The white working class is large — October 11, 2016

The white working class is large

I had been incorrectly thinking of the white working class as some small interest group, but — depending upon how you define it — it’s actually quite large. Check out the Census Bureau’s data on population sizes by educational attainment, which I’ve turned into a shared read-only spreadsheet.

(Note, by the way, that when I tried to import that Census XLSX file into Google Docs, Google mangled it and dropped the age breakdown in the leftmost column. Apple’s spreadsheet ingested it properly.)

If we define the white working class as white adults with less than a bachelor’s degree, there are 132.8 million such people. In a nation of 321 million people, that’s around 40% of the population. Given that 77.1% of the population is 18 years old or older, that means there are around 247 million adults. So of those 247 million adults, the majority are non-college-educated whites.

(Few of my friends lack a college degree. Another example of the bubble I’m in.)

It’s worth noting that around 3/4 of all voters in 2012 were non-Hispanic whites. And around 63% of all voters in 2012 did not have a bachelor’s or advanced degree (source: Census Bureau). I’ve not found cross-tabs that count voters by race and educational attainment, but then I haven’t looked very hard.

I have a hunch that elite discourse — being framed by journalists who’ve mostly been educated at elite universities — has convinced many of us that the white working class are a minority whose magnitude approximates that of many other minorities. My rough sense of the magnitudes here convinces me that, in fact, they’re a majority in whatever way you care to slice it.

I’m making no political point here. For one thing, whites are doing really well, relative to other races. And to be crystal-clear about it: nothing Donald Trump has said suggests that he would help the demographic that is purportedly his base. But it’s striking how large that base is.

The economy as a machine — October 6, 2016

The economy as a machine

The latest episode of 99% Invisible (a podcast that you definitely ought to be subscribed to) describes a project carried out by the Chilean government under Allende to manage the state’s economy using the tools of control theory. The episode is a little light on the details of what they did in their control room; it is, after all, a podcast about design, and less about control theory.

It did, however, light up a bunch of neurons in my head related to longstanding interests of mine. The big, vague picture I have is that at one point people believed economies were machines which could be controlled by appropriately skilled engineers. This connects to a few threads, all of which I know in vague outline:

  • The early Technocracy movement.
  • Cybernetics, as pioneered by Norbert Wiener and Warren McCulloch (he of McCulloch-Pitts neuron fame).
  • Control theory, specifically as applied to economies — and as I understand it, specifically pursued at the RAND Corporation.
  • Macroeconomic work from around the World War II era, including input-output matrices of the sort that won Leontief his Nobel Prize; and even Kuznets’ Nobel for measurement of GDP.
  • The socialist calculation problem: how to replace a decentralized economy with disinterested bureaucrats who put data into their input-output matrices and output the appropriate level of every price in the economy. Specifically the debate between Hayek and Lange, which conventional wisdom has decided in favor of Hayek (specifically after he wrote The Use Of Knowledge In Society). I’ve not read the full debate, except as filtered through Stiglitz; I’d like to read the whole thing.
  • Pursuing formal analogies of economies as distributed computers, with all the formal consequences that would entail (e.g., deadlocks and race conditions).
  • Keynesian demand-side stimulation of the economy during recessions.
  • The later disillusion with the idea of controlling economies — including Milton Friedman’s famous observation that the economy responds to monetary interventions with “long and variable lags”

The big arc I have (again vaguely) drawn out in my head runs from a time when people seemed optimistic that an economy was something which humans created and humans could control, to a time when people seem to believe that economies are natural systems that we couldn’t possibly control even if we wanted to.

Does anyone know of a book that ties these strands together? Or do I need to write it myself?

Peacetime hopelessness and Bernie — March 29, 2016

Peacetime hopelessness and Bernie

I don’t have time to expand on this idea as fully as I’d like, but just some quick notes:

