Category: Data Source
How to rise to the very top?
From athletes like Simone Biles and Michael Phelps to scientists like Marie Curie and Albert Einstein, identifying exceptional talent is essential in the science of innovation. But how does talent originate? Did the most talented athletes, scientists, and musicians reach peak performance relatively early or late in their career? Did they forgo mastering multiple sports, academic subjects, and musical instruments to reach world-class performance in only one? In an Analytical Review, Güllich et al. looked at published research in science, music, chess, and sports and found two patterns: Exceptional young performers reached their peak quickly but narrowly mastered only one interest (e.g., one sport). By contrast, exceptional adults reached peak performance gradually with broader, multidisciplinary practice. However, elite programs are designed to nurture younger talent.
That is from a new article in Science by Arne Güllich, Michael Barth, David Z. Hambrick, and Brooke N. Macnamara. Via Atta Tarki. But are they conditioning on a collider? Short players seem to do pretty well in today’s NBA…
An RCT on AI and mental health
Young adults today face unprecedented mental health challenges, yet many hesitate to seek support due to barriers such as accessibility, stigma, and time constraints. Bite-sized well-being interventions offer a promising solution to preventing mental distress before it escalates to clinical levels, but have not yet been delivered through personalized, interactive, and scalable technology. We conducted the first multi-institutional, longitudinal, preregistered randomized controlled trial of a generative AI-powered mobile app (“Flourish”) designed to address this gap. Over six weeks in Fall 2024, 486 undergraduate students from three U.S. institutions were randomized to receive app access or waitlist control. Participants in the treatment condition reported significantly greater positive affect, resilience, and social well-being (i.e., increased belonging, closeness to community, and reduced loneliness) and were buffered against declines in mindfulness and flourishing. These findings suggest that, with purposeful and ethical design, generative AI can deliver proactive, population-level well-being interventions that produce measurable benefits.
That is from a new paper by Julie Y.A. Cachia, et.al. A single paper or study is hardly dispositive, even when it is an RCT. But you should beware of those, such as Jon Haidt and Jean Twenge, who are conducting an evidence-less jihad against AI for younger people.
Via the excellent Kevin Lewis.
California facts of the day
At Berkeley, as recently as 2015, white male hires were 52.7 percent of new tenure-track faculty; in 2023, they were 21.5 percent. UC Irvine has hired 64 tenure-track assistant professors in the humanities and social sciences since 2020. Just three (4.7 percent) are white men. Of the 59 Assistant Professors in Arts, Humanities and Social Science appointed at UC Santa Cruz between 2020-2024, only two were white men (3 percent).
Here is the essay by Jacob Savage that everyone is talking about.
Growth Matters
Between 2011 and 2023 India’s GDP per capita grew at a rate of about 4.8% per year so in those 12 years GDP per capita, a good measure of the standard of living, nearly doubled (77%). Shamika Ravi and Sindhuja Penumarty look at what this means on the ground.
The percentage of the budget spent on food has declined–dropping below 50% for the first time ever–and that has enabled significant purchases of consumer durables.
It will perhaps not be surprising that mobile phones have become universal among both the poor and the rich but vehicle ownership is also converging with rural ownership of a vehicle (2 or 4 wheeler) nearly tripling from (19% to 59%).
Another standout is refrigerators which reflects growing income and reliable electricity. In the 12 years across the survey, refrigerator ownership in rural areas more than tripled from 9.4% circa 2011 to 33.2% in 2023. In urban areas refrigerator ownership went from less than half (43.8%) to more than two-thirds (68.1%) of urban households. Overall, only two states Bihar (37.1%) and Odisha (46.3%), had less than 50% of urban households owning a refrigerator in 2023-24.
Economists are often accused of “line go up” thinking but the truth is that line go up matters. The 4.8% annual growth matters because it shows up as a broad, visible upgrade in how people live.
