Felix Salmon

Today’s jobs report was a solid one, and shows that the recovery, while not exactly strong, is at least not slowing down: Neil Irwin calls it “amazingly consistent”. Whether you look at the past 1 month, 12 months, 24 months, or 36 months, you’ll see the same thing: average payrolls growth of roughly 170,000 jobs per month. That’s not enough to bring unemployment down very quickly, given the natural growth in the workforce. But unemployment is coming down slowly. And at the rate we’re going, at some point in the second half of 2014 we should see total payrolls reach their pre-crisis levels, and the headline unemployment rate hit the key 6.5% level.

There’s a real human cost to the fact that unemployment is coming down so slowly, but there are lots of reasons why it’s very hard to bring it down more quickly. First and foremost, of course, is the fact that US GDP growth is mediocre, coming in at less than 2% per year over the past few years. That’s not the kind of V-shaped recovery which creates jobs. Calculated Risk’s justly-famous jobs chart shows just how bad the recession was for employment, and just how painfully slowly we’re scratching our way back: we’re more than five years into this jobs recession, and we’re still at the worst levels seen in the wake of the dot-com bust.

One of the reasons is the undisputed conclusion of Reinhart and Rogoff: that recoveries from financial crises are much slower than recoveries from other crises. But there’s something bigger going on, too, which Joe Stiglitz writes about today in a very wonky blog post for the IMF.

This is more than just a balance sheet crisis. There is a deeper cause: The United States and Europe are going through a structural transformation. There is a structural transformation associated with the move from manufacturing to a service sector economy. Additionally, changing comparative advantages requires massive adjustments in the structure of the North Atlantic countries.

To put it another way: what looks like a broad economic recovery is actually a combination of many trends, including the end of what turned out to be a very short and weak recovery in manufacturing employment. Here’s Irwin:

The fact that the overall job growth numbers have been extraordinarily stable does not mean there isn’t some real churn going on in the U.S. workforce. In the earliest phase of the recovery, manufacturing jobs was a major driver of job creation, but that turned out to be not a longer-term trend but a partial reversal of the steep declines of the recession. Now, job creation is entirely confined to the services sector: Manufacturing had no net change in employment, construction lost 6,000 jobs, and even mining and logging was a net negative.

Government employment, meanwhile, continued its long swoon… That leaves one sector to drive the train of job creation: private sector services. This particular month, there were strong gains in leisure and hospitality, retail jobs, and professional and business services, and health care has been a mainstay of the expansion.

Stiglitz makes the case that in a recovery with so many moving parts, the single blunt instrument of setting short-term interest rates at the Fed will never be enough, and that “there needs to be close coordination between monetary and fiscal policy.”

What’s more, as Mohamed El-Erian says, policymakers should ideally be able to use job growth not just as a goal, but also as a tool for achieving other ends.

Robust employment growth would – and, let us hope, will – play a critical role in helping the US pivot to a better place… It would do this by maintaining consumption and allowing for a more sustainable savings rate; by countering an excessive upfront fall in public spending that increases the risk of a recession; by enabling the Fed to slowly and gradually normalise monetary policy before it breaks too many things; and by reducing the risk of financial bubbles.

The US economy is a highly complex machine, with many moving parts which ought to be working with each other rather than against each other. Stiglitz makes a strong case that the financial sector broadly is right now part of the problem rather than part of the solution: it’s not directing funding to help the economy grow and create jobs, even as it continues to represent a serious systemic risk. It should go without saying at this point that fiscal policy broadly is part of the problem as well: you don’t create jobs by firing people, and the government should be borrowing if and when the private sector won’t. And as for monetary policy — well, it’s probably too early to tell. It’s done a great job of making people with money richer, but it has had a much less obvious effect on creating jobs for those who want them and don’t have them.

And yet there’s real room for optimism in today’s jobs report. Look at the revised numbers for February: an incredibly heartening 332,000 jobs created, in one short month. Look at the number of people unemployed for 27 weeks or more: that unhappy cohort shrank by 5.6% in April alone, to 4.3 million people. It’s still far too high, but this time last year it was over 5 million, so we’re making a significant dent in what has been the toughest nut to crack.

We can — and should, and could, and must — do better than this. But doing so will require a thaw in the Washington gridlock. When Jack Lew became Treasury secretary, it was understood that the most crucial thing he could deliver would be greater cooperation between the White House, Treasury, and Capitol Hill. That hasn’t happened yet. I hope and trust that he’s been working very hard behind the scenes to make it happen — partly because he doesn’t seem to have achieved anything else, but mainly because it’s by far the most important thing that he could be doing right now. Behind the jobs numbers there are some powerful forces driving real recovery in large parts of the US economy. It’s Lew’s job to work with Congress to identify those forces, and to give them all the support the government can muster.

It’s May Day, and Henry Blodget is celebrating — if that’s the right word — with three charts, of which the most germane is the one above. It shows total US wages as a proportion of total US GDP — a number which continues to hit all-time lows. Blodget also puts up the converse chart — corporate profits as a percentage of GDP. That line, you won’t be surprised to hear, is hitting new all-time highs. He’s clear about how destructive these trends are:

Low employee wages are one reason the economy is so weak: Those “wages” are represent spending power for consumers. And consumer spending is “revenue” for other companies. So the short-term corporate profit obsession is actually starving the rest of the economy of revenue growth.

In other words, we’re in a vicious cycle, where low incomes create low demand which in turn means that there’s no appetite to hire workers, who in turn become discouraged and drop out of the labor force. Blodget’s third chart is one we’re all familiar with: the employment-to-population ratio, which fell off a cliff during the Great Recession and which will probably never recover. The current “recovery” is not actually a recovery for the bottom 99%, for real people who need to live on paychecks. And today is exactly the right day to point that out.

Conversely, today is exactly the wrong day to declare that these broad and inexorable trends are not really big top-down trends at all, and in fact merely reflect the inability of individual workers to “access learning, retrain, engage in commerce, seek or advertise a job, invent, invest and crowd source”. And yet that’s Tom Friedman’s column this May Day:

If you are self-motivated, wow, this world is tailored for you. The boundaries are all gone. But if you’re not self-motivated, this world will be a challenge because the walls, ceilings and floors that protected people are also disappearing. That is what I mean when I say “it is a 401(k) world.”

This manages to be both incomprehensible and incredibly offensive at the same time. I have no idea what Friedman thinks he’s talking about when he blathers on about disappearing protective floors; I can only hope that he isn’t making a super-tasteless reference to the recent disaster in Bangladesh. But it’s simply wrong that today’s world is “tailored” for anybody who happens to be “self-motivated”. Both the self and the motivation are components of labor, not capital, and as such they’re on the losing side of the global economy, not the winning side.

Friedman is a billionaire* (by marriage) who — like all billionaires these days — is convinced that he achieved his current prominent position by merit alone, rather than through luck and through the diligent application of cultural and financial capital. His paean to self-motivation recalls nothing so much as Margaret Thatcher’s “there is no such thing as society” quote: “parenting, teaching or leadership that ‘inspires’ individuals to act on their own will be the most valued of all,” he writes, bizarrely choosing to wrap his scare quotes around the word “inspires” rather than around the word “leadership”, where they belong.

True leadership, in a society where the workers are failing to be paid even half the fruits of their labor, would involve attempting to turn the red line in Blodget’s chart around, and to spread the nation’s prosperity among all its citizens. Rather than telling everybody that they’re “on their own” and that if they’re not a success then hey, they’re probably just not “self-motivated” enough.

The ultimate Friedman kick in the balls, however, doesn’t come from his lazily meritocratic priors. Rather, it comes from his overarching metaphor: the idea that if you have a 401(k) plan, then you’re somehow in charge of your own destiny. Friedman might be right that we’re living in a 401(k) world, but if he is then he’s right for the wrong reason. In Friedman’s mind, a 401(k) plan is an icon of self-determination: you get out what you put in. “Your specific contribution,” he writes, italics and all, “will define your specific benefits.”

In reality, however, a 401(k) plan is an icon of futility and the way in which the owners of capital extract rents from the owners of labor. Yves Smith is good on this, as is Matt Yglesias, although the real expert is Helaine Olen: the 401(k) is a way for both your government and your employer to disown you, and to leave your life savings to be raided by the financial-services industry and its plethora of hidden and invidious fees. The well-kept secret about old-fashioned pension funds is that, for the most part, they’re actually very good at generating decent returns for their beneficiaries. They tend to have extremely long time horizons, and are run by professionals who know what they’re doing and who have a fair amount of negotiating leverage when they deal with Wall Street. Savers are always strengthened by being united: disaggregating them and forcing them to take matters into their own hands is tantamount to feeding them directly to the Wall Street sharks.

Yglesias says that in a 401(k) world, “you’ve got to save a lot of money for retirement. More than you think.” This is true for five big reasons. Firstly, because wages are shrinking, any given level of savings will constitute a steadily-increasing proportion of any given worker’s GDP-adjusted paycheck. Secondly, because the employment-to-population ratio is shrinking, all workers need to save to support not only themselves in retirement, but also a number of dependents which is also growing over time. Thirdly, because 401(k) plans have lower returns than traditional pension plans, you need to save more in order to make up the difference. Fourthly, life happens: while the money in your 401(k) is nominally there for your retirement, in practice there’s a good chance that you’re going to tap it, at some point, to pay some kind of large and unexpected bill, whether that comes from unemployment or divorce or ill health. And finally, 401(k) plans don’t have the clever cross-subsidy that traditional pension plans have, where people who die early cross-subsidize people who live for a long time. With a pension plan, you get income when you need it — when you’re alive — and you don’t get money when you’re dead, and don’t need it any more. With a 401(k), by contrast, you have to save more than you really need, because there’s always a chance that you’re going to live to 102.

