Of Dollars And Data

6/23/2026

I recently saw this video where Anna Stansbury, an assistant professor at MIT, explains that people who grew up in poverty end up earning less than their more affluent peers, even when they attended the same university: We know that socio-economic background matters for how well someone does in school, whether they get the chance to go to university, what kind of university they go to, what kind of degree and grade they get. I think there's often an assumption that these effects of socio-economic background are kind of washed out from then onwards... But to document that two people who were literally getting exactly the same degree at the same university in the same subject at the same time with the same grade, still end up having a 7% earnings gap 10 years after graduation is the kind of big new striking finding I want to pull out. A study from researchers at the NBER, covering over 30 million students, illustrated this pattern at scale by examining the differences between parent and child incomes based on university attendance. Though children who attended college saw a smaller earnings gap between those from poor and wealthy families, a gap exists nonetheless. Before we can address why poorer kids lag behind their wealthier peers, let's see how much they lag behind in the first place. How Big is the Earnings Gap? We can see the size of the earnings gap (based on parental income) in the plot below which shows child income rank vs. parental income rank nationally (in grey), for children who attended two-year schools (yellow), elite colleges (in blue), and other four-year colleges (in green): This chart shows how a child's income rank (at age 32-34) compares to their parent's income rank across the income spectrum.  For example, if a parent was at the 20th percentile of income, we would expect their child to have a 42nd percentile income whether their child attended college or not. This is represented by the National (grey) line. However, if we knew that their child attended a two-year school, we would expect them to have a 48th percentile income (yellow line). If they attended a non-elite four-year college, we would expect them to have a 60th percentile income (green line). And if they attended an elite college, we would expect them to have a 73rd percentile income (blue line). Overall, future earnings tend to increase when children attend more selective educational institutions. This is why each line has a higher intercept (on the y-axis) than the one below it. This effect is so pronounced that the poorest students at more selective colleges tend to have higher expected earnings than the wealthiest students at less selective ones! This suggests that getting into a good school probably matters more for your future earnings than the family you grew up in. That's the encouraging part. However, the slope of each line is not zero, meaning that parental income is still correlated with child earnings even among students at the same institution type. On a national scale, the slope is 0.288 meaning that the children of the wealthiest families end up having incomes about 29 percentiles higher than the children of the poorest families (regardless of where they go to university). Once you focus on the children who attended non-elite four-year colleges, the slope decreases to 0.095. This means that the children of wealthiest families at these schools end up having incomes about 10 percentile points higher than the children of the poorest families. This suggests an equalizing effect of college attendance on earning outcomes. Finally, for children attending elite colleges, students from the wealthiest families only end up having incomes about 6.5 percentiles higher than the students from the poorest families. This is the smallest slope measured, suggesting that elite colleges come closest to equalizing earnings outcomes across family backgrounds. While this slope is smallest among elite colleges (only about 7 percentile points), it isn't nothing. To put this in perspective, a 30-34 year old household at the 70th percentile of income earned about $110,000 a year in 2022, while a 30-34 year old household at the 77th percentile of income earned about $120,000 a year. Those 7 percentile points translate into about $10,000 per year in additional income. That $10,000 a year might seem small, but over the course of a multi-decade career, it's hundreds of thousands of dollars in extra earnings. Though the NBER research uses individual income instead of household income, the point remains—small earnings gaps compound over time to create much larger wealth gaps in the future. While this is intriguing in its own right, how does this gap happen in the first place? The data tells us that the gap exists, but it can't tell us why. For that, we need to look beyond the numbers. What Creates the Gap? I know from personal experience that one of the reasons that less well-off students earn less than their more affluent peers is because they aren't as informed about how the corporate world works. For example, I didn't know that I had to apply for an internship in the winter of my sophomore year to get a sophomore summer internship to leverage into a junior summer internship to get a full-time offer senior year. That knowledge was graciously gifted to me by a college friend of mine who grew up in a wealthy Seattle suburb. If he hadn't told me about how these recruiting pipelines function, I wouldn't have gotten a sophomore summer internship. This would've put me far behind my peers when recruiting for junior summer internships the next year, and would've made full-time recruiting during my senior year (two years later) more difficult as well. Think about it. A single decision when I'm 19 years old ends up impacting my entire career trajectory. And many kids, especially poorer ones, are completely oblivious to how this all works. So they miss out and go into full-time recruiting senior year at a massive disadvantage to their peers who knew better. My experience isn't unusual either. The research suggests that this kind of informational and social advantage operates through three main channels: networks, internships, and hiring discrimination. Networks The reason my friend was so knowledgeable about college recruiting was because of his network. His father was a long-time software engineer at Microsoft. His friends came from well-to-do families in the Seattle area. His older frat brothers had already gone through this process before. This kind of knowledge gets passed through social networks, which are heavily segregated by income/wealth. For example, Raj Chetty and co-authors analyzed 21 billion Facebook friendships and found that a person's "economic connectedness" (the share of their friends who come from higher-income backgrounds) is the single strongest predictor of upward mobility in the research literature. This effect is so strong that children from low-income families with the same economic connectedness as their wealthier peers increased their earnings as an adult by about 20% on average. This matches research I discussed recently, which found that elite networks are most valuable to those outside of them (e.g. children from low-income families). But networks aren't useful if you don't have the resources to take advantage of them.  Internships Internships are a great way for students to gain real-world experience, but with many of them being unpaid, this limits who can actually take them. For example, one study found that 64% of students who did not take internships, but wanted to, cited the need to have paid work as one of the primary barriers.  Unfortunately, wealthier students can afford to take the unpaid (or low-paid) internships that open doors to high-paying careers that their less affluent peers can't. This is a structural advantage that has nothing to do with talent or effort. But even if someone can afford to take an unpaid internship, there's evidence that they are less likely to get it if they don't fit in. Hiring Discrimination/Social Cues Even when lower-income students manage to get the same degree from the same school and apply for the same jobs, they can face discrimination in the hiring process. A 2016 study sent fake resumes to 316 law firms. The resumes were identical in qualifications, but had different extracurricular activities and interests to signal different class backgrounds. Male resumes with traditionally upper-class extracurriculars received callbacks at a rate of 16.25%, more than four times the callback rate of male applicants with lower-class extracurriculars. Unfortunately, if your future coworkers don't think you'll fit in for one reason or another, they are less likely to hire you. I don't think this kind of discrimination is deliberate, but it happens nonetheless. This isn't just true at law firms, but has also been shown in academia as well. Anna Stansbury co-authored a paper titled The Class Gap in Career Progression: Evidence from US academia, which came to a similar conclusion (emphasis mine): First-generation college graduates are 10% less likely to be tenured at an R1, are tenured at institutions ranked 11% lower, earn 3% less, and report 5% lower job satisfaction, than their former PhD classmates (from the same institution and field) with a parent with a non-PhD graduate degree. Neither selection out of academia nor different preferences explain this gap; differential research productivity also plays little role. Instead, likely drivers are differences in cultural and social capital. Knowing the right people and having the right background seems to matter more for career success than people traditionally imagine. But there are small ways in which you can help to close the gap. How to Close the Gap (Share What You Know) Ultimately, all the factors that contribute to the earnings gap between poorer and wealthier students reinforce each other. Better networks lead to better internships, which lead to stronger resumes, which help you get past hiring screens. And once you land that first job, those advantages start compounding on themselves.  Of course, this system isn't fair, but life isn't fair. I only learned about all this stuff because a friend took the time to explain it to me. That single conversation changed my career.  So if you're someone who knows how the system works, share it. Be the friend or mentor who helps those around you. You'll be surprised at the impact you'll have, and it will only cost you a little bit of your time. And if you don't know anyone personally, consider volunteering as a mentor through a first-generation college student program. Many universities and nonprofits run them, and they're always looking for professionals willing to share what they've learned. This won't fix the system, but it's a start. Thank you for reading.  If you liked this post, consider signing up for my newsletter. This is post 508. Any code I have related to this post can be found here with the same numbering: https://github.com/nmaggiulli/of-dollars-and-data

6/16/2026

Working in England in the 14th century was difficult to say the least. Between the harsh conditions and low wages, you also had to fight against the occasional disease outbreak and a repressive government. As the Black Death spread across England, killing anywhere from 30%-50% of the population, King Edward III issued a decree to freeze wages and prevent workers from asking for more. Anton Howes summarized what happened next: As the plague still raged, in 1349 Edward III issued an emergency ordinance to try and contain the economic fallout. Even though half the population died, their gold and silver coins survived, so that there was suddenly twice as much coinage in circulation per head. And so one of the immediate effects was for the price of everything, including both goods and services, to rapidly rise. This rapid inflation, brought on as it was by so many people dying, inevitably led to higher wages being demanded for all kinds of work. “Seeing the necessity of masters and great scarcity of servants”, the ordinance explained, workers now found themselves able to pick and choose who they worked for, and to hold out for much higher wages than before. While the ordinance (with its threat of imprisonment) was successful in preventing wages from rising too rapidly, the market found an alternative solution to this problem—non-monetary compensation. Once again from Howes: Although the statute stipulated the amount of cash that workers could be paid, both with and without providing them with food and drink, it didn’t say anything about the quality or even the quantity of that food or drink. So instead of giving them bread made of rye, barley or beans, perhaps with a slice of old salted bacon to sweeten the deal, employers now had to provide their workers with only the best-quality wheaten bread, and with freshly-cooked meat still warm from the pot. Instead of providing them with mere water to quench their thirst, employers now had to give them the freshest of ales. As one contemporary complained, the servants were now demanding “to be better fed than those who hired them”. Ultimately, it was supply and demand that determined how workers were compensated, not royal decree. This example illustrates how market forces find a way to triumph over human intervention. But is the same thing true in the stock market? Can supply and demand tell us anything about future stock returns? Some data suggests so. The American Association of Individual Investors (AAII) has tracked aggregate investor allocations to stocks, bonds, and cash going back to 1987. Over this time period, individual investors allocated 62% of their portfolios, on average, to equities. You can see this in the chart below, which plots the aggregate investor allocation to equities over time (in black) along with the long-term historical average of this measure, 62% (in gray): When I look at this data I notice two things. First, the average allocation to equities tends to decline during market crises (e.g., DotCom, GFC, COVID, etc.). This makes sense as we would expect equities to make up a smaller portion of an investor's portfolio as prices fall. The second thing I notice is that the allocation to equities has been above its long-term average for the vast majority of the last decade. Some of this is due to the strong equity market over this time period (2015-2025) with relatively few crashes. However, it also suggests that investors are allocating a larger portion of their portfolio to equities than they have in the past. Unfortunately, if you look at the historical data, a higher allocation to equities usually meant lower future returns. The plot below highlights the negative relationship between the investor allocation to equities (from the AAII survey) and the annualized total real return of the S&P 500 over the next 10 years: In general, when the average allocation to equities was high, future returns were lower, and when the allocation was low, future returns were higher. This relationship held from 1987 until the GFC, but has since started to break down. Take the most recent data for example—the average allocation to equities in 2015 and the returns over the next decade (i.e., until 2025). This was a period of high allocation to equities and high future returns. You can see this in the chart below which shows the average allocation to equities for each month in 2015 and the annualized total real return of U.S. equities through the same month in 2025: If the most recent data suggests that owning more equities doesn't translate to lower future returns, then maybe the AAII data isn't as predictive as it used to be. For example, when I analyzed the AAII data back in 2018, I discovered a tactical model that would've outperformed a Buy and Hold approach with far less volatility. Here's how that model (which I've called the AAII AvgEquityShare model) worked: Start by being fully invested in U.S. stocks (i.e., S&P 500 index fund). When the average equity allocation goes above 70%, sell all your stocks and move into bonds (i.e., 5-year Treasuries). Stay in bonds until the average equity allocation drops below 50%, then sell all your bonds and move back into stocks. Repeat steps 2-3 until rich. The logic of the model made perfect sense—exit stocks when their demand is too high (i.e., average allocation >70%) and re-buy them when their demand is too low (i.e., average allocation <50%). More importantly, it worked too! The AAII AvgEquityShare was fully invested in U.S. stocks except during two periods: DotCom Bubble: The model sold stocks in September 1996 and didn't re-buy them until October 2002. Great Financial Crisis: The model sold stocks in May 2006 and didn't re-buy them until November 2008. Think about how amazing this is. It was a tactical model that perfectly predicted both the DotCom Bubble and the GFC without any false positives! However, it felt too good to be true. And I was right. As I wrote back in October 2018: I do not recommend changing your investment strategy based on the following information: The AAII AvgEquityShare model sold out of stocks in January 2018 after being fully invested every single month since November 2008. Yes, the model that called both the DotCom Bubble and the GFC signaled to get out of stocks back in January 2018. Thankfully, I didn't listen. If I had, I'd still be in bonds today and would've missed a 196% increase in the S&P 500 since. Supply and demand is useful for understanding (and possibly predicting) many markets. But it doesn't work as well with stocks anymore. Why? Because the nature of demand has fundamentally changed. Today, investors are far less price-sensitive than they were in the past. With the rise of automatic 401(k) contributions and passive indexing, billions of dollars flow into the markets every month regardless of valuation. This is the premise behind Just Keep Buying. Did this relentless bid for stocks finally break the relationship between high equity allocations and low future returns? Or was it the common knowledge that we share about markets? After all, everyone "knows" that the stock market "always" recovers. And everyone knows that everyone knows that. So, if everyone knows to buy the dip, how does a dip ever sustain itself? I don't know, and I don't look forward to finding out. Until then, happy investing and thank you for reading. If you liked this post, consider signing up for my newsletter. This is post 507. Any code I have related to this post can be found here with the same numbering: https://github.com/nmaggiulli/of-dollars-and-data