Cats, dogs, and babies, in Taiwan
Using newly linked Taiwanese administrative datasets, including an annual census of dog and cat registrations from 1999 to 2020 matched to complete personal tax records from 2009 to 2020, we revisit the claim that “pets crowd out babies.” We exploit two quasi-experimental price shocks: a childbirth subsidy and large receipt lottery windfalls. These allow us to estimate cross elasticities between childbearing and pet ownership. The results reveal a Marshallian cross elasticity of −1.32: as the effective cost of children falls, pet ownership rises. Combined with income elasticity estimates, we recover a child price elasticity of fertility of −0.21, suggesting that pets and children are complements, not substitutes. Event study evidence reveals dynamic asymmetry. Acquiring a dog sharply increases subsequent births among previously childless adults (a “starter family” effect), while a new baby temporarily depresses further pet acquisitions, likely due to time constraints. Overall, our findings challenge popular narratives and suggest that pet ownership may support, rather than displace, fertility.
That is from an AEA session paper by Kuan-Ming Chen, Ming-Jen Lin, Hau-Hung Yang, and Shirley Yen, here is the online abstract.
Is involuntary hospitalization working?
From Natalia Emanuel, Valentin Bolotnyy, and Pim Welle:
The involuntary hospitalization of people experiencing a mental health crisis is a widespread practice, as common in the US as incarceration in state and federal prisons and 2.4 times as common as death from cancer. The intent of involuntary hospitalization is to prevent individuals from harming themselves or others through incapacitation, stabilization and medical treatment over a short period of time. Does involuntary hospitalization achieve its goals? We leverage quasi-random assignment of the evaluating physician and administrative data from Allegheny County, Pennsylvania to estimate the causal effects of involuntary hospitalization on harm to self (proxied by death by suicide or overdose) and harm to others (proxied by violent crime charges). For individuals whom some physicians would hospitalize but others would not, we find that hospitalization nearly doubles the probability of being charged with a violent crime and more than doubles the probability of dying by suicide or overdose in the three months after evaluation. We provide evidence of housing and earnings disruptions as potential mechanisms. Our results suggest that on the margin, the system we study is not achieving the intended effects of the policy.
Here is the abstract online at the AEA site. I am looking forward to seeing more of this work.
How bad was British “austerity” anyway?
Chris Giles writes in the FT:
The main periods of measurement error came in the austerity years of 2012 to 2014, in 2017 during the early period after the Brexit referendum and in recent post-pandemic years. The truth is that a huge pessimistic bias in our national accounts has led us to be fed with contemporary reports of doom and gloom, which subsequently turn out to be nonsense.
But it is the first version of economic events that enters the national debate — and the national consciousness — for the entirely understandable reason that initial releases of economic data make news. You cannot expect people to care deeply about a revision to data that is three years old. Psychologically, they have made up their mind by then.
We are still told that 2010s austerity destroyed growth, but the data no longer supports that story: growth between David Cameron’s election victories of 2010 and 2015 now registers an annualised average of 2 per cent.
Somehow I am not seeing people jumping all over this story? Is it even correct? I have not seen anyone refute or counter it. Here is the analysis from 5.2 Pro, largely confirming, though it suggests 1.8% to 1.9% is a better estimate than 2%. I am very open to alternative points of view here, but at the moment it appears the correct stance was a) the British economic problems were largely structural and would not just be fixed by an aggregate demand boost, and b) fiscal consolidation was necessary, and while done imperfectly, not a disaster relative to the alternatives available.
The dust has not yet settled, but perhaps most of you were basically just wrong on this one?