Add them all together, and to a first approximation you arrive at our current world, where pretty much no one relying on their 401(k) is actually saving enough for retirement. If you’re rich today, you’ll probably be fine when you retire. But if you’re someone who (in contrast to Tom Friedman) actually lives on your paycheck, then there’s almost no chance that your retirement savings will be enough, when the time comes. That’s not your fault: the reasons are deeply systemic. And as a result, the solutions cannot possibly be the kind of bottom-up schemes that Friedman is extolling. They have to come from the top: from real leaders, rather than jumped-up “thought leaders“.

*Or was, anyway. Maybe he isn’t any more.

This chart comes from Arindrajit Dube, who has a fantastic post chez Rortybomb on whether high debt causes lower growth or whether it’s the other way around. What you’re looking at is the famous Reinhart-Rogoff dataset, as made available by their critics (and Dube’s colleagues), Herndon, Ash and Pollin. Reinhart and Rogoff are the poster children for the statement that high debt loads cause lower growth, especially once those debt loads exceed 90%. But do they?

There does seem to be an inverse correlation between debt and growth, but Dube shows that the correlation is strongest at low levels of debt, below 30% of GDP, rather than at high levels of debt. Countries with debt of 30% of GDP have a significantly lower growth rate, on average, than countries with debt of 10% of GDP, while the numbers at debt ratios above 90% have much wider error bars and are much less useful.

But let’s grand the correlation, for the sake of argument: the next question is whether the correlation implies causation, and if so, which way the causation flows. Here’s Dube:

Here is a simple question: does a high debt-to-GDP ratio better predict future growth rates, or past ones? If the former is true, it would be consistent with the argument that higher debt levels cause growth to fall. On the other hand, if higher debt “predicts” past growth, that is a signature of reverse causality.

That’s what you’re seeing in the charts. Both of them have the same axes: GDP growth on the y-axis, and debt/GDP on the x-axis. Both of them plot the correlations in the dataset, with the dark line being the signal and the dotted lines showing the 95% confidence interval. And just as in the main dataset, the correlations are much clearer at low levels of debt/GDP than they are at higher levels.

But the two charts are different, all the same, especially at levels of debt/GDP above that 90% level. If you look at the left-hand chart, it shows that it really doesn’t matter how much debt you have: you’re likely to average about 3% GDP growth a year over the next three years. On the other hand, if you look at the right-hand chart, it shows that the more debt you have, you’re significantly more likely to have experienced low growth in the past three years.

In other words, the causation here seems about as clear as causal analysis can ever be: low growth causes high debt, rather than high debt causing low growth. Indeed, once you get past 90% of GDP, your debt load doesn’t seem to have any significant effect on future growth at all!

Azam Ahmed has a report from Kabul’s ‘Car Guantánamo’ today:

Behind these walls are thousands of cars, trucks, vans, motorcycles and even bicycles, lined up in vehicular purgatory after falling afoul of the Kabul traffic police. Things that have landed cars in the slammer: illegal left turns, parking violations, involvement in fender-benders and, perhaps most egregious, failure to pay a bribe.

“I’ve been waiting two months to get my van back,” said Sayed Wahid, whose quest to reclaim it, after it was impounded for an expired international permit, propelled him on an exhausting odyssey through no fewer than six different government agencies…

In November, Mr. Wahid had driven his van from Kunduz down to Kabul when he was pulled over at a checkpoint in the capital. His license and car tags were clean, but a permit to cross international borders, though not needed for that specific trip, had expired.

For a moment, he said, he considered bribing the officer. He has regretted every day for the past two months his decision not to.

Ahmed explains that when it comes to Kabul’s traffic police, “the rules are unevenly applied, punitive to those who can least afford it, and mostly irrelevant to those with money and power.”

The point here is that it’s the poor, like Sayed Wahid, who are hit hardest by Kabul’s endemic corruption. Either they do the sensible thing, and pay a bribe they can ill afford, or else they’re at real risk of losing their livelihood. Meanwhile, the rich and powerful aren’t even asked to pay bribes: the police know better than to try this stunt on someone who could easily get them fired. It’s safe to solicit a bribe from a guy from Kunduz in a van; you’d have to be much braver to try it with a man in a suit driving a Mercedes.

It’s not that the rich don’t pay bribes at all; of course they do. But in general when the rich pay bribes, they tend to get even richer. That’s the deal: that’s business. When the poor pay bribes, by contrast, it’s a deadweight loss: it’s just money disappearing into the pockets of a corrupt official, never to be seen again.

A new paper by Shahe Emran, Asadul Islam, and Forhad Shilpi is instructive and sobering in this respect. Entitled “Admission is Free Only If Your Dad is Rich! Distributional Effects of Corruption in Schools in Developing Countries”, it looks at the cost, in bribes, of sending your kid to “free” school in Bangladesh. Exactly the same pattern is seen there as the one that Ahmed found in Kabul:

The results reported above in Tables 3 and 4 show that the poor are more likely to pay bribes. The estimates of Table 3 imply that a one percent lower income leads to a 0.73 percent increase in the propensity to pay bribes. The negative effect of income of propensity to pay bribe points to important role of a household’s “bargaining strength”. The richer households – with better bargaining power – are less likely to pay bribes than the poorer households. This is a depressingly perverse outcome given that the goal of free public schooling is to help the poor households, not to provide free schooling for the children of rich and influential only!!

Overall, households which paid a bribe to educate their children earned Taka 1930 per month, on average, while households which didn’t pay a bribe earned an average of Taka 2560 per month. And the bribes were large, too.

Among the households who reported positive amount of bribe payment, on average a household paid about Taka 241 during the survey year. To get a better sense of the financial burden imposed on the poor, it is instructive to look at the average bribe paid as a proportion of the household savings. The average bribes paid in schools is 9 percent of average annual household savings, while for the first and second quintile it amounts to 61 percent and 27 percent of annual household savings respectively.

The most famous line in Withnail and I is the point at which Withnail procures the key to his rich uncle’s cottage, explaining: “Free to those that can afford it, very expensive to those that can’t.” That phenomenon is well known: the richer you are, the more likely you are to be invited out to lunch, or dinner, or the Hamptons. But as we can see in Afghanistan and Bangladesh, the phenomenon doesn’t just apply to desirable luxuries such as the swag bags given out to celebrities at the Oscars. In the developing world, it applies to much more basic things, too, like the right to drive your car around Kabul, or the right to send your kid to a free school. And it’s not at all clear what if anything can be done about it.

The main problem with trying to explain the fiscal cliff, as I see it, is that people get far too caught up in the details — tax deductions, tax hikes, spending cuts, debt ceilings, and the like. Which are all important, but they’re not fundamentally what the austerity bomb is about. Rather, the reason that everybody’s worried about the effects of the fiscal cliff is simple Keynsian mathematics: if we cut spending and raise taxes, that means less economic activity — and a nasty recession, just when we can least afford it.

So this video is my attempt — with a big red dog, and Superman, and Batman — to get back to what really matters, and to try to underscore something quite interesting, which has been lost in the politics, which is that in terms of the deficit, both Obama and Boehner want something very similar. The deficit is big now — about $1.1 trillion — and they both want it to come down by roughly $200 billion, which is much less than what will happen automatically if they do nothing. In that case, the deficit would plunge by a disastrous $500 billion or so.

Deficits are a good thing, in terms of economic stimulus, and taking away a large deficit too quickly is a great way of causing a recession. I do understand that at some point deficits become a bad thing, especially if the bond markets decide that there’s a real question mark over whether all that borrowing can ever be repaid. But we’re not at that point yet. So it falls to Barack Obama and John Boehner to come together to prevent an entirely avoidable recession. They can do it, and they will do it. But we’ll have to suffer a lot of sturm und drang — not to mention gimmicky YouTube videos — before we get there.

Traffic is flowing in New York again this morning, for four reasons. First is the ban on private cars entering the island if they’re carrying fewer than three people. Second is the subways, which have started working again, in a limited manner. Third is a noticeable increase in bicyclists, even between yesterday and today: I have real hope that Sandy might persuade a whole swath of new people that bike commuting is incredibly fast and easy. And then there’s a much more mundane fourth reason: people are running out of gas.

With much critical infrastructure still out, many gas stations don’t have electricity to pump gas, and most of the rest — at least in New York and New Jersey — have sold out, as people filled up not only their cars but any other vessels they could find. Gasoline is precious right now: it powers generators which pump out flooded buildings, as well as powering the one form of transportation which is capable of getting stuff from Brooklyn or New Jersey into Manhattan. As for when new supplies might arrive, that’s extremely vague, but the consensus seems to be Saturday.

There’s something self-fulfilling about gas shortages: they’re the crisis equivalent of a bank run. So long as everybody just goes about their day in a normal manner, refilling their tank only when they get low, everything goes smoothly. But when people start thinking that there might not be enough to go around, everybody panics and rushes to the stations: while shortages in New Jersey have real Sandy-related causes, shortages in places like Westchester are essentially the product of self-fulfilling fears.

