Month: November 2024
More market price reactions
Market up like crazy (especially small caps),
1. Freddie Mac (FMCC) and Fannie Mae (FNMA) stocks just gained 35% and 30% respectively on the 2024 election news
https://x.com/Jon_Hartley_/status/1854278771546968569
2. Retail, solar and cannibis stocks all down.
https://x.com/Jon_Hartley_/status/1854286070000861638
While the overall stock market today gained on election news of market friendly regulatory and tax policies in the coming Trump Admin and Republican Senate & House (S&P500 +2.53%, Russell 2000 +5.84%), retail stocks, solar stocks and cannabis stocks all declined today amidst expectations of new tariffs, receding green energy subsidies, and failed cannabis legalization: Retail stocks: DLTR -6.5%, DG -5.1%, NKE -3.4%, YETI -3.0%, FIVE -9.9% Solar stocks: RUN -29.6%, SEDG -22%, ENPH -17%, FSLR -10% Cannabis stocks: CURA -30%, CGC -21%, TLRY -13%, CRON -7.1%
That is from Jon Hartley.
What I’ve been reading
1. Edwin Frank, Stranger Than Fiction: Lives of the Twentieth Century Novel. Very good short portraits of various classic novels, including Machado de Assis, Mann’s Magic Mountain, Dr. Moreau, Carpentier, Perec, and others. At this point I am usually sick of such books but this one I stuck with as it is rewarding throughout.
2. Peter Doggers, The Chess Revolution: From the Ancient World to the Digital Age, is a good book, though it is mostly interior to my current knowledge set.
3. Rebecca Charbonneau, Mixed Signals: Alien Communication Across the Iron Curtain. This book fit well into my recent “Soviet science” reading program. This is more of a “Cold War” book than a “UFO book.” And I learned the full saga behind the Byrds song “C.T.A. – 102” for the first time.
4. Geoffrey Wawro, The Vietnam War: A Military History, is the single best book on its topic and is both intelligent and highly readable.
Coming in 2025 is David Spiegelhalter, The Art of Uncertainty: How to Navigate Chance, Ignorance, Risk and Luck.
The Legacy of Robert Higgs, edited by Christopher J. Coyne, is a very good collection for those interested in the topics Bob worked on.
Louis Kaplow, law and economics professor at Harvard, rethinks merger analysis in Rethinking Merger Analyses.
I have not yet had a chance to start Agustina S. Paglayan, Raised to Obey: The Rise and Spread of Mass Education.
John Cassidy has a forthcoming collection of readings, Capitalism and its Critics, A History: From the Industrial Revolution to AI.
The market price reactions
The dollar surged by its most in two years and Wall Street was poised for big gains as Donald Trump’s historic US election victory sent investors around the world scrambling to price in a new regime of trade tariffs and tax cuts.
The US currency raced higher against the euro, the yen and the pound on Wednesday as traders returned to so-called “Trump trades” in expectation that the president-elect’s plans on tariffs and taxes would boost stocks, push up inflation and reduce the pace of interest rate cuts.
Wall Street was also on course for firm gains at Wednesday’s open, with futures on the S&P 500 index climbing 2 per cent and the Nasdaq 100 up 1.3 per cent.
That is from the FT. Bitcoin is up, and VIX is down.
What is the Best-Case Scenario for a Trump Presidency?
The economy is strong and Trump has a significant opportunity to simply take credit for that if he avoids major disruptions. While he must fulfill some of his campaign promises, people voted for Trump not for his policies per se. Trump has leeway. No one will accuse him of flip-flopping. While these are not my first-best policies, Trump won against astounding media and elite opposition and an attempted assassination. The people have spoken, so here’s a best-case outline for following through on Trump’s policies without cratering the economy:
- Trade Policy: Moderate tariff increases on China. No Chinese electric cars for us. But drop the “tariffs on everything” language. He can always say his rhetoric was a threat to get other countries to lower their tariffs. Let’s instead talk tough against our enemies but shift toward “friend-shoring”, maintaining or even lowering tariffs with allied nations, such as Canada, Europe, and possibly India, as part of a broader strategy to contain China’s influence.
- Border Control: Trump must strengthen the border. But let’s limit deportations to individuals who arrived in the past four years. Control the border, throw some illegals out but minimize human misery by not deporting long-term residents and their US-citizen families. Declare a win while avoiding economic disruption and strengthening the police state.
