Mulligan on Obamacare Marginal Tax Rates

Casey Mulligan wrote a nice Wall Street Journal Oped last week, summarizing his recent NBER Working Paper (also here on Casey’s webpage) on marginal tax rates.

What do I mean, tax, you might ask. Obamacare is about giving people stuff, not taxing. Sadly, no. Obamacare gives subsidies that are dependent on income. As you earn more, you receive fewer subsidies for health care, reducing the incentive to earn more. Casey tots this sort of thing up, along with the actual taxes people will pay.

Economists use the word “tax” here and we know what we mean, but it would be better to call it “disincentives” so it’s clearer what the problem is, and just how painful we make it for poor people in this country to rise out of that poverty.

As you can see, the average marginal “tax” rate went up 10 percentage points since 2007, and about 5 percentage points due to Obamacare alone.

Going back to the working paper, I think this is actually an understatement. (Probably the first time Casey or I have ever been accused of that!)


First, not even Casey can add everything up, and it all adds in one direction. State and local taxes, and vast number of state, county, city and other income or asset-based transfers all add. I haven’t read all his papers or the whole book yet, but did Casey get them all? For example, I just got in the mail notice for a little program offered by the state of Illinois to lower your property taxes if you earn less than $100,000 per year. Nice, but one more little incentive not to earn more than $100,000 per year, and not in Casey’s calculation.

In email correspondence, Casey pulled me back from these thoughts in a way that is revealing about the calculation. I wanted to add sales tax. After all, if you earn a dollar, but you have to pay 10% sales tax to do anything with it, that’s another 10% distortion, no? Casey responds no, because he wants to measure the income-compensated distortion to labor, period. If you don’t work, and somehow you also get income, you still have to pay the 10% sales tax. So the sales tax does not distort that pure work-no work decision. Casey’s right, but I think this clearly illuminates the conservative nature of his calculation and what it means. There are a lot more margins, wedges, and distortions out there, and he’s not trying to measure them all. He’s also not trying to measure the wedges and disincentives for employers to hire people, towards non-market activities, and certainly not the effects of the regulatory tangle.

Another note of conservatisim: “The results account for the fact that many people will not participate in programs for which they are eligible.” This is an important issue, that at least had not sunk in for me until reading a recent CBO report. People don’t sign up for all the benefits to which they are eligible. If they did, marginal tax rates would be astronomical. It also sends a warning: Just how long will it be before people in an increasingly stagnant economy figure out all the programs they are eligible for?

Drawing a single line can also be unduly calming. You might say, “well 50% isn’t so bad. Europeans still work, sort of, paying 50% marginal tax rates.”  But as Casey reminds us, the spread in marginal tax rates across people is enormous. For example, the paper has a nice example (p. 13, table 2) of how a typical earner will come out ahead by choosing to work part time and receive subsidies, rather than work full time. This is a case of a 100% marginal tax rate.

It’s likely that the effect of marginal taxes is nonlinear. Much of the labor decision comes in chunks: work or don’t work; work part time or full time; apply for benefits or don’t, with transactions costs and irreversibilities.  Suppose half the population feels a 100% marginal tax rate and half feels zero. Half the population works, half does not. That is likely a much larger effect than if the whole population felt a 50% marginal tax rate.

In sum, it’s probably worse than even Casey’s graph. But Casey is doing the right thing in putting up a carefully documented graph and paper rather than speculating. Speculation is for blogs, not papers and not for good opeds.

And Casey’s big point remains the additional effect of Obamacare and other changes to Federal programs. Whatever you think the level is, it’s now 10 percentage points more than what it used to be. On average.

Dupor and Li on the Missing Inflation in the New-Keynesian Stimulus

Bill Dupor and Rong Li have a very nice new paper on fiscal stimulus: “The 2009 Recovery Act and the Expected Inflation Channel of Government Spending” available here.

New-Keynesian models are really utterly different from Old-Keynesian stories. In the old-Keynesian account, more government spending raises income directly (Y=C+I+G); income Y then raises consumption, so you get a second round of income increases.