Art as Data in Political History
From Valentine Figuroa of MIT:
Ongoing advances in machine learning are expanding opportunities to analyze large-scale visual data. In historical political economy, paintings from museums and private collections represent an untapped source of information. Before computational methods can be applied, however, it is essential to establish a framework for assessing what information paintings encode and under what assumptions it can be interpreted. This article develops such a framework, drawing on the enduring concerns of the traditional humanities. I describe three applications using a database of 25,000 European paintings from 1000CE to the First World War. Each application targets a distinct type of information conveyed in paintings (depicted content, communicative intent, and incidental information) and a cultural transformation of the early-modern period. The first revisits the notion of a European “civilizing process”—the internalization of stricter norms of behavior that occurred in tandem with the growth of state power—by examining whether paintings of meals show increasingly complex etiquette. The second analyzes portraits to study how political elites shaped their public image, highlighting a long-term shift from chivalric to more rational-bureaucratic representations of men. The third documents a long-term process of secularization, measured by the share of religious paintings, which began prior to the Reformation and accelerated afterward.
Here is the link, via the excellent Kevin Lewis.
Did market power go up so much?
It seems not:
De Loecker et al. (2020) (DEU) estimate that markups increased significantly in the United States from 1955 to 2016. We find this result is sensitive to unreported sample restrictions that drop 27% of the available observations. Applying the methodology as described in the article to the full sample, markup increases are more muted until late in the sample period, and are almost entirely driven by Finance and Insurance firms. If these firms are removed, markup increases are modest. We conclude that the DEU methodology and data, as they are described in the article, do not support the conclusion that broad-based increases in market power have occurred in recent decades.
That is from a recent NBER working paper by Benkard, Miller, and Yurukoglu.
Quantifying human-AI synergy
From Christoph Riedl and Ben Weidmann:
We introduce a novel Bayesian Item Response Theory framework to quantify human–AI synergy, separating individual and collaborative ability while controlling for task difficulty in interactive settings. Unlike standard static benchmarks, our approach models human–AI performance as a joint process, capturing both user-specific factors and moment-to-moment fluctuations. We validate the framework by applying it to human–AI benchmark data (n=667) and find significant synergy. We demonstrate that collaboration ability is distinct from individual problem-solving ability. Users better able to infer and adapt to others’ perspectives achieve superior collaborative performance with AI–but not when working alone. Moreover, moment-to-moment fluctuations in perspective taking influence AI response quality, highlighting the role of dynamic user factors in collaboration. By introducing a principled framework to analyze data from human-AI collaboration, interactive benchmarks can better complement current single-task benchmarks and crowd-assessment methods. This work informs the design and training of language models that transcend static prompt benchmarks to achieve adaptive, socially aware collaboration with diverse and dynamic human partners.
Here is a useful tweet storm on the work. I do not love how the abstract is written, I would stress these sentences: “We demonstrate that collaboration ability is distinct from individual problem-solving ability. Users better able to infer and adapt to others’ perspectives achieve superior collaborative performance with AI–but not when working alone. Moreover, moment-to-moment fluctuations in perspective taking influence AI response quality, highlighting the role of dynamic user factors in collaboration.”
Does studying economics and business make students more conservative?
College education is a key determinant of political attitudes in the United States and other countries. This paper highlights an important source of variation among college graduates: studying different academic fields has sizable effects on their political attitudes. Using surveys of about 300,000 students across 500 U.S. colleges, we find several results. First, relative to natural sciences, studying social sciences and humanities makes students more left-leaning, whereas studying economics and business makes them more right-leaning. Second, the rightward effects of economics and business are driven by positions on economic issues, whereas the leftward effects of humanities and social sciences are driven by cultural ones. Third, these effects extend to behavior: humanities and social sciences increase activism, while economics and business increase the emphasis on financial success. Fourth, the effects operate through academic content and teaching rather than socialization or earnings expectations. Finally, the implications are substantial. If all students majored in economics or business, the college–noncollege ideological gap would shrink by about one-third. A uniform-major scenario, in which everyone studies the same field, would reduce ideological variance and the gender gap. Together, the results show that academic fields shape students’ attitudes and that field specialization contributes to political fragmentation.
That is a recent paper from Yoav Goldstein and Matan Kolerman. Here is a thread on the paper.
