Wednesday assorted links

1. Douglas Irwin on dismantling the Indian license raj.  And Indians praying for visas under Trump.  And podcast on Indian biotech potential.

2. New data on LLMs refereeing economics papers.

3. Do LLMs use trigonometry to do addition?

4. Is Occam’s Razor obsolete?

5. Oliver Kim on exchange rates.

6. New asteroid risk.

7. Heat and economic decision-making.

8. Czech beaver DOGE.

9. Zvi on Deep Research.

10. Is the Peter Principle actually true?

Trumpian policy as cultural policy

The Trump administration has issued a blizzard of Executive Orders, and set many other potential changes in the works.  They might rename Dulles Airport (can you guess to what?).  A bill has been introduced to add you-know-who to Mount Rushmore.  There is DOGE, and the ongoing attempt to reshape federal employment.

At the same time, many people have been asking me why Trump chose Canada and Mexico to threaten with tariffs — are they not our neighbors, major trading partners, and closest allies?

I have a theory that tries to explain all these and other facts, though many other factors matter too.  I think of Trumpian policy, first and foremost, as elevating cultural policy above all else.

Imagine you hold a vision where the (partial) decline of America largely is about culture.  After all, we have more people and more natural resources than ever before.  Our top achievements remain impressive.  But is the overall culture of the people in such great shape?  The culture of government and public service?  Interest in our religious organizations?  The quality of local government in many states?  You don’t have to be a diehard Trumper to have some serious reservations on such questions.

We also see countries, such as China, that have screwed-up policies but have grown a lot, in large part because of a pro-business, pro-learning, pro-work culture.  Latin America, in contrast, did lots of policy reforms but still is somewhat stagnant.

OK, so how might you fix the culture of America?  You want to tell everyone that America comes first.  That America should be more masculine and less soft.  That we need to build.  That we should “own the libs.”  I could go on with more examples and details, but this part of it you already get.

So imagine you started a political revolution and asked the simple question “does this policy change reinforce or overturn our basic cultural messages?”  Every time the policy or policy debate pushes culture in what you think is the right direction, just do it.  Do it in the view that the cultural factors will, over some time horizon, surpass everything else in import.

Simply pass or announce or promise such policies.  Do not worry about any other constraints.

You don’t even have to do them!

They don’t even all have to be legal!  (Illegal might provoke more discussion.)

They don’t all have to persist!

You create a debate over the issues knowing that, because of polarization, at least one-third of the American public is going to take your side, sometimes much more than that.  These are your investments in changing the culture.  And do it with as many issues as possible, as quickly as possible (reread Ezra on this).  Think of it as akin to the early Jordan Peterson cranking out all those videos.  Flood the zone.  That is how you have an impact in an internet-intensive, attention-at-a-premium world.

You will not win all of these cultural debates, but you will control the ideological agenda (I hesitate to call it an “intellectual” agenda, but it is).  Your opponents will be dispirited and disorganized, and yes that does describe the Democrats today.  Then just keep on going.  In the long run, you may end up “owning” far more of the culture than you suspected was possible.

Yes policy will be a mess, but as they say “man kann nicht alles haben.”  The culture is worth a lot, both for its own sake and as a predictor of the future course of policy.

Now let’s turn to some details.

In the first week, Trump makes a huge point of striking down DEI and affirmative action (in some of its forms) as the very beginnings of his administration.  The WSJ described it as the centerpiece of his program.  Take origins seriously!

Early on, we also see so many efforts to make statements about the culture wars.  Trans issues, for instance trans out of the military.  No more “Black History Month” for the Department of Defense.  There are more of these than I can keep track of, use Perplexity if you must.

It is no accident that these are priorities.  And keep in mind the main point is not to eliminate Black History Month, though I do not doubt that is a favored policy.  The main point is to get people talking about how you are eliminating Black History Month.  Just as I am covering the topic right now.

How is that war against US AID going?  Will it be abolished?  Cut off from the Treasury payments system?  Simply rolled up into the State Department?  Presidential “impoundment” invoked?  I do not know.  Perhaps nobody knows, not yet.  The point however is to delegitimatize what US AID stands for, which the Trumpers perceive as “other countries first” and a certain kind of altruism, and a certain kind of NGO left-leaning mindset and lifestyle.

The core message is simply “we do not consider this legitimate.”  Have that be the topic of discussion for months, and do not worry about converting each and every debate into an immediate tangible victory.

