A recent scout campout got me thinking about who gets an audience. A small group was sitting around a campfire silently. Eventually the person who piped up and sapped our attention was 9 years old, with all the maturity expected thereof. Who is to blame for the low quality of discourse that night? I didn’t expend any energy to make good use of that time. I could have taught those kids something, if I had told an engaging story or introduced a clever joke. It would have taken energy to communicate something important in a way that they would want to listen to it.
We have a limited number of minutes to pay attention to the world and we use few of them productively. There is a metaphorical campfire every night, after the work of subsistence is over. Who speaks up? Who gets an audience? When a journalist is doing their best to cover an important issue or sound an alarm, how many people bother to click or get a paid subscription?
I regularly see people complain that journalists or the media are doing it wrong. “Why didn’t the NYT cover X?” Jeremy regularly points out that the NYT did cover X, but not many people clicked.
Ship hijackings on the other side of the world aren’t very fun to read about. What really got clicks this past week was Melania’s hat.
Most of the handwringing over what the media should do is deflecting blame from what we should be doing, which is paying for good journalism and engaging in the boring/important news.
Even before LLMs, for decades, there has been no shortage of great serious writers and text could be shared at very low cost online. The bottleneck is the audience. Good readers are more scarce than writers.
Over the winter break I was able to catch up on a lot of podcasts. I also began listening to the Marginal Revolution podcast (which is phenomenal). I especially enjoyed the final episode of season 1 about options and how many transactions can be characterized as giving someone an option. Here, the term option echoes a financial option. You pay today for the ability to do something in the future. In financial markets, you can purchase the right to buy or sell at a particular price in the future.
But lots of things count as options. Staying in the financial context, purchasing a stock gives you the option to sell that stock at the future spot price. So, in this way, something can be characterized as an option even though we are not accustomed to describing as such explicitly. More mundane transactions can also be interpreted as options. Assume that you buy a can opener. You are buying the option to have that tool on hand in the future and to open some shelf-stable food. You can choose to exercise the option simply by opening your kitchen drawer.
But financial options often include the possibility of losing money. It may be that your grocery purchases never include canned items and that you never have occasion to use your can opener. Maybe that’s a bad investment. You sunk your money into something that you never used. Except… You did in fact have the option to use the can opener. Maybe you had peace of mind that you were well prepared just in case a guest arrived with a can of something. Buying a can opener is like buying an option.
Returning to the realm of finance, let’s discuss buying on margin. Buying an asset on margin is when you borrow from your broker in order to purchase a financial asset. It’s not entirely free money. They have rules about the amount you can borrow and, of course, you must pay back the loan with interest.
WSJ’s survey of economists reports that inflation expectations for 2025 were around 2% before the election, but are closer to 3% now. Their economists expect GDP growth slowing to 2%, unemployment ticking up slightly but staying in the low 4% range, with no recession. The basic message that 2025 will be a typical year for the US macroeconomy, but with inflation being slightly elevated, perhaps due to tariffs.
Kalshi has a lot of good markets up that give more detailed predictions for 2025:
For those who hope for DOGE to eliminate trillions in waste, or those who fear brutal austerity, the message from markets is that the huge deficits will continue, with the federal debt likely climbing to over $38 trillion by the end of the year. This is one reason markets see a 40% chance that the US credit rating gets downgraded this year.
While the US has only a 22% chance of a recession, China is currently at 48%, Britain at 80%, and Germany at 91%. The Fed probably cuts rates twice to around 4.0%.
Will wage growth keep pace with inflation? It’s a tossup. Corporate tax cuts are also a tossup. The top individual rate probably won’t fall below it’s current 37%.
If you want to make your own predictions for the year, but don’t want to risk money betting on Kalshi, there are several forecasting contests open that offer prizes with no risk:
ACX Forecasting Contest: $10,000 prize pool, 36 questions, must submit predictions by Jan 31st
Bridgewater Forecasting Contest: $25,000 prize pool, half of prizes are reserved for undergraduates. Register now to make predictions between Feb 3rd and March 31st. Doing well could get you a job interview at Bridgewater.
The paper primarily focuses on US state taxes, thus mostly ignoring local taxes, but in the Appendix the authors do show us similar charts for local taxes:
In broad terms, the history of taxation in the US in the 20th century is a history of the decline of the property tax, and the rise of the income and sales taxes. In 1900, there were barely any federal taxes (other than those on alcohol and tobacco), 50% of state taxes were property tax, and almost 90% of local taxes were property taxes. Property taxes were essentially the only form of taxation most Americans would directly recognize (excise taxes and tariffs were baked into the price of the goods).