The standard econowonk response to such things (see e.g. Yglesias, or for that matter Uber, which has reverted to “surge pricing”) is that if the market were just left to its own devices, none of this would happen. Prices fluctuate in response to changes in supply and demand, so when supply goes down and demand goes up, it’s only natural that they should rise to the point at which demand starts falling off and the two finally meet again. At that point, the gas stations will still sell most of their gas, but there won’t be massive lines at the pump, and there will always be gas — at a price — for those who really need it.

It doesn’t help matters that such arguments tend to come from the kind of people who can afford to pay extra for their essentials. Crises always hit the poor worse than the rich, even when prices don’t rise: in my own NYC neighborhood, for instance, there is tragic human suffering right now, even as I have a warm and comfy office to go to, a group of rich friends with spare rooms, and enough money to pay for a hotel or Airbnb room should I need it. If the Lower East Side’s handful of open bodegas started price-gouging just because they had a captive audience, that would only exacerbate the situation — quite aside from the fact that it would also open them up to the very real risk of grievous bodily harm.

At times like this, the charitable impulse, of helping out where and when you can, is very strong: hence the articles with headlines like “Donate to Hurricane Sandy Victims with a Simple Text Message”. Even as gas stations are running dry, individuals across the northeast are siphoning out gas from their cars’ tanks to provide fuel for people who need it more than they do. They’re not charging a market-clearing price for doing so: in fact, they’re not charging any money at all. Multiplied thousands of times, such small individual acts of charity make a huge difference.

Meanwhile, during a crisis, the opportunity costs involved in sitting in a long line for gas actually fall substantially. Yglesias is right that price-gouging would reduce those costs, but they are the least of the damage that a storm like this causes. Much more important is the feeling that your neighbors are rallying together at a very hard time. If we all run out of gas, we’ll all run out of gas. But we won’t try to profiteer from that, and we’ll try to use it in as effective a way as possible, rather than just letting it get acquired by whomever happens to be most price-insensitive.

That’s why there’s something a bit distasteful about Uber’s insistence that the only way they can provide a good service these days is by charging more money. The cost of gas has not gone up: either their drivers can find the gas to drive people around or they can’t. The drivers, for their part, already make good money from Uber, whose prices are high; doubling those prices seems excessive, especially when there’s a strong impulse at times like these to help people out without charging any money at all.

I’m not taking a position here on price-gouging laws: while I don’t like the practice, I’m also not convinced that it should be made illegal. But the fact is that the benefits of price-gouging tend to accrue to a handful of merchants and the price-insensitive rich, while the costs are borne by those who can least afford it. ‘Twas always thus, or course, but during a crisis, especially, it’s a good idea to try to minimize such mechanisms, rather than trying to encourage them.

Daniel Friedman has a question:

There are now a few companies — Upstart and Lumni to name two — trying to create a market where we can invest in people in exchange for a percentage of future income. If they succeed and reach scale, will student debt problems be alleviated? Will our future incomes be reliably predicted by newly developed algorithms? Will it encourage increased risk-taking?

The first thing to note here its that this is a market which does not exist. Lumni tried to gin up some interest in it and failed; at this point they won’t even return my calls or emails. Upstart has a bunch of high-profile venture backing (Google Ventures, Kleiner Perkins), and has even managed to launch a pilot with a few hand-picked students and investors. But it’s still very, very early days. Equity-in-people is an idea which comes around occasionally, but so far it has never really taken off, and there’s not much reason to believe that this time is different.

But still, it’s an interesting question: what would the consequences be if Upstart, and/or companies like it, became big and successful?

Firstly, Friedman asks, would student-debt problems be alleviated? The answer to this one, I think, is quite clearly no, for two reasons. The main reason is that tuition fees are induced, in much the same way that traffic is. If you build a nice big new road, traffic will appear to fill it up. And if you build a nice new source of funding for students, universities will raise their tuition fees so as to capture as much of that funding as possible. Yes, high student debt is a consequence of high tuition fees — but at the same time, high tuition fees are a consequence of the ready availability of student loans.

It’s worth pointing out here that Upstart’s model gives out funds at the end of a student’s four-year education, rather than at the beginning. If the student has lots of debt, and wants less debt, then she can use the funds to pay down some of that debt. But many students will choose to spend the money in other ways, simply layering the new equity funding on top of their old debt funding. Alternatively, if the expectation is that students will use their Upstart funds to pay down debt, then that only means, at the margin, that lenders will feel free to extend even more credit in the run-up to the early cash-out.

The other reason why student-debt problems won’t be alleviated is that Upstart funds are debt, if you look hard enough. The documentation is subject to change, but at heart would-be Upstarts are always going to find something along the lines of this in any Upstart contract:

YOU UNDERSTAND AND ACKNOWLEDGE THAT THE FUNDING AMOUNT YOU RECEIVE FROM US, IS A DEBT TO US.

The debt is not a typical loan, of course, and it can end up being repaid at less than face value, if the Upstart enters a poorly-remunerated career. But it’s still a debt. And if the student ends up defaulting on that debt, the penalties are generally enormous. When people take out loans, they nearly always have the best of intentions, and don’t think there’s any way they will end up defaulting — especially if the repayment amounts are tied to their income. But defaults happen. And when they do, anybody who has defaulted to Upstart is going to find out the hard way that Upstart loans are the most expensive of them all.

So at the margin, these kind of schemes are likely to exacerbate the student-loan problem: they’re hurting, rather than helping. Remember that ultimately the money for these schemes is coming from investors, who are taking a substantial risk and being promised returns significantly greater than anything seen in the debt markets. Remember too that a significant portion of the students will end up repaying less than they’re originally given — because they go into low-paying occupations, perhaps, or maybe because they just decide they’d rather settle down and have a family instead of a career. As a result, those students who do go into decently-paying careers will end up repaying sometimes double or triple the amount of money they were originally given. That doesn’t seem like an alleviation of student debt problems to me — not when we’re talking about sums in the $30,000 range. It sounds like piling an extra $60,000 of liabilities on top of all the existing student loans you might have.

Friedman’s second question is whether companies like Upstart will start being able to predict students’ future incomes. That’s certainly something that Upstart is spending quite a lot of time on, but I think the effort is premature: first you need to find out whether students are happy repaying the funds at all. And I, for one, don’t think that Upstart’s algorithms are going to be particularly good at predicting incomes.

For one thing, the students with predictable incomes — the doctors and lawyers and the like — are never going to accept Upstart’s offer. For another, there will always be a certain number of students who are looking to game the system. All these schemes have an adverse-selection problem: Upstart funding is going to be much more attractive to students who are pretty sure they’re never going to make much money. If you aspire to being a part-time primary-school substitute teacher, for instance, while spending the rest of your time working on the Great American Novel, then Upstart might be great for you — and it’s unlikely that any algorithm would be able to capture that.

What’s more, the biggest risk, from Upstart’s point of view, is that they’ll end up funding a student who marries someone very successful, gets pregnant pretty early on, and then never returns to the workforce. This still happens frequently enough that an honest algorithm would charge higher interest rates to women than to men. As a result, the algorithm can’t actually be honest.

Finally, there’s the group of students who want to follow the Silicon Valley dream and become entrepreneurs straight out of college. That’s generally a great time to found a company, and Upstart (slogan: “The startup is you“) is positively encouraging such people. But equally, the chances that any given person will have success as an entrepreneur are pretty much random: such things come mostly down to luck, and can’t be reduced to some algorithm. Especially when the really successful entrepreneurs are going to be the ones who can afford lawyers to shield their income from Upstart.

There is no algorithm which can tell you who’s going to be a successful entrepreneur and who isn’t. Some college dropouts are college dropouts; other college dropouts are Steve Jobs, or Bill Gates, or Mark Zuckerberg. Being dyslexic is generally not a great thing when it comes to total lifetime income, and yet dyslexics are massively overrepresented among highly-successful CEOs. If you’re looking for outliers — and successful entrepreneurs, pretty much by definition, are all outliers — then you can’t really start generalizing.

Friedman finishes by asking if this model will encourage increased risk-taking. I think the answer there depends on what you mean by risk-taking. It certainly encourages people to accept low-paying jobs with payoffs which get put into corporate shell vehicles or which don’t end up cashing out for a decade. And at the other end of the spectrum, it encourages people to take low-paying jobs which pay non-financial dividends: ski instructor, say. But in general, I don’t think that a new form of private income tax is a great way to encourage innovation. Generally, if you start taxing something, you get less of it, not more of it. And I see no reason why this model should work out any differently.

This morning, Nassim Taleb returned to Twitter, posting one of the technical appendices to his new book. And immediately he got into a wonderfully wonky twitterfight/conversation with Daniel Davies.

I don’t pretend to understand all the subtleties of the conversation between the two, but, for Tom Foster, here’s an attempt. Davies has promised a Crooked Timber post on other parts of the appendix; I’m really looking forward to that.

Today, September 11, is a day that all New Yorkers become hyper-aware of tail risk — of some monstrous and tragic disaster appearing out of nowhere to devastate our city. And so it’s interesting that the NYT has decided to splash across its front page today Mireya Navarro’s article about the risk of natural disaster — flooding — in New York.

Beyond the article’s publication date, Navarro doesn’t belabor the point. But in terms of the amount of death and destruction caused, a nasty storm hitting New York City could actually be significantly worse than 9/11. Ask anybody in the insurance industry: a hurricane hitting New York straight-on is the kind of thing which reinsurance nightmares are made of. And as sea levels rise in coming decades, the risks will become much worse: remember, it’s flooding from storm surges which causes the real devastation, rather than simply things blowing over in high winds.