6/9/2026

This week SpaceX is having its initial public offering (IPO) where it plans to raise $75 billion at a $1.77 trillion valuation. Anthropic and OpenAI have their own IPO plans for later this year. With these highly valued companies coming to market, there's been a lot of discussion around how index providers will include them in their funds. Index funds are governed by a set of inclusion criteria which determine which stocks can be added to a particular index and when. For example, historically the Russell 1000 only added a stock to its index if at least 5% of its overall shares were available to trade (i.e., 5% float). However, since SpaceX's IPO is only offering around 4% of its overall shares into the float, FTSE Russell decided to modify their inclusion criteria. Nasdaq also made changes to its inclusion criteria to fast-track larger IPOs after just seven days of being listed rather than on an annual basis in December. The good news is that not all index providers are changing their rules to fast-track SpaceX, Anthropic, and OpenAI into their funds. S&P Global recently stated that "there will be no changes to existing methodology" for their large and megacap index funds. In other words, SpaceX, Anthropic, and OpenAI will need to be public for 12 months and hit certain profitability metrics before they can be considered for the S&P 500 (and similar megacap funds). Nevertheless, some investors are up in arms with Nasdaq and FTSE Russell. They believe that the purpose of the recent rule changes is to force index investors to buy companies like SpaceX at elevated prices. In other words, some believe that index investors are being used as exit liquidity. I see the argument, but how much does this really impact the typical index investor? Let's find out. How Much Will SpaceX Impact the Typical Index Investor? When an index provider adds a new stock to their fund, the weighting is determined based on the float of the stock, or the total value of all shares publicly available to trade. In this case, SpaceX should have a float of around $75 billion. This is the amount of money the company plans to raise at its IPO. So, for a fund like VTI (Vanguard's Total U.S. Stock Market Index), which tracks a U.S. market worth around $70 trillion, SpaceX would represent about 0.11% of the index. But not every index does a simple weighting based on float. For example, Campbell Harvey noted how the Nasdaq 100 changed a rule to weight SpaceX at 3x their float, or around $270 billion in Harvey's estimation. Given that the Nasdaq 100 has a total market capitalization of around $40 trillion, SpaceX would make up roughly 0.68% of the index. In dollar terms, for every $100,000 invested in VTI, $110 would be in SpaceX. And for every $100,000 invested in QQQ (i.e., the Nasdaq 100), $680 would be in SpaceX. This isn't a lot in the grand scheme of things, but many investors believe that SpaceX is overvalued. And it might be. Aswath Damodaran recently did a deep dive on SpaceX and valued the company at $1.21 trillion before reviewing their prospectus and $1.22 trillion after digging in. This is 31% below the $1.77 trillion valuation that SpaceX plans to go public at. If we assume that Damodaran's valuation is accurate in the long run, then the typical VTI investor would lose 0.03% [31% of 0.11%] and the typical QQQ investor would lose 0.21% [31% of 0.68%] from the SpaceX investment. This equates to an expected loss of $30 for every $100,000 invested in VTI and $210 for every $100,000 invested in QQQ. This isn't nothing, but it isn't that large either. And this assumes that Damodaran is better at pricing SpaceX than the market, which may not be correct. Either way, while I agree with outraged index investors in principle, the dollar impact for the typical index fund investor is quite small. I don't want anyone to lose money from their investments, but, in the end, we have to trust the market to set prices. That doesn't mean the market is always right, just that it usually is. What will happen with SpaceX's valuation (and eventually Anthropic and OpenAI's) remains to be seen. Nevertheless, if you are still worried about investing in any of these companies through your index funds, there are some ways to overcome this. How to Avoid Being Exit Liquidity If you don't want to be "exit liquidity" for Elon Musk or Sam Altman, here are your best options as a passive index investor: Avoid the impacted funds. The best way to avoid overvalued IPO companies joining an index is to avoid the funds that will hold them. Of course, this is easier said than done. Avoiding tech (QQQ) is straightforward, but avoiding a total U.S. stock market fund is much harder. What you can do instead is own the S&P 500. An S&P 500 ETF won't immediately be impacted by these IPOs and yet still has a very high correlation with the overall stock market. It's easy to make this switch in a non-taxable account (e.g., IRA, 401k, etc.), but in taxable accounts you'll need to decide whether paying capital gains taxes is worth it. For most, it probably isn't. Use direct indexing. Another approach to avoid IPO companies is to use direct indexing. Direct indexing is the recreation of an index through a separately managed account (SMA) from a third party. So instead of owning an S&P 500 ETF, you would hold 500 (technically 505) stocks to replicate it. The best part about direct indexing is that you can create whatever index you want. You can have the S&P 500 minus SpaceX or the S&P 500 without OpenAI. One downside of direct indexing is that the account minimums tend to be a bit higher than if you were to buy a single share of a fund. While some fractional share direct indexing options exist, they are more limited in their effectiveness. Accept that you aren't smarter than the market. If avoiding these highly valued stocks isn't an option, then you may need to accept that they aren't as overvalued as you believe. I know how crazy that sounds when AI companies are participating in complex, circular financing deals. But the market is a lot smarter than you or I. For example, I've felt a bit bearish on AI since last year, yet many of these companies have managed to hit and even exceed their earnings targets. I'm glad I only "sinned a little" and left most of my equity allocation unchanged. This is further evidence that Just Keep Buying is the right long-term approach. Since we can't know which stocks will outperform (or underperform), owning all of them (via an index) is the most rational option. Ultimately, the impact that SpaceX, Anthropic, or OpenAI will have on your index funds pales in comparison to almost every other financial decision you make. Your career, your spending, and your asset allocation matter far more than whether your index fund has a weighting of 0.5% to a given stock.  Don't get me wrong. I don't like how some index providers are changing their rules to fast-track stocks into their funds, yet I also don't think the impact is as large as the naysayers claim. If you want to learn more about the nuances of this issue, I recommend this deep dive on the topic.  Happy investing and thank you for reading! If you liked this post, consider signing up for my newsletter. This is post 506. Any code I have related to this post can be found here with the same numbering: https://github.com/nmaggiulli/of-dollars-and-data

6/2/2026

I recently saw this Reddit post about a man who retired early (FIRE) only to be called a "loser" by his wife go viral. In the man's own words: 41m, $2mm liquid, $650k retirement and I get a $75k/yr royalty from a business I sold. Recently retired. Wife is a school teacher, good for healthcare. I make $125k/yr in income off my liquid assets. Since November began, it’s cold and dark early so a lot of what I do M-F when she’s at work is I play GTA (video game) on thc edibles bc nothing else to do where I live this time of year. Wife came home early today and I’m stoned in the middle of a conversation w/ my GTA online friends. She told me I’m becoming a “Loser” but this is me during the day when she works. I admit it’s immature but we dont have kids and I just want to chill after working a stressful job for 15 years I make dinner, clean the house, paid for our nice house and make 2x what she makes as a school teacher from my assets and royalty income. If I want to get high and play video games when she is working what is the problem? We take nice trips across the world in the summer when she’s off. She said I’m too old for this but there’s not much else to do in the winter. I just want to chill but I can tell she doesn’t like it. Early retirement does not fit well in this society. I get his confusion. He provides for his wife, takes care of their home, and isn't lazy. After all, if he was lazy, how did he acquire $2M in liquid assets by age 41?  At the same time, his wife is probably doing a different calculus. She's not just thinking about the man who acquired their resources, but the man who she's going to spend the rest of her life with. She's probably thinking about kids. Is $2M liquid and $650k retirement enough to raise multiple children while also supporting a stoned gamer? Would she be better off divorcing him, taking half of their assets, and starting over with someone new? I'm obviously speculating here, but you can see how both parties can feel like they are correct. The husband feels like he did his job (he provided financial security), but the wife may feel like the job's not done. Who's right? With the limited information provided, I can't say. Either way, this story is a great example of how resources by themselves don't command respect—how you got them and what you do with them does. Imagine you meet a self-made millionaire and a lottery winner. Which has higher status? It's obvious. One of them built their fortune while the other just got lucky. In the above scenario the man did build his fortune (as far as I can tell). However, his decision to get blazed and play Grand Theft Auto (GTA) every day was more of a turn-off than he realized. His wife likely saw a side of him that she hadn't seen before. This new person didn't match who she thought she married. Think about it. When they first met he was likely hard working and driven (given his stressful job). Now he's a full-time couch potato. That doesn't sound like what she signed up for. Such a change in behavior was likely too jarring for her. Her reaction is a good thing though. Because it suggests that money is less of a factor in attraction than people think. What matters more is your ambition. The academic literature on evolutionary biology supports this as well. In a study across 37 cultures, evolutionary psychologist David Buss found that, on average, both men and women valued "ambition and industriousness" more than "good financial prospects" when choosing a mate. In evolutionary terms, this is known as Resource Holding Potential (RHP), or your ability to acquire resources in the future. The husband signaled high RHP while working, but now signals low RHP given his choices in early retirement. Though he has the results (money), he lost the trait (ambition) that made him attractive in the first place. Why is ambition more attractive than the money? Because money says, "I was useful," while ambition says, "I am useful." And, naturally, people care about the future. People care about the genes they pass on to their offspring. And they want to pass on traits like industriousness because those traits will help their children acquire future resources, and so on. Don't get me wrong, having money makes you more attractive. But it's not the money that's actually appealing, only how you acquired it. The potential to collect more resources is the draw for both men and women. Does this mean that you have to keep working forever to be attractive? No, but indulging in endless consumption isn't the right path either. The point of financial independence isn't to never work again. The point is to find something you enjoy working on (whether you are paid for it or not) and do it with enthusiasm. That's the ambition that people are attracted to, even if it doesn't lead to the largest financial rewards. But don't just become ambitious for other people. Do it for yourself. In Drive, Daniel H. Pink discusses how Autonomy (being self directed), Mastery (improving your skills), and Purpose (connecting to something bigger than yourself) are the key components to human motivation and satisfaction. This is where proponents of FIRE often get it wrong—they overly focus on Autonomy at the expense of Mastery and Purpose. This was the husband's undoing. He had maximal freedom, but no vision for his future. And that's a tough way to go through life. Being rich is nice, but being useful is better. Thank you for reading. If you liked this post, consider signing up for my newsletter. This is post 505. Any code I have related to this post can be found here with the same numbering: https://github.com/nmaggiulli/of-dollars-and-data

5/26/2026

My wife and I recently started watching Hacks, the HBO TV series starring Jean Smart and Hannah Einbinder, about a legendary comedian trying to stay relevant in a changing world. It's funny, the writing is fantastic, and there are lots of great plot twists. But I really love the show because it explores the tension between doing something for money versus doing it for the art itself. Smart, who plays the veteran comedian, seems to care more about the commercial aspects of comedy (i.e., money and fame) while Einbinder, her writing partner, cares more about the artistic aspects (i.e., truth and authenticity). In this regard, Smart is closer to the "hack" while Einbinder is more like the "artist." Every creator on Earth sits somewhere on this continuum between hack and artist. If you don't know which is which, here are some examples to help guide you: Giving bad financial advice just to go viral? Hack. Promoting work that you are truly proud of? Artist. Making a fool of yourself to get more engagement? Hack. Turning down a lucrative project because it is low quality? Artist. Passing off AI writing as your own? Hack. Admitting to mistakes before others call you out on them? Artist. You get the point. Hacks do what they think works. They follow every trend and try to maximize money/status/fame wherever possible. Artists, on the other hand, care about what they actually produce and how it reflects on them. Few creators are complete hacks or complete artists. Most are some mixture of the two. While I wish I could say I've always been an artist, I haven't been. At times, I've cared a bit too much about financial rewards. I've taken on some partnerships that I probably shouldn't have. And while I made some mistakes, I also tried really hard to stay true to myself and what I believe in. It's a delicate balance, especially when you've never done it before. This categorization applies to anyone in any line of work too. You don't have to be a creator to embody the essence of a hack or an artist. You can be either, whether you're a waiter or a wealth manager. For example, if you're a financial advisor, do you see your clients as people you serve (artist) or as a source of revenue to capture (hack)? I get that we all need revenue to survive, but, at some point, the marginal dollar isn't worth it. So why do hacks exist in the first place? Because the rewards are quicker and require far less effort. More importantly, as we get rewarded for certain behaviors, we're more likely to repeat these behaviors rather than risk trying something new. This idea is called mode collapse and it helps explain why all the AI writing sounds the same. Henrik Karlsson wrote a great piece explaining how this occurs: Mode collapse is when a generative model (most notoriously GANs) stops producing diverse outputs and instead obsessively reproduces a small subset of patterns that reliably fool the discriminator. We’ve seen this happen with language models. The early models, up until about 2020, were deranged but could write spectacularly surprising prose from time to time. Now the models are much smarter, but they all write in that uncanny AI voice. “And honestly? That isn’t just sad—it’s stylistic trauma.” The wide space of potential ways of thinking and writing has collapsed into a limited mode. Karlsson notes that the same thing happens to us as humans. Our creativity is stripped out of us by adolescence as we get rewarded for producing work that is acceptable, rather than creative. In other words, we're incentivized to become hacks. You might think that the difference between being a hack and being an artist is a hypothetical one, but it isn't. It's fundamental to how you show up in the world. If you see yourself as an artist, you will make different choices than if you're motivated solely by money or fame. I raise this issue because many people are rightly worried about the continued improvements in AI and whether their work will be replaced by LLMs. As someone who makes a large portion of their income from writing, I get it. At the same time, I know I can't control how humanity will use AI in the future. I can't control the progress of LLMs. The only thing I can control is my behavior. And the same is true for you. Dan Koe wrote an intriguing piece about the future of AI titled "You have about 24 months to learn these skills." In it he argues that AI today is like Gutenberg's printing press from the mid-1400s: The printing press rendered scribes obsolete. Before Gutenberg, bookmakers employed dozens of trained artisans to hand-copy manuscripts. A skill that took years to master. Before they knew it, that skillset was worthless. A single press could produce 3,600 pages per workday. The scribes who refused to adapt disappeared. The ones who learned to operate the new machines thrived. I believe it's true that those who learn to use AI effectively will outperform those who don't. However, Koe's argument misses a fundamental point about the difference between the printing press and AI. The printing press replaced a job that didn't need to be done by a human. One scribe was no different than another. Their uniqueness as individuals didn't matter for the work they produced. But that's not completely true with AI. AI is trying to replace writers, designers, and many other creatives. Their work always has a source. And that source has experiences. And those experiences shape the work being produced. An LLM, by contrast, doesn't have experience. It can only approximate experience because its uniqueness doesn't exist. AI is the sterile amalgamation of all humans rather than the beautiful imperfections of one. This is why you still have an edge over the most advanced computational machines in the world. Because though these machines might be faster than you, more knowledgeable than you, and cheaper than you, they still aren't...you. That's what matters. That sliver of uniqueness. That humanity that can't be replaced. Of course, if your current job requires no part of your personality or experiences, then you should start looking for one that does. While I disagree with some of Dan Koe's logic, his ultimate thesis is right—what you do over the next 24 months will shape how your career plays out over the next 24 years. Whether you use that time to be a hack or an artist is up to you. Thank you for reading! If you liked this post, consider signing up for my newsletter. This is post 504. Any code I have related to this post can be found here with the same numbering: https://github.com/nmaggiulli/of-dollars-and-data

