Edward Conard

Top Ten New York Times Bestselling Author

  • “Unintended Consequences is far smarter and more thought-provoking than most economics written for the general public” - Greg Mankiw, Harvard University, Former Chairman of the Council of Economic Advisors
  • “…a comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
  • “Unintended Consequences provides a provocative interpretation of the causes of the global financial crisis and the policies needed to return to rapid growth. Whether you agree or not, this analysis is well worth reading.” - Nouriel Roubini, New York University; Chairman, Roubini Global Economics
  • “…a very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard University
  • “…reminds us that inequality sends a signal of what society lacks most, in America’s case, entrepreneurship and risk taking.” - Lawrence Lindsey, CEO, The Lindsey Group, former Director of the National Economic Council
  • “…a must-read for serious students of economic policy.” - Glenn Hubbard, Dean, Columbia Business School, and former Chairman of the Council of Economic Advisers
  • “…reminds us that inequality sends a signal of what society lacks most, in America’s case, entrepreneurship and risk taking.” - Lawrence Lindsey, CEO, The Lindsey Group, former Director of the National Economic Council
  • “…a very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard University
  • “Unintended Consequences offers deep and well-argued analyses on almost every issue.” - The New York Times
  • “Unintended Consequences should be read by anyone who takes for granted the superiority of progressive taxation and has not thought carefully about the trade-offs involved.” - The New Republic
  • “A full-throated defense of economic dynamism.” - The Wall Street Journal
  • “There are an amazing number of good ideas and interesting points made in Unintended Consequences. The thinking underlying it, and the obvious depth of understanding of the author, are very impressive.” - Steven Levitt, coauthor of Freakonomics; 2004 John Bates Clark Medal
Upside of Inequality Oxford Unintended Consequences

Evolution/Heredity

Macroeconomic perspectives worth noting on the science of evolution/heredity, with graphs to illustrate the point, curated from over 100 sources.

AI Summary. Analysis of ancient DNA from 15,836 West Eurasians estimates selection coefficients at 9.7m genetic variants and finds pervasive directional selection, including increases in genetic scores for light skin pigmentation and negative selection against variants linked to type 2 diabetes risk and psychoses such as schizophrenia and bipolar disorder.

Ali Akbari, Annabel Perry, Alison Barton, Mohammadreza Kariminejad, et al. Nature
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Ancient DNA from 15,836 West Eurasians reveals that natural selection accelerated dramatically in the past 10,000 years, following the agricultural revolution. The strongest selection drove improved immune function and lighter skin pigmentation.

Has human genetic selection continued to shape traits across West Eurasia?

Core argument: Applying a new test for directional selection to ancient DNA from 15,836 West Eurasians, 10,016 with newly reported data, the authors estimate selection coefficients at 9.7 million variants to study how selection shapes the genetic architecture of complex traits.

We present a method for detecting directional selection in ancient DNA time-series data that tests for consistent trends in allele frequency change over time, and apply it to 15,836 West Eurasians (10,016 with new data). We estimate selection coefficients at 9.7 million variants, enabling study of how Darwinian forces couple to allelic effects and shape the genetic architecture of complex traits. We focused on 12 traits of particular interest with significant signals from all three tests (Figure 4). One of the strongest signals is an increase over time in the PGS for light skin pigmentation. Type 2 diabetes risk factors give compelling signals of negative selection. We detected negative polygenic selection against alleles associated today with psychoses such as bipolar disorder and schizophrenia. We finally observed signals of selection for combinations of alleles that today are associated with three correlated behavioural traits: scores on intelligence tests, household income and years of schooling. An important caveat is [that] these effects were measured in industrialized societies, and it remains unclear how these relate to phenotypes that were adaptive in the past.

Takeaways by Macro Roundup® AI

  1. Applying a new test for directional selection to ancient DNA from 15,836 West Eurasians, 10,016 with newly reported data, the authors estimate selection coefficients at 9.7 million variants to study how selection shapes the genetic architecture of complex traits.
  2. Among 12 traits with significant signals from all three tests, one of the strongest is an increase over time in the polygenic score for light skin pigmentation, alongside negative selection on type 2 diabetes risk factors and on alleles associated today with bipolar disorder and schizophrenia.
  3. The authors observed signals of selection on combinations of alleles associated today with intelligence test scores, household income, and years of schooling, while cautioning that these effects were measured in industrialized societies and their relation to past adaptive phenotypes remains unclear.

