We are taking a short break from our Safe Withdrawal Rate Series (see the latest post here) to look into some pretty fascinating data we came across the other day. There’s a small place on earth with rampant wealth inequality. If you had just one single dollar in your name you’d be worth more than the entire bottom 27% of the wealth distribution combined. The bottom half of the population owns only about 8.6% of all wealth, while the richest 10% own 40% of all wealth, and the richest 20% own about 62% of all wealth.
Despite the wealth inequality, there is surprising harmony. There’s no call for building walls. And no call for redistributing the “ill-gotten” profits of “evil capitalists” either. There is no envy! Folks in the lowest wealth bracket would regularly compliment their richer counterparts and say “Geez, you are rich. Good for you!”
Where on earth is this place?
It’s not a country, not a state and not a city either. It’s a sample of personal finance bloggers who volunteer their net worth figures on their blogs. J Money’s website Rockstar Finance compiles those numbers (I presume automatically through RSS feed) and the current ranking is here:
RockstarFinance Net Worth Tracker
We took a snapshot of the data on 2/19/2017 when the database had 170 Net Worth numbers (and since then the number of bloggers has grown to 196!!!). Here’s what we learned from the data:
- The net worth numbers range from under -$500,000 (Red Two Green, and yes, that’s a “minus”!) to +$5,000,000 (Dr. Dahle’s White Coat Investor).
- There are 29 millionaires, about 17% of the bloggers. But 13 bloggers, or about 7%, have a negative net worth.
- The average net worth is about $547,000, while the median is just under $266,000. According to the 2013 Survey of Consumer Finances, the U.S. average net worth per household was pretty close, at $534,600 (likely a bit higher now, but 2013 was the last available year with data), and the median was quite a bit lower at $81,200,
- The Gini coefficient is about 0.61. The Gini is a measure between 0 and 1, where 0 means exactly equally distributed wealth. The Gini would be 1.0 if one single person owns everything and everyone else owns nothing, see here for more details. For most developed countries the Gini is between 0.55 and 0.80, with the U.S. right at the upper end. So, the RockstarFinance sample is a bit below the inequality here at home but about in line with a lot of developed countries and actually a bit higher than in some countries like Japan, Spain, South Korea, Ireland, or Italy. Source: Wikipedia, accessed 2/19/2017.
How come there is so much inequality? Very simple, this is a snapshot of people at different stages in their lives. Some are just starting with zero or even negative net worth (student loans!), some are halfway toward their goal of FIRE (Financial Independence/Retire Early) and some have made it already with a net worth in the seven figures. That alone creates a large degree of inequality, in fact, as much inequality or more than in some countries.
There is probably some envy from outside the community. Among the many examples, we remember the post by Freedom with Bruno after they were featured in a story on MSN and experienced some backlash from the doubters. But I have never seen envy within the FIRE community. For the most part, we all do our own thing, save aggressively and exchange ideas with other bloggers along the way. The bloggers who have already achieved FIRE are mainly a source of inspiration rather than a target for envy. Notably, J Money himself encourages everybody to “learn from those in advanced stages.”
How representative is the Rockstar Sample?
Critics could argue that any sample with voluntary self-reporting is not very reliable. People could exaggerate or completely make up their net worth. So let’s apply two simple tests to see how reasonable and representative the net worth numbers in the RockstarFinance sample are. Test 1 is a simple tool from forensic accounting (yes, there is such a field!) and Test 2 compares the RockstarFinance sample with the ERN family finances over time.
Test 1: Benford’s Law
Benford’s Law sounds so preposterous that most people who hear it for the first time will think you’re trying to fool them. It sounds so wrong that yours truly, Mr. ERN, has actually won several bets with folks who were oblivious to this well-known result from statistics. The law says that there are a lot of circumstances where the leading digit (that is, the first or leftmost digit) of numerical data is far from equally distributed. Whether it’s macroeconomic numbers, stock quotes, numbers in accounting statements and tax returns, and many other variables, the first digit will not show up with an equal 11.11% probability for each of the numbers 1 trough 9. Instead, the digit “1” is by far the most common with over 30% probability, while the number “9” has only less than 5% probability. The “1” is 6.5 times more frequent than the the number “9”. How crazy is that?!
The explanation for this phenomenon is that whenever numbers grow exponentially then in order to grow from 100 to 200 the variable has to double, while from 200 to 300 it has to grow by “only” 50%, and finally, to grow from 900 to 1,000 it has to grow by only 11.1%. So, naturally, a lot of variables spend more time with a 1 as a leading digit than a 9. Try it out at home: Start with any initial value, grow the variable by some percentage and count how many times the different leading digits show up before the variable grew by a factor of 10:
Why am I bringing up Benford’s Law? It’s a great fraud detection tool. Because people who make up numbers are likely to spread out the first digit more equally than the skewed distribution implied by Benford. Benford’s law is used in forensic accounting and by the IRS as well. So without trying to become an accomplice in accounting fraud or tax evasion, make sure you get the leading digit distribution right if you ever have to “make up” numbers. Or play it safe and avoid taxes the legal way, compliments of Go Curry Cracker!