So, what can or should be done? One option is to basically attempt to wall New York City off from the Atlantic Ocean:

A 2004 study by Mr. Hill and the Storm Surge Research Group at Stony Brook recommended installing movable barriers at the upper end of the East River, near the Throgs Neck Bridge; under the Verrazano-Narrows Bridge; and at the mouth of the Arthur Kill, between Staten Island and New Jersey. During hurricanes and northeasters, closing the barriers would block a huge tide from flooding Manhattan and parts of the Bronx, Brooklyn, Queens, Staten Island and New Jersey, they said.

Needless to say, this solution is insanely expensive: the stated price tag right now is $10 billion — well over $1,000 per New Yorker — and I’m sure that if such a project ever happened, the final cost would be much higher. And such barriers don’t last particularly long, either. London built the Thames Barrier in 1984, and there’s already talk about when and how it should be replaced. And building a single barrier across the Thames is conceptually and practically a great deal simpler than trying to hold back the many different ways in which the island of Manhattan is exposed to the water.

What’s more, there’s an environmental cost associated with barriers, as well as a financial cost. Which cuts against the kind of things which New York has been doing. They’re smaller, and much less robust. But they improve the environment, rather than making it worse. And they’re relatively cheap. For instance: installing more green roofs to absorb rainwater. Expanding wetlands, which can dampen a surging tide, even in highly-urban places like Brooklyn Bridge Park. Even “sidewalk bioswales”. (I’m a little bit unclear myself on exactly what those are, but they sound very green.)

Adam Freed, the outgoing deputy director of New York’s Office of Long-Term Planning and Sustainability, talks about making “a million small changes”, while always bearing in mind that “you can’t make a climate-proof city”. That’s a timely idea: we can’t make New York risk-free, and it’s not clear that it would make sense to do so even if we could. After all, as we all learned 11 years ago today, it’s impossible to protect against each and every source of possible devastation.

Other cities have similar ideas:

In Chicago, new bike lanes and parking spaces are made of permeable pavement that allows rainwater to filter through it. Charlotte, N.C., and Cedar Falls, Iowa, are restricting development in flood plains. Maryland is pressing shoreline property owners to plant marshland instead of building retaining walls.

Still, all of this green development does feel decidedly insufficient in comparison to the enormous risks that New York is facing. I like the idea of a “resilience strategy”, but there are still a lot of binary outcomes here, especially when it comes to tunnels. Either tunnels flood or they don’t — and if they do, the consequences can be really, really nasty. Imagine a big flood which took out all of the subway and road tunnels into Manhattan, or even just the subway tunnels across New York Bay as well as the Holland Tunnel. As such a flood becomes more likely, the cost of protecting against it with some big engineering work — insofar as such a thing is possible — becomes increasingly justifiable.

And this is just depressing:

Consolidated Edison, the utility that supplies electricity to most of the city, estimates that adaptations like installing submersible switches and moving high-voltage transformers above ground level would cost at least $250 million. Lacking the means, it is making gradual adjustments, with about $24 million spent in flood zones since 2007.

Lacking the means? What is that supposed to mean? New York City has a credit rating of Aa1 from Moody’s; ConEd has a crediting rating of A3. Interest rates are at all-time lows. There has never been a better time to invest a modest $250 million in helping to ensure that New York can continue to have power in the event of a storm. Doing lots of small things is all well and good, and I’m not convinced that the huge things are necessarily worthwhile — or even, in the case of moving people to higher ground, even possible. But the medium-sized things? Those should be a no-brainer right now.

There are two ways in which the national employment situation influences the election. The first is, simply, the effect of unemployment and underemployment on America’s animal spirits. People who are unemployed, or who are so discouraged that they’re not even looking for work any more, don’t tend to be very happy with their lot, and as a result are more likely to vote against the current president. It may or may not be fair, but the president does get blamed for current economic conditions, and arguments about first derivatives (“it’s bad, but it’s getting better”) or counterfactuals (“it’s bad, but it’s better than it would have been under the other guys”) tend to be pretty unpersuasive to voters.

On this level, today’s employment report is pretty gruesome. According to the establishment survey, employers added just 96,000 jobs this month — less than the amount needed just to keep up with population growth. According to the household survey, the size of the civilian labor force shrank by 368,000 people last month. And the number of people not in the labor force grew by an absolutely massive 581,000.

Right now, the proportion of Americans with a job is lower than it has been in over 30 years. America’s getting older, and you’d expect the number to be falling — but it shouldn’t be falling nearly as fast as this. We’re well below trend, when it comes to the employment-to-population ratio, and that’s really bad for the economy as a whole: it means we have fewer productive workers, and as a result the country is creating much less wealth than it could be creating if more people had jobs. At the margin, of course, anything that depresses the amount of wealth in the country is bad for the incumbent president.

So anybody trying to use the jobs report to handicap the result of the election should probably see a tick down, this morning, in the chances of Obama’s re-election. My feeling is, however, that the size of the tick is likely to be very small. These things depend much more on levels than on deltas, and in any case the current electorate is more polarized than ever, with political convictions which are hard to shake.

Which brings me to the second way that employment affects electoral outcomes. The employment numbers are reported, on the first Friday of every month, and political parties try to use the numbers to their best advantage. On this front, there’s really only one number that matters, and that’s the headline unemployment rate. Financial types care more about the payrolls number, because it’s more accurate and less fuzzy. The unemployment rate, by contrast, is harder to calculate, and is based on the idea that you’re only unemployed if you’re looking for work. But the fact is that from a rhetorical perspective, the unemployment rate is the thing which counts. And so in terms of the optics of today’s report, it’s good for Obama, just because the unemployment rate fell — to 8.1% this month from 8.3% last month and 9.1% a year ago.

That’s still well above the 7% at which the psephologists will tell you that it’s very hard for an incumbent to get reelected. And it still starts with an 8 — although there’s now a small chance that on the day we actually vote, the unemployment rate might start with a 7. But the Republicans can’t say that the unemployment rate is rising, and the Democrats can say that it is falling. Will that change votes? Again, not very many. But insofar as arguments have an effect on elections, this report — bad though it is — has failed to give the Republicans the kind of rhetorical ammunition they might have hoped for.

Underlying both of these dynamics is the way in which the story of discouraged workers — people falling out of the labor force entirely — has become increasingly important, to the point at which it makes the headline unemployment rate much less useful as an economic indicator. Once upon a time, if you didn’t have a job, you fell into one of two categories: either you didn’t want to work, or else you were looking for work. Nowadays, however, there’s a huge third category of discouraged workers who would love a job but don’t even see the point of looking any more.

The Bureau of Labor Statistics has an interesting-if-obscure data series called “labor force status flows”. Most of the people interviewed in the survey measuring the unemployment rate, it turns out, were also interviewed the previous month. So it’s possible to look at the number of people, on a month-to-month basis, who were unemployed last month and who were no longer in the labor force this month. Historically, that number has been somewhere between 1.5 million and 2 million per month, on a seasonally-adjusted basis. But when the recession hit, it spiked to more than 2.5 million, and even more than 3 million at the peak. And it’s still extremely high.

It’s natural for lots of unemployed people to move out of the labor force each month: the Boomers are retiring, after all. But a glance at this chart is all it takes to see that we’re well outside normal territory, and that we’re still seeing millions of people leave the labor force not because they want to but because they feel that there’s simply no point in looking for work any more. I don’t know when or whether this line will come back down to its historical levels. But so long as it’s as elevated as this, the Federal Reserve has its work cut out. Because it means that even if the unemployment rate comes down substantially, we still won’t have really reached full employment — not unless the size of the labor force increases substantially at the same time.

There are those who believe that the length of a mathematical paper is inversely proportionate to how interesting it is. Something similar can be said about the new paper — short and absolutely first-rate — from Steve Hanke and Nicholas Krus, entitled “World Hyperinflations“. It’s technically 19 pages long, but the first 12 are basically just throat-clearing, and the last two are references. The meat is the five pages in the middle: three pages of tables, and another two of footnotes, detailing every instance of hyperinflation that the world has ever seen.

Hyperinflation, here, has a clear quantitative definition: prices rising by at least 50% per month. (Remember that, the next time some scaremonger starts talking about how US monetary policy risks causing hyperinflation.) And after some three years’ work, Hanke and Krus have managed to come up with an exhaustive list of every hyperinflationary episode in history — 56 in all, or 57 if you include North Korea in early 2010, where the data aren’t solid enough to merit inclusion in the list.

Every entry gets its own footnote, and while there are a lot of relatively easy-to-obtain IMF publications in there, there’s also no shortage of much more obscure source material: Simeun Vilendecic’s Banking in Republika Srpska in the late XX and early XXI century, for instance, or Abram van Heyningen Hartendorp’s 1958 History of Industry and Trade of the Philippines.

The earliest hyperinflation on the list came in France, at the end of the 18th Century, when inflation hit a monthly rate of 304% in mid-August 1796. The famous Weimar hyperinflation in Germany is pegged as taking place between August 1922 and December 1923; it reached a monthly peak of 29,500% in October 1923, with prices increasing at 20.9% per day, and doubling every 3.7 days. And the longest period of hyperinflation comes in Greece, which saw hyperinflation for a whopping 55 months, from May 1941 to December 1945. There’s no particular reason, looking at this list, why Germany should have been particularly scarred by hyperinflation, to the point at which it fiercely attacks even the possibility of relatively modest inflation, where France and Greece (not to mention Hungary or China or Argentina) have been much less deeply affected.