Related Articles:

  • Pervasive Findings of Directional Selection Realize the Promise of Ancient DNA to Elucidate Human Adaptation — Analyzing ancient DNA for consistent trends in gene-variant frequency over time, the authors report that many hundreds of gene variants were affected by strong directional selection over the last ten millennia. They identify selection for variant combinations today associated with lighter skin color, lower schizophrenia and bipolar risk, slower health decline, and higher intelligence-test scores, income, and schooling.
  • Animal Mutation Rates Reveal Traits That Speed Evolution — An analysis of 68 vertebrate species published in Nature found germline mutation rates varied about 40-fold per generation but roughly 120-fold per year, a wider range than earlier studies suggested. The authors found species with larger effective population sizes had lower mutation rates, evidence for the "drift-barrier hypothesis" that natural selection weakens against mutation in smaller populations.
  • Frontiers Evolutionary Trajectories of Complex Traits in European Populations of Modern Humans — Genome-wide polygenic scores indicate European populations after the Neolithic period show increases in height, educational attainment, and intelligence scores, alongside decreases in scores for unipolar depression. The authors associate this shift from relative stagnation to accelerated evolutionary change with the spread of agriculture and animal domestication.

AI Summary. Analyzing ancient DNA for consistent trends in gene-variant frequency over time, the authors report that many hundreds of gene variants were affected by strong directional selection over the last ten millennia. They identify selection for variant combinations today associated with lighter skin color, lower schizophrenia and bipolar risk, slower health decline, and higher intelligence-test scores, income, and schooling.

David Reich, Ali Akbari, et al. bioRxiv
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David Reich and @aliakbari23 find that starting 10,000 years ago human evolution favored traits related to cognitive performance. Alleles associated with higher scores on intelligence tests increased by a standard deviation of .79.

What does ancient DNA reveal about recent human genetic selection?

Core argument: The authors estimate selection coefficients at 9.9 million genetic variants in ancient DNA time-series data, finding that many hundreds of alleles have been affected by strong directional selection over the last ten millennia.

We present a method for detecting evidence of natural selection in ancient DNA time-series data that leverages an opportunity not utilized in previous scans: testing for a consistent trend in allele frequency change over time. In the last ten millennia, many hundreds of alleles have been affected by strong directional selection. We identify selection for combinations of alleles that are today associated with lighter skin color, lower risk for schizophrenia and bipolar disease, slower health decline, and increased measures related to cognitive performance (scores on intelligence tests, household income, and years of schooling). We finally observe signals of selection for combinations of alleles that today predict three 368 correlated behavioral traits: scores on intelligence tests (increasing 0.79 ± 0.14), household 369 income (increasing 1.11 ± 0.14), and years of schooling (increasing 0.61 ± 0.13). We estimate selection coefficients at 9.9 million variants, enabling study of how Darwinian forces couple to allelic effects and shape the genetic architecture of complex traits.

Takeaways by Macro Roundup® AI

  1. The authors estimate selection coefficients at 9.9 million genetic variants in ancient DNA time-series data, finding that many hundreds of alleles have been affected by strong directional selection over the last ten millennia.
  2. The authors identify selection for combinations of alleles today associated with lighter skin color, lower risk for schizophrenia and bipolar disease, slower health decline, and increased measures related to cognitive performance.
  3. The authors report selection signals for combinations of alleles that today predict three correlated behavioral traits: intelligence test scores increasing 0.79 ± 0.14, household income 1.11 ± 0.14, and years of schooling 0.61 ± 0.13.

Related Articles:

  • Using DNA to Predict Education: a Meta-Analytic Review — A meta-analysis found that polygenic scores, person-specific aggregates of inherited DNA differences, are associated with educational attainment at a correlation of .27 and with educational achievement such as school grades at .24; after accounting for sample ancestry, age at assessment, and education measure, these estimates rose to .29 and .50. Only 15% of estimates came from samples of non-European ancestry.
  • Animal Mutation Rates Reveal Traits That Speed Evolution — An analysis of 68 vertebrate species published in Nature found germline mutation rates varied about 40-fold per generation but roughly 120-fold per year, a wider range than earlier studies suggested. The authors found species with larger effective population sizes had lower mutation rates, evidence for the "drift-barrier hypothesis" that natural selection weakens against mutation in smaller populations.
  • US PISA Results By Subpopulation — On the international PISA student assessments, American Asian and White students ranked at the top, American Hispanic students outscored Hispanic students elsewhere, and American Black students performed well. In reading, American Asian students placed first and American White students third.

AI Summary. A meta-analysis found that polygenic scores, person-specific aggregates of inherited DNA differences, are associated with educational attainment at a correlation of .27 and with educational achievement such as school grades at .24; after accounting for sample ancestry, age at assessment, and education measure, these estimates rose to .29 and .50. Only 15% of estimates came from samples of non-European ancestry.