5/19/2026

Over the last year, there have been a number of policies aimed at taxing the wealthy and ultra-wealthy. It started last November when the "2026 Billionaire Tax Act" ballot initiative was proposed in California to impose a one-time 5% wealth tax on its resident billionaires. In March 2026, the state of Washington passed a Millionaires Tax which would tax all incomes above $1 million at 9.9%. And, most recently, New York City proposed a pied-à-terre tax, which would levy a surcharge on all second homes worth more than $5 million in the city. The idea with all of these policies is more or less the same: raise taxes on those who have the highest ability to pay—the wealthy. However, just because the wealthy can pay doesn't mean that they will pay. For example, since the 2026 Billionaire Tax Act ballot initiative was announced in California, a handful of high profile billionaires including Google cofounders Sergey Brin and Larry Page and venture capitalist Peter Thiel have left the state. Some fear the same thing will happen in Washington state as millionaire earners flee before the Millionaires Tax takes effect in 2028. But, what does the data say about such policy changes? Do higher taxes actually cause wealthy people to move? Or is the fear of capital flight overblown? Do Higher Taxes Cause Capital Flight? Though raising taxes on the wealthy should increase overall tax revenue in theory, in practice this isn't always the case. The issue is that wealthy people can choose to leave and avoid the new tax. This is known as "capital flight" and it can actually lead to lower overall revenue after a tax hike is passed. How so? Well, if enough individuals leave, they avoid the new tax and they take their existing tax revenue with them. So not only does the state not get the higher revenue they hoped for, but they also lose revenue they already had. The net effect could result in lower overall tax revenue even after raising taxes. This is the double-edged sword of taxation and explains why raising taxes can be more of an art than a science. The problem with capital flight is that most people fall into one of two camps. They either believe that higher taxes cause capital flight or they don't.  But the issue isn't so simple. The decision to move because of tax policy is always made on the margin. For example, if a state proposed an additional $1 per year flat tax on all residents earning over $1 million, no individual would leave the state to avoid it. The cost is simply too small ($1) to lead to any behavioral change. On the flip side, if a state proposed a 99% tax on all income above $1 million, nearly all the millionaire earners would either move, work less, or find non-taxable ways to compensate themselves. This policy would create a huge behavioral change. At the extremes, you can see how policy would (or wouldn't) impact behavior. But what about at the margin? What does the historical evidence say about taxing the wealthy? For wealth taxes (not income taxes) in particular, the record hasn't been great. One report noted, "While 12 countries had net wealth taxes in 1990, there were only four OECD countries that still levied recurrent taxes on individuals’ net wealth in 2017." Most countries that implemented wealth taxes ended up repealing them because they weren't effective at raising revenue and led to some capital flight.  [Author's Note: An earlier version of this post cited an estimated loss from a Norwegian wealth tax policy change that was later discredited. I have removed such mention to maintain the accuracy of this piece.] But wealth taxes don't always fail. Switzerland has a wealth tax ranging from 0.1% to 0.7% across its 26 cantons (member states) that has been successful among its citizens. Why does the Swiss wealth tax succeed while others have failed? The Swiss wealth tax has low, predictable rates applied to a broad base of individuals, while others have had a higher rate applied to a narrower base of individuals. In general, tax policies targeted at a narrower base seem more likely to cause capital flight than policies that apply more broadly. But what about in the U.S.? Does tax policy tend to cause capital flight across state lines?  Historically, not all that much. Researchers analyzed over 45 million tax records across 13 years (1999–2011) and found that the millionaire migration rate was 2.4%, lower than the overall population migration rate of 2.9%. More importantly, when the authors modeled what would happen if all states had identical tax rates, elite migration fell by only about 2%. So while there is some relocation due to tax policy, in general most wealthy people in the U.S. seem quite embedded in their communities. This makes logical sense too. The wealthy have their career, their network, and their children's schools that they would need to leave behind if they wanted to move for lower taxes. So, unless a new tax policy is extreme, most wealthy people would simply complain about it and then get on with their lives. As you can see, when it comes to whether higher taxes cause capital flight, the devil is in the details. Policies that are too extreme and targeted seem to encourage wealth migration, while those that are reasonable and broader in application don't. So, if you want to raise taxes successfully on the wealthy, the record of history suggests that the policy should be reasonable in size and apply to a broader tax base. But, raising taxes is only half of the equation. How we spend the money is the other. It's the Spending, Stupid Some of you reading this might be thinking, "Nick it doesn't matter how much we raise taxes (and on who) if our government ends up spending the money irresponsibly." I completely agree. After all, the purpose of raising tax revenue is to spend it on helpful government programs. Things like education, healthcare, and infrastructure are worthwhile ways to invest in our society and its future. However, if there is rampant fraud, waste, and abuse in the system, then the real problem isn't necessarily revenue, but how we spend that revenue. For example, the Government Accountability Office (GAO) found that $236 billion in improper payments were made in 2023. This includes payments to deceased individuals and those no longer eligible for government programs. More importantly, the total amount of these improper payments has gone up nearly 7x over the past two decades: This is why any policy that aims to fix budget shortfalls should attack both sides of the ledger. Those that want to raise taxes on the wealthy should be just as vigilant on cutting administrative bloat. I understand that this is easier said than done, but it illustrates how "raising taxes" isn't the solution for runaway spending. The Bottom Line Every successful tax on the wealthy has been one that was small at first and increased slowly over time (or not at all). Switzerland's wealth tax is a prime example of this (small and stable), and so is the U.S. income tax (small initially before growing over time). When the U.S. income tax was implemented in 1913, the top 1% of U.S. households paid an effective income tax rate of less than 15%. It would take over 30 years before their effective rate exceeded 40% (from the Tax Foundation): Note that I say "effective" rate and not marginal rate for a reason. The 1950s are often cited as proof that high taxes on the wealthy work, since the top marginal rates often exceeded 90%. But marginal rates, by themselves, are misleading. After deductions, exemptions, and loopholes, the effective rate actually paid by the top 1% was only around 42% (as shown above). Since then, the effective income tax rate paid of the top 1% has declined slightly. Does this mean that income tax rates on the highest earners can increase again without much risk of capital flight? Yes, but these would need to be small increases in overall rates. Unfortunately, many recent tax proposals against the wealthy have been anything but.  This is why I believe California's 5% wealth tax on billionaires will likely fail. It's a big change that only targets a few hundred individuals, which is the exact kind of tax policy that has failed historically. Though Washington's millionaire tax is also a big change and may get struck down by the courts, it has a better chance of success precisely because it applies to a broader group of earners. Finally, NYC's pied-à-terre tax seems likely to succeed because the tax is modest and applies to over 13,000 units. However, given how mobile second-home owners can be, this tax may not raise as much revenue as initially projected. As the share of wealth held by the top 1% has increased in recent years, there are reasonable arguments to be made for increased taxation. However, as history suggests, successful tax policies tend to start small and apply to a broad base. Nevertheless, policymakers would be wise to examine overall spending in addition to finding new sources of revenue. Tax policy is one of those areas where both sides are correct. Yes, wealth concentration is high and undertaxed. However, poorly designed policies (and policies that don't address unchecked spending) aren't the answer. We have to find a way to solve both of these problems. Otherwise, no matter how much we tax the wealthy, we will end up where we started. Thank you for reading. If you liked this post, consider signing up for my newsletter. This is post 503. Any code I have related to this post can be found here with the same numbering: https://github.com/nmaggiulli/of-dollars-and-data

5/12/2026

There's a common belief that as your wealth increases, your capacity to take risk increases as well. After all, when you have more you can afford to lose more, right? This might be correct in the extremes, but this argument doesn't hold in more typical wealth ranges. Why? Because a dollar isn't always a dollar. And once you understand this, you'll never look at risk-taking the same again. A Dollar is Not a Dollar In the real world, people don't treat every dollar the same. As I discussed in The Wealth Ladder, your first $10,000 is more impactful than your next $10,000. It's also true that your first $1M is more impactful than your next $1M. And so forth. The reasoning for this is two-fold. First, every step up The Wealth Ladder creates a sort of lifestyle floor that people don't want to go below. For example, once you know what it's like to not worry about grocery prices, you don't want to go back to a world where you do. Second, the more wealth you have, the more wealth you require for a large lifestyle change. Going from taking a bus/train to taking a plane might cost 1.5x-2x more depending on where you're traveling. But going from flying first class to flying private will cost 10x more. It's these exponential increases in cost for marginal increases in convenience that creates this step-like structure for wealth. As a result, it becomes optimal to de-risk as your net worth increases. So while you can take more risk as you get richer, it doesn't mean that you should. Of course, the risks you take will always be relative to your desires. If you won't be satisfied until you're flying private in Level 5 ($10M-$100M), then you have to keep taking big risks. But, if you're content flying commercial in Level 4 ($1M-$10M), you can dial it back much sooner. As your wealth changes relative to your desires, your capacity to take risk will change with it. The closer you are to being fully content, the less risk you should want to take. I call this the Risk-Wealth Paradox. The Risk-Wealth Paradox The Risk-Wealth Paradox goes against the economic theory on risk appetites. Standard economic theory suggests that as our wealth grows, our absolute capacity for risk increases. As we build wealth, we can lose more and still survive. But the Risk-Wealth Paradox suggests that the rational choice is the opposite—as wealth grows, risk-taking behavior should collapse. This is true because while the financial cost of a loss goes down with more wealth, the psychological cost goes up. I've previously discussed how your appetite for risk should decline in middle age as your liabilities increase (e.g., children, aging parents, etc.). I would apply the same line of thinking to those who have built some wealth. As your net worth increases, preservation becomes more important than chasing increasingly expensive luxuries. Why is this the case? Because once you've won the game, the value of gaining a dollar plummets while the pain of losing a dollar soars. This is the fundamental principle behind prospect theory. Prospect theory states that people react to gains and losses asymmetrically. In other words, the pain of losing $100 is larger than the pleasure of winning $100, at least for most people. And when you're wealthier, it's like prospect theory on steroids. If you had a $2M net worth, the pain of losing $1M is significantly larger than the pleasure of gaining an additional $1M. It might even be larger than the pleasure of gaining $4M. While these amounts are arbitrary (and will vary from person to person), they exemplify the impact that wealth can have on risk-taking. The other reason for the risk-wealth paradox is the amount of time it takes to recover from a significant loss. If someone with $1,000 in a brokerage account lost it all, they could likely earn it back relatively quickly. But if someone lost $100,000 in their retirement account, it could take years to save that amount of money. Unless your income can keep up with your wealth over time, you'll have to decrease how much risk you take. Why? Because as your portfolio grows it becomes harder to replace future losses with future earnings. If you can save $50,000 a year, you can replace a 20% loss on a $1M portfolio in under 4 years (assuming a 5% return on your money). However, to replace a 20% loss on a $5M portfolio it would take over 14 years! This divergence is what contributes to what I call the risk squeeze. The Risk Squeeze Your ability to take risk throughout your financial life will be influenced by three primary factors—your age, your liabilities, and your level of wealth. As each increases, you should naturally want to take less risk. Unfortunately, these tend to all move up in middle-age. Does this mean we should be holding 100% Treasury bills when we are in our 40s? Of course not, but you have to consider how your risk taking should change over time. When I started invested I had 15% in U.S. bonds. Then I was 0% U.S. bonds for a few years. And now I'm 20% U.S. bonds with a growing amount of Treasury bills and tax-free munis on the side (for an eventual home purchase). Is this right? I have no clue. But it allows me to sleep at night. I've been fortunate to build some wealth and I also now have a family I'll need to support in the future. The risk squeeze is upon me and I've already taken steps to reduce my risk accordingly. I'm no longer playing to win. I'm playing to not lose. What about you? Where are you in your financial journey? Is the risk squeeze upon you? It's easy to critique someone else's risk-taking, but far harder to be honest about your own. I can't tell you how much risk to take. But if you've won the game, stop playing. Thank you for reading! If you liked this post, consider signing up for my newsletter. This is post 502. Any code I have related to this post can be found here with the same numbering: https://github.com/nmaggiulli/of-dollars-and-data

5/5/2026

It's 1:30 AM and my wife is in the middle of labor. We're both trying to get some sleep while she dilates further from 3cm to the ultimate goal—10cm. That's when I wake to one of the nurses telling my wife: We don't want you to panic, but you're about to hear a loud noise and then a lot of people are going to come into the room. Before I can turn my body to see what's going on, an alarm rings out. Within seconds, half the hospital staff seem to have spawned into our delivery room. The heart rate's dropping. Change her position. My wife, who was previously on her back, is now doing a cat pose as 20 eager faces stare at the monitors plotting our baby's heart rate. I know what's happening, or at least I think I do. Based on the handful of baby books I've read over the past few months, it seems like our baby's heart rate has fallen too low and the doctors are trying to raise it. If they can't, they'll need to perform an emergency C-section. That's when I hear: Wait. It's rising. A few moments pass as a slow calm takes over the room. One of the physicians walks over to examine my wife: She's 9cm. The room erupts with cheers. A moment of panic quickly turns into a moment of joy. Less than three hours later, my wife would give birth to our daughter. Since becoming a parent a few weeks ago, I've thought about this moment a lot. I've thought about it because it demonstrates how fragile life can be. Change a few conditions ever so slightly and my wife and I could've had a very different outcome in that delivery room. I'm thankful we didn't. Over the last nine months there have been many moments like this where something could've gone wrong. Moments where we were worried about one thing or another. Our pregnancy started with our baby not having a heartbeat at her first ultrasound. We didn't know it at the time, but we were simply looking too early. But even after the heartbeat came a few weeks later, the worries didn't end. We were concerned about genetic risks, down syndrome, our baby's organ development, my wife's glucose test, the baby's body position, and much more. While the probability of any one of these going wrong is small, taken together the chance of some complication is larger than you realize. And I say this as someone whose wife had as about as positive a pregnancy as you can have. We had no issues getting pregnant, no morning sickness, and no serious complications. I know how lucky we are. Unfortunately, some aren't so fortunate. One of our friends was diagnosed with cancer while pregnant. She was on chemotherapy while growing another human inside of her. Can you imagine how difficult that must have been? Another of our friends was hospitalized during her pregnancy due to her persistent morning sickness. We have friends who've failed to conceive after months of trying and tens of thousands of dollars spent on IVF. None of their embryos took.  I don't have the right words to express how sad this is. All I know is that when you examine all the ways life can fail, it makes you deeply appreciate it when it succeeds. And I say this within the context of modernity. Historically, the childhood mortality rate was astronomically higher. Our World in Data estimates that the probability of a child dying before age 15 was nearly 50% before the advent of modern medicine: It's horrific to imagine a world where nearly half of all children died before puberty. But this was our world until rather recently. Unfortunately, life is a great filter. Once you realize this, it's easy to see how precious every individual is. Because every one of us had to get through that filter to get here. This wasn't apparent to me until I experienced pregnancy and childbirth firsthand. I've always conceptualized why children are important, but now I can feel why they are. I now understand the time, the energy, the worry, and the hope it took to get here. And not just my own. But that of my parents, and their parents, and their parents, and so forth.  I have no clue what financial investments my great-grandparents made, if any. But I know they invested to raise my grandparents. And my grandparents did this for my parents, who, in turn, did this for me. Your ancestors did the same for you as well. I've spent nearly a decade writing about investing and it was only a few weeks ago that I got a deeper understanding of what that word really means. Yes, your investments involve what you do with your money, but also how you spend your time.  Every parent who loses sleep to feed their child or works a job in order to provide is investing too. They're investing in a better future for their children. This kind of investing doesn't show up on a balance sheet, but it's arguably even more important than the kind that does. Because without such investments, the world as we know it would cease to exist. I know this now and have already seen a change in how I spend my time. Having a newborn brings such immense clarity over your day. It focuses you in a way that nothing else can. Because I am no longer investing solely for myself. I'm investing for my daughter and the generations to come. I'm investing to help them get through the great filter. To all the mothers investing in their children, Happy Mother's Day and thank you for reading. If you liked this post, consider signing up for my newsletter. This is post 501. Any code I have related to this post can be found here with the same numbering: https://github.com/nmaggiulli/of-dollars-and-data