New-Keynesian models act entirely through the real interest rate.  Higher government spending means more inflation. More inflation reduces real interest rates when the nominal rate is stuck at zero, or when the Fed chooses not to respond with higher nominal rates. A higher real interest rate depresses consumption and output today relative to the future, when they are expected to return to trend. Making the economy deliberately more inefficient also raises inflation, lowers the real rate and stimulates output today. (Bill and Rong’s introduction gives a better explanation, recommended.)

So, the key proposition of new-Keynesian multipliers is that they work by increasing expected inflation. Bill and Rong look at that mechanism: did the ARRA stimulus in 2009 increase inflation or expected inflation?  Their answer: No.


This is a quantitative question. How much do the large-multiplier models say the ARRA should have increased inflation? Their answer: 4.6%. Where is it?

We know, of course, that inflation (especially core inflation) basically did nothing during the period of the ARRA, and Bill and Rong have some nice graphs. Defenders might say, aha, but except for the stimulus, we would have had a catastrophic deflation spiral. Critics might reply, that’s what George Washington’s doctors said while they were bleeding him. As always, teasing out cause and effect is hard.

Bill and Rong have a range of interesting facts that address this question. Here are two that I thought particularly clever. First, they look at the survey of professional forecasters, and examined how the forecasters changed inflation forecasts along with their changes in government spending forecasts, i.e. when they figured out a big stimulus is coming. I plotted the data from Bill and Rong’s Table 2

Dupor and Li Table 2

As you can see, in 2008Q4 and 2009Q1, many forecasters updated their views on government spending, a few by a lot.  However, there is next to no correlation between learning of a big stimulus and increases in expected inflation, especially among the forecasters who strongly update their stimulus forecasts.

Bill and Rong’s interpretation is that the stimulus failed to increase expected inflation. The main defense I can think of is to say that this evidence tells us about professional forecaster’s model, not about true inflation expectations. Professional forecasters are a bunch of old-Keynesians, not properly enlightened new-Keynesians; they don’t realize that stimulus works through inflation, they’re still thinking about a pre-Friedman consumption function. That’s probably true. But if so, it’s hard to think that everyone else in the economy does understand the new truth, and changed their inflation forecasts dramatically when they learned of the stimulus.

Another nice piece of evidence: The US had much bigger government spending stimulus than the UK. The behavior of expected inflation revealed in the real vs. nominal treasury spread was almost exactly the same. (Yes, Bill and Rong delve into the TIPS pricing in the crisis.)

Source: Dupor and Li

Finally, a key point missing in most of the stimulus debate. These models predict big multipliers not just at the zero bound, but anytime that interest rates don’t respond to inflation. We don’t have to just rely on theory, there is some experience. New-Keynesians since at least Clarida Gali and Gertler’s famous regressions have said that the Fed was not increasing interest rates fast enough in the 1970s, and the 1930s and interest-rate peg of the late 40s and early 50s are another testing ground. Using standard measures of exogenous spending increases, Bill and Rong find no impact of government spending on inflation in any of these periods.

New Keynesian stimulus analysis has been particularly slippery, on the difference between the models and the words, and on advocating the policy answers without checking or believing the mechanisms. The models are Ricardian: the same stimulus happens whether paid for by taxes or borrowing. The opeds scream that the government must borrow. The models say totally useless spending stimulates. The opeds are full of infrastructure, and roads and bridges. (At least, the “sprawl”  complaint is temporarily quiet.) The models say that spending works by creating inflation, not through a consumption function. Inflation being totally flat, and the counterfactual argument weak, you don’t hear much about that in the opeds.  The models say we should be in a huge deflation with strong expected output growth. The facts are protracted stagnation. (More in my last stimulus post.) The models are models, worthy of careful examination and empirical testing. All I ask is that their proponents take them seriously, and not as holy water for a completely different old-Keynesian agenda.

Rogoff on UK Defaults

Ken Rogoff wrote a very interesting FT oped on UK finances (FT original, Rogoff webpage if you can’t see FT.)

The issue: Should we worry about huge sovereign debts of advanced countries? Or was the only problem with fiscal stimulus that it was not big enough?