- Vaccine and Health Policy: Appoint Robert F. Kennedy Jr. to head a committee on vaccine policy and, after several years of investigation, write a report. Take medical freedom more seriously.
- Crypto Regulation: Appoint Hester M. Peirce to head the SEC. Stabilize the regulatory environment for cryptocurrency. Simplify tax rules for crypto. Support digital dollar growth and treat stablecoins as what they are, namely, the US dollar dominating world electronic payments.
- Space and Innovation: U.S. Space Force! Commit to Mars exploration and position the U.S. as a leader in space innovation. Get advice from Elon.
- US AI. Immediately approve Meta for its nuclear-AI program. Swat the bees. Approve Amazon as well. Tell the FERC that their job is to increase the supply of energy. Keep the Chip Act but make it clear that the goal is to dominate the space not make jobs or social policy. We are the world leaders in AI. Let’s keep it that way.
- Kill Bureaucracy: Let Elon Musk take the chainsaw to a few bureaucracies like Javier Milei. Afuera! Afuera! Afuera! Streamline bureaucratic processes, cut red tape and invigorate tech and infrastructure initiatives.
- Respect Meritocracy: End race and gender based discrimination in government programs.
- Expand Housing Supply: Build baby build! Trump is a natural to lead this. Trump the developer! Incentivize states and localities to streamline zoning laws and reduce restrictions that hamper new housing developments. Increase housing supply.
Each of these policies is consistent with Trump’s priorities and rhetoric and has broad appeal for voters who value economic opportunity, accountability, and national resilience. The economy is strong. Trump has the wind at his back. If he is sensible, all of this would make for a successful presidency. If Trump wants the judgment of history, the path is open should he choose to walk it.
Rising in status
1. Prediction markets
2. Competitive primary elections
3. Elon
4. French whales
5. The integrity of the American electoral system
6. J.D. Vance
7. The word “trifecta”
8. Twitter
9. Podcasts
10. Long podcasts
11. The Amish
12. Men
What else?
You don’t have to like all of those outcomes, but that is my assessment. Sometimes I do a “Falling in Status” companion post, but I feel any reasonable approach to that one would be mean-spirited, so I will leave it aside.
Political Sorting in the U.S. Labor Market
That is the central topic of the job market paper of Sahil Chinoy from Harvard University. Here is the abstract:
We study political sorting in the labor market and examine its sources. Merging voter file data and online résumés to create a panel of 34.5 million people, we show that Democrats and Republicans choose distinctive career paths and employers. This leads to marked segregation at the workplace: a Democrat or Republican’s coworker is 10% more likely to share their party than expected. Then, we ask whether segregation arises because jobs shape workers’ politics or because workers’ politics shape their job choices. To study the first, we use a quasi-experimental design leveraging the timing of job transitions. We find that uncommitted workers do adopt the politics of their workplace, but not workers who were already registered Democrats or Republicans. The average effect is too small to generate the segregation we document. To study the second, we measure the intensity of workers’ preferences for politically compatible jobs using two survey experiments motivated by the observational data. Here, we find that the median Democrat or Republican would trade off 3% in annual wages for an ideologically congruent version of a similar job. These preferences are strong enough to generate segregation similar to the observed levels.
Co-authored with Martin Koenen, also a job market candidate from Harvard. Koenen’s other papers, at the link, look very interesting too.
Artificial Intelligence, Scientific Discovery, and Product Innovation
This paper studies the impact of artificial intelligence on innovation, exploiting the randomized introduction of a new materials discovery technology to 1,018 scientists in the R&Dlab of a large U.S. firm. AI-assisted researchers discover 44% more materials, resulting in a 39% increase in patent filings and a 17% rise in downstream product innovation. These compounds possess more novel chemical structures and lead to more radical inventions. However, the technology has strikingly disparate effects across the productivity distribution: while the bottom third of scientists see little benefit, the output of top researchers nearly doubles. Investigating the mechanisms behind these results, I show that AI automates 57% of “idea-generation” tasks, reallocating researchers to the new task of evaluating model-produced candidate materials. Top scientists leverage their domain knowledge to prioritize promising AI suggestions, while others waste significant resources testing false positives. Together, these findings demonstrate the potential of AI-augmented research and highlight the complementarity between algorithms and expertise in the innovative process. Survey evidence reveals that these gains come at a cost, however, as 82% of scientists report reduced satisfaction with their work due to decreased creativity and skill underutilization.