4/28/2026

As of today, I've published 500 blog posts online since January 2017. That's slightly more than 1 per week. Given this, I wanted to discuss the biggest lessons I've learned from this and how they can help you. Consistency Beats Everything If there were one idea that I could bestow upon anyone who wants success in life, it's—consistency beats everything. This is true in investing, in fitness, in your career, with your relationships, and so much more. It's been true everywhere I've ever looked. Those who are consistent outperform those who aren't in the long run. Kobe Bryant is probably the best example of this. Kobe was known for his early AM workouts, but what he did to prepare for the 2012 Olympics was on another level. One trainer for Team USA described how he helped Kobe work out for 75 minutes at 5 AM, went back to his hotel to get some sleep, and then returned by 11 AM to see Kobe still practicing. Kobe had never left and told the trainer that he wanted to make 800 shots before the main practice at 11. And he did. Kobe outworked everyone in the league and is today considered one of the greatest basketball players of all time as a result. Consistency can also be used to make seemingly impossible tasks far more manageable. For example, when I was writing The Wealth Ladder, I knew I had to end up with a book that was around 55,000 words. This can seem insurmountable when staring at a blank page. But when I broke it up across 6 months, I realized I only had to write a little over 300 words a day. That wasn't too bad. A few paragraphs a day and I'd end up with a book. All I had to do was be consistent. No matter what you pursue in life, consistency is the trick to get through it. It's also how you improve as well. Doing is Improving When I first started blogging, I wasn't a great writer. Read my earliest work and you'll see. Actually, don't read it. Because if you did, you'd see that I don't have a God-given talent for prose. I'm much more of a numbers guy than a poet.  But things didn't stay this way. I kept writing week after week. And, slowly, I got better. I didn't read books on "how to become a better writer" or take an online writing course. I just kept writing. The act of doing was how I improved. And this improvement didn't happen all at once either. I didn't go to bed one night a bad writer and wake up a good one. No, it was a gradual process that I'm still working on almost 10 years later. Why is doing the ultimate form of mastery? Because it forces reps, reps, reps. That's how you learn and get better. Don't just take it from me though, consider one of my favorite experiments on the topic.  In the experiment, students in a ceramics class were split into two groups. One group would be graded on the quantity of the work they produced while the other group would be graded on the quality of the work they produced. The quantity group had to create as many clay pots as possible over the semester while the quality group only had to produce a single clay pot as best they could. Months later when the students turned in their pots to be graded, the teacher came to a surprising realization — all of the highest quality pots were actually produced by students in the quantity group. Those who focused on producing actually improved more than those who were told to explicitly focus on improving. When pursuing perfection, we fail to find it. But when pursuing production, we somehow do. Nevertheless, improving can't be your only goal. Because focusing too much on the outcome is the wrong way to approach life. The Journey is the Outcome It's natural to judge your performance based on the outcome. If you release a product, you want people to buy it. If you write a book, you want it to sell. I get it. But being too outcome-focused always leads to dissatisfaction. Because you either: fail to reach your goal, or accomplish it and are left wondering, "What's next?" As Jim Carrey once said: I think everybody should get rich and famous and do everything they ever dreamed of so they can see that it's not the answer. I've been fortunate enough to meet a lot of successful people in the financial and literary space. And none of them seem far happier than anyone else. If anything, many wanted even more success. And there's nothing wrong with that, but it's a dangerous game to play for long because you can't win. And if no outcome ever brings ultimate satisfaction, then your only option is to focus on the journey. Not because it will bring rewards, but because it's who you are. It's only the journey that can lead to fulfillment, not the destination. Once you realize this, it completely redefines how you view success. Being successful is no longer about a number or amount. It's also about how you accomplished what you did. It's the way you went about it. Did you have to lie? Did you have to cheat? Did you compromise who you are? There are a lot of ways to be successful, but there's only one way to be you. Were you true to that person?  When you focus on the journey, it becomes the outcome. And that outcome will often surprise you. The World Will Surprise You Of all the reasons to pursue something for a long time, the unexpected benefits are probably the most compelling. I don't know a single person who's worked on a project for many years and hasn't had at least one upside surprise while doing so. This doesn't mean that every project will be a smash hit. But every project is likely to have some benefit that you didn't envision at the outset. For me, that upside surprise has been all the fans I've gained internationally. 80% of the sales of Just Keep Buying have been outside the U.S., mostly in Japan and Taiwan. I never could've predicted that my work would take off more abroad than at home, but it has. Despite the vast cultural differences, my writing has had more universal appeal than I originally imagined. Whether you decide to write 500 blog posts, do 500 workouts, or help 500 clients, I promise that you will find yourself pleasantly surprised with the results. Even if you don't accomplish what you originally had in mind, you'll gain greater experience and will have learned something new in the process. Then again, what would I know? I've only written 500 blog posts once. Thank you for reading. If you liked this post, consider signing up for my newsletter. This is post 500. Any code I have related to this post can be found here with the same numbering: https://github.com/nmaggiulli/of-dollars-and-data

4/21/2026

In 2015, Tai Lopez started running his now famous "Here in my garage" ad on YouTube as a way to promote his 67 Steps self-help course. The ad featured Lopez standing in front of a brand new Lamborghini before panning over to seven bookshelves he had installed to fit 2,000 books he had recently purchased. Following the release of the ad, Lopez became an overnight sensation. Despite being widely ridiculed, "Here in my garage" was a massive success that, according to some sources, generated over $50 million in revenue for Lopez. Based on this success, Lopez founded a marketing business that did well as his YouTube following grew. However, by 2019, Lopez shifted his focus and created a holding company, Retail Ecommerce Ventures LLC ("REV"), to invest in distressed brick-and-mortar stores. REV raised $112 million from investors to buy companies like Radio Shack, Pier 1 Imports, and Linens 'n Things. Unfortunately, this is where things went south. As these distressed investments failed to pan out, REV allegedly started missing payments to investors, and everything came undone. In September 2025, Lopez was charged with fraud and running a Ponzi scheme by the SEC.  I've been thinking about Lopez's story a lot over the last six months. How does someone who's won the game end up losing so badly? I don't mean to pick on Lopez either, because it's happened with so many others. Sam Bankman-Fried went from the world's richest person under 30 to a 25-year prison sentence. Elizabeth Holmes went from the cover of Forbes to 11 years in prison. All of these falls from grace illustrate a deeper truth—survival is the only success. It doesn't matter what you do in life if you can't sustain it. You could make $100 million, but if you end up in a prison cell or broke, who cares? That's not success. In fact, it's the opposite. Using this definition, you are more successful than Tai Lopez, Sam Bankman-Fried, and Elizabeth Holmes. I am too. If you don't believe me, ask yourself one question: Would you trade places with any of them? I know I wouldn't. I bet you wouldn't either. There's no amount of money and fame that is worth the loss in reputation and freedom.  Here's the funny part though—Lopez, Bankman-Fried, and Holmes all could've enjoyed their success if they had just stopped earlier. Lopez and Bankman-Fried had real, profitable businesses. They didn't need to chase after more. Holmes could've failed with Theranos (without the fraud) and I guarantee she'd get funding for her next venture. But they didn't stop. Why? Because greed is a hell of a drug. Greed drives people to behave in absolutely irrational ways. It drives some people to risk everything for just a little bit more. It's the most negatively asymmetric payoff you could imagine—the upside is capped, but the downside is unlimited. And yet people still make this trade all the time. There are people out there doing it right now. They may look successful today, but they won't hold onto their success. I was reminded of this after recently re-reading Fooled by Randomness by Nassim Taleb. Taleb tells a story of a trader who is rewarded with larger and larger bonuses each year by pursuing a high risk, levered strategy. The trader outperforms all of his peers, further affirming that his approach is best. All is well until something happens in the market that the trader wasn't expecting. Their strategy blows up and they lose everything. Taleb's story demonstrates why survival is the ultimate financial goal. Because it doesn't matter how you perform for a month, a year, or even a decade. All that matters is what you can keep in the long run. Whether you can make it to the end game. This is why I'm not a fan of those who "generate income by selling options." These people are trading immediate rewards for future risks. And when those future risks inevitably arrive, many of them get wiped out. As Taleb writes: Options sellers, it is said, eat like chickens and go to the bathroom like elephants. Unfortunately, option sellers are the opposite of investors. They collect rewards now for risk later. Investors take risks now for rewards later. So which do you want to be?  You don't have to sell options or run a Ponzi scheme to fall victim to this either. There are plenty of ways that retail investors do this on a much smaller scale. They put most of their money into a single stock because it's surging upward. They juice their returns with leverage or chase the latest trend.  All of these work great...until they don't. Unfortunately, when they stop working, you can lose more than just your capital. You can lose your confidence too. That's where the psychological cost of investing shows up. You start to question whether you know how to invest or whether you're just lucky. This is why survival matters far more than short-term performance. Because survival allows you to compound your money for a longer period of time. And it's this compounding that builds true wealth. There's a great irony in this though. Because the people who compound their money for decades aren't the ones you typically read about. There's no headline for someone who invested consistently for 40 years and retired comfortably. There's no documentary about someone who built a small fortune while working a 9-5 job. But these are the real financial success stories. Everything else is just noise. It reminds me of this interaction I saw not too long ago on about index investors: So, if you want to be financially successful—just survive.  Thank you for reading. If you liked this post, consider signing up for my newsletter. This is post 499. Any code I have related to this post can be found here with the same numbering: https://github.com/nmaggiulli/of-dollars-and-data

4/14/2026

Picture this: You're in your mid-40s and you've just quit your stressful corporate job. You've set aside enough money to fund your future retirement and now can work a more enjoyable (but lower paying) job to cover your living expenses until then.  This is the definition of Coast FIRE. You don't have enough assets to never work again, but you have enough to never save again. You can "coast" until you get to retirement. Sounds pretty nice, right? This is why I love Coast FIRE. Out of all the variations of the FIRE movement, it's by far the most appealing. You get most of the flexibility of financial independence with fewer of the costs. Under Coast FIRE, you don't need to acquire as many resources as you do with traditional FIRE, and you don't need to be as frugal either. Coast FIRE captures most of the benefits of FIRE without its extreme sacrifices. But has this changed in the age of AI? With the recent discussion around AI bots replacing white collar workers in the near future, is retiring early still the right move? Let's dig in. How AI Could Impact Coast FIRE If you've recently hit Coast FIRE or are thinking about it in the next few years, below are some potential issues to consider: Could AI Automate Your New Career? The premise of Coast FIRE is that you leave behind your traditional 9-5 job in favor of a new career or side hustle. That new career/side hustle might pay less than your prior job, but it pays enough to cover your living expenses until you reach retirement. So what happens if that new career/side hustle gets automated by AI? For example, imagine someone who quits their job to work as a graphic designer because they reached Coast FIRE. How do they keep their clients when AI can replicate some of their work for much cheaper? This isn't a rhetorical question either. This has already started happening. There's a reason why Fiverr (the online gig work platform) had its stock cut in half over the last year.  Before you take the leap to pursue Coast FIRE, consider how future technological changes could impact your ability to coast. I'm not asking you to predict the future, but you should think deeply about how you'll earn money in a world where LLMs are even more powerful than they are today. How Will AI Impact Your Investments? Another area where AI could impact Coast FIRE is on the investment side. After all, those pursuing Coast FIRE must rely on the growth in markets to meet their future retirement needs. So how will AI impact future equity returns? I don't know (no one does). Nevertheless, some of the benefits of AI will accrue to public equity holders of AI and AI-adjacent businesses. While many AI companies are currently privately held, you'll still get plenty of exposure to AI in a broad U.S. index fund (via the Magnificent 7 and others). You could increase this exposure by owning a tech-focused index fund (like the NASDAQ), but I don't believe this is necessary. Overall, I don't think AI is going to impact your investments as much as it could impact your career. So, if you want to stay ahead of the curve when it comes to AI, focus on your paycheck, not your portfolio. Could AI Actually Help Coasters?  While AI could harm some in the Coast FIRE community, there's an argument to be made that it could help some as well. There are people out there who could use the latest models to expand their business or get more done in less time. Instead of looking at AI as a competitor, you could team up with it to enhance your new career. For example, you could have an LLM check your work or summarize meetings and emails to save you time. While AI functionality is somewhat limited today, it won't be by the time many of you approach Coast FIRE. Additionally, coasters (Coast FIRE adherents) may be uniquely suited to benefit from AI because they tend to be flexible in their thinking/planning. If you're someone who regularly thinks about and plans your future, you are probably also someone who could use cutting-edge technology to find solutions to your problems. And AI may provide such solutions. Should You Grind it Out For a Few More Years to be Safe? Regardless of how you feel about AI, maybe you should ignore Coast FIRE for now to accumulate more capital before it's too late. There's a recurring argument in the AI community that you have 3 years (it always seems to be 3 years) before AI automates all of our jobs. While AI will definitely do more white collar work in the future, I don't believe the job market will be as dire as some AI fanatics believe. But what if I'm wrong? Wouldn't grinding it out for a few more years be the prudent thing to do? Why take the step back now when you could do it in a few years? After all, if AI doesn't take your job, you're fine. And if it does, you'll be glad you acquired as much capital as possible while you still had the chance. The problem with this logic is that there's always an excuse to keep grinding. It's easy to argue that AI or inflation or something else will require you to save more than you originally planned for. Unfortunately, if you start thinking this way, you'll never stop. It reminds me of that time John D. Rockefeller was asked, "How much money is enough?" and he replied, "Just a little bit more." If you want to use AI as an excuse to delay Coast FIRE, go ahead, but you'll easily find another excuse in years ahead. While there are many ways in which AI could impact those pursuing Coast FIRE, we won't know which of them will occur until after the fact. As much as I'd like to tell you everything will be okay, I don't know for sure. Unfortunately, AI has injected a fair dose of uncertainty into all of our futures. But uncertainty is just part of the game. No matter when you retire, you'll run into it eventually. For example, imagine pursuing Coast FIRE in 2007. The very next year the Great Financial Crisis would hit and you'd be questioning everything. You'd wonder if you should go back to work. You'd wonder if you could even go back to work. You'd probably have the same experience coasting at the onset of COVID in 2020, during the tech crash in 2022, and the AI boom of today. The story changes, but the feeling remains the same.  This is true for all forms of early retirement. They all come with risk. You just have to accept these risks when you take the leap. AI isn't special in this regard. AI is merely the next unknown in a line of unknowns that will worry retirees into the future. So, did AI kill Coast FIRE? Not necessarily. It's just the latest reason to worry about it. Thank you for reading. If you liked this post, consider signing up for my newsletter. This is post 498. Any code I have related to this post can be found here with the same numbering: https://github.com/nmaggiulli/of-dollars-and-data