  1. During World War II, the federal government managed the U.S. economy to an unprecedented extent, including price and wage controls, and (I just learned) limits on the production of durable goods. The durable-goods limits were so intense that the spread of television was delayed until the war ended.
  2. After the war, millions of Americans were able to go to college through the G.I. Bill.
  3. Clearly, when we want to make something happen, we can make it happen.
  4. It’s equally clear that we only believe we can achieve the impossible during wartime.
  5. I’ve seen no reason for this belief.
  6. It may be the case that World War II was singular and irreplicable. But I’ve not seen this argued. We have every reason to believe that if the country needed to gear up for total war, it could do so. All economic slack would be removed and the unemployment rate would effectively drop to zero.
  7. It seems clear that society has reached a point in its development where macroeconomic outcomes are all a choice. We choose to tolerate involuntary unemployment. We choose not to use the government as an employer of last resort. We choose not to build good mass transit, choose not to house the homeless, choose not to feed the hungry.
  8. American economic ideology is stuck in an earlier mindset, wherein these are not choices. If we don’t feed the hungry, it’s because we can’t afford it, and/or because of the moral failings of the hungry.
  9. People probably believe this ideology sincerely. It just happens that this ideology is convenient for those who don’t want to feed the hungry.
  10. The chink in the armor for those who support this ideology is the nearly instantaneous availability of cash whenever war calls for it. War is a choice we make available to ourselves; improving our society is not.
  11. The Sanders campaign has been attacked for the unreality of its economic plans. I’ve not investigated very deeply, but if Sanders’s plans are unrealistic, they’re probably unrealistic in not saying all of the above: that the money is available, and we spend it on wars without hesitation, and that we just need to turn our society’s focus from the violent destruction of life to the improvement of life. Sanders’s presentation (“millionaires and billionaires”) has been narrow and monotonous, and hasn’t really approached the full scope of what’s available to a modern society. If we wanted a Manhattan Project to give every child a college education, we could do it. If it were a Manhattan Project for bombs, we could do it. There’s no reason to believe that a Manhattan Project for college is more difficult.
  12. The argument against Sanders is essentially an argument for hopelessness.
  13. I don’t mean that in a disparaging way, actually. Who knows: it may in fact be hopeless to dream of achieving Sanders-like outcomes. But what makes it hopeless is not a fact about reality or a fact about economics, but rather a fact about politics.
  14. So if you’re going to argue against the Sanders campaign, don’t argue it on the basis of economic reality or fiscal plausibility. Argue it on the basis of political reality. Because that’s the only real ground on which this opposition stands.
  15. If political reality stands between us and Sanders-like outcomes, and if we desire those outcomes, then it seems that the top question on everyone’s mind ought to be how to change political outcomes.
  16. By “changing political outcomes” I mean something like “making the results of our collective decisionmaking match the results of our collective desires.” If we, as a society, would prefer to have a tax-financed system of public universities that leave our students debt-free, but our political system doesn’t make that outcome feasible, then there’s something wrong with the way that our policy desires are translated into political outcomes.
  17. Which candidate is more likely to change political outcomes? The typical argument for Hillary is that we’re never going to change political outcomes if a Republican is elected, and that Hillary is the only electable one. The typical argument for Bernie and against Hillary is that Hillary wouldn’t do the right things if elected — that she’s too comfortable with the system as it is — and that she’d aim in the direction of the right policies without fundamentally changing the political structure. The argument against Bernie here is that he would be one man among many, and that his noble intentions would be crushed by the system. Bernie’s argument for himself is that his election would signal a political revolution; this would mean that the very organization of political life had changed.
  18. There’s a certain fashionable pessimism these days: our children will live worse lives than ours, globalization is destroying the American economy, and we need to settle for smaller dreams. These are all choices. If we, as a society, decide that we deserve better, and we choose to not achieve better, we are making a moral choice rather than succumbing to economic necessity.
A bit of data fiddling for your Sunday — November 8, 2015

A bit of data fiddling for your Sunday

I saw the headline The unemployment rate doubled under Bush. It’s fallen by more than one-third under Obama. when I was reading Vox this morning, and I got ready to bust out the stat that “the labor-force participation rate is still way down” — as indeed it is:

That is, the fraction of Americans working hit its peak under Clinton, fell under Bush, really fell when the housing bubble popped, and hasn’t really recovered.

Some of that drop can come from young people deciding to stay in school and get graduate degrees when the economy is doing poorly, or from older people deciding to retire early. So what if you focus on ages 25 to 54, i.e., the “prime-age labor-force participation rate”? The story there is somewhat better:

The rate still took a noticeable hit in 2008, but we’ve regained some ground. Let’s zoom in on the period starting in 2005:

Moving slowly in the right direction. Now, much of the gain since 1948 can be attributed, one assumes, to women entering the workforce. Do the data bear that out? Seemingly yes:

That’s interesting: women’s labor-force participation seems to have flat-lined starting in 1990. Why? And what can be done to get it moving again?

On the flip side, how about the male labor-force participation rate? That’s quite striking:

It has decreased more or less continuously since 1960.

There’s no real moral here. I just find it interesting that, as you dig into the data, there’s something more going on than a story about the 2009 recession. Seems like, recession or not, men are leaving the workforce. And women aren’t entering it fast enough to offset that drop.