What about those ridiculous nominations, starting with RFK, Jr.?  As a result of the nomination, people start questioning whether the medical and public health establishments are legitimate after all.  And once such a question starts being debated, the answer simply cannot come out fully positive, whatever the details of your worldview may be.  People end up in a more negative mental position, and of course then some negative contagion reinforces this further.

JFK and UAP dislcosure?  The point is to get people questioning the previous regime, why they kept secrets from us, what really was going on with many other issues, and so on.  It will work.  The good news, if you can call it that, is that we can expect some of the juicier secrets to be made public.

I think by now you can see how the various attempts to restructure federal employment fit into this picture.  And Trump’s “war against universities” has barely begun, but stay tuned.  Don’t even get me going on “Gaza real estate,” the very latest.

Finally, let’s return to those tariffs (non-tariffs?) on Canada and Mexico.  We already know Trump believes in tariffs, and yes that is a big factor, but why choose those countries in particular?  Well, first it is a symbol of strength and Trump’s apparent ability to ignore and contradict mainstream opinion.  But also those are two countries most Americans have heard of.  If Trump announced high tariffs on say Burundi, most people would have no idea what it means.  They would not know how to debate it, and they would not know if America was debasing itself or thumbing its nose at somebody, or whatever.

Canada and Mexico gets the cultural point across.  Canada, all the more so, and thus the Canadian tariffs might be harder to truly reverse.  At least to many Yankee outsiders, Canada comes across as exactly the kind of “wuss” country we need to distance ourselves from.

To be clear, this hypothesis does not not not require any kind of cohesive elite planning the whole strategy (though there are elites planning significant parts of what Trump is doing).  It suffices to have a) conflicting interest groups, b) competition for Trump’s attention, and c) Trump believing cultural issues are super-important, as he seems to.  There then results a spontaneous order, in which the visible strategy looks just like someone intended exactly this as a concrete plan.

In a future post I may consider the pluses and minuses of this kind of political/cultural strategy.

Deep Research

I have had it write a number of ten-page papers for me, each of them outstanding.  I think of the quality as comparable to having a good PhD-level research assistant, and sending that person away with a task for a week or two, or maybe more.

Except Deep Research does the work in five or six minutes.  And it does not seem to make errors, due to the quality of the embedded o3 model.

It seems it can cover just about any topic?

I asked for a ten-page paper explaining Ricardo’s theory of rent, and how it fits into his broader theory of distribution.  It is a little long, but that was my fault, here is the result.  I compared it to a number of other sources on line, and thought it was better, and so I am using it for my history of economic thought class.

I do not currently see signs of originality, but the level of accuracy and clarity is stunning, and it can write and analyze at any level you request.  The work also shows the model can engage in a kind of long-term planning, and that will generalize to some very different contexts and problems as well — that is some of the biggest news associated with this release.

Sometimes the model stops in the middle of its calculations and you need to kick it in the shins a bit to get it going again, but I assume that problem will be cleared up soon enough.

If you pay for o1 pro, you get I think 100 queries per month with Deep Research.

Solve for the equilibrium, people, solve for the equilibrium.

Tuesday assorted links

1. Congestion Pricing Tracker update, sigh…Economists like to think they are useful, but if the initial policy is not right you can expect the results to be disappointing, as these are so far.  It is true congestion prices that work, not “cordon prices.”

2. How is GPT-4o as a judge?

3. North Koreans at McDonald’s.

4. Redux of my sovereign wealth fund column for Bloomberg.  I am against the idea for the United States, while recognizing that any arbitrarily small version of it will appear to make sense.

5. Trump’s CEA nominee wrote a long memo on how to restructure the global trading system.  I turned to o1 pro for comment.

6. Peter Coy is ending his NYT newsletter.

7. Scott Alexander update on model cities.

8. My Bloomberg column on the economics of the Luka trade.

9. Economist Richard Nelson has passed away.

The New Consensus on the Minimum Wage

My take is that there is an evolving new consensus on the minimum wage. Namely, the effects of the minimum wage are heterogeneous and take place on more margins than employment. Read Jeffrey Clemens’s brilliant and accessible paper in the JEP for the theory. A good example of the heterogeneous impact is this new paper by Clemens, Gentry and Meer on how the minimum wage makes it more difficult for the disabled to get jobs:

…We find that large minimum wage increases significantly reduce employment and labor force participation for individuals of all working ages with severe disabilities. These declines are accompanied by a downward shift in the wage distribution and an increase in public assistance receipt. By contrast, we find no employment effects for all but young individuals with either non-severe disabilities or no disabilities. Our findings highlight important heterogeneities in minimum wage impacts, raising concerns about labor market policies’ unintended consequences for populations on the margins of the labor force.

