innovative approach called Mendelian randomization, which leverages genetic variants to establish causal relationships rather than mere correlations. This technique revealed that the IQ-forecasting accuracy link stems from genuine cognitive differences, not just education or social advantages.
Real-World Implications
The findings help explain why IQ predicts success across multiple life domains. Poor probability assessment can lead to suboptimal financial decisions, inadequate retirement planning, and risky health choices.
“IQ is already known to predict health, wealth, income, occupational status and educational attainment and this research highlights one possible channel through which people with a lower IQ do worse on all these outcomes,” Dawson notes.
The study found that people with low IQ (two standard deviations below average) had predicted forecast errors of 26.37 percentage points, while high IQ individuals (two standard deviations above average) showed errors of just 12.13 percentage points.
Beyond Bias to Noise
Importantly, the research identified that lower IQ individuals don’t just make systematic errors—they also show more random inconsistency in their judgments. When asked to make the same type of prediction multiple times, their accuracy varied much more than higher IQ individuals.
This “noise” in decision-making may be just as costly as systematic bias, since it leads to unpredictable and chaotic deviations from good choices. The finding aligns with recent psychological research suggesting that random errors deserve as much attention as systematic biases.
Practical Applications
The research suggests practical solutions for helping people prone to forecasting errors. “Explicitly stating probability estimates on information relating to health and finance, rather than relying on individuals to do their own calculations, could help people make more informed, accurate decisions,” Dawson recommends.
The study utilized genetic analysis alongside traditional IQ testing, examining both participants’ cognitive test performance and their genetic predisposition to intelligence and educational success. This dual approach strengthened confidence that the relationship between intelligence and forecasting accuracy reflects genuine causal effects.
“Expectations about the future shape how households make critical decisions—like how much to save, when to retire, or whether to invest,” Dawson explains. “Poorly calibrated expectations can lead to bad financial decisions, and reduced economic welfare, which can adversely affect national growth.”
The findings open new avenues for understanding how cognitive abilities shape life trajectories and suggest that improving people’s probability assessment skills could have widespread benefits for individual and societal well-being.
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