John Wallis (2000) provided a similar, and simpler picture of these changes: considering all taxes in the US, property taxes were over 40% of the total in 1900, but today are under 10%. Income taxes come out of nowhere and are now about half of all government revenues in the US:
As most of us know, artificial intelligence (AI) has taken big steps forward in the past few years, with the advent of Large Language Models (LLM) like ChatGPT. With these programs, you can enter a query in plain language, and get a lengthy response in human-like prose. You can have ChatGPT write a computer program or a whole essay for you (which of course makes it challenging for professors to evaluate essays handed in by their students).
However, the lords of Big Tech are not content. Their goal is to create AI with powers that far surpass human intelligence, and that even mimics human empathy. This raises a number of questions:
Is this technically possible? What will be the consequences if some corporations or nations succeed in owning such powerful systems? Will the computers push us bumbling humans out of the way? Will this be a tool for liberation or for oppression? This new technology coming at us may affect us all in unexpected ways.
For those who are interested, there will be a 75-minute webinar on Saturday, January 25 which addresses these issues, and offers a perspective by two women who are leaders in the AI field (see bios below). They will explore the ethical and practical aspects of AI of the future, from within a Christian tradition. The webinar is free, but requires pre-registration:
Joanna Ng is a former IBM-er, pivoted to a start-up founder, focusing on Artificial Intelligence, specialized in Augmented Cognition, by integrating with IoT and Blockchain, in the context of web3, by applying design-thinking methodology. With forty-nine patents granted to her name, Joanna was accredited as an IBM Master Inventor. She held a seven-year tenure as the Head of Research, Director of the Center for Advanced Studies, IBM Canada. She has published over twenty peer-reviewed academic publications and co-authored two computer science books with Springer, The Smart Internet, and The Personal Web. She published a Christianity Today article called “How Artificial Intelligence Is Today’s Tower of Babel” and published her first book on faith and discipleship in October 2022, titled Being Christian 2.0.
Rosalind Picard is founder and director of the Affective Computing Research Group at the MIT Media Laboratory; co-founder of Affectiva, which provides Emotion AI; and co-founder and chief scientist of Empatica, which provides the first FDA-cleared smartwatch to detect seizures. Picard is author of over three hundred peer-reviewed articles spanning AI, affective computing, and medicine. She is known internationally for writing the book, Affective Computing, which helped launch the field by that name, and she is a popular speaker, with a TED talk receiving ~1.9 million views. Picard is a fellow of the IEEE and the AAAC, and a member of the National Academy of Engineering. She holds a Bachelors in Electrical Engineering from Georgia Tech and a Masters and Doctorate, each in Electrical Engineering and Computer Science, from MIT. Picard leads a team of researchers developing AI/machine learning and analytics to advance basic science as well as to improve human health and well-being, and has served as MIT’s faculty chair of their MindHandHeart well-being initiative.
Failure to elucidate (or the intended obscuring) of unseen policy costs and benefits is the kind of stuff that sends economists to an early retirement. The most common example is the unrealized gains from potential trade that haunt any and all forms of protectionism, but I often find more “micro” examples easier to convince an audience of because it allows them to delve into their own lived experience for supporting evidence.
I’m a big fan of this conversation with co-founder Reed Hastings about severance package generosity at Netflix. The interviewer is absolutely baffled that they offer a minimum of 4 months severance for all employees, with 100% pay and benefits, immediately after hiring, and it grows with length of tenure after that. How could a company afford such a costly line item, particularly one that yields no benefits at all? It’s exactly the kind of policy a central casting stereotype of an MBA would never consider or, perhaps more telling, would be the first on the chopping block when cutting costs to pump up quarterly earning numbers.
What Hastings lays out, besides just the warm-glow benefits of a more “compassionate” severance policy, is the subtle efficiency at the margin. The people making the decision to lay off an employee are sympathetic, pro-social, perfectly normal human beings. They don’t want to hurt someone else which means, perhaps even selfishly, they will take a series of costly intermediate steps to delay the prospective firing of a poorly matched or unproductive employee. The manager will incur costs that perhaps signal to the employee that they are inherently valued, that they, the manager and the company, want the employee to succeed, that any eventually possible firing is only an action of last resort. These actions, as anyone who’s ever had a job will know, rarely if ever succeed in reorienting the employee to a new and fruitful line of productivity. Rather, they simply delay their eventual firing, leaving them in the lurch to find new employment. The costs incurred to soften the impact of the inevitable firing are internalized as benefits by neither the employee nor the firm.