Kirsty Wilding, Megan Wright, and Sophie von Stumm Educational Psychology Review
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A meta-analysis of international studies finds a 24% correlation between education achievement, as measured by grades, and “polygenic scores that are person-specific aggregates of inherited DNA differences.”

How well do inherited DNA differences predict educational attainment and achievement?

Core argument: A multilevel meta-analysis of 20 estimates covering 314,757 individuals found polygenic scores associated with educational attainment at ρ = .27 (95% CI .22–.32), and with educational achievement at ρ = .24 (95% CI .18–.30) across 19 estimates and 83,788 individuals.

Recent advances in genomics make it possible to predict individual differences in education from polygenic scores that are person-specific aggregates of inherited DNA differences. Here, we systematically reviewed and meta-analyzed the strength of these DNA-based predictions for educational attainment (e.g., years spent in full-time education) and educational achievement (e.g., school grades). For educational attainment (k = 20, n = 16, Ntotal = 314,757), a multilevel meta-analysis showed an association with polygenic scores of ρ = .27 (95% CI from .22 to .32). For educational achievement (k = 19, n = 10, Ntotal = 83,788), the association was ρ = .24 (95% CI from .18 to .30). Eurocentric biases were evident with only 15% of estimates being reported in samples of non-European ancestry. After accounting for sample ancestry, age at assessment, and education measure, the meta-analytic estimates increased to ρ = .29 (95% CI from .24 to .33) for educational attainment and ρ = .50 (95% CI from .39 to .61) for educational achievement, indicative of large effect sizes.

Takeaways by Macro Roundup® AI

  1. A multilevel meta-analysis of 20 estimates covering 314,757 individuals found polygenic scores associated with educational attainment at ρ = .27 (95% CI .22–.32), and with educational achievement at ρ = .24 (95% CI .18–.30) across 19 estimates and 83,788 individuals.
  2. After accounting for sample ancestry, age at assessment, and education measure, the meta-analytic estimates rose to ρ = .29 (95% CI .24–.33) for educational attainment and ρ = .50 (95% CI .39–.61) for educational achievement, described as large effect sizes.
  3. Eurocentric biases were evident in the reviewed literature, with only 15% of estimates reported in samples of non-European ancestry.

Related Articles:

  • Standardized Test Scores and Academic Performance at Ivy-Plus Colleges — Using admissions records and first-year grades at multiple Ivy-Plus colleges, the authors find SAT and ACT scores substantially predict college academic success even among students with the same high school grades, while high school grade point average does little to predict it. Conditional on test scores, students from lower- and higher-resourced high schools have virtually identical college grades.
  • Steeper At The Top: Cognitive Ability and Earnings in Finland and Norway — Administrative data on over 350,000 men each in Finland and Norway show a convex relationship between earnings rank and cognitive ability measured by military conscription tests: top-percentile earners score about 1 standard deviation above median earners, who score about 0.5 above bottom-percentile earners. The lowest scores are almost absent among top earners.
  • US PISA Results By Subpopulation — On the international PISA student assessments, American Asian and White students ranked at the top, American Hispanic students outscored Hispanic students elsewhere, and American Black students performed well. In reading, American Asian students placed first and American White students third.

AI Summary. A new paper argues that persistent drought in southern California during the 1970s emptied swimming pools, turning them into de facto urban skateboard parks. The authors link this to the rise of skateboarding companies, skateboarding media, and a subculture that eventually became mainstream.

Paul Kedrosky Applied Complexity
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Describing how skateboarding evolved out of a prolonged southern California drought which emptied pools @pkedrosky theorizes “Humans are products of scarcity, not abundance….we are living in a world, one of abundance, to which we are poorly adapted.”

Did drought create skateboarding culture by emptying swimming pools?

Core argument: A paper argues that persistent drought in southern California during the 1970s emptied swimming pools, creating de facto urban skateboard parks that seeded skateboarding companies, skateboard media, and a subculture that later went mainstream.

There is a striking new paper on the origins of skateboarding. It shows how persistent drought in southern California in the 1970s caused the emptying of pools, giving rise to de facto urban skateboard parks. This, in turn, helped drive the rise of skateboarding companies, skateboard media, and an entire subculture that eventually became mainstream. You can see some of this in a graphic from the paper, where early skateboarding magazine covers showed pools as filled and part of the built urban environment, while later covers turned skateboarding into something that happened inside the objects formerly known as pools. Humans, it can be strongly argued, are products of scarcity, not abundance. We see this in everything from our metabolic response to fasting, to the rise of skateboarding in southern California. We are, to that way of thinking, living in a world, one of abundance, to which we are poorly adapted.

