inequality

Millennials Have Caught Up to Boomers: Generational Wealth Update (2022q2)

Jeremy Horpedahl2 Comments

Last week I wrote about wealth growth during the pandemic, but my favorite way to look at wealth data is comparing different generations. Last September I wrote a post comparing Boomers, Gen Xers, and Millennials in wealth per capita at roughly the same age. At the time, Millennials were basically equal to Gen X at the same age, and we were a year short of having comparable data with Boomers.

What does it look like if we update the chart through the second quarter of this year?

I won’t explain all of the data in detail — for that see my post from last September. I’ll just note a few changes. We now have single-year population estimates for 2020 and 2021, so I’ve updated those to the most recent Census estimates for each cohort. Inflation adjustments are to June 2022, to match the end of the most recent quarter of data from the Fed DFA. We still have to use average wealth rather than median wealth for now, but the Fed SCF is currently in progress so at some point we’ll have 2022 median data (most recent currently is 2019, and there’s been a lot of wealth growth since then).

What do we notice in the chart? First, we now have one year of overlap between Boomers and Millennials. And it turns out… they are pretty much at the same level per capita! Millennials have also now fallen slightly behind Gen X at the same time, since they’ve had no wealth growth (in real, per capita terms) since the end of 2021 to the present.

But Millennials have fared much better in 2022 with the massive drop in wealth: about $6.6 trillion in total wealth in the US was lost (in nominal terms) from the first to the second quarter of 2022. None of that wealth loss was among Millennials, instead it was roughly evenly shared among the three older generations (Boomers hid hardest). This difference is largely because Millennials hold more assets in real estate (which went up) than in equities (which went way down). The other generations have much more exposure to the stock market at this point in their life.

You can clearly see that affect of the 2022 wealth decline if you look at the end of the line for Gen X. You can’t see the effect on Boomers, since I cut off the chart after the last Gen X comparable data, but they saw a big decline since 2021 as well: about 6% per capita, along with 7% for Gen X. Even so, Gen X is still about 18% wealthier on average than Boomers were at the same age.

Of course, even since the end of the second quarter of 2022, we’ve seen further declines in the stock market, with the S&P 500 down about 4%. And who knows what the next few months and quarters will bring. But as of right now, Millennials don’t seem to be doing much worse than their counterparts in other generations at the same age.

Wealth Growth During the Pandemic

Jeremy Horpedahl3 Comments

In the US wealth distribution, which group has seen the largest increase in wealth during the pandemic? A recent working paper by Blanchet, Saez, and Zucman attempts to answer that question with very up-to-date data, which they also regularly update at RealTimeInequality.org. As they say on TV, the answer may shock you: it’s the bottom 50%. At least if we are looking at the change in percentage terms, the bottom 50% are clearly the winners of the wealth race during the pandemic.

chart created at https://realtimeinequality.org/

Average wealth of the bottom 50% increased by over 200 percent since January 2020, while for the entire distribution it was only 20 percent, with all the other groups somewhere between 15% and 20%. That result is jaw-dropping on its own. Of course, it needs some context.

Part of what’s going on here is that average wealth at the bottom was only about $4,000 pre-pandemic (inflation adjusted), while today it’s somewhere around $12,000. In percentage terms, that’s a huge increase. In dollar terms? Not so much. Contrast this with the Top 0.01%. In percentage terms, their growth was the lowest among these slices of the distribution: only 15.8%. But that amounts to an additional $64 million of wealth per adult in the Top 0.01%. Keeping percentage changes and level changes separate in your mind is always useful.

Still, I think it’s useful to drill down into the wealth gains of the bottom 50% to see where all this new wealth is coming from. In total, there was about $2 trillion of nominal wealth gains for the bottom 50% from the first quarter of 2020 to the first quarter of 2022. Where did it come from?

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Economic freedom and income mobility

Vincent GelosoLeave a comment

A few weeks ago, my friend James Dean (see his website here, he will soon be a job market candidate and James is good) and I received news that the Journal of Institutional Economics had accepted our paper tying economic freedom to income mobility. I think its worth spending a few lines explaining that paper.

In the last two decades, there has been a flurry of papers testing the relationship between economic freedom (i.e. property rights, regulation, free trade, government size, monetary stability) and income inequality. The results are mixed. Some papers find that economic freedom reduces inequality. Some find that it reduces it up to a point (the relationship is not linear but quadratic). Some find that there are reverse causality problems (places that are unequal are less economically free but that economic freedom does not cause inequality). Making heads or tails of this is further complicated by the fact that some studies look at cross-country evidence whereas others use sub-national (e.g. US states, Canadian provinces, Indian states, Mexican states) evidence.