Colors of growth
This looks pretty tremendous:
We develop a novel approach to measuring long-run economic growth by exploiting systematic variation in the use of color in European paintings. Drawing inspiration from the literature on nighttime lights as a proxy for income, we extract hue, saturation, and brightness from millions of pixels to construct annual indices for Great Britain, Holland, France, Italy, and Germany between 1600 and 1820. These indices track broad trends in existing GDP reconstructions while revealing higher frequency fluctuations – such as those associated with wars, political instability, and climatic shocks – that traditional series smooth over. Our findings demonstrate that light, decomposed into color and brightness components, provides a credible and independent source of information on early modern economic activity.
That is new research by Lars Boerner, Tim Reinicke, Samad Sarferaz, and Battista Severgnini. Via Ethan Mollick.
Planning sentences to ponder
Planning assistance caused municipalities to build 20% fewer housing units per decade over the 50 years that followed.
Here is the full abstract:
We study how the federal Urban Planning Assistance Program, which subsidized growing communities in the 1960s to hire urban planners to draft land-use plans, affected housing supply. Using newly digitized records merged with panel data across municipalities on housing and zoning outcomes, we exploit eligibility thresholds and capacity to approve funds across state agencies to identify effects. Planning assistance caused municipalities to build 20% fewer housing units per decade over the 50 years that followed. Regulatory innovation steered construction in assisted areas away from apartments and toward larger single-family homes. Textual evidence related to zoning and development politics further shows that, since the 1980s, assisted communities have disincentivized housing supply by passing on development costs to developers. These findings suggest that federal intervention in planning helped institutionalize practices that complicate community growth, with subsequent consequences for national housing affordability.
Hail Martin Anderson! The above paper is by Tom Cui and Beau Bressler, via Brad, and also Yonah Freemark.
Congressional leadership is corrupt
Using transaction-level data on US congressional stock trades, we find that lawmakers who later ascend to leadership positions perform similarly to matched peers beforehand but outperform them by 47 percentage points annually after ascension. Leaders’ superior performance arises through two mechanisms. The political influence channel is reflected in higher returns when their party controls the chamber, sales of stocks preceding regulatory actions, and purchase of stocks whose firms receiving more government contracts and favorable party support on bills. The corporate access channel is reflected in stock trades that predict subsequent corporate news and greater returns on donor-owned or home-state firms.
That is from a new NBER working paper by Shang-Jin Wei and Yifan Zhou. Of course Alex T. has been on this issue for a long time now.
Meta-analytical effect of economic inequality on well-being or mental health
Some of us have known this for some time:
Exposure to economic inequality is widely thought to erode subjective well-being and mental health, which carries important societal implications. However, existing studies face reproducibility issues, and theory suggests that inequality only affects individuals in disadvantaged contexts. Here we present a meta-analysis of 168 studies using multilevel data (11,389,871 participants from 38,335 geographical units) identified across 10 bibliographical databases (2000–2022). Contrary to popular narratives, random-effects models showed that individuals in more unequal areas do not report lower subjective well-being (standardized odds ratio (OR+0.05) = 0.979, 95% confidence interval = 0.951–1.008). Moreover, although inequality initially seemed to undermine mental health, the publication-bias-corrected association was null (OR+0.05 = 1.019; 0.990–1.049)17. Meta-analytical effects were smaller than the smallest effect of interest, and specification curve analyses confirmed these results across ≈95% of 768 alternative models. When assessing study quality and certainty of evidence using ROBINS-E and GRADE criteria, ROBINS-E rated 80% of studies at high risk of bias, and GRADE assigned greater certainty to the null effects than to the negative effects. Meta-regressions revealed that the adverse association between inequality and mental health was confined to low-income samples. Moreover, machine-learning analyses19 indicated that the association with well-being was negative in high-inflation contexts but positive in low-inflation contexts. These moderation effects were replicated using Gallup World Poll data (up to 2 million participants). These findings challenge the view that economic inequality universally harms psychological health and can inform public health policy.
That is now published in Nature, by Nicholas Sommet, et.al., via the excellent Kevin Lewis.