Takeaways by Macro Roundup® AI

  1. A paper argues that persistent drought in southern California during the 1970s emptied swimming pools, creating de facto urban skateboard parks that seeded skateboarding companies, skateboard media, and a subculture that later went mainstream.
  2. Early skateboarding magazine covers in the paper's graphic depicted pools as filled features of the built urban environment, while later covers depicted skateboarding taking place inside the objects formerly known as pools.
  3. Humans, on this argument, are products of scarcity rather than abundance, as seen in the metabolic response to fasting, and are poorly adapted to a world of abundance.

Related Articles:

  • Global Water Scarcity: H2O No! — Less than 1% of the planet's water is usable; water demand has risen about 40% over 40 years and is estimated to increase another 25% by 2050, while supply has more than halved since 1970. Some 57% of global freshwater aquifers are beyond their tipping point, and one-third of piped fresh water is lost to leakage.
  • Arizona Is Running Out of Cheap Water. Investors Saw It Coming — Phoenix-area suburbs are paying sharply higher prices for water rights from a basin west of the city, with one suburb approving $80m for 6,000 acre-feet — more than double the per-acre-foot price another suburb paid earlier. Arizona's groundwater replenishment assessments rose from $154 to $768 per acre-foot.
  • The Rapid Loss Of Antarctic Sea Ice Brings Grim Scenarios Into View — Unusual wind and wave patterns are a leading short-term explanation for the loss of Antarctic sea ice, which holds the continent's coastal ice shelves in place. If those shelves collapsed, continental ice could flow rapidly into the oceans; the West Antarctic ice sheet alone holds enough water to raise global sea level by 11 feet.

AI Summary. An analysis of 68 vertebrate species published in Nature found germline mutation rates varied about 40-fold per generation but roughly 120-fold per year, a wider range than earlier studies suggested. The authors found species with larger effective population sizes had lower mutation rates, evidence for the "drift-barrier hypothesis" that natural selection weakens against mutation in smaller populations.

Yasemin Saplakoglu Quanta Magazine
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.@QuantaMagazine reports on a @Nature study that tracked the tempo of evolution across 68 species and found that the mutation rate per year was higher than expected.

.@QuantaMagazine reports on a @Nature study that tracked the tempo of evolution across 68 species and found that the...

Does population size shape how fast species mutate?

Core argument: Germline mutation rates across 68 vertebrate species varied by about 40-fold per generation but roughly 120-fold per year, a wider range than previous studies had suggested, according to the analysis published in Nature.

A massive analysis of 68 diverse vertebrate species, from lizards and penguins to humans and whales, has made the first large-scale comparison of the rates at which species mutate — a first step toward understanding how quickly they can evolve. The findings, published in the journal Nature, unearthed surprising insights into how the tempo for mutations can change and what sets that pace. The most surprising finding that emerged from the data was the wide range of germline mutation rates. When the researchers measured how often the mutations occurred per generation, the species varied by only about fortyfold. But when they looked at the mutation rates per year rather than per generation, the range increased to about 120-fold, which was larger than previous studies had suggested. The study authors found that the higher the average effective population size for a species, the lower its mutation rate. That provided good evidence for the “drift-barrier hypothesis” devised a little over a decade ago. “Selection is relentlessly trying to reduce the mutation rate because most mutations are deleterious,” Michael Lynch, an evolutionary biologist at Arizona State University explained. But in species with smaller effective population sizes, natural selection gets weaker because genetic drift—the effect of pure chance on the spread of a mutation—gets stronger. That allows the mutation rate to rise.

Takeaways by Macro Roundup® AI

  1. Germline mutation rates across 68 vertebrate species varied by about 40-fold per generation but roughly 120-fold per year, a wider range than previous studies had suggested, according to the analysis published in Nature.
  2. The study authors found that species with larger average effective population sizes had lower mutation rates, which they report as evidence for the drift-barrier hypothesis.
  3. Michael Lynch, an evolutionary biologist at Arizona State University, explains that selection continually pushes mutation rates down because most mutations are deleterious, while in species with smaller effective population sizes stronger genetic drift weakens selection and allows mutation rates to rise.

AI Summary. A study of 394,378 U.S. adults in an online personality and ability assessment project found lower annual cognitive ability scores over 13 years, across education, gender, and age groups. The decline in scores was steeper among those without a four-year college degree.