4/7/2026

Over the last year, I've come to an unsettling realization—the upper middle class is caught in a trap, and many of them don't realize it. A few weeks ago I wrote about why private school isn't worth the cost. My argument hinged on the fact that the upper middle class pays a lot for private education despite there being no significant impact on lifetime outcomes. In The Death of the Amex Lounge, I found the same thing—premium travel experiences had become crowded while remaining expensive. And, after recently digging into the data on housing, I'm having déjà vu. Homes are getting smaller even as prices rise. LendingTree reported that, from 2014 to 2024, the average size of new single-family homes shrunk by 11% even as the price per square foot surged by 74%! This is just the average too. A home near a public elementary school with a GreatSchools rating of 9 or 10 costs 78.6% more than a home in the surrounding county. All of these trends point toward the same thing—people are paying more and getting less. This is what I call the upper middle class trap. The Financial Arms Race Right now, the upper middle class is in fierce competition for a marginal improvement in lifestyle. They're working more and relaxing less to purchase products and services with clearly declining quality. It's a financial arms race that doesn't make any sense. You have people making six-figure incomes going into a frenzy for nicer homes, better schools, and more luxurious travel experiences. What's the end result of this status contest? Overpaying, and by a lot. For example, one group of researchers found that bidding wars on housing tend to decrease long-term returns by a significant margin. As they stated: The coefficient estimate for bidding war transactions is negative and statistically significant, indicating homebuyers who purchase their house in a bidding war experience 6.9% lower levered annualized returns than homebuyers who did not purchase their house in a bidding war. That's nearly 7% per year in lost returns simply due to price competition. This same competitiveness partially explains why college tuition and private school costs have grown twice as fast as overall inflation over the past few decades. With more students applying to roughly the same number of spots, you can keep raising prices. This is especially true at the top universities. Since 2015, the number of college applicants has gone up 78% while acceptance rates at elite colleges have plummeted: This increasing struggle for scarce positional goods keeps the upper middle class overworked and trapped in the rat race. And do you know what's making this problem even worse? AI. Not only are many high-income workers worried about AI taking their job, but they're competing with other high-income workers to increase their productivity and not get left behind. We see this clearly in the data. As the Brookings Institute noted in November 2025: AI use also varies across income levels, rising from 9% usage among earners below $30,000 to 34% among those making $100,000 or more. Individuals with the highest incomes tend to use AI the most. This is a rational response if you believe that AI is a serious threat to your high-paying career. However, it has an unintended consequence–it makes the upper middle class trap even more solidified. How? Because it forces people to work even harder to continue competing for the same set of scarce resources. Think about it. If AI doubled everyone's productivity overnight, suddenly someone with half your skill would be able to compete with you just by using AI. Therefore, you have to learn AI just to keep up. It's the Red Queen all over again. You have to run as fast as you can just to stay in the same place. Anecdotally, I'm seeing the same thing. The most successful people I know are using AI more than anyone else. Though they would still be successful without such tools, they are learning them nonetheless. If you're already working hard to live an upper middle class lifestyle, AI has made it such that you need to work harder to stay on top of the latest developments. But is there a better way? Escaping the Trap The issue with the upper middle class trap is that it's a collective action problem. Individually, every decision is rational. It's rational to send your children to the best schools, to want a nicer home, and to travel to opulent destinations. But, collectively it's self-defeating. When everyone is vying for the same limited resources, it lowers quality of life across the board. It reminds me of the value of college degrees over time. When fewer people had them, a college degree made you stand out. But now that so many have them, it's table stakes. Now, we spend four years and tens of thousands of dollars to end up in the same place. This is why the best way to escape the upper middle class trap is to stop participating in it altogether. Opt out of those ultra-competitive sectors that won't materially change your lifestyle. Send your kids to good public schools instead of costly private ones. Skip first class and fly economy. Buy a little less house than you can afford. The ironic part is that the data supports this. Children from the upper middle class who attended elite schools performed no better than similar kids who attended public ones. The bidding war data illustrates that many people overpay for housing. And, as I demonstrated last year, premium travel experiences aren't what they used to be. So figure out if private school, a nicer home, and more extravagant vacations are actually worth the high price, then move on. Ask yourself: Am I buying this to improve my quality of life, or merely because other people are buying it? Those who can navigate this question successfully will end up better off financially and with more leisure time too. You'll have more flexibility and freedom without having to worry about chasing more status trophies. That's how you escape permanently. But there's one part of the upper middle class trap that will be difficult to opt out of—AI. Thankfully, if you're spending time learning AI this early in the cycle, you're already ahead of the game. The people most at risk from AI aren't reading about it. They don't even know what it is. The same is true for the upper middle class trap—it only impacts those who don't see it. But, hopefully, now you do. Thank you for reading! If you liked this post, consider signing up for my newsletter. This is post 497. Any code I have related to this post can be found here with the same numbering: https://github.com/nmaggiulli/of-dollars-and-data

3/31/2026

There seems to have been a vibe shift in the U.S. housing market over the past six months. What started in places like Austin, Texas with falling rents and home prices, seems to have spread to other parts of the country. As you can see in the table below, it's not just Austin that has experienced double-digit rent declines since 2022: And what has happened in the rental market seems to be occurring to home prices as well. Analysis from Residential Club shows that 75% of the largest metro areas in the U.S. saw inflation-adjusted home price declines over the last year. But will this trend continue? And what might we expect from U.S. housing over the next few years? Let's dig in. Rates Aren't the Problem Anymore When we talk about U.S. housing, the first thing we need to address is affordability. After all, if people can't afford houses, they don't buy them. The big issue with affordability, as you likely already know, is that incomes haven't risen in line with mortgage payments. In fact, you need nearly twice as much income today to afford the typical U.S. home compared to before COVID: Part of this problem is that 30-Year mortgage rates more than doubled from the early 2020s. But, 30-Year mortgage rates were an outlier (on the low side) from 2010 through the early 2020s: So seeing them revert back to their historical norm today isn't all that surprising. But what hasn't reverted back to its historical norm? Prices. As the chart below illustrates, the inflation-adjusted Case Shiller Home Price Index is higher today than it was during the 2000s Housing Bubble: This suggests that, all else equal, prices are the problem, not rates. Thankfully for homebuyers, prices have started to slow (and even decline in real terms) over the past few years. You can see this by looking at the annual nominal returns of U.S. housing from 2020-2025 (h/t Ben Carlson): U.S. housing saw a negative return (after inflation) in 2025. This might just be the beginning too. As Reuters recently reported, new home sales dropped by 17.6% in January 2026, the lowest level since October 2022. This is occurring as the number of homebuyers in the market reaches a record low: And as home-purchase cancellations reach a record high: People aren't buying, or they are reconsidering buying, as prices begin to creep downward. And I believe that prices can continue to creep downward for one simple reason—home equity. There's Room to Fall The main reason why home prices can continue to decline is that homeowners have record levels of home equity: And a good portion of this home equity was created in the last few years (as the chart above illustrates). As a result, homeowners won't feel the sting of home price declines as badly as they normally would. We can prove this with a simple example. Imagine you bought a house for $100,000 (and all houses cost $100,000). Now imagine that all home prices doubled to $200,000. Have you gained anything? Relative to non-homeowners, you have. But relative to other homeowners, you are no different. If you sold your $200,000 house and bought another one, it would cost you $200,000. Nothing gained, nothing lost. Now imagine that all home prices then dropped to $175,000. Have you lost anything? Relative to homeowners, you haven't. You sell your $175,000 house and buy another one for the same price. This is a simplified version of what happened to U.S. homeowners over the past few years. They gained a lot of home equity (on paper) that hasn't translated into any real difference in their lives. So, if that home equity were to decline somewhat (in aggregate), there would be very little impact on them. Outside of imagining what they could've had (aka selling at the top), they haven't lost much. But there's another side to this. Homeowners with large equity cushions can actually afford to cut their asking price and still walk away with a profit. This makes it more likely that they reduce their price compared to someone with far less equity. Nevertheless, it won't feel that way. Especially because housing makes up such a large portion of overall wealth. Among U.S. households with $1M-$5M, housing comprises around 30%-40% of their net worth: As a result, many of these households will fight tooth and nail to hold onto this home equity, even if it's just on paper. Of course, this assumes that these homeowners have the luxury of holding out. If the economy deteriorates and people are forced to sell—due to job loss or other financial distress—equity cushions matter far less. Either way, this fight is going to play out over the next few years. Housing Remains Slow...and Local I don't claim to be an expert on U.S. housing, but one thing I know for sure is that home prices move much slower than other asset classes. While U.S. equities bottomed in March 2009 (during the Global Financial Crisis), U.S. housing didn't hit its lows until 2012, over 3 years later.  I suspect that the same thing will occur with U.S. housing over the next few years. Why? Because it's going to take time for people to update their beliefs and face reality. They will need to accept that their home isn't selling because of the listing description, the photos, or even their agent. It's not selling because of the price. Once this becomes common knowledge, then the U.S. housing market will start picking up once again. Of course, this won't happen everywhere. In San Francisco and New Jersey (my home market), I've seen recent examples where homes were getting multiple offers and selling above ask. These areas may not experience the same "belief revision" that the rest of the country will likely go through. Regardless of what happens, the housing market remains local. This is the most important thing to keep in mind as homebuyer (or seller) in the near future. Housing is a complex asset class where averages can mask what's really going on. For example, one neighborhood could see prices plummeting while another nearby remains strong. This is why you have to do your homework and understand your target market. I'm generally not a fan of market timing when it comes to buying income-producing assets. But when it comes to housing (which I consider a consumption good), price matters a lot. Not only is it likely to be the biggest financial decision of your life, but it's an un-diversified one at that. So, do your homework, stay informed, and buckle up. If you're a buyer, time is on your side for the first time in many years. Thank you for reading! If you liked this post, consider signing up for my newsletter. This is post 496. Any code I have related to this post can be found here with the same numbering: https://github.com/nmaggiulli/of-dollars-and-data

3/24/2026

For months now there's been an online joke that anyone who doesn't learn about AI will be a part of the "permanent underclass." The permanent underclass represents the new have-nots of society—all of those who will be left behind in the coming AI wave. While a subset of the population will have all of their work done by LLM-powered agents, the permanent underclass will be left jobless and in perpetual destitution.  It's a nice theory, but it has no historical precedent. For example, the share of the U.S. workforce employed on farms fell from 90 percent in 1790 to less than 2 percent today. If I came to you in 1790 and told you that 98 percent of all farming jobs would be eliminated in the future, you'd have a difficult time predicting what all of those people would be doing today. You'd have no clue that they'd be social media managers, real estate agents, data scientists, or the thousands of other roles that literally didn't exist at the time. This is why the fear mongering around AI today is misguided. Because this technological shift will create many new roles and increase demand within existing ones. This explains why software development job postings are up over 10% over the last year despite increased reliance on AI for creating software. As Kenton Varda, a technical lead at Cloudflare, explained: Worries that software developer jobs are going away are backwards. There is SO MUCH software to build right now, that previously wasn't possible (uses AI directly) or wasn't cost-effective (too niche). We're going to have more developers, and orders of magnitude more software. This phenomenon is known as Jevons' paradox, where the increased efficiency of a given resource (e.g., software creation) leads to an increase, not decrease, in its consumption. This is going to happen across a host of different jobs and industries as a result of AI. And when it does, humans will be better off in the long run.  Some will argue that "this time is different" because AI is replacing knowledge work, not just physical work. And, if this comes to pass, what will there be left for people to do?  It's a compelling argument, but people made similar arguments about the automation of physical work. There was literally a group of people in England in the early 1800s called the Luddites who destroyed weaving machines due to their adverse impact on textile workers. The Luddites couldn't imagine what would replace their livelihoods and the same is true for us now. There will be future roles that require a different set of human skills that we can't even imagine today. These skills won't directly compete with LLMs, but will enhance them. And while the speed of AI disruption will likely be faster than previous cycles, the recovery will be as well. Since information travels much faster today than in the past, people will be able to reorganize and re-skill at a much faster pace than in prior centuries.  David Oks wrote a great piece on why the impact of AI on the labor market won't be as harsh as people initially expect: ...the relevant question for labor impacts is not whether AI can do the tasks that humans can do, but rather whether the aggregate output of humans working with AI is inferior to what AI can produce alone. Fortunately, we are still at the point where AI + human is better than AI alone. If you're still worried though, consider how prior technological changes have permeated throughout society. I know of no case in recorded history where a new technology was widely adopted and the percentage of people living in poverty increased over time. In fact, over the last half century, the opposite seems to have happened. The number of people worldwide living in extreme poverty has declined by roughly 66% since the 1970s, despite many groundbreaking, technological advancements: Of course, there have been short periods where a new technology has led to some local displacement/decline. The early years of the Industrial Revolution were a period where life was arguably worse for the typical laborer (e.g., the Luddites). However, such setbacks were short-lived and never resulted in a permanent underclass. Some of you will see this data and argue that it's irrelevant because extreme poverty isn't the right metric. What matters is the relative difference in wealth, not the absolute difference. After all, even if we eliminated all extreme poverty, there still can be an underclass, right? In some ways, yes. But that's already true today. We already have a small subset of the global population that flies private, owns a yacht (or two), and doesn't need to work a 9-5 job. Thankfully, such lofty positions are almost never permanent. The Temporary Elite One of the biggest reasons why I'm not worried about an AI-induced class divide (even if it does come to pass), is that it's likely not to last very long. If you look over the course of history, you will notice that fortunes tend to rise and fall within families. Some families have wealth and power in one generation, only to lose it in the next. If you are under the impression that rich families stay rich forever, consider this (from Fortune's Children): When 120 of Cornelius Vanderbilt's descendants gathered at Vanderbilt University in 1973 for the first family reunion, there was not a millionaire among them. Cornelius Vanderbilt was born poor, yet became the richest man on Earth. Nevertheless, even that fortune didn't last more than a few generations. The dominant industry of Vanderbilt's time (railroads) gave way to others that overtook it. This simple example illustrates how even those in the current AI-elite will eventually lose their fortune in one way or another. It reminds me of that Warren Buffett quote: I try to invest in businesses that are so wonderful that an idiot can run them. Because sooner or later, one will. Well, guess what? No matter how rich or successful you are today, one of your future descendants will be the "idiot" that loses your fortune, one way or another. Attributes like talent, intelligence, and temperament exhibit mean reversion over time. This is what makes it near impossible for a family to hold onto great wealth for long. It's also why I'm skeptical of a future, AI-induced class divide. Because, even if there is, it won't last. There will be no permanent underclass because there is no permanent elite. All such places of privilege and power are temporary. History has demonstrated this time and time again. So, stop worrying about getting left behind and start focusing on how to be more useful in the first place. Thank you for reading. If you liked this post, consider signing up for my newsletter. This is post 495. Any code I have related to this post can be found here with the same numbering: https://github.com/nmaggiulli/of-dollars-and-data

