Category: Data Source
The sick leave culture that is German
Germans are the “world champions in sick leave”, according to the head of the country’s biggest insurer, who was criticised for demanding that workers without a doctor’s note are unpaid for their first day off.
With the economy slowing and the welfare system under pressure, Germany can ill afford its average per worker of 20 sick days a year, said Oliver Bäte, the chief executive of Allianz SE. The EU average is eight.
The figure of 20 days, based on research by the health insurer DAK, puts a further dent in Germany’s ailing work ethic reputation. Last April, Christian Lindner, then finance minister, admitted that the French, Italians and other nationalities worked “a lot more than we do”, after OECD data showed Germans put in significantly fewer working hours per year than their EU and British neighbours…
“In countries like Switzerland and Denmark people work a month longer per year on average — with comparable pay,” he pointed out.
Here is more from the Times of London. If you can get through the gate, you will see it is Mexico that is the work ethic country.
Evolving Returns to Personality
Weanalyze trends in labor-market returns to psychological traits using data from half a million Finnish men from 2001 to 2015. Cognitive skills’ value declined, while noncognitive skills’ value increased. Our novel findings show that extraversion drives this rise, while conscientiousness remains stable. Extraversion’s rising returns are most pronounced for lower earners and those on the employment margin. These traits predict different labor market paths: extraversion predicts lower education and more work experience, while cognitive ability and conscientiousness lead to higher education and high-paying jobs.
That is from a recent paper by Ramin Izadi and Joonas Tuhkuri.
One early report on congestion pricing in NYC
That is my latest Bloomberg column, here is one bit:
The core version of the plan stipulates a $9 toll for drivers entering Manhattan below and including 60th Street. Implementation is by E-Z Pass, and the tolls can vary in complex ways. But if you don’t cross the line, you don’t pay. So residents below 60th Street are exempt, provided they stay within the zone.
And:
The data do indicate some effective immediate adjustments. Most notably, morning commutes through the major bridges and tunnels into Manhattan have eased. Presumably the tolls have discouraged some drivers whose trips were less important to them, leading to quicker travel times for those drivers willing to pay. Economists typically consider such changes to be an improvement.
Such changes, however, aren’t of much help to native New Yorkers, in particular those living inside the zone. The earliest measurements indicate that traffic within the zone has not eased notably. So far, I would say the biggest beneficiaries of the policy are the wealthier residents of New Jersey and the New York state government, which is now set to take in more revenue.
Whatever you think of those consequences — YMMV, as they say — at least there is now actual data to sift through. You can track it here, and again it is important to stress that these preliminary assessments may change with time.
Many Manhattanites supported the charges on the grounds that they wanted a quieter, cleaner, less congested center city that was more friendly to bicycles and pedestrians. Think of Copenhagen or Amsterdam, if you have ever been. What they may end up getting is a central city more friendly to their cars — and less friendly to outsiders. It remains to be seen if central Manhattan has a path to becoming truly pleasant in the Nordic sense.
I will continue to follow this issue, as new results will be coming in. Of course stiff tolls on those living inside the zone were the correct thing to do. But that is not how politics works.
When did sustained economic growth begin?
The subtitle is New Estimates of Productivity Growth in England from 1250 to 1870, and the authors are Paul Bouscasse, Emi Nakamura, and Jón Steinsson. Abstract:
We estimate productivity growth in England from 1250 to 1870. Real wages over this period were heavily influenced by plague-induced swings in the population. Our estimates account for these Malthusian dynamics. We find that productivity growth was zero prior to 1600. Productivity growth began in 1600—almost a century before the Glorious Revolution. Thus, the onset of productivity growth preceded the bourgeois institutional reforms of 17th century England. We estimate productivity growth of 2% per decade between 1600 and 1800, increasing to 5% per decade between 1810 and 1860. Much of the increase in output growth during the Industrial Revolution is explained by structural change—the falling importance of land in production—rather than faster productivity growth. Stagnant real wages in the 18th and early 19th centuries—“Engel’s Pause”—is explained by rapid population growth putting downward pressure on real wages. Yet, feedback from population growth to real wages is sufficiently weak to permit sustained deviations from the “iron law of wages” prior to the Industrial Revolution.
The 17th century truly is the important century.
Covering immigration is a mixed bag
This paper investigates the effect of media coverage on immigration attitudes. It combines data on immigration coverage in French television with individual panel data from 2013 to 2017 that records respondents’ preferred television channel and attitudes toward immigration. The analysis focuses on within-individual variations over time, addressing ideological self-selection into channels. We find that increased coverage of immigration polarizes attitudes, with initially moderate individuals becoming more likely to report extremely positive and negative attitudes. This polarization is mainly driven by an increase in the salience of immigration, which reactivates pre-existing prejudices, rather than persuasion effects from biased news consumption.