Elizabeth Dworak, William Revelle and David Condon Intelligence
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Evidence from an online personality test suggests that the Flynn effect reversed in the United States between 2006-2018 for all levels of education attainment, with the most significant decline for individuals without a college degree.

Are U.S. adult cognitive ability scores declining over time?

Core argument: Across 394,378 U.S. adults in the SAPA Project from 2006 to 2018, composite cognitive ability scores measured by 35 items were lower each year regardless of education, gender, and age.

Thirteen years of cross-sectional data from a subsample of adults (n = 394,378) were obtained from the Synthetic Aperture Personality Assessment Project (SAPA Project) to examine if cognitive ability scores changed within the United States from 2006 to 2018.  Regardless of education, gender, and age, lower annual scores were observed for composite cognitive ability measured by 35 items, and the matrix reasoning and letter and number series scores measured across the 13 years of assessment. A reverse Flynn effect was also present across all levels of educational attainment, with the rate of decreasing scores being steeper for those with less than a 4-year college degree.

Takeaways by Macro Roundup® AI

  1. Across 394,378 U.S. adults in the SAPA Project from 2006 to 2018, composite cognitive ability scores measured by 35 items were lower each year regardless of education, gender, and age.
  2. Matrix reasoning and letter and number series scores also declined across the 13 years of SAPA Project assessment.
  3. A reverse Flynn effect was present at all levels of educational attainment, with steeper rates of decline among adults with less than a 4-year college degree.

AI Summary. A multilevel meta-analysis of 254 studies with 6,984 participants finds music training does not significantly improve children's cognitive skills or academic performance, with an overall effect size near zero. The authors attribute apparent benefits to study design weaknesses such as the absence of random allocation and active control groups.

Giovanni Sala Memory & Cognition
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Music training cognitive benefits debunked: Meta-analysis (n=6,984, 254 studies) shows zero effect size. Perceived gains (g=0.200) stem from study design flaws, not actual cognitive enhancement.

Does music training improve children's cognitive skills and academic performance?

Core argument: A multilevel meta-analysis of 254 studies covering 6,984 participants finds an overall effect size of about 0 for music training on children's cognitive skills and academic performance.

A comprehensive meta-analysis involving 6,984 participants across 254 studies reveals that music training does not significantly enhance cognitive skills or academic performance, with an overall effect size of 𝑔̅ ≈ 0. The analysis shows that any perceived benefits are largely due to study design flaws, such as lack of random allocation and non-active controls, which inflate effect sizes to 𝑔̅ ≈ 0.200. Bayesian analyses confirm these findings, indicating that music training's impact is negligible across various outcome measures, participant ages, and training durations. The study underscores that optimism about music training's cognitive benefits is empirically unfounded, highlighting the need for rigorous experimental designs in future research.

Takeaways by Macro Roundup® AI

  1. A multilevel meta-analysis of 254 studies covering 6,984 participants finds an overall effect size of about 0 for music training on children's cognitive skills and academic performance.
  2. Studies lacking random allocation and using non-active control groups inflate the estimated benefit of music training to an effect size of about 0.200, according to the meta-analysis.
  3. Bayesian analyses in the meta-analysis indicate music training's impact is negligible across outcome measures, participant ages, and training durations, and the authors call for more rigorous experimental designs.

Core of paper, “…Music training has repeatedly been claimed to positively impact children’s cognitive skills and academic achievement (literacy and mathematics). This claim relies on the assumption that engaging in intellectually demanding activities fosters particular domain- general cognitive skills, or even general intelligence. The present meta-analytic review (N = 6,984, k = 254, m = 54) shows that this belief is incorrect. Once the quality of study design is controlled for, the overall effect of music training programs is null (𝑔̅≈ 0) and highly consistent across studies (τ2 ≈ 0). Results of Bayesian analyses employing distributional assumptions (informative priors) derived from previous research in cognitive training corroborate these conclusions. Small statistically significant overall effects are obtained only in those studies implementing no random allocation of participants and employing non-active controls (𝑔̅≈ 0.200, p <.001). Interestingly, music training is ineffective regardless of the type of outcome measure (e.g., verbal, non-verbal, speed-related, etc.), participants’ age, and duration of training. Furthermore, we note that, beyond meta-analysis of experimental studies, a considerable amount of cross-sectional evidence indicates that engagement in music has no impact on people’s non-music cognitive skills or academic achievement. We conclude that researchers’ optimism about the benefits of music training is empirically unjustified and stems from misinterpretation of the empirical data and, possibly, confirmation bias…”

Supporting Evidence

“…This meta-analysis - which includes 38 studies, 118 effect sizes, and 3,085 participants - found an overall effect of𝑑̅= 0.16. It also highlighted that the impact of music training on cognitive skills and academic performance was a function of the quality of the study’s experimental design. Specifically, the magnitude of the music-induced effects was significantly smaller (around zero) in those studies implementing active controls and random allocation of the participants to groups….”