3/17/2026

I recently saw the following table about the increasing cost of private school in NYC: For context, the annual tuition at Harvard is $59,320, or over $3,000 less than the cheapest school on this list (for 2025-2026). Excuse me, but what the hell is going on? How are high schools charging more than one of the most prestigious universities in the world? I'll tell you how—private schools have convinced the upper classes in the United States to believe that they are worth the cost. But the truth is...they aren't. In fact, private schooling is the most expensive placebo in America. I can prove it too. It's the Genes (Mostly) When researchers study the impact of a particular factor on lifetime outcomes for children, they break it into three components: genetics ( heritability), the shared environment, and the non-shared environment. Genetics is exactly what you think—the DNA you get from your ancestors. The shared environment are those things that siblings have in common, like the same parents or attending the same school. The non-shared environment are things that children don't have in common, like different friends or different teachers. To measure these three components, researchers compare the outcomes of identical twins (siblings born with the same genetics) versus fraternal twins (siblings born on the same date, but with different genetics). In doing so, they can infer how much genetics impacts height, intelligence, or any other trait compared with the shared or non-shared environment. For example, let's imagine a set of identical twin boys versus a set of fraternal twin boys. The identical twins share 100% of their genetics and 100% of the shared environment (i.e., parents, schools, etc.). So any difference in their outcomes must come from the non-shared environment. On the other hand, fraternal twins share 50% of their genetics and 100% of the shared environment. So any difference in their outcomes must be partially genetic and partially from the non-shared environment.  This framework was laid out by Robert Plomin, behavioral geneticist, in Blueprint: How DNA Makes Us Who We Are. And when Plomin examined all the data on school achievement, he came to a surprising conclusion: In fact, heritability of school achievement is about 60 percent across the school years, higher than the heritability of intelligence, which is about 40 percent. This means that genetics (heritability) explains 60% of the differences in school achievement between children. What's the other 40%? The shared and non-shared environment. And the research suggests that half of this 40% is in the shared environment. Plomin once again: Environmental influence shared by children attending the same schools as well as growing up in the same family accounts for only 20 per cent of the variance of achievement in the school years and less than 10 percent of academic performance at university. Think about that. All your interactions with your children. The way you raise them. The schools you send them to. All of that only contributes 20% to their school outcomes. It's not zero, but is it large enough to justify such exorbitant costs? I don't think so. In fact, when researchers measure school quality directly, the effect size collapses much further. Plomin found that school quality in the UK explained "less than 2 percent" of the variance in test scores, after controlling for primary school achievement. In other words, the "best" schools aren't making the students better, they are just selecting better students from the outset.  In this way, it's not the school that makes the students, but the students that make the school. Why the Students Make the School (Not the Other Way Around) You might argue that schools as a whole may not make much of a difference in lifetime outcomes, but selective schools do. Unfortunately, the academic literature doesn't support this. How do they demonstrate that selective schools don't really make a difference? They do something called a regression discontinuity study. That's just a fancy way of saying "compare people right above a cutoff to those right below it." For example, many selective New York high schools have testing cutoffs. If you score above the cutoff, you get into the school, and if you score below the cutoff, you don't. Researchers compare the students who scored right above the cutoff to those who scored right below it. In effect, they compare students with near identical ability. They aren't comparing the all-stars to those who flunked the test. They are comparing students where one or two different answers on a test determined which high school they attended for the next four years. If the selective schools were so impactful, we would expect to see the students right above the cutoff having much better outcomes than those right below the cutoff. Do we see such an effect? Nope. As researchers at the National Bureau of Economic Research (NBER) concluded: ...as best we can tell, there is little effect of an exam school education on achievement even for the highest-ability marginal applicants and for applicants to the right of admissions cutoffs. In other words, selective schools achieve great outcomes because they pick the students that are likely to have great outcomes. This doesn't mean that school choice doesn't matter. But choosing a good (free) public school over an elite (expensive) private school doesn't seem to make much of a difference. A 2006 paper published in the American Educational Research Association (AERA) supports this assertion: In fact, after demographic differences had been controlled, the private school advantage disappeared and even reversed in most cases. This finding has been replicated in various voucher programs (see here and here) where students from public schools were given the chance to attend a private school. In both cases, scores did not materially improve (and sometimes fell). The Network Matters (For Those Outside of It) I know what you might be thinking though, "I don't care about the impact of the school on my child, but the impact of the other students at that school. It's the network that is valuable, not the education. That's why I send my kids to private school." Funny enough, this seems to be true, but not in the way you think. The network is valuable, but only for those far outside of it. As research published in the Quarterly Journal of Economics found: ...students who attended more selective colleges earned about the same as students of seemingly comparable ability who attended less selective schools. Children from low-income families, however, earned more if they attended selective colleges. Don't you see the irony though? All the families that can afford private school aren't low income. In other words, those who can afford private school don't need it, and those who can't, do.  This makes logical sense. Someone with a high income likely has high income colleagues, neighbors, and friends. They don't need to send their kid to an elite school to have access to a good network. But the lower income family does. I can speak on this from personal experience too. I attended a low quality high school. 89% of students (myself included) were considered "socioeconomically disadvantaged." Our senior class president didn't graduate. There was no elite network. But I was fortunate enough to get into Stanford University. This gave me access to classmates and professors that helped me at multiple points while I was in school. Without this network, I'm certain I wouldn't be where I am today. If you have no access to such a network, paying for it can be worth the cost. But for most high income families, you'll be better off saving (and investing) the tuition money than blowing a quarter of a million dollars for a marginal impact. That $250,000 in forgone tuition could end up being $400,000 (in real terms) for a downpayment on a home by the time your child turns 30. Your children can thank me later. Until then, thank you for reading! If you liked this post, consider signing up for my newsletter. This is post 494. Any code I have related to this post can be found here with the same numbering: https://github.com/nmaggiulli/of-dollars-and-data

3/10/2026

I recently saw this video of Alex Hormozi where he talks about a speaking event he attended. At the event, the speaker wrote $1,000,000 on a large whiteboard. Then the speaker asked someone in the audience how much they make and they replied, "$50,000 per year." So the speaker wrote $50,000 under the $1,000,000 and put a minus sign in front of it. Then the speaker said: Did you know that it's costing you $950,000 a year to not know how to make $1,000,000 a year? The point of the story is that our largest financial cost isn't our housing, food, or healthcare, but our ignorance on how to make more money. As someone who champions raising your income (instead of cutting your spending) to build wealth, I'm in full agreement. Growing your income is the most reliable way to have more wealth in the future. Every dataset I've seen suggests so.  But before we start growing our income, we have to believe it's possible in the first place. I don't typically discuss beliefs and mindsets because it's too difficult to prove whether one belief leads to better outcomes than another. On the other hand, I also know from personal experiences that beliefs matter. Much of the success I've had as a writer comes from a single belief I had in early 2017—I can write one blog post every week. I've followed that belief for over 492 weeks in a row and it's completely changed my life. I was reminded of this after reading Nir Eyal's latest book Beyond Belief. In it, Eyal argues that beliefs aren't fixed truths, but malleable tools we can use to our benefit. To determine whether a particular belief is helpful, Eyal challenges us to ask, "Is this belief serving me or am I serving it?" I loved this idea because it made me realize that many of our financial beliefs are either assets or liabilities. They either help us build wealth or hold us back. But, how do you know which is which? Beliefs that are liabilities actively harm you or prevent you from living up to your potential. Things like, "If I keep gambling, I'll eventually win big," or "I could never make $100,000 a year." Believing such things could ruin your financial life. On the other hand, beliefs that are assets help you become your best self. Things like, "The best time to start investing is today," or "I can overcome any financial difficulty." Believing such things will help you improve your finances over time. This isn't just conjecture either—academic research supports it as well. In an article from Avantis Investors, researchers explored the impact of "financial self-efficacy" (or the belief that one's actions can influence the future) and found that it was a direct predictor of financial stability. As the study notes: We document a strong negative correlation between self-efficacy and financial distress. Individuals with high self-efficacy, measured earlier in life, are subsequently less likely to default on outstanding loans or fall behind on bill payments than their peers with low self-efficacy. This is a prime example of a belief acting as an asset. Those who believe they can improve their financial situation achieve better results than those who don't. However, not all beliefs can be so easily categorized. Some beliefs masquerade as assets, but are actually liabilities. For example, take the belief that "The stock market always goes up." While this will make you lots of money during bull markets, it could do the opposite during a bear market. If you believe that stocks only go up, you could panic sell and miss out on future gains when they inevitably crash. Conversely, some beliefs that look like liabilities are actually assets. Consider the belief, "I'm not smart enough to beat the market." On the surface, it might seem defeatist. However, anyone who knows the data understands that it's actually an edge. Admitting that you can't outsmart the collective wisdom of millions of people makes it more likely that you'll outperform many of those who think otherwise. A belief doesn't actually have to be true to be an asset. What matters is whether it produces the right behavior. For example, believing that you can't beat the market may be false, but it frees you up to focus on growing your income (or other more profitable things) This is why beliefs are so important. They shape the way we see the world and the actions we take. And those actions ultimately determine our results. So if you want to change your results, you have to start by changing your beliefs. As Confucius once said: The man who says he can, and the man who says he can't, are both right. Given this framework, ask yourself, "Which of my financial beliefs are assets and which are liabilities?" I've done this for a handful of my financial beliefs, which I've categorized below: Asset Beliefs Income is the foundation upon which most wealth is built. Markets (as a whole) generate wealth in the long run. Consistency is more important than allocation or timing. Liability Beliefs There is no such thing as too much diversification. I'll never make it into Level 5 ($10M-$100M) without a drastic lifestyle change.  Illiquid investments aren't worth the returns. My beliefs that are assets help me to build long-term wealth—my career, my ongoing investments, and perseverance. Why aren't all of my financial beliefs considered assets? Because some of them are based on my preferences and not necessarily what would maximize my wealth. I'd probably be richer if I were less diversified, less liquid, and more open-minded in my career. But everyone has their preferences. Some people pay off their mortgage early even when they have a super low interest rate. I wouldn't do this, but some would. And that's fine. As the saying goes, "Personal finance is personal." Some of my beliefs are a huge benefit to me and others less so. I'm not 100% sure which is which, but I have my theories. Happy investing and thank you for reading! If you liked this post, consider signing up for my newsletter. This is post 493. Any code I have related to this post can be found here with the same numbering: https://github.com/nmaggiulli/of-dollars-and-data

3/3/2026

For the past few decades, being in shape was the ultimate "proof of work." You couldn't buy it. You had to earn it. Unless you had top 5% genetics, you had to build your physique through diet and exercise. But then something incredible happened. GLP-1 agonists (like Ozempic) hit the market and, overnight, a better body was only a weekly injection away. As a result, the old signal (being fit) became less valuable as it could now be acquired without the physical exertion. The same thing is happening with writing. Writing used to be a craft where someone toiled for hours thinking through a set of ideas before putting them out into the world. Today, that's no longer necessary. You can have an LLM generate seemingly infinite text at will. This explains why I saw more books published in 2025 than I can remember in recent years, especially by people who don't write regularly. Funny, huh? Of course, if you rely too heavily on AI, your "writing" won't be all that good. Either way, the written word is far less useful as a signal of thought or effort than it used to be. I call this signal collapse and it's happening again and again across different domains. For example, writing code used to be a reliable signal of skill and dedication. But with OpenAI's Codex and Anthropic's ClaudeCode, today that seems less true. AI doomer articles over the past few weeks haven't helped the situation either. On February 9, Matt Schumer released Something Big is Happening, and on February 22, Citrini released The 2028 Global Intelligence Crisis, which both went viral.  There's a lot I don't agree with in both articles, yet both seem directionally accurate. We are moving toward a future more reliant on LLM-intelligence, not less. And in that future, many signals that used to demonstrate value will be easier to fake. So, how do we display value going forward? What's the new proof of work? The New Proof of Work In a world increasingly dominated by low-effort, here are a few ways to signal the opposite: Leverage Your History: If you had a particular skill before it became commoditized, demonstrate that. Lean into it. By showing people that you did something before it was easy, it proves that you are willing to put in the work to master something. More importantly, it showcases that you have an actual interest in the field. If I had to pick between hiring a programmer who's been doing it for 20 years or one who started with AI a few years ago, I'd take the veteran every time. Though knowledge is becoming commoditized via LLMs, experience, taste, and judgement are still at a premium. This explains why top lawyer fees have skyrocketed even as AI usage explodes. Unfortunately, leveraging your history won't be helpful for those just starting out, but it showcases how you can go about building your career. Do Deep Work: Focus is a superpower and, increasingly, a signal. In an age of distraction, those who can spend weeks, months, or years on a single project will separate themselves from the pack. Cal Newport calls this idea Deep Work. You can demonstrate deep work by completing things that require sustained attention—like complex projects, novel content, or differentiated research. Most people can't work for an hour straight without checking their phone or logging into social media. But, if you can, then you'll have a huge edge over others in everything you do. In a world where our attention is being pulled in 100 different directions, the ability to focus on one at a time is an unfair advantage. Command Attention: Speaking of attention, if you want to stand out, command the attention of others. Because our world is so easily distracted, having people's attention is proof that you have created something valuable. That attention doesn't have to come from social media either. Having the attention of a local community or a niche group can be just as powerful as having it within a popular online space. You don't need to be a content creator, but if you can keep attention and build a community, you will undoubtedly be rewarded for it. I believe this will be especially true for in-person communities in 2026 and beyond. Embrace the Machine: If you can't beat 'em, join 'em. Instead of looking at AI as a foe to be avoided, treat it as a partner to help you level up. As I'm sure you've heard before, "AI isn't going to take your job—someone using AI is going to take your job." There's no better way to counteract this than to become the person who knows how to use AI. I'm not saying you need to become an AI expert, but you should know enough to expand your capabilities and keep up with the latest tools. Not only will this demonstrate that you take this seriously, but it also highlights that you can be adaptable. Don't just take it from me though. In Deep Work, Cal Newport highlighted the people that he thought would have an advantage in an increasingly digital economy (and this was from 2016!): In this new economy, three groups will have a particular advantage: those who can work well and creatively with intelligent machines, those who are the best at what they do, and those with access to capital. Newport's categories map well onto the ones above: Those who work well with intelligent machines = Embrace the Machine Those who are the best at what they do = Leverage Your History + Do Deep Work Those with access to capital = Command Attention I swapped capital with attention because, in many ways, attention is the new capital.  Whatever you decide to do, there's a structural shift happening in the economy that's going to take some time to play out. Some believe that this transformation will make labor obsolete. I'm skeptical, but some of the signs are there.  For example, the labor share of the nonfarm business sector in the U.S. has declined about 15% since the turn of the century. As you can see in the chart below, labor's share (of the nonfarm business sector) was basically flat from 1947 to 2001. But it's been on a gradual decline ever since: We are also seeing economic trends that rarely occur. Kelly Evans recently wrote about how there's a jobless boom—where the economy surges even as the labor market remains weak. This isn't normal. Historically, growth and hiring typically moved together. But today, that doesn't seem to be the case. For the past few weeks I've written a bit more about AI than you might expect from a personal finance/investing blogger. But there's a reason for it. Though I'd love to "stay on message" and write more posts validating Just Keep Buying, this would be doing you a disservice. Because, the truth is, your finances will be impacted more by your career than what the market does. Of course, the market matters, but your income matters more. How AI transforms your industry matters more. How you rise above signal collapse matters more. If I want to continue to be helpful, I must periodically address these issues. Though the signals of the future will continue to evolve, if we continue to evolve with them, we'll do just fine. Thank you for reading. If you liked this post, consider signing up for my newsletter. This is post 492. Any code I have related to this post can be found here with the same numbering: https://github.com/nmaggiulli/of-dollars-and-data