The more efficient policy, to the benefit of everyone involved, is to make the employment separation as early as possible, rolling over as much of those saved costs into a (nearly) pure cash severance that will soften their landing and subsidize their search for their next job. In anything less than the weakest job market four months is enough time to not just find a job, but to be selective in that search. Extended severance strengthens the bargaining power of the former employee in their job search because they don’t have to say yes to the first offer.
From the employer side, they can rest easy knowing that because their managers will not have to incur the emotional cost of wrecking their employees lives with cold calculating decisions to leave in employees in the lurch with 2 weeks pay and a “good luck” out the door, managers will, in turn, make employment decisions faster and more decisively. Generous severance pay is a perfect example of an excellent policy that only looks inefficient to those naive to the actual decisions being made on the ground. Conversely, a more draconian policy carries the pretense of a colder efficiency, when the reality is a flailing hodgepodge of spinning wheels and sundry transaction costs.
What other policies, micro or macro, might see their efficiency aspirations and denunciations wholly inverted if we were to consider not just their line item magnitudes on a spreadsheet, but the whole of their of interconnected costs and benefits?
The Chair on Netflix is entertaining and I’d recommend it to EWED readers.
Plot, via Wikipedia: Professor Ji-Yoon Kim is the newly appointed chair of the English department at Pembroke University. The first woman chosen for the position, she attempts to ensure the tenure of a young black colleague, negotiate her relationship with her crush, friend, and well-known colleague Bill Dobson, and parent her strong-willed adopted daughter.
Something I like about the writing is that there is genuine suspense. Going into the last episode, I didn’t know what would happen with the romance or the threat of job dismissals.
The show is funny, occasionally. If you are looking for something easy to watch in 30-minute episodes at the end of the day that won’t leave you too upset, this will work.
Some of the issues they raise deserve serious treatment, but the serious treatment will not be found in The Chair. It’s for Netflix, with binge watching potential. Without offering any spoilers, I’d say they supply the kind of ending that viewers want. You need not overthink it.
The US Equal Opportunity Commission identifies characteristics by which an employee can’t be harassed, hired, paid, or promoted. A challenge with enforcing the non-discriminatory standards is that the evidence must be a slam dunk. There needs to be a smoking gun of a paper trail, recorded conversation, or multiple witnesses. Mere statistical regularities are insufficient for demonstrating that characteristics like race, age, or sex are being considered inappropriately.
If employees are all identically qualified, then we’d expect the employment at a firm to reflect the characteristics of the applicant pool, within a margin of error due to randomness. One difficulty is that plenty of discrimination can occur within that margin of error. A firm may not have sexist policies, but a single manager can be sexist once or even multiple times and still keep the firm-level proportions within the margin of error. This is especially stark if the company managers or officers are the primary positions for which discrimination occurs.
Another difficulty is that randomness can cause extreme proportions of employee characteristics. Having a workplace that is 95% male when the applicant pool is 60% male isn’t necessarily discriminatory. In fact, given a sample size, we can calculate how likely such an employee distribution would occur by randomness. Even by randomness, extreme proportions will inevitably occur. As a result, lawsuits or complaints that have only statistical evidence of this sort don’t go very far and tend not to win big settlements.
But this doesn’t stop firms from avoiding the legal costs anyway. Firms generally prefer not to have regulatory authorities snooping around and investigating. Most people break some laws even unintentionally or innocuously, and a government official on the premises increases the expected compliance costs. Further, even if untrue accusations are made, legal costs can be substantial. Therefore, firms have an incentive to ensure that they can somehow demonstrate that they are not being discriminatory based on legally protected characteristics.
However, as I said, extreme proportions happen randomly. If those extremes are interpreted as evidence of illegal discrimination, then the firms have an incentive to hire among identical applicants in a non-random manner. They have an incentive to tilt the scales of who gets hired in favor of achieving a specific distribution of race, sex, etc. People have a variety of feelings about this. Some call it ‘reverse discrimination’ or discrimination against a group that has not historically experienced widespread disfavor. Others say that hiring intentionally on protected characteristics can help balance the negative effects of discrimination elsewhere. I’m not getting into that fight.