P.S.: A friend asks whether labor-force participation is really an end in itself. The short answer is probably “No, though it’s a good proxy for what we actually care about.”

Perhaps, for instance, people choose to stop working because they want to be full-time parents. Let’s call that a “happy” labor-force detachment. On the other hand, perhaps they drop out of the labor force because they know they’ll never get a job. Or maybe (I’ve seen this happen a lot) they’re mothers who want to spend time with their kids, but the only jobs that they could get would hardly cover the cost of child care; they want to work, but for economic reasons they choose not to. Call that a “sad” labor-force detachment: they’d like to work, but can’t.

It’s going to be hard to measure this in full detail, of course, and there are going to be almost as many boundary cases as there are people who aren’t working. But if you want to measure “how is the economy doing?” you have to set your boundaries somewhere. That’s why the Bureau of Labor Statistics has a number of different measures of unemployment:

U-1, persons unemployed 15 weeks or longer, as a percent of the civilian labor force;
U-2, job losers and persons who completed temporary jobs, as a percent of the civilian labor force;
U-3, total unemployed, as a percent of the civilian labor force (this is the definition used for the official unemployment rate);
U-4, total unemployed plus discouraged workers, as a percent of the civilian labor force plus discouraged workers;
U-5, total unemployed, plus discouraged workers, plus all other marginally attached workers, as a percent of the civilian labor force plus all marginally attached workers; and
U-6, total unemployed, plus all marginally attached workers, plus total employed part time for economic reasons, as a percent of the civilian labor force plus all marginally attached workers.

U-6, for instance, has improved noticeably over the last few years.

There are a lot of terms in here with precise definitions, and the definitions matter, and you need to think carefully about what you’re counting and aren’t. For instance, what does “civilian labor force” mean? Who’s in it and who’s not? This isn’t secret or mysterious at all; the BLS explains it in clear language. Here you go:

Civilian noninstitutional population: Persons 16 years of age and older residing in the 50 states and the District of Columbia, who are not inmates of institutions (e.g., penal and mental facilities, homes for the aged), and who are not on active duty in the Armed Forces.

Civilian labor force: All persons in the civilian noninstitutional population classified as either employed or unemployed.

Note well: this means that if you’re in prison, you’re not part of the labor force. This is where unemployment definitions intersect with Becky Pettit’s Invisible Men: Mass Incarceration and the Myth of Black Progress. To put it briefly: if every single black man but one were in prison, and that remaining black man had a job, then by the official statistics the unemployment rate among black males would be zero. Obviously we would consider this situation horrifying. So “a low rate of unemployment” is not necessarily synonymous with “a happy economy”. Maybe we want to add the institutionalized population to the current definition of the labor force. Or maybe not: those in prison surely cannot work and are not looking for work. And if we’re going to add those who can’t work for reasons of imprisonment, why then wouldn’t we add back lots of other people who cannot work and aren’t looking for work because, e.g., they’re permanently disabled? It’s certainly useful to measure all such populations. Different data series have different uses. Probably the best you can say is that different questions require different sorts of data, that no one data series can answer all questions, that you really need to look carefully at multiple sources of data, and that you should carefully look at the assumptions embedded in each.

What if you count the total civilian labor force (which, again, includes the noninstitutionalized population) and divide it by the overall population? You get this:

Earlier, we were tallying the “labor force participation rate”, which is defined as “The labor force as a percent of the civilian noninstitutional population.” As more people are imprisoned (“institutionalized”) or enter the military (i.e., they’re no longer “civilian”), the denominator goes down, which means the participation rate goes up. Whereas if you divide by the total population, an increasing prison population would cause the participation rate to decrease — arguably closer to what we actually want.

Again, this graph is likely dominated by women’s entry into the workforce. FRED seems to track the right thing here, namely the employment-to-population ratio over time for males. In the numerator, that’s going to include men who choose to stay in school longer, and men who choose to retire early, so one wants the employment-to-population ratio among prime-age males. In the denominator, it’s going to include the full U.S. population rather than just the labor force, so the ratio will decrease as more black men are imprisoned. FRED has the correct series, seemingly, but it’s via a different (OECD) data source that I’ve not dug into yet. It has the parallel data source for females.

The moral is just that there are many ways to measure unemployment, and which measure you pick will depend on which question you want answered. If you want to measure whether people are opting out of the labor force for happy reasons or sad reasons, the government tracks that. If you hear someone say that government statistics are bunk and that they don’t address Objection Objection x, your first assumption should be that the speaker is wrong.