2/24/2026

What if I told you that getting a college degree provides no long-term financial benefits unless you get married? What if I told you that the typical single business owner is wealthier than most married couples who don't own businesses? Though both of these statements might seem far-fetched, statistically, both are true. For the past few years I've been obsessed with understanding how wealth is built in the United States. I even published a book about it. Despite this, my quest hasn't stopped. I recently ran a bunch of regressions on my favorite wealth dataset (the Survey of Consumer Finances) and I was a bit surprised at what I found. The punchline is that the two most common paths to wealth in the United States are: Marry a college graduate (or get married as a college graduate) Start a business Individuals in these two groups have more wealth than all the other groups I examined. But before I explain why this is true, let's start by discussing what predicts wealth in the first place. What Predicts Wealth? When it comes to predicting who has wealth and who doesn't, the first thing I considered was age. After all, age is highly correlated with wealth accumulation because older individuals have had more time to work, save, and invest their money. For my first model, I simply regressed U.S. household net worth against different age cohorts (<35, 35-44, 45-54, etc.) in the 2022 data to see how well age predicted wealth. Thankfully, the results fit my expectation and were all statistically significant. Model 1: Age As you can see in the table below, the model predicted that the median net worth for someone under 35 (the baseline) was $2,228.03. If we wanted to find the median net worth prediction for those aged 35-44, we would simply multiply this baseline value by the multiplier on that row: So, for those age 35-44, the model would predict a median net worth of $29,610.52 [$2,228.03 * 13.29]. For those age 65-74, the model would predict a median net worth of $231,314 [$2,228.03 * 103.82]. And so forth. Were these predictions close to the actual values? Sometimes. For those 65-74, the predicted median net worth was $231,314 while the actual median net worth was around $266,000. For those 35-44 the prediction was $29,611 while the actual was closer to $91,000. So hits and misses.  Thankfully, we can improve our predictions by adding more variables to the model. Model 2: Education The next thing I decided to add was educational attainment. After all, we've been told for decades that going to college is a financial home run. Well, is it? According to the data, yes. Those who received a college degree had a predicted median net worth that was 2.92x higher than those with only a high school education (the baseline). More importantly, this was statistically significant at the 1% level: The predicted median net worth of all U.S. households under 35 with a high school education (the baseline) was $1,961.85. For those with a college degree, that number shot up to $5,728.60 [2.92* $1,961.85]. While having more education can help you on the upside, having less of it can definitely harm you on the downside. As you can see in the table above, individuals with no high school education only had 13% (0.13x) as much wealth as their high school graduate counterparts. This was true regardless of age, since we already controlled for age in our regression. But we can improve this model even further by considering its structure. You have to remember that this is household wealth data. Because of this, we know that our results will be skewed if there is more than one person in a household. After all, a married couple is likely to have two earners compared to only one for a single member household. To adjust for this, let's add marital status. Model 3: Marriage When we add marital status to the model, we see a few big things. First, the multiplier on marriage is 27.15! This means that a married couple has about 27x more wealth than their single counterparts with the same age and education status. Second, because of this huge marriage multiplier, the baseline predicted median net worth (for single high school graduates under 35) is now only $356.63: Unfortunately, marriage explains a lot of the net worth variation in the data, and it's statistically significant. In addition, the multiplier on a college degree dropped from 2.92 (in Model 2) to 2.21, though it's still statistically significant. This got me thinking, what if we adjust for the interaction of marriage and educational status. This would let me know whether it's just a college degree that impacts wealth, whether it's just marriage, or whether it's a combination of the two. Model 4: Education * Marriage When we include the interaction effects of education and marriage in the model, something shocking happens—the wealth multiplier on having a college degree declines below 1 and is no longer statistically significant! I've highlighted both of these changes in the table below. As you can see, the multiplier on a college degree dropped from 2.21 (in Model 3) to 0.89 while losing all statistical significance: This means that, statistically, the wealth benefit of having a college degree is near zero...unless you get married. Think about that. Someone with a college degree who isn't married has the same predicted median net worth as a single high school graduate.  We know that college degrees are correlated with higher incomes, but those gains are typically offset by debt and a four-year delay into the workforce. While high school grads can start building wealth at 18, many college grads don't start until 22 and are already a bit behind (i.e., in debt). This suggests that one of the primary benefits of college isn't actually the skills, but the fact that you get to meet lots of people and (hopefully) pair off with one of them at some point in the future. This dual high-income household formation is what helps to create this wealth premium. This isn't just conjecture either. There's academic research showing how assortative mating can lead to higher income inequality (which also contributes to rising wealth inequality). One writer even argued that this dynamic creates an informal American caste system: The primary caste division that I’m pointing to is often called “the Professional Managerial Class (PMC),” and that’s a good enough label for the central division. Essentially, we see roughly ~70-80% of the population that largely don’t have undergrad degrees, are fatter, shorter, have fewer marriages, work fewer hours per week, and own less real estate. And then we see the PMC, which has undergrad and grad degrees, high marriage rates, high home ownership, taller and fitter men, longer work weeks, and skinnier and more educated women. What's crazy is how extreme this effect is in the data. If you are a single college graduate, your net worth is not statistically different from a single high school graduate. But get married and it's likely to be 35.6x higher! We get to that value by multiplying the college degree multiplier (0.89) by the marriage multiplier (8.19) by the college degree*marriage interaction multiplier (4.89) [0.89*8.19*4.89 = 35.6].  In other words, if a high school graduate gets married, their predicted wealth increases by 8.19x (the marriage premium). But if a college graduate gets married, their predicted wealth increases by 35.6x, over 4x more. I know what you might be thinking. How much of this college * marriage effect is just rich kids marrying other rich kids? Well, we have a solution for that, and it's called adjusting for inheritance. Model 5: Inheritance When controlling for households that had any inheritance, the model suggests that predicted wealth increases by 4.98x for those who had one (highlighted below). Unsurprisingly, inherited wealth is a predictor of current wealth: But, even after adjusting for inheritance, our total college marriage multiplier still exists at 28.3x. Once again we get to this by multiplying the college degree multiplier (0.72) by the marriage multiplier (7.00) by the college*marriage interaction multiplier (5.62) [0.72*7.0*5.62 = 28.3]. Though this overall multiplier declined from 35.6x (in Model 4), it demonstrates that there's still a real benefit to being married to a college graduate (or being a married college graduate yourself). But, marrying a college graduate is just one proven path to wealth. The other is business ownership. Model 6: Business Ownership When we include whether an individual owns a private business in the model, a new (statistically significant) high wealth contender emerges (highlighted below): This new model suggests that a single business owner would have about 9.9x the wealth of a single high school graduate who doesn't own a business. Once again, this is after controlling for age, inheritance, and education. Additionally, after adding the effect of business ownership, our model now only predicts a 19.1x wealth increase for being a married college graduate [0.60*5.76*5.53 = 19.1] relative to a single high school graduate (the baseline). This is a big decrease from 28.3x (in Model 5) because that model was including the wealth impact of business ownership itself in that college educated marriage premium. By adjusting for this, this premium now shows the wealth impact of being married and college-educated for those that do not own businesses. But there's one final adjustment we should make to improve the model further—looking at the interaction between business ownership and marriage itself. Model 7: Business Ownership * Marriage When we add the interaction of marriage and business ownership, a few big things change. First, the premium on being a single business owner sky rockets to 36.5x from 9.9x in Model 6 (highlighted below). Second, the interaction between being a business owner and married is less than one, which means that the predicted wealth boost of getting married overwhelming goes to non-business owners. Lastly, the college degree premium has decreased further (and remains statistically insignificant): Putting it all together, this model (which is our most accurate one yet) highlights the two primary paths to wealth—being married to a college graduate (or being a married college graduate yourself) and business ownership. In this final model, the overall married college graduate premium is 22.2x [0.54*6.44*6.39 = 22.2x]. So while a single college graduate shows no statistically significant difference in wealth (compared to a single high school graduate), a married college graduate is expected to have 22.2x more net worth! The other high wealth path is business ownership. Single business owners tend to have 36.5x more wealth than their single, non-business owner counterparts (from the multiplier in the table above). How does marriage impact this? It increases predicted wealth, but only by an additional 16% (1.16x). This 1.16 comes from the marriage premium (6.44) multiplied by the business owner*marriage interaction multiplier (0.18) [6.44 * 0.18 = 1.16]. Taken together, married business owners are predicted to have 42.3x more overall wealth [36.5*6.44*0.18 = 42.3] than single, non-business owners.  This is an intriguing result because it suggests that while getting married does provide some wealth boost to business owners (1.16x), it's nowhere near the wealth boost we see for college educated, non-business owners (22.2x) relative to their single counterparts. Business ownership is such a powerful wealth generator on its own that the marriage bonus doesn't provide as much benefit as it does to a college graduate. So, if you aren't going to be a business owner, the next best bet for getting wealthy is marrying a college graduate (or becoming a college graduate and getting married). Of course, getting married by itself isn't necessarily the cause of the increased wealth. Though being married can lead to cost savings (e.g, shared expenses, tax benefits, etc.), what seems more likely is that the type of people who get married have other characteristics that are also positively correlated with building wealth. For example, if you have a high income, you will be more attractive on the dating scene and more likely to get married, all else equal. So what's important isn't just getting married, but being the type of person who gets married. Because these types of people tend to be wealthier than their non-married counterparts for a variety of reasons. But is there more going on with this story than meets the eye? Let's see as we wrap things up. Is It All Survivorship Bias? While I would love to tell you that getting married to a college graduate or becoming a business owner is your guaranteed path to wealth, unfortunately, no such foolproof plan exists. Why? Because of survivorship bias. When we see that married college graduates and business owners are wealthy, we are only looking at the successful marriages and successful businesses in the data. What we have overlooked are all the divorced college graduates and failed business owners who should bring the median values downward, but don't. The mechanism of failure causes this because as soon as you fail you leave the desired group. Divorce makes you single and, therefore, only impacts the overall wealth statistics of single people. A failed business turns you into a "non-business owner" and only impacts the overall wealth statistics of non-business owners. Do you see the problem? But it's not all survivorship bias. How do I know? Because if it was, we would see some of it in the data. There would be lots of struggling business owners who failed to build wealth. There would be lots of married people who failed at it as well. But because the effect sizes are so strong, it suggests that something real is going on here that helps build long-term wealth. This doesn't mean that you should get married (as a college grad) or that you need to start a business. But making choices that are more like what those people do is likely to benefit your finances for decades to come. Thank you for reading! If you liked this post, consider signing up for my newsletter. This is post 491. Any code I have related to this post can be found here with the same numbering: https://github.com/nmaggiulli/of-dollars-and-data

2/17/2026

Right now many people are debating why the U.S. housing market is broken. Some blame interest rates. Some blame prices. Some blame zoning laws. While the truth is a mix of all of these factors, there's one thing that no one seems to agree on—supply. Does the U.S. actually have a housing shortage, or is something else going on? When Supply is Not Supply While many believe that the U.S. housing market has a supply problem, this view isn't universally shared. For example, Jon Brooks, a real estate analyst, recently tweeted the following: Everyone keeps saying America has a “housing shortage.” It doesn’t. Divide total homes by population and you get this: We’ve never had more housing per person than we do right now. The problem isn’t supply. It’s prices. Total units divided by population isn't the best measure of this since U.S. households have been getting smaller (i.e. fewer married couples, fewer children, etc.) over time. But this isn't even the primary issue here. Brooks' argument overlooks a more important point—many of these housing units aren't in areas where people actually want to live. Housing units in unsafe areas or locations with a lack of economic opportunity aren't ones that people want. Nowhere is this more true than in major American cities (particularly in the Midwest) that saw both increased crime and a declining economy over the latter half of the 20th century. Peter Banks, President of the Boyd Institute, summarized this trend well: Between 1960 and 1992 America went from less than 9,000 murders a year to a peak of 24,000. Other crimes such as burglary underwent a similar process and increased by a factor of nearly 5. A disproportionate share of this growth occurred in the old industrial cities of the Northeast and Midwest, which were also entering a period of economic decline during that era, the result of a weakening US industrial base. Because of this dual shock of massively elevated crime and a weakening of the industrial sector, many of these cities entered into what can only be characterized as a death spiral. St. Louis, Cleveland, and Pittsburgh each also lost roughly half their populations, and even cities like Chicago (which managed to weather the storm relatively well) shed nearly a third of their residents. While "where people want to live" is subjective, areas with low crime and good economic opportunity tend to be universally valued. As a result, these are the only areas where housing supply truly matters.  But the current supply of good housing is just one issue. Where new housing is being built is another. Location, Location, Location Even if you agree that there's a lack of "good" housing in the U.S., the data suggests that new home construction isn't helping as much as we'd like. Unfortunately, there's a geographic gap between where homes are being built and where people actually live. This 2024 report from the Office of the Comptroller of the Currency (OCC) highlights how the areas with the highest housing production tend to be in the Southeast, South, and Mountain West (Quintile 5 in orange): Quintile 5 only contains 22% of the U.S. population, but had half of the single family home completions in 2023! More importantly, quintiles 1 and 2, which contain heavily populated areas like New York, California, and Chicago, hold 40% of the U.S. population, yet only had 34% of all single family completions. In other words, we're building more housing in areas where there aren't as many people (Quintile 5) and less housing where there are lots of people (Quintiles 1 & 2).  I don't blame the builders though. As much as they want to build more housing, many times their hands are tied by local regulations. Why Zoning & Interest Rates Keep Supply Offline In places like New York and California, strict zoning regulations limit the supply of housing. When builders are forced to adopt certain standards, they don't have the freedom to build any kind of home that they want.  Nowhere is this more true than with the "starter home" (i.e., homes that are 800-1,200 square feet in size). As this chart from Bankrate shows, the median new home size in the U.S. grew from 1,525 square feet in 1973 to a peak of 2,467 square feet in 2015 before declining to 2,146 square feet by 2024: While one might argue that larger home sizes are a matter of consumer preference, the real issue seems to be structural in nature. As Patrick Tuohey wrote earlier this year for the Better Cities Project: Builders respond to the financial and regulatory environment cities create. Minimum lot sizes, setback requirements, parking mandates, and other local rules often make small homes difficult to build legally, let alone profitably. After the Great Recession, many builders also shifted toward higher-margin projects to reduce risk, reinforcing a preference for larger houses aimed at wealthier buyers. The result is that the traditional starter home—a roughly 1,000-square-foot house on a modest lot—has become financially implausible in many markets. Even when builders want to offer smaller units, land costs and zoning constraints push them toward higher price points. Since builders tend to only construct bigger homes, this means that many households will need to delay their first home purchase until they can afford such a home. These delays in household formation are also showing up in the data. As Freddie Mac's November 2024 housing report concluded: If housing costs as measured by rents were more affordable, we estimate that the U.S. would have added 1 million more households with most of the growth coming from younger households. That is 1 million households that are staying at home or living with a roommate that wouldn't have otherwise. That's how bad the U.S. housing market is today. What makes this dynamic even worse is that 30-year mortgage rates are still hovering around 6%. As a result, many existing homeowners (with lower rates) are unwilling to move and accept a higher rate. This keeps their housing supply locked up longer than normal. This problem is particularly pervasive among older adults, who likely would have downsized after their children moved away. However, since they've decided to stay put, their housing remains underutilized. This keeps younger families from moving into these larger homes that better fit their current needs. Whether we look at the lack of good supply, increased underutilization, or elevated interest rates, the U.S. housing market has seen better days. However, there are signs that the market may be near a turning point. A New Hope for U.S. Housing? While it's quite clear that the U.S. has a housing supply problem, there are a few things that could help to resolve it. First, more homeowners are borrowing at higher interest rates. As Realtor.com reported, as of Q3 2025, the share of mortgages with an interest rate above 6% surpassed the share of mortgages below 3%: This is good news because it shows that borrowers are becoming desensitized to higher rates, which could signal a new normal across the housing landscape. Second, sellers seem to be more willing to sell their homes than in previous years. As the Kobeissi Letter reported: Home sellers outnumbered buyers by 47.1% in December 2025, the largest gap since Redfin data began in 2013. While some might look at this as a bad thing, it actually signals a big shift in seller behavior. With more people trying to sell their homes, it will put downward pressure on prices and start to unfreeze the real estate sector. Lastly, President Trump recently nominated Kevin Warsh to chair the Federal Reserve. Warsh has commented on how he wants to lower interest rates—a stance that aligns with Trump's public comments on the matter. While lowering the Fed Funds Rate isn't guaranteed to drop mortgage rates, they're going to try. And, if they succeed, then we will see a lot of supply enter the market. Of course, there will be more demand as well, so it's anyone's guess whether lower rates will "fix" the housing shortage.  Though U.S. housing has been in a bind for the past few years, recent developments suggest that things are starting to give. Borrowers are getting used to current rates, more homeowners are trying to sell, and policymakers are signaling a push to lower interest rates. While no single factor will revive the U.S. housing market on its own, maybe a combination of them will. Until then, thank you for reading! If you liked this post, consider signing up for my newsletter. This is post 490. Any code I have related to this post can be found here with the same numbering: https://github.com/nmaggiulli/of-dollars-and-data