But probably the thing that causes the most confusion in attempts to measure inequality and economic freedom is the reason why inequality is picked as the variable of interest. Inequality is often (but not always) used as a proxy for social mobility. If inequality rises, it is argued, the rich are enjoying greater gains than the poor. Sometimes, researchers will try to track the income growth of the different income deciles to go at this differently. The idea, in all cases, is to see whether economic freedom helps the poor more than the rich. The reason why this is a problem is that inequality measures suffer from well-known composition biases (some people enter the dataset and some people leave). If the biases are non-constant (they drift), you can make incorrect inferences.

Consider the following example: a population of 10 people with incomes ranging from 100$ to 1000$ (going up in increments of 100$). Now, imagine that each of these 10 people enjoy a 10% increase in income but that a person with an income of 20$ migrates to (i.e. enters) that society (and that he earned 10$ in his previous group). The result will be that this population of now 11 people will be more unequal. However, there is no change in inequality for the original 10 people. The entry of the 11th person causes a composition bias and gives us the impression of rising inequality (which is then made synonymous with falling income mobility — the rich get more of the gains). Composition biases are the biggest problem.

Yet, they are easy to circumvent and that is what James Dean and I did. We used data from the Longitudinal Administrative Database (LAD) in Canada which produces measures of income mobility for a panel of people. This means that the same people are tracked over time (a five-year period). This totally eliminates the composition bias and we can assess how people within that panel evolve over time. This includes the evolution of income and relative income status (which decile of overall Canadian society they were in).

Using the evolution of income and relative income status by province and income decile, we tested whether economic freedom allowed the poor to gain more than the rich from high levels of economic freedom. The dataset was essentially the level of economic freedom in each five-year window matching the LAD panels for income mobility. The period covered is 1982-87 to 2013-18.

What we found is in the table below which illustrates only our results for the bottom 10% of the population. What we find is that economic freedom in each province heavily affects income mobility.

Image

More importantly, the results we find for the bottom decile are greater than the results “on average” (for all the panel) or than for the top deciles. In other words, economic freedom matters more for the poor than the rich. I hope you will this summary here to be enticing enough to consult the paper or the public policy summary we did for the Montreal Economic Institute (here)

Racial Gaps and Data Gaps

Jeremy HorpedahlLeave a comment

Are there racial gaps in the distribution of the COVID-19 vaccine? This is an important and interesting question in its own right. But I’ll talk about this question today because it’s an interesting example of how confusing and sometimes misleading data can be.

How do we answer this question? One is by surveying people. There are a number of surveys that ask this question, but a recent one by the Kaiser Family Foundation finds that among adults 70% of Blacks and 71% of Whites report being vaccinated. And given the sampling error possible with surveys, we would say that these are virtually identical. No racial gap! (Note: there was a racial gap when they did the same survey back in April, with 66% of Whites and 59% of Blacks vaccinated.)

But, surveys are just a sample, and perhaps people are lying. Maybe we shouldn’t trust surveys! And shouldn’t there be hard data on vaccines? Indeed, the CDC does publish data on vaccinations by race. That data shows a fairly large gap: 42.3% of Whites and only 36.6% of Blacks vaccinated. This is for at least one dose, and the percentages are of the total population (which is why it’s lower than the survey data). So maybe there is a racial gap after all!

But wait, if you look closely at the footnotes (always read the footnotes!), you’ll see something curious: the CDC admits that the race data are only available for 65.8% of the data. We don’t have the race information for over one-third of those in this data. Yikes! And given the exist disparities we know about in terms of income and access to healthcare, we might suspect that the errors are not randomly distributed. In other words, if there is probably good reason to suspect that Blacks are disproportionately reflected in the “unknown” category. But we just don’t know.

So what can we do? Since this data comes from US states, we can look at the individual state data and see if perhaps some of it is better (fewer unknowns). What does that data show us?

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Who is the Wealthiest Generation?

Jeremy Horpedahl19 Comments

Have you seen this chart?

I have seen it many times. It comes from this Washington Post article, but it seems to go viral on Twitter about every 6 months or so.

The implication of the chart seems to confirm what many young people feel in their bones: Boomers had it much easier, and it’s getting harder and harder for later generations to catch up and build wealth. For many the graph… explains a lot, as one recent viral Tweet put it (in the weird world of social media, 5 short words and a recycled chart are all it takes for 20,000 retweets).