Jeb Bush and 4% GDP growth — July 14, 2015

Jeb Bush and 4% GDP growth

There are many infuriating things about Jeb Bush’s idea that Americans should work more to achieve 4% GDP growth. Among the more infuriating is that the press is actually engaging with it.

Here’s the part that drives me the most crazy: it’s seemingly all based on an accounting trick that no one (to my eye, anyway) has explicitly called out: if we’re going to obsess over GDP, what actually matters is productivity growth. Alternatively, if you’re an ordinary human being, what matters is per-capita GDP growth. Neither productivity nor per-capita GDP growth increases with the number of people in the society, nor with the number of hours that people work. Indeed, to the extent that the 41st hour of your workweek is less productive than your 40th, working more hours might decrease marginal productivity.

If, though, we continue to focus on the wrong goal — namely increasing total output — there’s a very easy way to get there: allow more people to immigrate to the U.S. More people means more work, which means more GDP. Problem solved.

I eagerly await Jeb Bush’s plan for increased immigration.

ESPPs: magical free money — November 23, 2014

ESPPs: magical free money

Akamai has an Employee Stock Purchase Plan, which I’ve tried very hard not to think of as magical free money. But I think it basically is. It works like this: you set aside some fraction of your after-tax paycheck, and every six months the company uses that money to buy the company’s own stock for you. There are some limits on how the ESPP can be structured: the company can give you the stock at a discount, but the discount can’t be any more than 15% off the fair market value (FMV); you can’t get more than $25,000 in stock (at FMV) per year; and Akamai (in keeping, apparently, with general practice) imposes a further limit, such that you can contribute at most 15% of your eligible compensation.

To see how great the return on this is, consider first a simplified form of an ESPP. You put some money in, then wait six months; the company buys the stock, and you sell it immediately. They gave it to you at a 15% discount, i.e., 85 cents on the dollar. So basically you take your 85 cents, turn around, and sell it for a dollar. That’s a 17.6% return (1/.85 ~ 1.176) in six months. To turn that into an annual rate, square it. That makes it a 38% annual return.

Introducing some more realism into the computation makes it even better, because your money isn’t actually locked up for six months. In practice, you’re putting away a little of your money with every paycheck. So the money that you put in at the start of the ESPP period is locked up for six months, but the money you put in just before the end of the period is locked up for no time at all. The average dollar is locked up for three months. So in exchange for three months when you can’t touch the average dollar, that dollar turns into $1.176. Annualized, that’s a 91.5% return.

Doing this in full rigor means accurately counting how long each dollar is locked up. A dollar deposited at the start is locked up for 6 months; a dollar deposited two weeks later is locked up for six months minus two weeks; and so forth. It looks like this:

End of pay period 0: You have $0 in the bank.

End of pay period 1: You deposit $1. Now you have $1.

End of pay period 2: You deposit $1, and you earn a rate r on the money that’s already in the bank. So now you have 1 + (1 + r) dollars in the bank.

End of pay period 3: You deposit $1. The 1 + (1 + r) dollars already in there earn rate r, meaning that they grow to (1 + (1 + r))(1 + r) = (1 + r) + (1 + r)2. In total you have 1 + (1 + r) + (1 + r)2.

In general, at the end of period n, you have 1 + (1 + r)2 + (1 + r)3 + … + (1 + r)n-1 in the bank. That simplifies nicely: at the end of period n, you have (1 – (1 + r)n)/(1 – (1 + r)), or (1/r) (-1 + (1 + r)n) dollars in the bank.

At the end of the n-th period, you get back (1/.85)n dollars for the n dollars that you put in. So what does r have to be so that you end up with n/.85 dollars when period n is over? You need to solve (1/r) (-1 + (1 + r)n) – n/.85 = 0 for r. Use your favorite root-finding method. I get r=0.02662976. That’s the per-period interest rate. (It’s also known as the Internal Rate of Return (IRR).) In our case it’s a 6-month ESPP period, with money contributed every two weeks, so there are about n=13 periods. So the return on your money is ~1.026613 in six months, or 1.026626 in a year. That comes out to about a 98% return. Which is, to my mind, insane.

The full story would be both somewhat better and somewhat worse than that. Somewhat better, in that the terms of our ESPP are even more generous: when it comes time to buy the stock, Akamai buys it for you at the six-months-ago price, or the today price, whichever is lower. So imagine you have $12,500 in the ESPP account, that the stock is worth $60 today, and that it was worth $40 six months ago. You get shares valued at $40 apiece, minus the 15% discount. So the company buys shares at .85*$40=$34. It can buy at most $12,500 in shares (at FMV), so it can buy floor(12500/40)=312 shares. Cool. Now you have 312 shares, which you can turn around and sell for $60, for a total of $18,720. That is, you put in $12,500, and you got out $18,720. Magic $6,220 profit.