“…The overall effect size of the RVE intercept model was𝑔̅= 0.184, SE = 0.041, 95% CI, m = 54, k = 254, df = 38.36, p <.001, τ2 = 0.041, I2 = 43.16%. Different values of within-study effect-size correlation (ρ) did not significantly affect the results (𝑔̅range 0.184- 0.185, τ2 = 0.041). The random-effect (RE) model (with Cheung & Chan’s correction) yielded very similar estimates:𝑔̅= 0.176, SE = 0.037, p <.001, τ2 = 0.033. Overall, the results showed a small and moderately heterogeneous overall effect of music training on cognitive and academic outcomes. The results were not affected by modeling choices (i.e., ρ values and procedure for modeling nested data)…. Baseline difference and Type of controls were the only two statistically significant moderators (p =.031 and p =.035, respectively) and accounted for part of the true heterogeneity (τ2 = 0.038, I2 = 34.87%). Age was not significant (p =.403), neither was Allocation (p =.518). No significant differences were found across the four broad groups of outcome measures (all ps ≥.624; Holm’s correction for multiple comparisons), nor across the more fine-grained categorization (eight levels, all ps ≥.362), and there was no difference between cognitive skills and measures of academic achievement (p =.981). Duration of training was not significant either (p =.266, p =.952, and p =.662 for hours, weeks, and sessions, respectively).

Cognitive and academic benefits of music training with children: A multilevel meta-analysis: Extended Excerpt Image 1

Giovanni Sala and Fernand Gobet, "Cognitive and academic benefits of music training with children: A multilevel meta-analysis,"Memory & Cognition, July 29, 2020, https://link.springer.com/article/10.3758/s13421-020-01060-2

AI Summary. A meta-analysis of 142 effect sizes from 42 data sets covering over 600,000 participants finds that an additional year of education is associated with a gain of roughly 1 to 5 IQ points. The authors report this association across multiple cognitive abilities, across the lifespan, and in three quasi-experimental designs.

Stuart Ritchie Science
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Education boosts intelligence by 1-5 IQ points per year, according to a meta-analysis of 142 effect sizes from 42 data sets involving over 600,000 participants.

How much does an additional year of education raise IQ?

Core argument: A meta-analysis of 142 effect sizes from 42 data sets covering more than 600,000 participants finds an additional year of education is associated with a gain of roughly 1–5 IQ points.

A comprehensive meta-analysis of 142 effect sizes from 42 data sets involving over 600,000 participants reveals that an additional year of education is consistently associated with a gain of approximately 1 to 5 IQ points. This effect persists across various cognitive abilities and throughout the lifespan, highlighting education as a robust method for enhancing intelligence. The analysis utilized three quasi-experimental designs: control prior intelligence, policy change, and school-age cutoff, each demonstrating significant educational impacts on cognitive outcomes. For instance, the school-age cutoff design showed an average increase of 5.229 IQ points per additional year of education. These findings underscore the economic implications of investing in education as a means to boost cognitive skills, which are crucial for workforce productivity and economic growth.

Takeaways by Macro Roundup® AI

  1. A meta-analysis of 142 effect sizes from 42 data sets covering more than 600,000 participants finds an additional year of education is associated with a gain of roughly 1–5 IQ points.
  2. The school-age cutoff design yielded an average increase of 5.229 IQ points per additional year of education, one of three quasi-experimental designs alongside control of prior intelligence and policy change, each showing significant educational effects on cognitive outcomes.
  3. The estimated education effect persists across various cognitive abilities and throughout the lifespan, underscoring the economic implications of investing in education to boost cognitive skills relevant to workforce productivity and economic growth.

Summery, “…Intelligence test scores and educational duration are positively correlated. This correlation could be interpreted in two ways: Students with greater propensity for intelligence go on to complete more education, or a longer education increases intelligence. We meta-analyzed three categories of quasi-experimental studies of educational effects on intelligence: those estimating education-intelligence associations after controlling for earlier intelligence, those using compulsory schooling policy changes as instrumental variables, and those using regression-discontinuity designs on school-entry age cutoffs. Across 142 effect sizes from 42 data sets involving over 600,000 participants,we found consistent evidence for beneficial effects of education on cognitive abilities of approximately 1 to 5 IQ points for an additional year of education.Moderator analyses indicated that the effects persisted across the life span and were present on all broad categories of cognitive ability studied. Education appears to be the most consistent, robust, and durable method yet to be identified for raising intelligence….”