2/10/2026

Let's turn the clocks back a little over a year. Going into 2025, the consensus view on markets was: U.S. Exceptionalism: The U.S. is the only equity game in town. Europe and the rest of the world had fallen behind on AI and tech innovation. Lower Rates: Investors expected rate cuts and, by extension, much lower interest rates in the near future. The End of Inflation: The battle against inflation had been won and price stability was a guarantee. Unfortunately, all three of these things didn't turn out as planned. Over the last year, U.S. stocks underperformed international stocks, rates dropped less than expected, and inflation proved to be stickier (and higher) than we realized. Of course, things don't always go according to plan. But when we make major financial decisions based on the consensus view, they can backfire. As Mark Twain once said: It ain't what you don't know that gets you into trouble. It's what you know for sure that just ain't so. Why does this happen? Why does the consensus view fail more often than we might expect? Why Does the Consensus View Fail? There are a few key reasons why markets sometimes get it wrong: Recency Bias: We think the future will be like the recent past. When U.S. stocks dominated on the global stage in 2024, many investors believed the same would continue into 2025. As a result, U.S. stocks were bid up and priced for more of the same. Unfortunately, things didn't play out that way and U.S. stocks struggled relative to international stocks. The problem with thinking the future will be like the recent past is that it skews the risk-reward tradeoff. When everyone expects the status quo, assets are priced to reflect that. Therefore, any deviation from those expectations can cause investors to rush for the exits.  Chaos Theory: We can imagine the future all we want, but no amount of mental simulation will ever compete with the randomness of nature. As chaos theory has demonstrated, even simple systems with simple rules will behave in unpredictable ways. Now imagine what happens with complex systems with complex rules. Morgan Housel said it best: "We are very good at predicting the future, except for the surprises—which tend to be all that matter." And these surprises can lead to the most unlikely of outcomes. For example, who thought that gold would soar and Bitcoin would falter with rising geopolitical tensions? Not me. But that's exactly what's happened this year. I thought Bitcoin was "digital gold," but that doesn't look to be the case anymore. I was surprised by some things that transpired recently and it's changed my view on the asset class. I won't say much more other than I have a stop loss set at a much lower price. If it triggers, I'm out. It was good while it lasted, but I no longer need this asset class to reach my financial goals. The Stability Illusion: The reason the consensus view sometimes fails is because it's often right. The world typically changes slowly. So betting on the world not changing can be a profitable strategy. For example, there was a trader on Polymarket (the event prediction market) who bet "No" on almost everything and made $2M in profit. If you believe that "nothing ever happens," you're usually right. However, this can create a false sense of security. Because when we bet on stability, it's easy to get blindsided by instability. As Vladimir Lenin once said: There are decades where nothing happens and weeks where decades happen. Whether it's recency, chaos, or the illusion of stability, the consensus view fails more often than we think. So, what's the solution? The Antidote to Certainty Given that the consensus view can be wrong, here are some ways to counteract this uncertainty in your financial life: Diversification: I know how cliché this sounds, but diversification is something you should practice both inside and outside of your portfolio. I've paid the price for owning international stocks for years, but for the first time since 2012, my portfolio is outperforming the S&P 500. This is the upside of diversification I've been waiting for. Outside of your portfolio, you should try and make diversified financial decisions as well. If you are convinced that rates will drop in the next year, don't bet big on such an outcome. We all know someone who took out a variable rate mortgage because they were "certain" that rates would drop. Well, they are feeling the pain now that they can't refinance as planned. You can diversify across time, across geographies, within your career, and much more. The key is to spread out risk so that no single decision is a point of failure. Anti-Optimization: Instead of trying to predict the future based on what the market thinks, be okay with suboptimal outcomes. I've previously argued that you shouldn't try to optimize your life, and I believe this applies here as well. When someone makes an all-or-nothing financial decision, they are trying to create an optimal outcome. They are trying to avoid leaving money on the table. This is completely natural, but it can also drive you mad. If you're an optimizer, it's easy to always be second-guessing yourself. But that's no way to go through life. The better approach is to accept that you won't make the best choice and let the chips fall where they may. This doesn't mean to be stupid about your decisions, but don't obsess over them either. When you admit that you don't know the future, it's a lot easier to deal with it when it doesn't go as planned. Ultimately, the only antidote to certainty is to embrace uncertainty. It's to prepare for a future that we can't yet imagine. We do this through diversification and accepting that we won't always get it right. After all, these are the only things we can control. If you do this right, you won't be alarmed when the consensus view turns out to be wrong. Because you planned for things to not go according to plan all along. Thank you for reading! If you liked this post, consider signing up for my newsletter. This is post 489. Any code I have related to this post can be found here with the same numbering: https://github.com/nmaggiulli/of-dollars-and-data

2/3/2026

I recently saw this tweet from Pieter Levels arguing that inflation is actually much higher than people think because of decreasing product quality (and not just increasing prices): I think we're 100% in some kind of hyperinflationary state But the hyperinflation is hidden from prices and instead shows up in the extreme decrease in quality of almost every product and service We're in an asset boom where stock prices look like they're growing but they just show the underlying value or currencies is rapidly dropping That's why the same product or service you bought 2 years ago is now twice the price but more than half the quality, so essentially became 4x more expensive You can't measure this inflation easily because quality is subjectively perceived and not included in inflation data (how would you?) but it's happening for sure I wouldn't go as far to say we are in a "hyperinflationary" state, but I see his point. Last year I wrote about the death of the Amex lounge and how the explosion in Level 4 ($1M-$10M) wealth has led to reduced quality across many traditional "upper middle class" services. One area where I've seen this is the restaurant industry. I remember going to one of my favorite steakhouses and ordering a ribeye and was delighted to see the price hadn't gone up. But when my steak came out I was shocked—it was by far the smallest ribeye I've ever been served. I looked down at the plate and couldn't believe it. What is this? A ribeye for ants? I didn't complain but haven't been back since. My wife had a similar experience at one of those all-you-can-eat Brazilian steakhouses. After sampling a few of the meats making their rounds, she asked for ribeye (her favorite). They told her it was "cooking" and when it finally came out 45 minutes later, there was one round of it and then it never came back. Over the course of her 2 hour dinner she got one slice of ribeye. So much for all-you-can-eat, but hey, at least the price didn't increase, right? While both of these examples are anecdotal, they illustrate a more pernicious form of inflation—reduced size or quality. Technically, the BLS does adjust for shrinkflation, or when the size of a product decreases even as the price stays the same. You may have noticed this with shrinking candy bars and paper products over the last few years. But the BLS doesn't adjust for what's being called skimpflation, or when a business skimps on the quality of their product or service while keeping the price the same. If you're a big consumer of chocolate bars, you've probably noticed a difference in taste recently as manufacturers swapped out cocoa for cheaper alternatives. The same thing happened with salad dressing as some producers reduced the amount of oil in their product to save money. The reduction in service quality may be even worse than the reduction in product quality though. The American Consumer Satisfaction Index (ACSI) Restaurant and Food Delivery 2025 study found that customer ratings dropped across every category for full-service restaurants from 2024 to 2025: This 5% average drop in service quality (across all categories) occurred even as restaurant prices increased by about 5% in 2025. While a drop in service quality isn't the same as an increase in price, the end result is—you get less for your money. As a result, you can see how the true inflation rate in 2025 is higher than what's officially reported. Why does skimpflation exist? Because it's easier to conceal reduced quality than higher prices. When a restaurant increases their prices, regulars notice immediately. But when they lay off a busboy and the food takes a few minutes longer to come out, it's not immediately obvious. What makes skimpflation even worse is that it's not tracked in the official data. When a company replaces their customer service team with AI chatbots, the price of the service is unchanged. But now you have to spend 10 minutes fighting with a chatbot instead of 1 minute with a human who can solve your problem. Your price is the same but your cost is higher. While shrinkflation was found to be a negligible part of overall inflation, skimpflation may not be. My guess is that skimpflation could be 5% per year at worst in some industries. What is it across the entire economy? I don't know, but let's assume it's half as bad, so 2%-3% per year. That takes the experienced inflation rate closer to 5%-6%. That's nowhere near hyperinflation, but it's a bit higher than what's being reported (~3%). I don't think this is some grand conspiracy either, just rational economic actors responding to market forces. Consumers are tired of price increases over the last few years and companies know this. So their best option is some shrinkflation or skimpflation rather than raising prices further. Is skimpflation proof of widespread dollar debasement? Not necessarily. Yes, the U.S. dollar is losing value. That's not up for debate. But, it's always losing value. The only time it didn't lose value in the last century was during The Great Depression. And who wants to go back to that? I think the real issue is that we've grown accustomed to 2% inflation over the past few decades. So when inflation comes in higher than that, some people get carried away and assume the dollar is hyperinflating. From 1913 to 2025, USD inflation averaged a little over 3% per year. We are slightly above that now (if you include skimpflation). But to jump from a 5%-6% inflation rate to hyperinflation is a stretch. Don't get me wrong, too much inflation is a bad thing. It's not good for consumers or markets. No one likes the instability. But there's a big difference between elevated inflation and hyperinflation. I just hope that none of us ever realize it first hand. Thank you for reading. If you liked this post, consider signing up for my newsletter. This is post 488. Any code I have related to this post can be found here with the same numbering: https://github.com/nmaggiulli/of-dollars-and-data

1/27/2026

One time I saw someone ask James Clear, the author of Atomic Habits, "What's the point of writing a book when there are already so many books out there? Isn't the market oversaturated?" Clear agreed that this was true if your book wasn't any good. But, if your book is good, it won't matter. As he concluded, "There's always room for quality." Anytime someone asks me whether they should start a blog, write a book, or launch a business, I'm reminded of Clear's idea. After all, he's right. No one complains about having more quality in the world. The existence of Denzel Washington doesn't make watching Daniel Day-Lewis less enjoyable. Listening to Taylor Swift doesn't make listening to Beyonce worse. Warren Buffett's wisdom doesn't detract from Jack Bogle's. Greatness never crowds out greatness. But this isn't how most people view the world. They see the world as zero-sum. They see it as full of competition. In some circumstances, this is true. If two artists hold a concert on the same night, fans of both can only choose one of them. But how often is this the case? Rarely. When you create something great, it almost never detracts from what others create. For example, as a financial writer you might argue that Morgan Housel, Christine Benz, and Ramit Sethi are some of my competition. But this couldn't be further from the truth. As I've argued before, these writers all increase interest in the financial space and help me gain more readers, not lose them. My career has undeniably benefitted from my fellow writers. Do you want to know who my real competition is? Netflix. TikTok. Instagram. My competition is anything pulling people away from reading financial content (or reading in general). But I can't change that in any significant way. I can't change the global trends in reading and video consumption. What I can change is the quality of the work I produce. The same is true for you. No matter what you do to support yourself, you have direct control over the quality of your work. You have control over its speed, its accuracy, and its perception. Is it timely? Is it error-free? Do people enjoy it? You can answer these questions whether you're a cashier or a CEO. What's important isn't what you do as much as how you do it. Because how you show up in your work bleeds into every other part of your life. I know it's cliche, but the saying is true—how you do one thing is how you do everything. So, how do you change the way you work to increase quality? Let's find out. How To Increase "Quality" When it comes to increasing the quality of your work, there are two ideas I'd recommend focusing on: Seasonality: Go through periods of high intensity, followed by recovery Editing: Remove distractions to focus on the most important things My friend Jonathan Goodman is launching a book today called Unhinged Habits that tackles both of these topics wonderfully. On seasonality, Goodman argues that we should embrace cycles of intensity and recovery rather than trying to maintain constant balance. I witnessed the benefits of this approach when writing The Wealth Ladder over an extremely busy six-month period in 2024. During that time, I was working every night and weekend trying to fit years of research into my new framework. I didn't realize it at the time, but this was when I leveled up the most as a writer. Though I had been blogging weekly for years, it was when I was immersed in writing books that I saw the greatest growth in my skills. Goodman explains why: Long-term consistency and stacking habits is a great way to make sure you do stuff like floss your teeth more often. But without intensity (visits to the dentist), you’ll never earn a pearly white smile. Intensity is for gaining. Consistency is for maintaining. I also love this approach because it allows me to relax more when I'm not working. Previously I'd have some guilt during periods of extended leisure. But since embracing seasonality, I can now enjoy my unproductive time much more because I know it's essential for my mental recovery. Yet, going all-in on seasonality first requires one thing—editing. As Goodman notes, “Great editing ... prides itself on subtraction, not addition. On discipline via omission.” He argues that we should remove anything that is distracting us from our ultimate goals. Not necessarily forever, but for now. I've used this to great effect. Going into 2026 I've said "No" to more things than ever before. I did this not only to prioritize what's most important in my career, but outside of it too. With my first child on the way, editing out distractions allows me to shift my priorities to those things that truly matter. Such prioritization is necessary to help clarify what you actually care about. And when you work on what you care about, the quality of your work naturally increases. The academic literature supports this as well. In a 2014 study, researchers conducted a 40-year meta-analysis of motivation styles and performance and concluded: ...intrinsic motivation predicted more unique variance in quality of performance, whereas incentives were a better predictor of quantity of performance. In other words, how much you personally enjoyed something (intrinsic motivation) was a higher predictor of quality than how much you were paid to do it (incentives). Money didn't produce higher quality, caring did. As I discussed earlier this year, the evidence is overwhelming for focusing on intrinsic motivation.  And it applies everywhere in your life too. Show a genuine interest in something and watch the quality of it improve. It could be your work, your health, your relationships, and more. If you combine this intrinsic motivation with intentional seasonality and editing, better quality is the natural byproduct. And in a world of increasing AI slop, true quality is what we need. After all, there's always room for more of it. Thank you for reading! If you liked this post, consider signing up for my newsletter. This is post 487. Any code I have related to this post can be found here with the same numbering: https://github.com/nmaggiulli/of-dollars-and-data