There is, however, a very strong correlation between the length of time that a period of hyperinflation goes on, and the levels that it can reach at its height. If you look at the top six hyperinflations on the list — which include both Germany and that 55-month period in Greece — all but one lasted for longer than a year. Meanwhile, five of the bottom six hyperinflations took place in just a single month, with the sixth lasting just three months.

At their highest, the numbers start to beggar the imagination: in mid-November 2008, for instance, inflation in Zimbabwe reached a monthly rate of 79,600,000,000%. That’s 79 billion percent per month. At that rate, prices pretty much double every day. And Zimbabwe doesn’t even manage to grab the top spot: in July 1946, Hungary saw hyperinflation of 41,900,000,000,000,000%. That’s 42 quadrillion percent in one month, with prices doubling every 15 hours.

The real value of this paper is its exhaustive nature. By looking down the list you can see what isn’t there — and, strikingly, what you don’t see are any instances of central banks gone mad in otherwise-productive economies. As Cullen Roche says, hyperinflation is caused by many things, such as losing a war, or regime collapse, or a massive drop in domestic production. But one thing is clear: it’s not caused by technocrats going mad or bad.

For that matter, there are no hyperinflations at all in North America: the closest we’ve come, geographically speaking, was in Nicaragua, from 1986-91. In fact, if you put to one side the failed states of Zimbabwe and North Korea, there hasn’t been a hyperinflation anywhere in the world since February 1997, more than 15 years ago, despite the enormous number of heterodox central-bank actions in that time.

All of which is to say that hyperinflation, in and of itself, really isn’t anything to worry about. It’s pretty much impossible to predict — and if your country has hyperinflation, it almost certainly has even bigger other problems. In fact, I’d hesitate to categorize hyperinflation as a narrowly economic phenomenon at all, as opposed to simply being a symptom of much bigger failures at the geopolitical level. Those failures are exacerbated by hyperinflation, of course: there’s very much a vicious cycle in these episodes. But you only ever find hyperinflation under extreme conditions, and, with a single exception (Peru), I’m not even sure I can find any genuine democracies on this list.

Update: As many people have helpfully pointed out, Weimar can definitely be considered a genuine democracy, even if it was suffering extraordinary geopolitical burdens.

Bob Litan, formerly of the Kauffman Foundation and the Brookings Institution, has recently taken up a new job as director of research for Bloomberg Government, where he’s going to have to be transparent and impartial. But one of his last gigs before moving to Bloomberg — a paper on the subject of people borrowing money from their 401(k) accounts — was neither of those things.

To understand what’s going on here, first check out Jessica Toonkel’s article from Friday about Tod Ruble and his company, Custodia.

Tod Ruble is trying to sell retirement plan insurance that employers say they do not want and their employees may not need.

But the Dallas-based veteran commercial real estate investor is not letting that stop him. Since late 2010, he has started up a company, Custodia Financial, and spent more than $1 million pushing for legislation that would allow companies to automatically enroll employees who borrow from their 401(k) plans in insurance that could cost hundreds of dollars a year.

Once you’ve read that, go back and check out a spate of stories that hit a series of major news outlets in July. Alan Farnham of ABC News, for instance, ran a story under the headline “401(k) Loan Defaults Skyrocket”:

A new study estimates that such defaults might total $37 billion a year, a sharp increase from 2007, when defaults totaled only $665 million.

Similarly, check out Walter Hamilton, in the Chicago Tribune (and LA Times): the headline there is “Defaults on 401(k) loans reach $37 billion a year”. At Time, Dan Kadlec also ran with the $37 billion number, saying that “the default rate on these loans has skyrocketed since the recession”. Similar stories came from Blake Ellis at CNN Money (“Loan defaults drain $37 billion from 401(k)s each year”), Mitch Tuchman at MarketRiders (“401k Loan Default Time Bomb Is Ticking”), and many others.

The only hint of skepticism came from Barbara Whelehan at BankRate. She noted that the study cited Kevin Smart, CFO of Custodia Financial, as a source — and she also noted that “it would be a boon for the insurance industry to get the rules changed, and it is working behind the scenes to do just that. In April, Custodia Financial submitted a statement to the House & Ways Committee arguing for automatic enrollment into insurance coverage for 401(k) loans.”

Whelehan also smelled something fishy in the way the paper was paid for:

This paper by Navigant Economics, which made a big splash in the press, was financially supported by Americans for Retirement Protection. That organization has a website, ProtectMyRetirementBenefits.com, but no “about us” link. It does give you the opportunity to sign a petition demanding protection of retirement funds through insurance. Take a look at it, and see if you think the website was created by average Americans or by the insurance industry.

Whelehan was actually breaking news here: there’s no public linkage between Americans for Retirement Protection, the organization which paid for the paper, and the astroturf website. In fact, Americans for Retirement Protection seems to have no public existence at all, beyond a footnote in the paper, which was co-authored by Bob Litan and Hal Singer.

Enter Toonkel, writing her story about Custodia. In the course of her reporting, she discovered — and Custodia confirmed — that Americans for Retirement Protection, and ProtectMyRetirementBenefits.com, are basically alter egos of Custodia itself. Custodia would welcome other organizations joining in, but that’s unlikely to happen, because Custodia owns the patents on the big idea that the paper and the website are pushing — the idea that 401(k) loans should come bundled with opt-out insurance policies.

Once you’re armed with this information, it’s impossible not to look at the Litan-Singer paper in a very different way. Its abstract concludes: “We demonstrate that the social benefits of steering (but not compelling) plan participants towards insurance when they borrow are likely positive and economically significant.” And yet nowhere in the paper is there any indication that it was bought and paid for by the very company which has a patent on doing exactly that.

And what about that $37 billion number? Are defaults on 401(k) loans really as big a problem as the paper says that they are? After all, the smaller the problem, the less important it is to introduce an expensive fix for it.

The simple answer is no: 401(k) loan defaults are not $37 billion per year. But the fact is that nobody knows for sure exactly where they are, which makes it much easier to come up with exaggerated estimates. As the paper itself admits, “the sum total of 401(k) defaults ought to be an easily accessible statistic, but it is not”. And the $37 billion, far from being a good-faith estimate, in fact looks very much like an attempt to get the largest and scariest number possible.

So how did Litan and Singer arrive at their $37 billion figure? Let’s start with the only concrete numbers we have — the ones from the Department of Labor, whose most recent Private Pension Plan Bulletin gives a wealth of information about all private pension plans in the country. Every pension plan has to file something called a Form 5500, and the bulletin aggregates all the numbers from all the 5500s which are filed; the most recent bulletin gives data from 2009.

This bulletin has two datapoints which are germane to this discussion. First of all, there’s Table A3, on page 7 of the bulletin (page 11 of the PDF). That shows that loans from defined-contribution pension plans to their own participants totaled $51.7 billion in 2009. Secondly, there’s Table C9, the aggregated income statement for the year. If you look at page 32 of the bulletin (page 35 of the PDF), you’ll see a line item called “deemed distribution of participant loans”, which came to $670 million for the year. If you borrow money from your 401(k) and you don’t pay it back, then that money is deemed to have been distributed to you, and counts as a default. So we know that the official size of 401(k) defaults in 2009 was $670 million — a far cry from Litan and Singer’s $37 billion.

Now the $670 million figure does not account for all 401(k) defaults. Most importantly, in some situations, if you default on a 401(k) loan after having been fired from your job, then the money is counted as an “actual distribution” rather than as a “deemed distribution”.

The Litan-Singer paper goes into some detail about this. “According to a recent study by Smart (2012),” they write, “although Form 5500 reflects actual distributions, there is no way to determine the amount of actual defaults.” They then look in detail at Smart’s figures, footnoting him five consecutive times, and treating him as an undisputed authority on such matters. Their citation is merely “Kevin Smart, The Hidden Problem of Defined Contribution Loan Defaults, May 2012.”

Where might someone find this paper? Here, since you ask: it’s helpfully hosted at CustodiaFinancial.com. And on the front page of the paper, Kevin Smart is identified as the “Chief Financial Officer, Custodia Financial”.

There’s no indication whatsoever in the Litan-Singer paper that the “Smart” they cite so often is the CFO of Custodia Financial, the company which has the most to gain should their recommendation be accepted. And there’s certainly no indication that he’s essentially their employer: that Custodia paid them to write this paper. In fact, the name Custodia appears nowhere in the Litan-Singer paper at all.

It’s instructive to look at the Smart paper’s attempt to estimate the magnitude of the 401(k) default problem. I’ll simplify a little here, but to a first approximation, Smart assumes that 12% of people with 401(k) loans lose their jobs. He also assumes that if you lose your job when you have a 401(k) loan, there’s an 80% chance you’ll default on that loan. As a result, he comes up with a 9.6% default rate on 401(k) loans. He then multiplies that 9.6% default rate by total 401(k) loans of $51.7 billion, adds in some extra defaults due to death and disability, and comes up with a grand total of $6.2 billion in loan defaults per year, excluding the “deemed distributions” of $670 million. Call it $7 billion in total, of which $6 billion could be protected by insuring loans against unemployment, death, and disability.

Now remember that this is a paper written by the CFO of Custodia Financial — someone who clearly has a dog in this race. It’s in Smart’s interest to make the loan-default total look as big as possible, since the bigger the problem, the more likely it is that Congress will agree to implement Custodia’s preferred solution.