The “somewhat worse” part is that you pay taxes on two pieces of that. First, you pay taxes on the discount that they gave you (since it’s basically like salary). Second, if you hold the stock for any period of time and pick up a capital gain, you pay tax on that; if you held the stock for less than a year, that’s short-term capital gains (taxed at your regular marginal rate), whereas if you hold for a year or more you pay long-term cap gains (15%, I believe).

I’ve not refined my return calculation to incorporate the tax piece, but I doubt it changes the story substantially. First, it’s hard for me to imagine that the taxes lower the rate of return from 98% down to, say, 15%. Second, any other investment (a house, stocks, bonds, a savings account) would also require you to consider taxes. And since the question isn’t “Is an ESPP good?” but rather “Is an ESPP better than the alternatives?”, I suspect that taxes would affect all alternatives equally. It strikes me that ESPP must win in a rout here — which would explain why the amount you can put in the ESPP is strictly limited; otherwise it really would be an infinite magical money-pumping machine.

Why can’t my portfolio exactly match the full market? — June 25, 2014

Why can’t my portfolio exactly match the full market?

So far as I understand the conceptual basis for a lot of theorems in finance, one of the ideas seems to be reasonably straightforward: if some type of investment — domestic equities, foreign equities, bonds, housing, whatever — were systematically higher-yielding than some other type of investment, then everyone would just invest in the higher-yielding category and wipe out the difference in yield. So in the long run, you’d expect yields across asset classes to equilibrate.

Yes, this is based on assumptions, which might well be false. But let’s assume that it’s roughly true. Then the usual argument says that you can’t beat the market, and you’ll never do better than to diversify your portfolio. But note carefully what “diversify” means here. It *doesn’t* just mean “invest in all 500 stocks in the S&P 500”. There’s a whole lot more market out there! That is, there are a lot more asset classes than just large industrial stocks of the sort that the S&P traffics in. Even within the class of U.S. stocks, there are larger indexes like the Wilshire 5000. Or there’s the set of stocks tracked by the Vanguard Total Stock Market Index Fund. And then there are foreign stocks. And then government bonds. And municipal bonds. And corporate bonds.

But there’s *still* a lot more market out there. Some asset classes are harder to invest in than others, like houses. Wouldn’t it be cool if you could buy housing across many worldwide markets? It’s a little weird to imagine exactly how that would work, though large property owners do own a shocking amount of property across many cities. So in our imagined perfectly diversified portfolio, we’d have a bunch of housing. And we’d also have a lot of unlisted stocks. And we’d have some private equity. And we’d own some mines. Because again, the principle behind the diversification is that if everyone already knew that some asset class yielded outsized returns, they’d already be investing in it. The only way to beat the market in such a case is to know something that others don’t — to avoid some asset class that you know yields lower returns than the rest of the world thinks it does, or to invest in an asset class that others are systematically avoiding. In principle, I can’t see any reason why your buddy Doug’s new venture doesn’t count as an asset class for the purposes of this argument.

So here’s my question: how do I, J. Random Small Investor, get my portfolio fully diversified across all possible asset classes? One of Piketty’s observations in his masterwork is that the wealthy are able to obtain systematically above-market returns, in no small part because they can invest in asset classes that you and I don’t have access to. And in one example he gives — the Harvard endowment — it helps that the Harvard Corporation spends $100 million every year to manage $30 billion in assets. You and I could probably also do very well as investors if we spent all day every day managing our investments, and if we had a staff to do it, and if we had enough money to play with that we could offset some losing bets with more winning bets.

But that argument isn’t convincing to me, because we *do* have that ability; this is why we hire mutual funds. Apparently the Vanguard Total Stock Market Index Fund has $190 billion in assets. Granted, that particular fund won’t be investing in obscure corners of the asset universe, but why doesn’t Vanguard set up a fund that’s truly diverse across all asset classes, draw many billions of dollars from investors like me, and earn the same returns as the Harvard endowment or Bill Gates?

One possible answer is that regulation forbids them from investing in risky asset classes (like hedge funds or complicated swaps) if non-rich guys like me are on the other end of the trade. Is there some other reason I’m missing why wealthy people *must* earn higher returns than mutual funds do?