Stuart Ritchie and Elliot Tucker-Drob, "How Much Does Education Improve Intelligence? A Meta-Analysis,"Psychological Science, 2018, https://labs.la.utexas.edu/tucker-drob/files/2019/08/Ritchie-Tucker-Drob-2018-Psych-Science-How-Much-Does-Education-Improve-Intelligence.pdf

“….Table 2 shows the results from each study design after the inclusion of multiple moderators. We included as many moderators as possible for each design, though we chose to include the “achievement” categorization of the outcome test for the school-age-cutoff design (instead of the alternative categorization involving composite, fluid, and crystallized tests, which we used for the other designs) because it had such a substantial effect in the single-moderator model. Including multiple moderators reduced the τ statistic—to a larger degree for the control-prior-intelligence design than for the others— though significant heterogeneity remained in all cases. The moderators that were individually significant (e.g., age in the control-prior-intelligence design or achievement tests in the school-age-cutoff design) were also significant in the multiple-moderator model, indicating that their effects were incremental of the other moderators that we included….”

“…We tested whether studies that included only male participants showed a differential educational effect. This was not the case for control prior intelligence (effect for the 2 male-only estimates: 2.261 IQ points, SE = 0.897, p =.012; effect for 24 mixed-sex estimates: 1.027 IQ points, SE = 0.110, p = 6.79×10−21; difference SE = 0.905, p =.173), or for policy change (effect for the 8 male-only estimates: 1.683 IQ points, SE = 0.507, p =.001; effect for 22 mixed-sex estimates: 2.215 IQ points, SE = 0.788, p =.005; difference SE = 0.941, p =.572). There were no male-only school-age-cutoff studies….”

Multiple moderators.

“….Splitting the outcome cognitive tests into three broad categories—composite, fluid, and crystallized tests—we tested whether the category moderated effect sizes. For the control-prior-intelligence design, there were stronger educational impacts on composite tests (1.876 IQ points, SE = 0.467, p = 5.94×10−05) than on fluid tests (0.836 points, SE = 0.097, p =.152), and the difference between composite and fluid was significant (1.039 points, SE = 0.496, p =.036).There was only one crystallized outcome test for the control-prior- intelligence design (1.893 points, SE = 0.348, p = 5.34×10−08), so we did not include it in the moderator comparison here. For the policy-change design, there were significant effects for both composite (2.314 IQ points, SE = 0.869, p =.008) and fluid (2.272 points, SE = 0.765, p =.003) but not crystallized (1.012 points, SE = 1.125, p =.368) tests; however, the effects on the three different categories were not significantly different from one another (all difference p values >.35). Finally, for the school-age-cutoff design, there were significant effects of a year of education on composite (6.534 points, SE = 2.433, p =.007), fluid (5.104 points, SE = 0.621, p = 2.05×10−16), and crystallized (5.428 points, SE = 0.170, p = 1.04×10−223) tests; there were, however, no significant differences between effect sizes across outcome types (difference p values >.5). We then split the outcome tests into “achievement” tests versus “other” tests. There was only one achievement test in the control-prior-intelligence design, so we did not run this analysis. For policy change, there was no significant difference in the educational effect on the 7 achievement tests (2.760 IQ points, SE = 0.968, p =.004) versus the 23 other tests (1.784 points, SE = 0.553, p =.001; difference SE = 1.011, p =.334). However, for school-age cutoff, which had the largest proportion of achievement tests (38 of the 86 tests were classed as achievement tests), achievement tests showed a substantially and significantly larger educational effect (6.231 points, SE = 0.339, p = 2.85×10−75) than other tests (3.839 points, SE = 0.412, p = 1.11×10−20; difference SE = 0.371, p = 1.19×10−10)….”

Male-only studies.

Outcome test category.

“…Figure 1 shows the effect sizes in the first two study designs as a function of the participants’ mean age at the outcome test. For the control- prior-intelligence studies, outcome age was a significant moderator: The effect size of education declined by −0.026 IQ points per year of age (SE = 0.012, p =.029). At the youngest age (18 years) the effect size of having had an additional year of education was 2.154 IQ points, whereas at the oldest age (83 years) the effect size was 0.485 IQ points. This effect was smaller but still significant if the largest effect size (> 3 IQ points for an additional year) was excluded (−0.011 IQ points per year of age, SE = 0.005, p =.018). There was no significant moderating effect of age at outcome for the policy-change studies (0.014 IQ points per year, SE = 0.022, p =.543): The effect at the youngest age (18 years; 1.690 IQ points) was not significantly different from the effect at the oldest age (71 years; 2.413 IQ points). There was comparatively little variation in the age at the outcome test for the school-age- cutoff design (SD = 1.6 years; see Table 1); there was no significant age moderation effect (−0.027 points per year, SE = 0.399, p =.947)….”