But when Litan and Singer looked at Smart’s paper, they weren’t happy going with his $6 billion figure. Indeed, as we’ve seen, their paper comes up with a number six times larger. So if even the CFO of Custodia only managed to estimate defaults at $6 billion, how on earth do Litan and Singer get to $37 billion?

It’s not easy. First, they double the total amount of 401(k) loans outstanding, from $52 billion to $104 billion. Then, they massively hike the default rate on those loans, from 9.6% to 17.9%. And finally, they add in another $12 billion or so to account for the taxes and penalties that borrowers have to pay when they default on their loans.

It’s possible to quibble with each of those changes — and I’ll do just that, in a minute. But it’s impossible to see Litan and Singer compounding all of them, in this manner, without coming to the conclusion that they were systematically trying to come up with the biggest and scariest number they could possibly find. It’s true that whenever they mention their $37 billion figure, it’s generally qualified with a “could be as high as” or similar. But they knew what they were doing, and they did it very well.

When the Chicago Tribune and the LA Times say in their headlines that 401(k) loan defaults have reached $37 billion a year, they’re printing exactly what Custodia and Litan and Singer wanted them to print. The Litan-Singer paper doesn’t exactly say that defaults have reached that figure. But if you put out a press release saying that “the leakage of funds in 401(k) plans due to involuntary loan defaults may be as high as $37 billion per year”, and you don’t explain anywhere in the press release that “leakage of funds” means something significantly different to — and significantly higher than — the total amount defaulted on, then it’s entirely predictable that journalists will misunderstand what you’re saying and apply the $37 billion number to total defaults, even though they shouldn’t.

But let’s backtrack a bit here. First of all, how on earth did Litan and Singer decide that the total amount of 401(k) loans outstanding was $104 billion, when the Department of Labor’s own statistics show the total to be just half that figure? Here’s how.

First, they decide that they need the total number of active participants in defined-contribution pension plans. They could get that number — 72 million — from the Labor Department bulletin: it’s right there in the very first table, A1. But the bulletin isn’t helpful to them, as we’ve seen, so instead they find the same number in a different document from the same source.

That’s as much Labor Department data as Litan and Singer want to use. Next, they go to the Investment Company Institute, which has its own survey, covering some 23 million of those 72 million 401(k) participants. According to that survey, in 2011, 18.5% of active participants had taken out a loan; Litan and Singer extrapolate that figure across the 401(k) universe as a whole.

Finally, Litan and Singer move on to Leakage of Participants’ DC Assets: How Loans, Withdrawals, and Cashouts Are Eroding Retirement Income, a 2011 report from Aon Hewitt which is based on less than 2 million accounts, of the 72 million total. According to the Aon Hewitt report, which doesn’t go into any detail about methodology, when participants took out loans, “the average balance of the outstanding amount was $7,860″. Needless to say, that number was never designed to be multiplied by 72 million, as Litan and Singer do, to generate an estimate for the total number of loans outstanding.

If you want an indication of just how unreliable and unrepresentative the $7,860 number is, you just need to stay on the very same page of the Aon Hewitt report, which says that 27.6% of participants have a loan. If Litan and Singer think that the $7,860 figure is reliable, why not use the 27.6% number as well? If they did that, then the total number of 401(k) loans outstanding would be $7,860 per loan, times 72 million participants, times 27.6% of participants with a loan. Which comes to $156 billion.

But of course we know that there were just $51.7 billion of loans outstanding in 2009; evidently Litan and Singer reckoned that it just wouldn’t pass the smell test if they tried to get away with saying that number might have trebled in a single year. So they confined themselves to merely doubling the number, instead.

Litan and Singer give no reason to mistrust the official $51.7 billion number, except to say that it’s “outdated”. But if it’s outdated, it’s only outdated by one year: it’s based on 2009 data, while the much narrower surveys that Litan and Singer cite are generally based on 2010 data. At one point, they cite the ICI survey to declare that there is “an estimated $4.5 trillion in defined contribution plans”, despite the fact that the much more reliable Labor Department report shows that there was just $3.3 trillion in those plans as of 2009. This, I think, quite neatly puts the lie to the Litan-Singer implication that the problem with the Labor Department numbers is merely that they are out of date, and that when we get numbers for 2010 or 2011, they might well turn out to be in line with the Litan-Singer estimates. There’s simply no way that total DC assets rose from $3.3 trillion to $4.5 trillion in the space of a year or two.

In other words, whatever advantage the ICI and Aon Hewitt surveys have in terms of timeliness, they more than lose in terms of simply being based on a vastly smaller sample base. Litan and Singer adduce no reason whatsoever to believe that the ICI and Aon-Hewitt surveys are in any way representative or particularly accurate, despite the fact that the discrepancies between their figures and the Labor Department figures are prima facie evidence that they’re not representative or particularly accurate. If the ICI and Aon Hewitt surveys were all we had to go on, then I could understand Litan-Singer’s decision to use them. But given that the Labor Department already has the number they’re looking for, it just doesn’t make any sense that they would laboriously try to recreate it using less-reliable figures.

It’s true that the Labor Department’s figures do undercount in one respect: they cover only plans with 100 or more participants — and therefore cover “only” 61 million of the 72 million active participants in DC plans. If Litan and Singer had taken the Labor Department’s numbers and multiplied them by 72/61, or 1.18, that I could understand. But disappearing into a rabbit-warren of private-sector surveys of dubious accuracy, and emerging up with a number which is double the size of the official one? That’s hard to justify. So hard to justify, indeed, that Litan and Singer don’t even attempt to do so.

That, indeed, is the strongest indication that the Litan-Singer paper can’t really be taken seriously. For all their concave borrower utility functions and other such economic legerdemain, they simply assert, rather than argue, that they “believe” it is “more appropriate” to use private-sector surveys rather than hard public-sector data. Such decisions cannot be based on blind faith: there have to be reasons for them. And Litan-Singer never explain what those reasons might be.

Now the move from public-sector to private-sector data merely doubles the total size of the purported problem, while Litan-Singer are much more ambitious than that. So their next move is to bump up the default rate on loans substantially.

There’s no official data on default rates at all, so Litan and Singer, following Smart’s lead, decide to base their sums on a Wharton paper from 2010. Once again, they have to extrapolate from a very small sample: the Wharton researchers had at their disposal a dataset covering 1.5 million plan participants (just 2% of the total). Looking at what happened over a period of three years, from July 2005 to June 2008, the researchers found that the number of terminations, and the number of defaults, remained pretty steady:

These are the numbers that Smart used in his paper: roughly 12% of loan holders being terminated each year, and roughly 80% of those defaulting on their loans.

But these are not the numbers that Litan-Singer use. Instead, they notice that the overall default rate, as a percentage of overall loans outstanding, was roughly double the national unemployment rate at the time. And so since the unemployment rate doubled after June 2008, they conclude that the default rate on outstanding 401(k) loans probably doubled as well.

Do they have any evidence that the default rate on 401(k) loans might have doubled after 2008? No. Well, they have a tiny bit of evidence: they look at the small variations in default rates in each of the three years covered in the Wharton study, and see that those variations move roughly in line with the national unemployment rate. Never mind that the default rate fell, from 9.9% to 9.7%, between 2006 and 2008, even as the unemployment rate rose, from 4.8% to 5.0%. They’ve still somehow managed to convince themselves that it’s reasonable to assume that the default rate today is nowhere near the 9.6% seen in the Wharton survey, and in fact is probably closer to — get this — 17.9%.

This doesn’t pass the smell test. The primary determinant of the default rate, in the Wharton study, was the percentage of loan holders who wound up having their employment terminated, for whatever reason. And so what Litan-Singer should be looking at is the increase in the probability that any given employee will end up being terminated in any given year.

Remember that in any given month, or year, the number of people fired is roughly equally to the number of people hired. When the former is a bit larger than the latter for an extended period, then the unemployment rate tends to go up; when it’s smaller, the rate goes down. But the churning in the employment economy is a constant, even when the unemployment rate is very low.

When the unemployment rate rose after 2008, that was a function of the fact that the number of people being fired was a bit higher than normal, while the number of people being hired was a bit lower than normal. But looked at from a distance, neither of them changed that much. In terms of the Wharton study, what we saw happening to the unemployment rate is entirely consistent with the percentage of loan-holders being terminated, per year, staying pretty close to 12%. Of course it’s possible that number rose sharply, but it’s really not possible that number rose as sharply as the unemployment rate did. And so I find it literally incredible that Litan and Singer should decide to use the national unemployment rate as a proxy for the number of people whose employment is terminated each year.

Well, maybe not literally incredible — the fact is there’s one very good reason why they might do that. Which is that they were being paid by Custodia to use any means possible to exaggerate the number of annual 401(k) loan defaults.

Litan and Singer do actually provide a mini smell test of their own: they say that their hypothesized rise in 401(k) loan defaults is more or less in line with the rise in, say, student-loan defaults or in mortgage defaults over the same period. But those statistics aren’t comparable at all, because Litan and Singer are already assuming that the default rate on 401(k) loans, among people who lose their job, was a whopping 80% before the financial crisis. There’s a 100% upper bound here: you can’t have a default rate of more than 100%. Remember that the whole point of this paper is to provide the case that people taking out 401(k) loans should insure themselves against unemployment: any rise in the default rate from people who don’t lose their job (or die, or become disabled) is more or less irrelevant here. And when your starting point is a default rate of 80%, there really is a limit to how much that default rate can rise; it’s certainly going to be difficult to see it rise by more than 85%, even if you allow a simultaneous increase in the number of people being terminated.