Or Neumark and Kayla on the minimum wage and blacks:

We provide a comprehensive analysis of the effects of minimum wages on blacks, and on the relative impacts on blacks vs. whites. We study not only teenagers – the focus of much of the minimum wage-employment literature – but also other low-skill groups. We focus primarily on employment, which has been the prime concern with the minimum wage research literature. We find evidence that job loss effects from higher minimum wages are much more evident for blacks, and in contrast not very detectable for whites, and are often large enough to generate adverse effects on earnings.

Remember also that a “job” is not a simple contract of hours of work for dollars but contains many explicit and implicit margins on work conditions, fringe benefits, possibilities for promotion, training and so forth. For example, in Unintended workplace safety consequences of minimum wages, Liu, Lu, Sun and Zhang finds that the minimum wage increases accidents, probably because at a higher minimum wage the pace of work increases: 

we find that large increases in minimum wages have significant adverse effects on workplace safety. Our findings indicate that, on average, a large minimum wage increase results in a 4.6 percent increase in the total case rate.

Note that these effects don’t always happen, in large part because, depending on the scope of the minimum wage increase and the industry, large effects of the minimum wage may be passed on to prices. For example here is Renkin and Siegenthaler finding that higher minimum wage increase grocery prices:

We use high-frequency scanner data and leverage a large number of state-level increases in minimum wages between 2001 and 2012. We find that a 10% minimum wage hike translates into a 0.36% increase in the prices of grocery products. This magnitude is consistent with a full pass-through of cost increases into consumer prices.

Similarly, Ashenfelter and Jurajda find there is no free lunch from minimum wage increases, indeed there is approximately full pass through at McDonalds:

Higher labor costs induced by minimum wage hikes are likely to increase product prices.4 If both labor and product markets are competitive, firms can pass through up to the full increase in costs (Fullerton and Metcalf 2002). With constant returns to scale, firms adjust prices in response to minimum wage hikes in proportion to the cost share of minimum wage labor. Under full price pass-through, the real income increases of low-wage workers brought about by minimum wage hikes may be lower than expected (MaCurdy 2015). There is growing evidence of near full price pass-through of minimum wages in the United States….Based on data spanning 2016–20, we find a 0.2 price elasticity with respect to wage increases driven (instrumented) by minimum wage hikes. Together with the 0.7 (first-stage) elasticity of wage rates with respect to minimum wages, this implies a (reduced-form) price elasticity with respect to minimum wages of about 0.14. This corresponds to near-full price pass-through of minimum-wage-induced higher costs of labor.

You can draw your own conclusions about the desirability of the minimum wage, but the fleeting hope that it raises wages without trade-offs is gone. The effects of the minimum wage are nuanced, heterogeneous, and by no means entirely positive.

Gradual Empowerment?

The subtitle is “Systemic Existential Risks from Incremental AI Development,” and the authors are Jan Kulveit, et.al.  Several of you have asked me for comments on this paper.  Here is the abstract:

This paper examines the systemic risks posed by incremental advancements in artificial intelligence, developing the concept of `gradual disempowerment’, in contrast to the abrupt takeover scenarios commonly discussed in AI safety. We analyze how even incremental improvements in AI capabilities can undermine human influence over large-scale systems that society depends on, including the economy, culture, and nation-states. As AI increasingly replaces human labor and cognition in these domains, it can weaken both explicit human control mechanisms (like voting and consumer choice) and the implicit alignments with human interests that often arise from societal systems’ reliance on human participation to function. Furthermore, to the extent that these systems incentivise outcomes that do not line up with human preferences, AIs may optimize for those outcomes more aggressively. These effects may be mutually reinforcing across different domains: economic power shapes cultural narratives and political decisions, while cultural shifts alter economic and political behavior. We argue that this dynamic could lead to an effectively irreversible loss of human influence over crucial societal systems, precipitating an existential catastrophe through the permanent disempowerment of humanity. This suggests the need for both technical research and governance approaches that specifically address the risk of incremental erosion of human influence across interconnected societal systems.

This is one of the smarter arguments I have seen, but I am very far from convinced.  When were humans ever in control to begin with?  (Robin Hanson realized this a few years ago and is still worried about it, as I suppose he should be.  There is not exactly a reliable competitive process for cultural evolution — boo hoo!)