So, let’s see if the bloggers’ net worth numbers follow Benford’s Law. I simply counted the frequency of the leading digits (including negative) and, lo and behold, the leading digit has pretty much exactly the distributions predicted by Benford’s Law. The “1” shows up with a probability of around 30%. There are a few deviations along the way (4 vs. 5 and 6 vs. 7) but they are minor and likely due to the small sample size. But it’s still true that the “1” and “2” show up significantly more often than an “8” or “9”.
So, Benford’s Law is alive and well in the RockstarFinance blogger sample (for the math and statistics geeks: the standard statistical tests cannot reject the hypothesis that the observed distribution is different from Benford’s, at any reasonable confidence level). We can’t prove that everybody is truthful about their net worth numbers but at least there isn’t any blatant evidence for manipulation. It passes a simple smell test from forensic accounting!
For full disclosure, though, there are a lot of instances where Benford’s Law does not apply, namely when variables are (mostly) equally distributed by construction, such as Social Security numbers, ZIP codes, telephone numbers, etc.
Test 2: ERN family finances
If the vast inequality in the RockstarFinance sample is due to observing folks at different stages of their lifecycle, then how about we compare the Rockstar snapshot with the experience of the ERN household over time? Specifically, let’s look at ten snapshots of the ERN family household net worth over time. The first window starts when Mr. ERN turns 18, and the last window ends on January 31, 2017. The additional eight snapshots in between are taken at equal intermediate points in time. All net worth numbers are adjusted for CPI inflation to make numbers comparable across time.
In the figure below we compare the blogger net worth numbers (averages in the 10 deciles) with our 10 snapshots. To make the numbers easier to compare we scaled the highest observation to 100.
By and large, the ERN family net worth path is not too different from the blogger distribution. There are some differences, of course, especially the fact that we have never had any sizeable debt. Mr. ERN also got a late start in the job market after spending a lot of time in graduate school, so the third and fourth snapshots are significantly behind the blogger figures, not in dollars but percentages! In contrast, the ERN family’s ninth decile seems quite high because of the post-crisis equity market surge (remember the stock market in 2012-13?) combined with some pretty nice home equity gains, while the stock returns and home equity gains have slowed quite a bit in 2014-2016. What’s more, we calculate the Gini coefficient in our own 10 snapshots as 0.62. How amazing is that? That’s almost the same as the blogger Gini coefficient and it’s also in the same ballpark as some countries’ Gini coefficients.
This exercise goes to show that a large portion of wealth inequality is simply due to life-cycle patterns in savings and asset accumulation. Imagine all Americans went through life as little ERN household clones. Scary thought, I know, but bare with me for this thought experiment! They all start at age 18, essentially penniless, work through college and graduate school, get a real job and save towards FIRE. Aggressively! Then at any point in time, we observe exactly the wealth distribution cited above (abstracting from deaths and immigration for simplicity) with 10% of the population falling into each of the ERN net worth buckets. There is no intra-cohort wealth inequality but massive wealth inequality across cohorts. Despite the inequality, nobody is unhappy because every cohort will move to higher net worth levels eventually. Just like in the blogging community there is no need for envy.
Conversely, had we succumbed to the consumerism that befalls many of our countrymen and kept a constant net worth of zero over all those years by spending all of our disposable income, the Gini would have been exactly 0.00. Perfect wealth equality, but not something we’d recommend!
Whether or not you liked today’s post, try to spot Benford’s Law in the data. And be almost guaranteed to win a bet about the “1” being way more likely than the “9” as the leading digit. Also, just to be sure, we don’t want to belittle inequality. There is still the issue of discrimination that holds back some people. Or dumb and lazy people ending up richer than smart hard-working folks. But we were astonished by how much inequality can emerge just from savings patterns over the life-cycle. The Rockstar Finance Blogger Sample has a Gini Coefficient as high as some countries. And the blogger net worth distribution and Gini coefficient are not unlike the lifetime net worth path of the typical FIRE saver like the ERN family.
24 thoughts on “This place has extreme wealth inequality, yet everybody is happy!”
Great analysis. While I did not choose to have the net worth data in the sample set, the evolution over different age cohorts followed essentially what your family data showed. There is a serious compounding effect in later stages of the journey that most don’t see at early stages to keep them motivated on the path. But its there! You and I are proof of it. So, if any young aspirant or millennial is reading this comment, I have the same advice as Obi Wan Kanobi did: Stay The Course. May be FIRE be with you!
Thanks TFR! Yes, I’m on the fence too if I should let the cat out of the bag and publish our personal NW number. But it’s amazing how the process accelerates, as you say. Growth rates might be a bit lower in the later stage because the contributions are less in % of the net worth, but the $ amounts grow pretty impressively. The FIRE-force be with us!
Thx for telling about Benford’s law…! Could one day make up a great bet.