All of this massive exaggeration has an impressive effect: if you take $104 billion in loans, and apply a 17.9% default rate, then that comes to a whopping $18.6 billion in 401(k) loan defaults every year. A big number — but still, evidently, not big enough for Litan and Singer. After all, their number is $37 billion: double what we’ve managed to come up with so far. We’ve already doubled the size of the loan base, and almost-doubled the size of the default rate, so how on earth are we going to manage to double the total again?

The answer is that LItan and Singer, at this point, stop measuring defaults altogether, and turn their attention to a much more vaguely-defined term called “leakage”. Once again, they decide to outsource all their methodology to Custodia’s CFO, Kevin Smart. The upshot is that if you borrowed $1,000 from your 401(k) and then defaulted on that loan, the amount of “leakage” from your 401(k) is deemed to be much greater than $1,000. Litan and Singer first add on the 10% early-withdrawal penalty that you get charged for taking money out of your plan before you retire. They also add on the income tax you have to pay on that $1,000, at a total rate of 30%. (They reckon you’ll pay 25% in federal taxes, and another 5% in state taxes.) So now your $1,000 default has become a $1,400 default.

How does that extra $400 count as leakage from the 401(k), rather than just something that gets added to your annual tax bill? Smart explains:

Most participants borrow from their retirement savings because they are illiquid and do not have access to other sources of credit. This clearly demonstrates that participants who default on a participant loan do not have the financial means to pay the taxes and penalty. Unfortunately, their only source of capital is their retirement savings plan so many take the remaining account balance as an additional early distribution to pay the taxes and penalty, further increasing the amount of taxes and penalties due. These taxes and penalties become an additional source of leakage from retirement assets.

Smart’s 16-page paper has no fewer than 24 footnotes, but he fails to provide any source at all for his assertion that “many” people raid their 401(k) plans in order to pay the taxes on the money they’ve already borrowed. In any event, Smart (as well as Litan and Singer, following his lead) makes the utterly unjustifiable assumption that not only many but all 401(k) defaulters end up withdrawing the totality of their penalties and extra taxes from their retirement plan. And then, just for good measure, because that withdrawal also comes with a penalty and taxes, they apply a “gross-up” to that.

By the time all’s said and done, the $1,000 that you lent yourself from your 401(k) plan, and failed to pay back in a timely manner, has become $1,520 in “leakage”. Add in some extra “leakage” for people who default due to death or disability (apparently even dead people raid their 401(k) plans to pay income tax on the money they withdrew), and somehow Litan and Singer contrive to come up with a total of $37 billion.

It’s an unjustifiable piling of the impossible onto the improbable, and the press just lapped it up — not least because it came with the imprimatur of Litan, a genuinely respected economist and researcher. Custodia hired him for precisely that reason: they knew that if his name was on the front page of a report, that would give it automatic credibility. But for exactly the same reason, Litan had a responsibility to be intellectually honest when writing this thing.

Instead, he never even questioned any of the assumptions made by Custodia’s CFO. For instance: if you’re terminated, and you default on your 401(k) loan, what are the chances that the money you received will end up being counted as an “actual distribution” rather than as a “deemed distribution”? Smart and Litan and Singer all implicitly assume that the answer is 100%, but they never spell out their reasoning; my gut feeling is that it’s not nearly as clear-cut as that, and that it all depends on things like when you lost your job, when you defaulted, and who your pension-plan administrator is.

Custodia’s business, and the Litan-Singer paper, are based on the idea that if people who borrowed money from their 401(k) plans had insurance against being terminated from their jobs, then that would have significant societal benefit. In order for the societal benefit to be large, the quantity of annual 401(k) loan defaults due to termination also has to be large. But right now, there’s not a huge amount of evidence that it actually is: in fact, we really have no idea how big it is.

I can say, however, that Custodia has already won this battle where it matters — in the press. “Protecting 401(k) savings from job loss makes a lot of sense,” said Time’s Kadlec in his post — and so long as Custodia can present lawmakers with lots of headlines touting the $37 billion number and supporting their plan, Litan and Singer will have done their job. The truth doesn’t matter: all that matters is the headlines, and the public perception of what the truth is.

Come to think, maybe this makes Litan the absolutely perfect person to run the research department at Bloomberg Government. On the theory that it takes a thief to catch a thief, Bloomberg has hired someone who clearly knows all the tricks when it comes to writing papers which come to a predetermined conclusion. And he also has a deep understanding of the real purpose of most of the white papers floating around DC: it’s not to get closer to the truth, but rather to stamp a superficially plausible institutional imprimatur onto a policy that some lobbyist or pressure group desperately wants enacted. I can only hope that in the wake of using his talents in order to serve Custodia Financial, Litan will now turn around and use them in order to serve rather greater masters. Like, for instance, truth, and transparency, and intellectual honesty.

Tim Harford is a fan of the clear way in which Alex Tabarrok has couched the debate — which started with a Tyler Cowen post back in January — about the desirability of intergenerational economic mobility. Or, in English, is it a good thing if quite a lot of poor people become rich?

The Marginal Revolution guys say that looking at economic mobility is overrated; Cowen, also in January, linked to a bunch of critics of that position, including John Quiggin, Brad DeLong, and Paul Krugman. Recently, DeLong resuscitated the discussion, and Krugman came back for a second go-round as well, all of which resulted in Cowen being rude about Krugman, and Tabarrok trying to clear things up.

Tabarrok’s post is indeed clear, but it’s clear in an invidious way. He basically starts with his conclusion, saying that if a high-mobility society has no better outcome, in general, than low-mobility society, then there’s not very much to choose between them. And similarly, he says, if both a high-mobility society and a low-mobility society have the same very good outcome, then again there’s not much to choose between them.

But this obtusely misses the fundamental reason why high mobility is a good thing: that it improves outcomes. A sclerotic society where no rich people become poor and where no poor people become rich is never going to be a hive of creative destruction. Cowen even comes close to admitting this, when he says that “if the general standard of living is rising, mobility takes care of itself over time” — except he has the causality largely backwards. If you have lots of social mobility, then the general standard of living is going to go up: you’ll have lots of poor people becoming richer, and you’ll also have the rich protecting their downside, in the likely event that they become poorer, by doing their best to improve the lot of the poor.

So when Cowen talks about economic mobility not mattering much “for a given level of income”, or when Tabarrok talks about “some simple societies” with fixed levels of income, they’re taking the variable in the equation and they’re turning it into a constant. What they should be doing is looking at two societies, equal in all respects except that one is high-stasis and the other is high-churn, then fast-forwarding to see which one turns out better. The answer, of course, is the high-churn society — which means, working backwards, that if you want growth, you also want social mobility.

As a result, it’s reasonable to conclude that anything which impedes social mobility — like rising inequality, say — also impedes growth. The effect might not be huge, but it’s there. And the only way not to see it is to effectively assume your conclusions.

Michael Kinsley tackles outsourcing today, complaining that Barack Obama is a protectionist who doesn’t understand its value, and that Mitt Romney is keener to pander to protectionists than he is to defend free-market principles. He writes:

Romney or Obama? “I don’t want the next generation of manufacturing jobs taking root in countries like China or Germany.” Early in the Republican primary campaign, China was the one subject Romney seemed genuinely agitated about. Imposing tariffs on Chinese goods was on the long list of things Romney said he was going to do on Day One of his presidency. Maybe he still is, but he doesn’t play it up the way he used to.

Meanwhile, if Romney is a free trader at heart, faking a bit of protectionism, Obama seems to be a protectionist at heart, faking a belief in free trade. That quote in the previous paragraph is from Obama, and shows a fundamental misunderstanding of how markets work. Trade is not a zero-sum game. There isn’t a certain number of manufacturing jobs that will either go to China or Germany, or come to us. We want China and Germany to have lots of manufacturing jobs. The more they have, the richer they are, the better off we will be as well. Beggar-thy-neighbor policies don’t work.

Kinsley is probably right on the politics, here, but he’s wrong on the economics. Here’s Obama’s quote, in context:

I was able to sign trade agreements with Korea and Colombia and Panama so our businesses can sell more goods to those markets. That’s why I’ve fought for investments in schools and community colleges, so that our workers remain the best you’ll find anywhere, and investments in our transportation and communication networks, so that your businesses have more opportunities to take root and grow.

I don’t want America to be a nation that’s primarily known for financial speculation and racking up debt buying stuff from other nations. I want us to be known for making and selling products all over the world stamped with three proud words: “Made in America.” And we can make that happen. (Applause.)

I don’t want the next generation of manufacturing jobs taking root in countries like China or Germany. I want them taking root in places like Michigan and Ohio and Virginia and North Carolina. And that’s a race that America can win.

This, it seems to me, is an entirely coherent economic policy if what you’re trying to do is maximize the number of good working-class jobs in America. There’s no doubt that US employment, as a whole, is on a long-term secular trend away from goods and towards services. And at the same time, the two countries with the world’s biggest trade surpluses — China and Germany — are precisely the two countries with the healthiest manufacturing industries. What’s more, neither of them is suffering a jobs crisis.

So the question arises: should the US continue to accept the Ricardian bargain whereby it concedes to China and Germany the comparative advantage in manufacturing, while keeping for itself the comparative advantage in borrowing-to-consume and constructing synthetic CDOs? The answer is no, and not only because there’s something hollow and dangerous about an economy which is too reliant on financial whiz-bangery. There’s something more important at stake here, and that’s employment.