Note the argument here is not that a few rich people will own all the AI.  Rather, humans seem to lose power altogether.  But aren’t people cloning DeepSeek for ridiculously small sums of money?  Why won’t our AI future be fairly decentralized, with lots of checks and balances, and plenty of human ownership to boot?

Rather than focusing on “humans in general,” I say look at the marginal individual human being.  That individual — forever as far as I can tell — has near-zero bargaining power against a coordinating, cartelized society aligned against him.  With or without AI.  Yet that hardly ever happens, extreme criminals being one exception.  There simply isn’t enough collusion to extract much from the (non-criminal) potentially vulnerable lone individuals.

I do not in this paper see a real argument that a critical mass of the AIs are going to collude against humans.  It seems already that “AIs in China” and “AIs in America” are unlikely to collude much with each other.  Similarly, “the evil rich people” do not collude with each other all that much either, much less across borders.

I feel if the paper made a serious attempt to model the likelihood of worldwide AI collusion, the results would come out in the opposite direction.  So, to my eye, “checks and balances forever” is by far the more likely equilibrium.

Emergent Ventures Africa and Caribbean winners, sixth cohort

Maya Chouikrat, Algeria, to support training for an international olympiad of informatics team.

Mercy Muwanguzi and Kwesiga Pather, Uganda, for sanitation robotics to be used in medical centers.

Johan Fourie, South Africa,  Professor of Economics at Stellenbosch University, to write a graphics novel on classical liberalism in a South African context.

Ken Opalo, Associate Professor, Georgetown University, for blogging on African economic development.

Katharine Patterson, Botswana, to support graduate internship in robotics research at NASA Jet Propulsion Laboratory.

Cyril Narh, Ghana, for general career development.

Jon Ortega, travel grant to Silicon Valley.

Alex Kyabarongo, Uganda, Doctor of Veterinary Medicine from Makerere University, to pursue graduate school in the USA for biosecurity.

Joshua Regrello, Trinidad and Tobago, first Steelpannist to perform on the Great Wall of China, Guinness Record Holder for longest steelpan performance, for general career development.

Liam O’Dea, London/Argentina, data science research into parliamentary records of the Caribbean for the last 200 years.

Joshua Payne, undergrad at University of Chicago, for research into mRNA vaccine optimisation, and career development.

Abdoulaye Faye, Senegal, developing Catyu, a firm that designs remotely operated robots.

Deveron Bruce, Barbados, PhD candidate at UWI, to support research in political reform in the Caribbean.

Tony Odhiambo, Kenya, undergrad at MIT, for enhanced training of top performers in mathematics olympiads in Kenya.

Sebastian Naranjo, Panama, PhD candidate at Renmin University of China, to support research on the diplomatic relations of China in Central America.

Ivoine Strachan, Bahamas, for research into designing and developing a VR bodysuit

Phumiani Majozi, South Africa, to establish a think tank promoting classical liberalism in South Africa

Pearl Karungi, Rwanda, for research into redesigning menstrual products.

Emmanuel Nnadi, Nigeria, Microbiologist, to support visiting research at the University of Waterloo in phage therapies.

Youhana Nassif, Egypt, to support an animation and arts showcase in Cairo.

Frida Andalu, Tanzania, to support visiting research in petroleum engineering at the University of Aberdeen.

Rupert Tawiah-Quashie, Ghana, to support his research internship at Harvard University concerning symbolic reasoning in AI models.

I thank Rasheed Griffith for his excellent work on this, and again Nabeel has created excellent software to help organize the list of winners, using AI.

Those unfamiliar with Emergent Ventures can learn more here and here. The EV African and the Caribbean announcement is here and you can see previous cohorts here. If you are interested in supporting this tranche of Emergent Ventures, please write to me or to Rasheed.

Does the Gender Wage Gap Actually Reflect Taste Discrimination Against Women?

One explanation of the gender wage gap is taste discrimination, as in Becker (1957). We test for taste discrimination by constructing a novel measure of misogyny using Google Trends data on searches that include derogatory terms for women. We find—surprisingly, in our view—that misogyny is an economically meaningful and statistically significant predictor of the wage gap. We also test more explicit implications of taste discrimination. The data are inconsistent with the Becker taste discrimination model, based on the tests used in Charles and Guryan (2008). But the data are consistent with the effects of taste discrimination against women in search models (Black, 1995), in which discrimination on the part of even a small group of misogynists can result in a wage gap.

That is a new NBER working paper by Molly Maloney and David Neumark.