But wait. A few questions probably come to mind. For example, when Boomers were young they comprised a much larger share of the population. The original article makes an attempt to adjust for this, by calculating a few ratios towards the end of the article. However, there’s a much more straightforward way to adjust for this, which also nicely fits into a chart: put wealth in per capita terms!

If we do that, here’s the chart we get (also, of course, adjusted for inflation).

Data is for 1989-2021 from the Federal Reserve’s Distributional Financial Accounts, but only the first quarter is available right now for 2021. For 1989, it is the average of the third and fourth quarters. Population data comes from Census single-year of age estimates for various years. 2020 and 2021 population estimated using growth rate from 2010-2019.
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Inequality VS the Environment

Zachary BartschLeave a comment

What do we know?

We know that density is good for most environmental measures. With greater density comes less water runoff, less carbon emissions, less burned fossil fuel. With density, fewer people own vehicles, implements of yard curation, and we require fewer roofs per person.

What else do we know?

We know that in a static economy, progressive taxation makes after-tax incomes more equal. There are formal models that say the same thing about dynamic economies. Progressive taxation results in more income equality, and regressive taxation results in less. For clarity, income tax progressivity is determined by percent of income paid in taxes. When the rich pay a higher percent tax rate, that’s more progressive.

Are you ready?

Wealthy people tend to have more valuable land. That is, they improve the land and the things built on it. Do you want to tax land progressively? Then what you want is a property tax with a sliding tax rate. This way, you can make those rich people pay their ‘fair share‘. Even without a sliding scale, rich people will pay more dollars for their improved land.

Uh-oh.

Now that we are taxing property on land proportionally, rich people are seeking alternatives. They’re trying to avoid taxes! What do they do? Well, a smaller and cheaper house is a nonstarter. What is all that wealth for, if not to enjoy it partly through one’s home environment? The rich are going to find a place to live where they can be comfortable and where their property taxes are lower. Maybe a place where the land is not so expensive. Hello rural estate!

Do you want a proportional property tax so that rich people pay for the value of their property? Be ready to say hello to suburbanization and sprawl. All those benefits of urbanization mentioned above? Invert all of them to see the results.

Okay…

I see the attraction of taxing immovable property. Taxing a residence is nice for the government because the tax revenues are nice and stable, given the relatively inelastic demand for real property.

If only there were a real property tax scheme that provided stable revenues and encouraged urbanization… Well, the answer is not to try taxing the value of the land without taxing the value of property. What am I? A Georgist?

A Georgist I am not. But, I do have an affinity for lump sum taxes.

If, as a polity, you want urbanization, then impose lump sum taxes per area of land owned. Doesn’t matter if it’s a house. Doesn’t matter if it’s commercial. Doesn’t matter if it’s unimproved farm land. Just sit back and watch the skyline rise, our environmental footprint shrink, and plenty of land being turned into wildlife preserves and parks.

Oh dear.

People have feelings. Consider a beautiful multi story single-family home on an acre. Now consider a mobile home with a large yard and some trees – also on an acre. With a standard, flat proportional property tax, the owner of the big pricey house pays more. With lump sum taxes per square foot of land, they pay the same dollar figure. In other words, the less wealthy person pays a higher proportion of his properties value in taxes. In case you missed it, this beautiful solution to sprawl and environmental degradation comes hand-in-hand with proportional regressivity.

BTW:

I live in Collier County Florida. If all of the land, excluding surface water, in the county was taxed at the same lump sum per square foot, then we would need to pay about $1,600 per acre in order to replace all revenues currently collected from a variety of sources. If we assume that government property is excluded from the tax and we assume that the government owns a very liberal 10% of all property, then it is more like $1,780.

I haven’t even discussed all of the improved economic performance that an already developed counties might enjoy by eliminating the distortionary excise taxes and ad valorem taxes. I don’t know about you, but $1,600 doesn’t sound too bad in exchange for eliminating all the other nickel and dimes that add up to quite a bit.

(Just as I am not a Georgist, I am also not a revolutionary. We need not jump in head-first. We could ease our way into such a system. We’d just add a fixed lump-sum portion to existing property tax bills that increases over time. Property taxes bills would be calculated slope-intercept style with a portion being constant and a portion being dependent of property value.)

Preferences for Equality and Efficiency

Joy1 Comment

Most people would consider both equality and efficiency to be good. They are “goods” in the sense that more of them makes us happier.  However, in some situations, there is a trade-off between having more equality and getting more efficiency. Extreme income redistribution makes people less productive and therefore lowers overall economic output.