John Bogle, the founder of Vanguard, wrote a short book in 2006 that explains his investment philosophy. I can sum it up at much less than book length: the best investment advice for almost everyone is to buy and hold a diversified, low-fee fund that tracks an index like the S&P 500.
Of course, a strategy that is simple to state may still take time to understand and effort to stick to. So the book helps to build intuition for why this strategy makes sense. I think Bogle makes his case well, though the book is getting a bit dated- the charts and examples end in 2006, and he sets up mutual funds as the big foil, when today it might be high-fee index funds or picking your own stocks.
The silver lining of any dated investing book is that we can check up on how its predictions have fared. In chapter 8, Bogle compared the performance of the 355 equity mutual funds that existed in 1970 to that of the S&P over the 1970-2006 period. He notes that 223 of the funds had gone out of business by 2006, and even most of the surviving funds underperformed the S&P. But he identifies 3 funds that outperformed the S&P significantly (over 2% per year) on a sustained basis (consistently good performance, not just high returns at the beginning when they were small): Davis New York Venture, Fidelity Contrafund, and Franklin Mutual Shares. But how have they done since the book came out?
It is a huge victory for the S&P (in blue). Franklin Mutual Shares is basically flat over the past 20 years, while Davis New York Fund actually lost money. Fidelity Contrafund returned a respectable 281% (about 7% per year), and matched the S&P as recently as 2020. But as of 2025 the S&P is the clear winner, up 411% in 20 years (over 8% per year). Score one for Bogle.
But I still have to wonder if there is a way to beat the S&P- and I think one of Bogle’s warnings is really an idea in disguise. He warns repeatedly about “performance chasing”:
But whatever returns each sector ETF may earn, the investors in those very ETFs will likely, if not certainly, earn returns that fall well behind them. There is abundant evidence that the most popular sector funds of the day are those that have recently enjoyed the most spectacular recent performance, and that such “after-the-fact” popularity is a recipe for unsuccessful investing.
The claim is that investors pile into funds that did well over the past 1-3 years, but these funds subsequently underperform. But if this is true, could you succeed by reversing the strategy, buying into the unpopular sectors that have recently underperformed? I’ve been wondering about this, though I have yet to try seriously backtesting the idea. I was surprised to see Mr. Index Fund himself support such attempts to beat the market toward the end of his book:
Building an investment portfolio can be exciting…. If you crave excitement, I would encourage you to do exactly that. Life is short. If you want to enjoy the fun, enjoy! But not with one penny more than 5 percent of your investment assets.
He goes on to say that even for the fun 5% of the portfolio he still doesn’t recommend hedge funds, commodity funds, or closet indexers. But go ahead and try buying individual stocks, or actively managed mutual funds “if they are run buy managers who own their own firms, who follow distinctive philosophies, and who invest for the long term, without benchmark hugging.”
The average price of a dozen eggs is back up over $4, about the same as it was 2 years ago during the last avian flu outbreak. Egg prices are up 65% in the past year. But does that mean the grocery inflation we experienced in 2021-22 is roaring back?
No really. Spending on eggs is around 0.1% of all consumer spending, and just about 2% of consumer spending on groceries. Symbolically, it may be important, since consumers pick up a dozen eggs on most shopping trips. But to know what’s going on with groceries overall, we have to look at the other 98% of grocery spending.
It’s been a wild 4 years for grocery prices in the US. In the first two years of the Biden administration, grocery prices soared over 19%. But in the second two years, they are up just 3% — pretty close to the decade average before the pandemic (even including a few years with grocery deflation!).
As any consumer will tell you, just because the rate of inflation has fallen doesn’t mean prices on average have fallen. Prices are almost universally higher than 4 years ago, but you can find plenty of grocery items that are cheaper (in nominal terms!) than 1 or 2 years ago: spaghetti, white bread, cookies, pork chops, chicken legs, milk, cheddar cheese, bananas, and strawberries, just to name a few (using BLS average price data).
There is no way to know the future trajectory of grocery prices, and we have certainly seen recent periods with large spikes in prices: in addition to 2021-22, the US had high grocery inflation in 2007-2009, 1988-1990, and almost all of the period from 1972-1982 (two-year grocery inflation was 37% in 1973-74!). Undoubtedly grocery prices will rise again. But the welcome long-run trend is that wages, on average, have increased much faster than grocery prices:
Economist Writing Every Day 