Monday assorted links

1. The world’s most elite sober coach? (FT…his fees seem low to me?)

2. El Salvador planning on releasing many from prison?

3. An early version of portfolio theory, from the late 19th century.  French, of course.

4. Deep Research okie-dokie.  It is amazing.  And a wee bit of data.  And another relevant comment.

5. Ezra on the blitzkrieg strategy (NYT).

6. Medieval trade routes.

7. “525-Lb. Bear Discovered Under Evacuated Altadena Home Too Fat to Tranquilize.

8. Gemini and Cursor in the federal government?

Genetic Prediction and Adverse Selection

In 1994 I published Genetic Testing: An Economic and Contractarian Analysis which discussed how genetic testing could undermine insurance markets. I also proposed a solution, genetic insurance, which would in essence insure people for changes in their health and life insurance premiums due to the revelation of genetic data. Later John Cochrane would independently create Time Consistent Health Insurance a generalized form of the same idea that would allow people to have long term health insurance without being tied to a single firm.

The Human Genome Project completed in 2003 but, somewhat surprisingly, insurance markets didn’t break down, even though genetic information became more common. We know from twin studies that genetic heritability is very large but it turned out that the effect from each gene variant is very small. Thus, only a few diseases can be predicted well using single-gene mutations. Since each SNP has only a small effect on disease, to predict how genes influence disease we would need data on hundreds of thousands, even millions of people, and millions of their SNPs across the genome and their diseases. Until recently, that has been cost-prohibitive and as a result the available genetic information lacked much predictive power.

In an impressive new paper, however, Azevedo, Beauchamp and Linnér (ABL) show that data from Genome-Wide Association Studies can be used to create polygenic risk indexes (PGIs) which can predict individual disease risk from the aggregate effects of many genetic variants. The data is prodigious:

We analyze data from the UK Biobank (UKB) (Bycroft et al., 2018; Sudlow et al., 2015). The UKB contains genotypic and rich health-related data for over 500,000 individuals from across the United Kingdom who were between 40 and 69 years old at recruitment (between 2006 and 2010). UKB data is linked to the UK’s National Health Service (NHS), which maintains detailed records of health events across the lifespan and with which 98% of the UK population is registered (Sudlow et al., 2015). In addition, all UKB participants took part in a baseline assessment, in which they provided rich environmental, family history, health, lifestyle, physical, and sociodemographic data, as well as blood, saliva, and urine samples.

The UKB contains genome-wide array data for 800,000 genetic variants for 488,000 participants.

So for each of these individuals ABL construct risk indexes and they ask how significant is this new information for buying insurance in the Critical Illness Insurance market:

Critical illness insurance (CII) pays out a lump sum in the event that the insured person gets diagnosed with any of the medical conditions listed on the policy (Brackenridge et al., 2006). The lump sum can be used as the policyholder wishes. The policy pays out once and is thereafter terminated. 

Major CII markets include Canada, the United Kingdom, Japan, Australia, India, China, and Germany. It is estimated that 20% of British workers were covered by a CII policy in 2009 (Gatzert and Maegebier, 2015). The global CII market has been valued at over $100 billion in 2021 and was projected to grow to over $350 billion by 2031 (Allied Market Research, 2022).

The answer, as you might have guessed by now, is very significant. Even though current PGIs explain only a fraction of total genetic risk, they are already predictive enough so that it would make sense for individuals with high measured risk to purchase insurance, while those with low-risk would opt out—leading to adverse selection that threatens the financial sustainability of the insurance market.

Today, the 500,000 people in the UK’s Biobank don’t know their PGIs but in principle they could and in the future they will. Indeed, as GWAS sample sizes increase, PGI betas will become more accurate and they will be applied to a greater fraction of an individual’s genome so individual PGIs will become increasingly predictive, exacerbating selection problems in insurance markets.

If my paper was a distant early warning, Azevedo, Beauchamp, and Linnér provide an early—and urgent—warning. Without reform, insurance markets risk unraveling. The authors explore potential solutions, including genetic insurance, community rating, subsidies, and risk adjustment. However, the effectiveness of these measures remains uncertain, and knee-jerk policies, such as banning insurers from using genetic information, could lead to the collapse of insurance altogether.

o1 pro

Often I don’t write particular posts because I feel it is obvious to everybody.  Yet it rarely is.

So here is my post on o1 pro, soon to be followed by o3 pro, and Deep Research is being distributed, which uses elements of o3.  (So far it is amazing, btw.)

o1 pro is the smartest publicly issued knowledge entity the human race has created (aside from Deep Research!).  Adam Brown, who does physics at a world class level, put it well in his recent podcast with Dwarkesh.  Adam said that if he had a question about something, the best answer he would get is from calling up one of a handful of world experts on the topic.  The second best answer he would get is from asking the best AI models.