Examining the preferences people have for efficiency and equality is hard to do because the world is complicated. For example, a lot of baggage comes along with real world policy proposals to raise(lower) taxes to do more(less) income redistribution. A voter’s preference for a particular policy could be confounded by their personal feelings toward a particular politician who might have just had a personal scandal.

With Gavin Roberts, I ran an experiment to test whether people would rather get efficiency or equality (paper on SSRN). Something neat that we can do in a controlled lab setting is systematically vary the prices of the goods (see my earlier related post on why it’s neat to do this kind of thing in the lab).

One wants to immediately know, “Which is it? Do people want equality or efficiency?”. If forced to give a short answer, I would say that the evidence points to equality. But overly simplifying the answer is not helpful for making policy. The demand curve for equality slopes down. If the price of equality is too high, then people will not choose it. In our experiment, that price could be in terms of either own income or in group efficiency. We titled our paper “Other People’s Money” because more equality is purchased when the cost comes in terms of other players’ money.

The main task for subjects in our experiment is to choose either an unequal distribution of income between 3 players or to pick a more equal distribution. Given what I said above that people like equality, you might expect that everyone will choose the more equal distribution. However, choosing a more equal distribution comes at a cost. Either subjects will give up some of their own earnings from the experiment or they will lower the total group earnings. As is true in policy, some schemes to reduce inequality are higher cost than others. When the cost is low, we observe many subjects (about half) paying to get more equality. However, when the cost is high, very few subjects choose to buy equality.

This bar graph from our working paper shows some of the average behavior in the experiment, but it does not show the important results about price-sensitivity.

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How to Think About Inequality Data and Public Policy

Jeremy HorpedahlLeave a comment

Lately I’ve been thinking about the disagreements among economists about the extent to which inequality has increased in recent decades. I am facilitating a reading group at my university on inequality this semester with some great undergrads, so it has very much been on my mind.

With conflicting data showing different trends, how are we as economists to judge this? How can the general public even have a clue how to judge this?

You may have seen this chart before. It comes from an article in The Economist, which actually does a really good job of explaining the debate over the data if you know nothing about it.

TaxProf Blog

According to some estimates, the share of income going to the top 1% has doubled and is now over 20%. That sounds bad. Maybe we need some more redistribution. Maybe a wealth tax.

But according to other estimates, and taking account of our existing system of progressive taxes and redistribution, the share of income going to the top 1% has not risen at all, is only about 5%. Less worrisome. The existing system of taxes and transfers seems to be doing a pretty good job, or at least no worse than in the last 60 years. No need for a new wealth tax, etc.

So who is right?

Sorry, I don’t have the answer. I think I’m pretty good at digging into economic data (follow me @jmhorp on Twitter for an almost daily dose of data debunking!), but I am no expert in this area. There’s probably only a dozen economists that really understand this data and the trade-offs in different forms of measurement.

So instead of giving you the “correct” answer, I offer you a chance to reflect. Our temptation is to say the “correct” data is the one that comports with our political preferences. If you are a progressive, you probably think inequality is bad and getting worse. Piketty is your man. If you are more of a libertarian, you probably think it’s about the same as recent years. Auten and Splinter must be right!

Stop. And instead, consider how you might view the policy implications of the data you don’t like being the correct data. If you are a progressive, would you still think we need a wealth tax even if the Auten and Splinter data is correct? If you are a libertarian, would you still think things are just fine and maybe we should cut the top tax rate if it turns out that Piketty and co-authors have the real data?

If you answer is the same for the policy implications regardless of what the data say, you might want to check yourself. And if so, why are we even arguing about the data?

Perhaps your answer is “I might have the same policy answer regardless of the data, but there are people out there that are convinced by data.” I think that’s possibly reasonable, and I would like it to be true, but where are these people?

Perhaps the answer is “as a libertarian, I don’t care about inequality so long as the poor and middle class are also sharing in the gains.” Or “as a progressive, I will continue to worry about inequality until the top 1% only has 1% of national income.”

I think these are the normal fallback answers. But really? Libertarians: if the income of the top 1% doubled in a decade, but the bottom 99% increased by 0.5%, you would be fine with this, because at least no one declined? Progressives: you would really support increasing taxes on the rich, despite any downside to this, until incomes were exactly equalized?

Frankly, I don’t believe anyone really holds either of those extreme positions. So surely, the data must matter? We want some reasonably shared benefits from economic growth, but no one really demands that they be exactly equal, right?

So, consider your own biases. Don’t engage in motivated reasoning. And think through how your views might change if you are wrong about the data. Perhaps someday Mother Nature will reveal herself, we’ll have the true inequality data, and we’ll see if we were honest about our reflections.