Awesome! Just make sure you don’t use Benford on postal codes or phone numbers! It only works on real economic or accounting data. 🙂
What a great post, ERN, both informative and fun and lighthearted at the same time. Well done! Never would have thought to look at the Rockstar Directory data in this way, so that was really interesting to see. I was also only vaguely familiar with Benford’s law, but I really enjoyed the way you laid it out and found it entirely intuitive as I followed along.
Right on! Actually, I found an excellent recent post of yours along some of the same lines:
There is over-consumption and that certainly holds back some people. You generate even more inequality than in the Rockstar sample when one portion of the population behaves like us and saves and the other portion accumulates no assets because they live paycheck to paycheck.
Thanks for stopping by!
Way to crunch those numbers, Big ERN. I heart stats!
Benford’s law is new to me, also. Very cool how it can be used to validate. Now I gotta go see who the heck has $5 million.
Oh, it’s my buddy WCI. I believe at least half that is the value of his company. Not that there’s anything wrong with that.
Thanks Dr.! Glad you liked the number-crunching and Benford’s Law! Yes, not a big surprise that the top spot is a medical doctor. Way to go, WCI!
I love the use of stats on the blogger data. You also hit on one of my biggest pet peeves. Every time I see a money based stat in the mainstream media it neglects adjusting for age. Society is not homogenous, if you don’t control for certain variables in your sample set you will get the wrong answer. It’s a bit of a duh moment that a persons net worth should be correlatable to their age in aggregate. Why is it so hard to separate people into cohorts to avoid issues in the variability of cohort size? sorry for the rant.
Haha, great rant. My thoughts precisely. By looking at snapshots of inequality one gets the impression that there is never any improvement and poor folks stay poor forever. But the Gini coefficient says nothing about mobility. OK, now I’m ranting, too! 🙂
Thanks for stopping by!
Thank you! I teach psych stats, and I always tell my students: with few exceptions, journalists are trained how to write, not how to do stats or to think about numbers. So even though I can’t really blame them, I wish the people who have all this influence would take more time to think things through! But hey, you don’t meet deadlines by stopping to think, I suppose…
Great point! A more sinister view is that, at least in some corners of the journalism profession, there is already a predetermined narrative, capitalism=inequality=bad, and if the data fit the narrative they run with it.
PS: For some reason, your comment was filtered out as “spam” – very strange! Glad I found it, thanks for stopping by! 🙂
I loved everything about this post. I liked the way you took data that I’ve looked at so many times before and still managed to make it new and interesting. And I learned something new (Benford’s law). I can already picture how much fun I’m going to have with this and how people are going to slowly gravitate away from me, muttering under their breaths, at our next beer bash.
Haha, yes, don’t overdo it with Benford’s Law. Even without that I got “geek” written all over my forehead.
Thanks for stopping by!
Ha you and your stats, ERN. They never seize to amaze me! The conclusion I draw is that the personal finance blogging community is very harmonious! We are all here to help others (and each other) and encourage others no matter what stage you’re in today. It’s all about learning and growing.
Thanks for the interesting read!
Gotta love the stats, yes! And, yes, we are a very harmonious bunch. It would be hard to find the knowledge, inspiration, encouragement and motivation anywhere else. Thanks for stopping by!
I really enjoyed this analysis, and more so because it was relevant to our community. I think you hit on the reason why many personal finance enthusiasts start a blog. Sure it might seem glamorous when reading the blogs of big hitters, but in reality it’s because they want to be able to engage with others of the same mindset without the judgement that comes with talking money. I agree that we still have some real underlying inequality in our society, but in the midst of that we have lost the idea that a wealth journey is just that, a long focused path, with few real shortcuts. Thanks for spending the time on this ERN!
Thanks! Yup, the Rockstar Finance sample makes clear there are no shortcuts. There are plenty of non-millionaires. But they will be millionaires once they have as many years under their belt as the heavy hitters!
How do you come up with this stuff, Big ERN? Amazing. Many, many of us saw the Rockstar database, but you, and only you, took the initiative to do this awesome statistical analysis!
Another example of why you’re crushing it! Great, and fascinating, post. Yet again.
Wow, thanks for that compliment! Number-crunching is what we do here, so when I saw that database I thought I have to analyze the numbers, haha!
Thanks for stopping by, Fritz!
Intriguing post, for sure! But: Wouldn’t Benford’s Law go out the window if you transformed the USD denominated net worth numbers into a different currency? Say, 1USD = 0.8 British Pound, so a lot of the 1’s would be become 8’s?
Thanks, E.R.! That’s an excellent comment! Let’s assume a round number for the exchange rate, 1 GBP = 1.25 USD. Then a net worth of, say, $1,000,000 would become 800,000 pounds.
True, some of the 1’s would become 8’s and 9’s. But all numbers with a leading digit sequence of 1.25 to 1.999999 would still stay in the 1’s and numbers that were previously starting with a 2 to 2.249999 would now have a 1 as leading digit when previously they didn’t. You gain some, you lose some. The distribution of leading digits would largely stay the same.
So, that’s one of the beauties of Benford’s law: It’s independent of scaling and measurement units and currency conversion. As long as the conversion is applied to all numbers.