US manufacturing in fact is extremely competitive on a global scale; the problem is that output has lagged productivity improvements, with the result that we’re making more stuff with ever fewer people.

There’s no particular reason why that should be the case: when manufacturers in China and Germany become more efficient, that’s their sign to employ more people, rather than fewer. As each employee becomes increasingly profitable, it makes perfect sense to keep on adding more employees. Or at least it does in some countries. In the US, by contrast, capital is cheap and plentiful, and there’s much more incentive here to replace people with capital goods wherever possible.

But at that point, why even invest the money in the manufacturing industry at all? Everything becomes a question of opportunity cost, and if you can get higher returns in say the financial sector, then the rational thing to do is to start an investment bank, make lots of money from your trading desk, and then take the proceeds and spend them on manufactured goods from China and Germany. That’s how markets work: goods and money become interchangeable, and if you have money then you don’t need to be able to actually make things any more. Money gives you all the competitive advantage you need.

Except, that’s a strategy which works until it doesn’t. I’m reminded of this bit from Kurt Eichenwald’s piece on Microsoft’s Steve Ballmer in the latest Vanity Fair:

The Microsoft CEO used to proclaim that it would not be first to be cool, but would be first to profit — in other words, i would be the first to make money by selling its own version of new technologies. But that depended on one fact: Microsoft could buy its way into the lead, because it always had so much more cash on hand than any of its competitors.

No more. The advantage that Ballmer relied on for so long is now nonexistent. Google has almost the same amount of cash on its books as Microsoft — $50 billion to Microsoft’s $58 billion. Apple, on the other hand, started the year with about $100 billion. Using superior financial muscle won’t work for Microsoft or Ballmer anymore.

A technology company’s ability to innovate is not a bad metaphor for an economy’s ability to manufacture things and employ people while doing so. If it’s lacking, then for a certain amount of time that hole can be patched with money. But not forever.

And so I think that Barack Obama’s push to bring manufacturing employment back to Michigan and Ohio and Virginia and North Carolina makes all the sense in the world. Trade is not a zero-sum game — Kinsley is right about that — but at the same time that’s no reason to feel sanguine when you see good working-class jobs get exported to countries where the idea of building a blue-collar career in the manufacturing sector is still a perfectly sensible and reasonable one. America does not have a jobs crisis among college graduates, even if the employment situation for recent graduates right now is grim. It does have a jobs crisis in areas where factories have closed and industrial skills are no longer valued.

If you run a company, one of your jobs is to ensure that your company’s money isn’t wasted. And similarly, if you run an economy, one of your jobs is to ensure that your country’s labor force isn’t wasted. There are far too many Americans, right now, who could be working and aren’t. That’s downright inefficient. Their skills are well suited to the manufacturing industry. And so, if new manufacturing jobs are to be created, somewhere in the world, it makes a huge amount of sense that they be created in places like Michigan and Ohio and Virginia and North Carolina: that’s where the low-hanging fruit lies, in terms of hard-working employees with enormous potential productivity gains.

Kinsley’s right that we want China and Germany to have manufacturing jobs. But here’s the thing: China and Germany have manufacturing jobs. New manufacturing jobs, at least in the short term, should move where there’s both a shortage of such things right now, and a large potential labor force willing to get to get to work tomorrow. Certainly it’s the job of the president to encourage precisely that. And if he succeeds, he will have built a powerful economic engine in a part of America which is not doing well at the moment.

Note that Obama talked about bringing those jobs to America not in any protectionist context, but rather in the context of a series of free trade agreements which, at the margin, make outsourcing easier rather than harder. His goal is not to steal jobs from elsewhere, but rather to make America a place where the infrastructure and workers are so attractive that companies around the world decide to source their manufacturing here. No one cares, any more, about the nationality of the employers in these states: a job is a job, whether your employer is American or Brazilian or Swedish.

The computer I’m writing this on was made by an American company in China, but there’s no particular reason why other items in my household shouldn’t be made by a Chinese company in America. If the US can create the conditions for that to happen — if Chinese companies voluntarily move some of their manufacturing here because that’s how effective the US manufacturing sector has become — then everybody wins. That’s what Obama wants. And wanting that requires no misunderstanding whatsoever of how markets work.

Brian Chen has the news today that Uber is rolling out a cheaper version of its service:

Uber’s convenience comes with a cost. People are paying not just for the service, but also the gas used by the big sedans. That’s where hybrid vehicles will help bring down the price: drivers will spend less time and money fueling up…

In San Francisco, for example, the hybrid cars will cost $5 for the base fee, and then $3.25 a mile after that. By contrast, the town cars cost $8 for the base fee and then $4.95 a mile.

A quick back-of-the-envelope calculation shows that this has very little to do with the amount of money that drivers spend fueling up. Compare a Prius (51 miles per gallon) to an Escalade (10 miles per gallon): if gas is $3.78 per gallon, that puts the cost of gas per mile at 7.4 cents for the Prius and 37.8 cents for the Escalade — a difference of 30 cents per mile. Whereas Uber’s price for the Escalade is a premium of $1.70 per mile.

What’s more, since the drivers of these cars can’t pick up hails on the street, they have a lot of downtime waiting for the next gig. As a result, it doesn’t really cost the Escalade driver extra money if she ends up having to refuel once a day rather than once a week. Obviously, the fuel costs are higher — but the opportunity cost of her time is negligible.

Here’s Chen:

The company convinced its car-service partners to buy a total of 50 hybrids just for customers coming through Uber — a sign that drivers are making money with the start-up.

But of course it’s more complicated than that. If drivers were happy with the money they were making with Uber, then they’d stick happily with what they’ve got. In order to be persuaded to switch over, they have to believe that they’ll make more money in a hybrid than they would in a sedan. And that’s despite the fact that “in general”, according to Uber’s Scott Munro, “hybrids will cost 30 to 40 percent less than Uber’s black town cars”.

If that’s the case, then if you compare a sedan driver and a hybrid driver, the hybrid driver will need to be making three trips for every two the sedan driver makes, just to end up with the same amount of money. In order for the hybrid to be more attractive than the sedan, and taking into account the fact that at the margin you’d rather make fewer trips than more trips, a typical driver would realistically be hoping to double the number of fares she was getting before she was happy switching to the cheaper car.

But I suspect that the real relationship here is not between Uber and its drivers, so much as it is between Uber and car-service companies. Any given driver might well prefer to continue driving a sedan, rather than being moved over to a hybrid. But the car-service companies make money on every fare, and so their best interest is served just by increasing the total number of fares, rather than the average income received per driver per day.

As a result, I suspect that this move is going to decrease Uber drivers’ take-home income, on average, rather than increase it. As you might expect, when prices drop. But it will increase income for both the car-service companies and for Uber itself — and it will increase the total number of Uber drivers.

It’s easy to sign up with Uber if you’re a company; much harder if you’re a single driver. The Uber model is that Uber contracts with the owners of capital, who then employ the labor needed to provide the service. And once again, the rich will end up making more, the not-rich will end up making less, and the rich will present the whole thing as a victory for all concerned.

But there’s something else going on here, too, which is the way that companies love to push the idea that we’re paying for extra costs, even when we’re not. Uber sedans are more expensive than Uber hybrids because Uber reckons that’s the way it can best maximize its revenues and profits — not because the sedans are significantly more expensive to drive. Another example of this? Gas stations which offer different prices for cash and credit.

I like this idea, in theory, because gas prices are the most salient prices in America: we’re much more conscious of how much gas costs than we are of how much anything else costs. And if the price for gas on credit is significantly more than the price for cash, then that will help drive home just how big those credit interchange fees are.

Except, gas stations have no particular reason to charge just the interchange fee as a premium. Is the difference 10 cents a gallon? That’s about 3%, which is at the high end of credit interchange fees. After that, it’s all just pure profit for the gas station — and sometimes the difference can be as much as 2 dollars a gallon.

That isn’t a condign surcharge; it’s price gouging. And even a relatively common 20-cent surcharge is basically a convenience or ignorance fee, a way of extracting extra money from people who don’t have the cash or who don’t realize how much extra they’re paying. The rate of paying-with-plastic ranges between 60% and 100%, which means that realistically what we’re talking about here is essentially a bait-and-switch: attract customers with a low headline price, and then charge them a higher one.

Part of modern life is the way in which we naturally gravitate towards easy and automatic ways of paying. If you give Uber your card number once, you never really need to pay at all; you just find the charge on your credit-card statement. It’s certainly convenient — but it also allows Uber to charge quite enormous sums for what they provide. And similarly, at the gas pump, we just want to swipe our cards and get out of there, rather than faffing about with cash. And so there’s an incentive for companies like Uber and gas stations to inexorably increase the implied convenience fee we get charged for using easy payments methods — even if those payments work out cheaper for them. (After all, it would cost Uber a fortune if we paid our drivers in cash and then Uber had to try to reclaim its share from those drivers.)

My radical new universal payments system would help a little bit here, since it would make it impossible for vendors to claim that the more convenient payments method was somehow more expensive for them. But it wouldn’t solve the deeper problem, which is that the more painless payments are, the less we feel the pain. And so merchants will always find ways to charge us more now, if we’re not going to really feel how much we paid until much later. And then, when customers start revolting at the high prices they’re paying, the merchants will act like they’re doing us a favor by offering an inferior and cheaper option.