Except, at least for the moment, you don’t need to make that plural.  There is a single best model, at least when it comes to tough questions (it is more disputable which model is the best and most creative writer or poet).

I find it very difficult to ask o1 pro an economics question it cannot answer.  I can do it, but typically I have to get very artificial.  It can answer, and answer well, any question I might normally pose in the course of typical inquiry and pondering.  As Adam indicated, I think only a relatively small number of humans in the world can give better answers to what I want to know.

In an economics test, or any other kind of naturally occurring knowledge test I can think of, it would beat all of you (and me).

Its rate of hallucination is far below what you are used to from other LLMs.

Yes, it does cost $200 a month.  It is worth that sum to converse with the smartest entity yet devised.  I use it every day, many times.  I don’t mind that it takes some time to answer my questions, because I have plenty to do in the meantime.

I also would add that if you are not familiar with o1 pro, your observations about the shortcomings of AI models should be discounted rather severely.  And o3 pro is due soon, presumably it will be better yet.

The reality of all this will disrupt many plans, most of them not directly in the sphere of AI proper.  And thus the world wishes to remain in denial.  It amazes me that this is not the front page story every day, and it amazes me how many people see no need to shell out $200 and try it for a month, or more.

Sundry observations on the Trump tariffs

Brad Setser estimates the costs at 0.8 percent of U.S: gdp.  I am not sure if he is considering exchange rate adjustments in that figure.

Kevin Bryan writes:

The problem with escalating, again, is that Canada is more reliant on US energy than vice versa, US ports than vice versa, US intermediate goods than vice versa, and DT is basically a narcissist. Again: no normal negotiation here, as the tariffs itself have no logical basis! 4/x

The fentanyl excuse seems like a flimsy (and should be illegal) one to let the exec branch set a tariff rate that constitutionally is Congress’ job. But maybe there is some “give Trump a fake win and de-escalate”. I worry about what that does in the future, though. 5/x

Ben Golub notes:

Modern supply chains don’t look like trade theory 101! They involve constant border crossings, each now hit by tariffs. Tariffs raise prices, but the more important thing they do is disrupt supply relationships.

So when a shock hits, you don’t just have a bit less activity by a few of the least profitable firms. You suddenly knock out some of the relationships (contracts) and some of the nodes (companies) in a large and very complex network. This can be pretty disruptive!

Here is Noah’s post.  Here is the Yale Budget Lab on likely price effects in America.

Here is an Alan Beattie FT piece on how tariffs often matter less than you think.  The size of the costs here can be disputed, but the most relevant fact is that there simply isn’t any upside to the Trump tariff policy.  If you think it is about fentanyl, I have a prediction: the price of fentynal will not be rising anytime soon across the window of a one-year moving average.  Here are some additional relevant points about fentanyl, which from Canada is not a major problem.

Remember when I said Luka was overrated?

Oh the howls that claim elicited.  Basically Dallas did not want to give him a Supermax extension for $345 million (no, Luka did not ask to be traded).  So Luka is now gone, here are some notes from ESPN:

The Mavericks were motivated to move Doncic because of his constant conditioning concerns, sources told MacMahon. There had been significant frustration within the organization about Doncic’s lack of discipline regarding his diet and conditioning, which team sources considered a major factor in his injury issues.

Though Doncic was relatively svelte by his standards when he reported to camp, his weight ballooned to the high 260s early this season, sources said. He sat out five games in late November, when the Mavs listed him with a sprained right wrist, an extended absence to allow Doncic to focus on his conditioning. He had a similar early-season layoff in the 2022-23 season.

Doncic has been limited to only 22 games this season because of a variety of injuries. He has twice strained his left calf since reporting back to Dallas before training camp in late September, although the Mavs reported the fall injury only as a calf contusion, sources said.

Doncic has not played since straining his calf again on Christmas Day but has been targeting a return before the All-Star break later this month, sources told MacMahon. Davis has also been out after being diagnosed with an abdominal muscle strain earlier this week. He has sat out the Lakers’ past two games. Davis was expected to be reevaluated in a week, according to the Lakers on Wednesday.

POTMR.  In the short run this trade makes both teams worse off (LA defense), although longer run LA will keep around a franchise player of sorts.  Here is one comment from an NBA star.  It all shows in the body language.

p.s. LAL should now trade Lebron, and Bronny, to a contender for a pile of draft picks.