That is by Sarah Schneider-Strawczynski and Jérôme Valette, and here is the AEA-gated link, here are less gated copies. You can even see this effect in the MR comments section and also on Twitter. People are not persuaded by good arguments, rather they just think about the issue more, which in many cases leads them into further error and negative contagion.
How Socio-Economic Background Shapes Academia
We explore how socio-economic background shapes academia, collecting the largest dataset of U.S. academics’ backgrounds and research output. Individuals from poorer backgrounds have been severely underrepresented for seven decades, especially in humanities and elite universities. Father’s occupation predicts professors’ discipline choice and, thus, the direction of research. While we find no differences in the average number of publications, academics from poorer backgrounds are both more likely to not publish and to have outstanding publication records. Academics from poorer backgrounds introduce more novel scientific concepts, but are less likely to receive recognition, as measured by citations, Nobel Prize nominations, and awards.
That is from a new NBER working paper by
Is academic writing getting harder to read?
To track academic writing over time, The Economist analysed 347,000 PhD abstracts published between 1812 and 2023. The dataset was produced by the British Library and represents a majority of English-language doctoral theses awarded by British universities. We reviewed each abstract using the Flesch reading-ease test, which measures sentence and word length to gauge readability. A score of 100 roughly indicates passages can be understood by someone who has completed fourth grade in America (usually aged 9 or 10), while a score lower than 30 is considered very difficult to read. An average New York Times article scores around 50 and a CNN
article around 70. This article scores 41…We found that, in every discipline, the abstracts have become harder to read over the past 80 years. The shift is most stark in the humanities and social sciences (see chart), with average Flesch scores falling from around 37 in the 1940s to 18 in the 2020s. From the 1990s onwards, those fields went from being substantially more readable than the natural sciences—as you might expect—to as complicated. Ms Louks’s abstract had a reading-ease rating of 15, still more readable than a third of those analysed in total.
Here is more from The Economist, via the excellent Samir Varma.
The importance of transportation for productivity
We quantify the aggregate, regional and sectoral impacts of transportation productivity growth on the US economy over the period 1947-2017. Using a multi-region, multi-sector model that explicitly captures produced transportation services as a key input to interregional trade, we find that the calibrated change in transportation productivity had a sizable impact on aggregate welfare, magnified by a factor of 2.3 compared to its sectoral share in GDP. The amplification mechanism results from the complementarity between transport services and tradable goods, interacting with sectoral and spatial linkages. The geographical implications are highly uneven, with the West and Southwest benefiting the most from market access improvements while the Northeast experiences a decline. Sectoral impacts are largest in transportation-intensive activities like agriculture, mining and heavy manufacturing. Our results demonstrate the outsized and heterogeneous impact of the transportation sector in shaping US economic activity through specialization and spatial transformation.
That is from a recent NBER working paper by
The new o3 model from OpenAI
Some more results. And this:
Yupsie-dupsie, delivery of this:
Happy holidays people, hope you are enjoying the presents!
Unconventional Indicators of National Aspiration
What are your top indicators of national aspiration? Percentage of GDP devoted to R&D would be a good conventional indicator. What about some unconventional indicators? My top five:
1) Top marginal tax rate
2) Space Program
3) Distance to travel to mother’s home
4) Tallest statue
5) Cultural exports
On these, the US and India perform well. India leads on tallest statue and its space program is impressive for a developing country. Cultural exports are currently low but historically high–I would not be surprised at a rebound. A lot of eastern European countries such as Hungary and Romania have flat taxes with top rates of 10-15%. Israel has a space program.
I am always surprised by how little people tend to move from the family home. In the US:
…80% of young adults migrate less than 100 miles from where they grew up. 90% migrate less than 500 miles. Migration distances are shorter for Black and Hispanic individuals and for those from low-income families
If anything this seems to be down in the US despite the much greater ease of moving today than in the past.
Your unconventional indicator?
Hat tip: Connor.
Why are Top Scientists Leaving Harvard?
Harvard magazine has an excellent interview with three scientists, Michael Mina, Douglas Melton and Stuart Schreiber, all highly regarded in their fields of life sciences, who have recently left Harvard for the private sector.
Why did they leave? Mina tells an incredible story of what happened during the pandemic. At the time Mina was a faculty member at the Chan School of Public Health, he is extremely active in advising governments on the pandemic, and he brings Harvard millions of dollars a year in funding. But when he tries to hire someone at his lab, the university refuses because there is hiring freeze! Sorry, no hiring for pandemic research during a pandemic. In my talk on US Pandemic Policy I discuss the similar failure of the Yale School of Public Health and how miraculously and absurdly Tyler stepped in to save the day. The rot is deep.
Melton also notes the difference in speed of response between the public and private/commercial sector:
Polls have shown that principal investigator biologists now spend up to 40 percent of their time—it’s a shocking number, 40 percent of their time—writing grants.
In industry, the funding allows for very rapid change. There’s no writing a grant and waiting six months to see if it could get funded, and then waiting another six months for the university to make arrangements to receive the funds. The speed with which you can move into a new area is not comparable.