“…. For the policy-change design, we tested whether the age at which the educational policy change produced an increment in compulsory schooling moderated the intervention effect. This was not the case: The effect size increased by a nonsignificant 0.038 IQ points per year of age at the intervention (SE = 0.228, p =.867). The meta-regression model implied that at the youngest intervention age (7.5 years), the effect size was 1.765 IQ points, and at the oldest (19 years) it was 2.204 IQ points….”

Age at outcome test.

“…For the control-prior-intelligence design, we tested whether the age at which the participants had taken the initial (control) cognitive test, or the gap between this early test and the outcome test, moderated the effect size. The age at the early test, which did not vary substantially (see Table 1) was not significantly related to the effect size (−0.024 IQ points per year, SE = 0.064, p =.706). For the youngest early-test age (10 years), the meta-regression model indicated that the effect size of 1 additional year of education was 1.243 IQ points; for the oldest (16 years), the effect size was 1.099 IQ points. Conversely, the time lag between the tests was a significant moderator of the effect size (−0.031 IQ points per year, SE = 0.015, p =.033). This meta-regression indicated that at the smallest age gap (5 years), the effect size was 2.398 IQ points, whereas for the largest age gap (72.44 years), the effect size was a substantially smaller 0.317 IQ points. Note that this age gap is almost fully confounded with the age at the out- come test (r =.988), assessed as a moderator below….”

Age at intervention.

Age at early test and time lag between tests.

“…We analyzed results from the three most prominent quasi-experimental methods for testing the effects of education on intelligence. We defined intelligence as the score on a cognitive test; see below for consideration of how the test scores might relate to the underlying psychological processes. Each method implements a different approach to minimize effects stemming from selection processes. Full meta-analytic inclusion criteria are reported below, but first we describe each of the three designs, providing a canonical example of each..…. The first research design, which we label control prior intelligence, is a longitudinal study in which cognitive testing data are collected before and after variation in the duration of education. This allows the relation between education and the second test to be adjusted for by each participant’s earlier ability level. An example of this design is the study by Clouston et al. (2012), who analyzed data from three large U.S. and UK cohort studies, all of which had both an adolescent and a midlife cognitive test. Results indicated that completing a university education was linked to higher midlife cognitive ability, above and beyond adolescent intelligence….…The second design, policy change, relies on changes in educational duration that are, by all accounts, exogenous to the characteristics of the individuals. An example of this design is the study by Brinch and Galloway (2012), who used large-scale data from a 1960s educational reform in Norway. This reform increased compulsory education by 2 years; critically, it was staggered across municipalities in the country. This allowed the researchers to estimate the effect of an additional year of school on a later intelligence test, taken by males at entry to military service as part of Norway’s universal military draft. Under the assumption that the policy change affected intelligence only via increasing years of schooling, the authors used an instrumental-variables analysis to estimate the effect of 1 year of schooling on intelligence at approximately 3.7 points on a standard IQ scale (M = 100, SD = 15 in the population)….…The third design takes advantage of a school-age cutoff. These studies use regression-discontinuity analysis to leverage the fact that school districts implement a date-of-birth cutoff for school entry. The first study to use this method was by Baltes and Reinert (1969), but the most highly cited example is by Cahan and Cohen (1989), who, in a sample of over 12,000 children across three grades of the Israeli school system (between the ages of approximately 10-12 years), found that schooling exerted positive effects on all of 12 tests covering a variety of cognitive domains. These educational effects were around twice the effect of a year of age. The strict assumptions of this method are some- times not fully met (Cliffordson, 2010); methodological issues are discussed in more detail below….”

Their Evidence

“…In three separate unconditional random-effects meta- analytic models (one for each study design), we estimated the effect of 1 additional year of education on cognitive outcomes. For all three study designs, there was a significant effect of 1 additional year of education. For control prior intelligence, the effect was 1.197 IQ points (SE = 0.203, p = 3.84×10−09); for policy change, it was 2.056 IQ points (SE = 0.583, p = 4.23×10−04); and for school-age cutoff, it was 5.229 IQ points (SE = 0.530, p = 6.33×10−23). An overall model including all estimates from all three designs found an average effect size of 3.394 IQ points for 1 year of education (SE = 0.503, p = 1.55×10−11)….”

Types of Studies They Looked At