That is from a new paper by Aidan Toner-Rodgers. Via Kris Gulati.
Reupping my post on the vibe shift
You can re-read it here. Much-maligned at the time, I might add.
Track your ballot measure
Here is the link.
Tuesday assorted links
If you must discuss today’s events…
…comments are open. Just don’t expect Alex and I to read it…
The Amazon nuclear project
Nuclear power plants are designed to withstand a plane crash. We are now getting a live experiment in whether the nuclear sector is built of similar stuff, after federal regulators dropped a bomb on Friday night. In a 2-1 vote, the Federal Energy Regulatory Commission rejected an amended interconnection agreement for the deal that sparked a frenzy for nuclear power stocks earlier this year: Amazon.com’s acquisition of a datacenter co-located with a reactor owned by Talen Energy Corp. Few saw it coming, and the sector dived on Monday morning.
Here is more from Bloomberg, via Nicanor.
How much is a rare bee worth?
Plans by Mark Zuckerberg’s Meta to build an AI data centre in the US that runs on nuclear power were thwarted in part because a rare species of bee was discovered on land earmarked for the project, according to people familiar with the matter.
Zuckerberg had planned to strike a deal with an existing nuclear power plant operator to provide emissions-free electricity for a new data centre supporting his artificial intelligence ambitions.
However, the potential deal faced multiple complications including environmental and regulatory challenges, these people said.
Here is more from the FT.
Generative AI and the Nature of Work
Here is a new paper by the following set of authors: Manuel Hoffmann Harvard Business School, Sam Boysel Harvard Business School, Frank Nagle Harvard Business School, Sida Peng Microsoft Corporation, Kevin Xu GitHub, Inc. Here is the abstract:
Recent advances in artificial intelligence (AI) technology demonstrate considerable potential to complement human capital intensive activities. While an emerging literature documents wide-ranging productivity effects of AI, relatively little attention has been paid to how AI might change the nature of work itself. How do individuals, especially those in the knowledge economy, adjust how they work when they start using AI? Using the setting of open source software, we study individual level effects that AI has on task allocation. We exploit a natural experiment arising from the deployment of GitHub Copilot, a generative AI code completion tool for software developers. Leveraging millions of work activities over a two year period, we use a program eligibility threshold to investigate the impact of AI technology on the task allocation of software developers within a quasi-experimental regression discontinuity design. We find that having access to Copilot induces such individuals to shift task allocation towards their core work of coding activities and away from non-core project management activities. We identify two underlying mechanisms driving this shift – an increase in autonomous rather than collaborative work, and an increase in exploration activities rather than exploitation. The main effects are greater for individuals with relatively lower ability. Overall, our estimates point towards a large potential for AI to transform work processes and to potentially flatten organizational hierarchies in the knowledge economy.
Via the excellent Kevin Lewis.
Causal claims in economics
From a new and very interesting web site on that topic:
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Significant Increase in Causal Claims: The average proportion of causal claims in papers rose significantly from approximately 5% in 1990 to around 28% in 2020, reflecting the impact of the credibility revolution in economics.
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Growth in Causal Inference Methods and decline in Theoretical and Simulation Methods…
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Intricate Causal Narratives Enhance Publication and Citation Impact: Papers featuring intricate and interconnected causal narratives are more likely to be published in top-tier journals, particularly the top 5 journals, and receive more citations, especially within those journals.
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Key Measures of Causal Narrative Complexity: Increases in the number of unique paths and the longest path length in causal knowledge graphs are positively associated with both publication in leading economics journals and higher citation counts. This highlights the value placed on depth and complexity in causal narratives.
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Depth Over Quantity in Causal Claims: While the overall number of claims made is positively correlated with top journal publications, the number of causal edges alone does not show the same positive association with publication outcomes or citation counts. This suggests that depth over breadth in causal claims is valued...
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Novel Causal Relationships Enhance Publication but Not Citation Impact: Papers introducing novel causal relationships that have not been previously documented are more likely to be published in top 5 journals, indicating a premium on originality for publication success. However, this does not necessarily translate into higher citation counts once published.
Here is an associated tweet storm,
Obviously it can be argued either way, but I see these results as more negative for the causality revolution than positive? It seems there is too much emphasis on generating a defensible results from a hitherto unused data set. I understand the signaling value here, but the social value is not always obvious. I am struck by how often I meet economics graduate students who can reason about programming more effectively than they can reason about the real world.