Years ago, the pharmaceutical industry rarely did discovery research. But now, pharmaceutical companies do basic science. That’s been a good shift, in my opinion, but it’s been a shift.
“The computational resources, the sequencing, the chemical screening— it’s not comparable to what we can do in any university.”
Everything gets done much quicker. For example, when you want to file for a patent at a company, the next morning there are two patent attorneys in your office ready to write that patent. The computational resources, the sequencing, the chemical screening— it’s not comparable to what we can do in any university. It’s a whole order of magnitude different.
Our last hire at GMU took well over a year to complete. It’s outrageous. There are no functional reasons why universities should be so slow. Don’t forget, Harvard has an endowment of $50 billion!
Melton also asks whether a new private-public partnership model is possible:
Why can’t we find a way—since many of our undergraduates and graduates will end up working in industry—why can’t we find a way for them to do their studies and their Ph.D. and their postdoctoral work in conjunction with Harvard, with MIT, and with Vertex? There are reasons for that, but we haven’t been imaginative enough to think about a compromise.
Hat tip: R.P.
Thomas Storrs on elastic data supply (from my email)
Regarding your post yesterday Are LLMs running out of data?, the National Archives has 13.5 billion pieces of paper and only 240 million are digitized. Some of this is classified or otherwise restricted, but surely we can do better than less than 2%.
NARA says they aim to increase this to 500 million by the end of 2026. Even with an overly generous $1/record estimate, it makes sense to me for someone to digitize much of the remaining 13 billion though the incentives are tricky for private actors. Perhaps a consortium of AI companies could make it work. It’s a pure public good so I would be happy with a federal appropriation.
Admittedly, I have a parochial interest in specific parts’ being digitized on mid-20th century federal housing policy. Nonetheless, supply of data for AI is obviously elastic and there’s some delicious low-hanging fruit available.
The National Archives are probably the biggest untapped source of extant data. There are hundreds of billions of more pages around the world though.
Technological Disruption in the US Labor Market
Deming, Ong and Summers have a good overview of long-run and very recent changes in the US labor market. Using a measure of occupational titles the authors find:
The years spanning 1990-2017 were the most stable period in the history of the US labor market, going back nearly 150 years.
It’s a bit too early to distinguish an AI revolution from a COVID shock but the last four years look to be more disruptive than any since the 1970s and over a slightly longer period there are trends including a decline in retail, as consumers shift to online shopping and delivery, and a decline in office work, the latter especially suggesting an AI effect:
There were 850,000 fewer retail sales workers in the US in 2023 compared to 2013 even though the US economy added more than 19 million jobs over this period.
There are nearly five hundred thousand fewer secretaries and administrative assistants in the US labor force now than there were a decade ago. At the same time, management and business occupations have grown very rapidly. There were four million more managers and 3.5 million more business and financial operations jobs in the US in 2023 than there were in 2013.
Keep in mind that these changes are occurring as employment and wages overall are rising.
The Effects of Gender Integration on Men
Evidence from the U.S. military:
Do men negatively respond when women first enter an occupation? We answer this question by studying the end of one of the final explicit occupational barriers to women in the U.S.: in 2016, the U.S. military opened all positions to women, including historically male-only combat occupations. We exploit the staggered integration of women into combat units to estimate the causal effects of the introduction of female colleagues on men’s job performance, behavior, and perceptions of workplace quality, using monthly administrative personnel records and rich survey responses. We find that integrating women into previously all-male units does not negatively affect men’s performance or behavioral outcomes, including retention, promotions, demotions, separations for misconduct, criminal charges, and medical conditions. Most of our results are precise enough to rule out small, detrimental effects. However, there is a wedge between men’s perceptions and performance. The integration of women causes a negative shift in male soldiers’ perceptions of workplace quality, with the effects driven by units integrated with a woman in a position of authority. We discuss how these findings shed light on the roots of occupational segregation by gender.
That is all from
Gender Composition and Group Behavior
Evidence from city councils:
How does gender composition influence individual and group behavior? To study this question empirically, we assembled a new, national sample of United States city council elections and digitized information from the minutes of over 40,000 city-council meetings. We find that replacing a male councilor with a female councilor results in a 25p.p. increase in the share of motions proposed by women. This is despite causing only a 20p.p. increase in the council female share. The discrepancy is driven, in part, by behavioral changes similar to those documented in laboratory-based studies of gender composition. When a lone woman is joined by a female colleague, she participates more actively by proposing more motions. The apparent changes in behavior do not translate into clear differences in spending. The null finding on spending is not driven by strategic voting; however, preference alignment on local policy issues between men and women appears to play an important role. Taken together, our results both highlight the importance of nominal representation for cultivating substantive participation by women in high-stakes decision making bodies; and also provide evidence in support of the external validity of a large body of laboratory-based work on the consequences of group gender composition.
That is from a new NBER working paper by