A little history:

Yes, from the 1800s until the first world war, the UK was a global superpower that commanded vast colonial resources and investments. Over long periods, these foreign assets yielded returns well in excess of interest on debt. But comparing government debt ratios back then, when the UK was a massive net creditor, to debt ratios today, when British foreign liabilities exceed foreign assets, is utterly misleading. Moreover, back in the 1820s, the UK was pioneering the industrial revolution; things are not quite the same today. Back then, the UK did not have to worry about pension liabilities or existential threats to the banking system that could require massive injections of cash to fix. …

During the 1930s, Britain defaulted on debt to the US accumulated during the first world war and its aftermath. …

It is often stated that after the second world war the UK debt reached almost 250 per cent of gross domestic product and was brought down merely through growth and inflation. This is a myth …

Then there is the high-inflation era of the 1970s – another de facto default. Last but not least, what about the UK’s serial dependence on International Monetary Fund bailouts from the mid-1950s until the mid-1970s? This is hardly a country with an indestructible credit status. …

Being a UK bondholder has had its ups and downs.

Looking forward, an important point: a country needs to be substantially below its ultimate borrowing limit, or it loses its ability to fight crises going ahead.

..a euro collapse would have triggered a stampede out once investors realised that the UK banks and trade would be savaged, a flexible currency notwithstanding. In that scenario, UK leaders would have been forced to close massive budget deficits almost overnight. That would have been truly catastrophic austerity. …

We now know the euro did not collapse. [yet – JC] With 20-20 hindsight, yes, the UK could have borrowed more. But we do not have hindsight at the moment decisions have to be taken. 

Kan and Carmen Reinhart have been at the receiving end of Paul Krugman’s tender commentaries lately, and I’m interested to see Ken taking up the issue. Krugman likes to lambaste people for “predictions” that he imagines they made which didn’t come out. On the euro blowing up, Ken seems to be offering a taste of his own medicine, made more bitter by the fact that Krugman actually did say what Ken says he said:

…This was the big call – the one that everyone was focusing on. To state that credit risk was gone by 2010 is ludicrous. None other than The New York Times columnist Paul Krugman prognosticated the euro’s early demise regularly from April 2010 to July 2012. His big call has turned out – so far – to be dead wrong.

I will be curious if we see more of that from Ken. Stay tuned.

Litterman on carbon finance

I just read a very nice article by Bob Litterman in CATO’s “Regulation” on the finance of carbon taxes. It includes a review of some of the recent academic calculations.

(Related, Ronald Bailey at Reason.com takes on the Administration’s latest cost of carbon estimates, and reviews Robert Pindyk’s recent NBER working paper “What do the models tell us?” also covered by Bob.)

Like just about every economist, Bob favors a carbon tax or tradeable emissions right over the vast network of regulatory controls on which we are now embarked. I might add that getting rid of the large subsidies for carbon emissions implicit in many country’s policies would help before we start taxing.

But let’s get to business, how big should the carbon tax be?


It’s a hard question. The economic costs of warming are hard to assess. Moreover, they come in a century or more, when presumably our descendants are much wealthier than we are, and hopefully have technologies we have not imagined. Or civilization will have collapsed so they have a lot more pressing problems. How do we trade off costs now and uncertain benefits in a century?  What discount rate should we use?

Bob has good points on this question that I hadn’t thought of, and are good applications of finance thinking (as you’d expect from Bob) which is sort of my excuse for covering it here.

Carbon beta

First, climate costs are likely to have a strong negative beta, and thus climate investments have a large positive beta.

Here’s the thinking. The rate of economic growth over the next century is a major uncertainty. Will the historically unprecedented growth of the post WWII era continue, say 2% real per capita? Or does our current scleroscis settle us into 1% growth? Or are the end-of-growth prognosticators right? When you compound over a century, these add up to truly major uncertainties over how wealthy our descendants will in fact be.

But they also add up to truly major uncertainties over how much carbon we will emit in the meantime. If growth stops, carbon emissions stop too. Yes, it’s not one for one (a perfect correlation). Technology choice matters; everything from windmills to deregulated nuclear power to driverless cars and trucks makes a difference. But there is a strong positive correlation.

So, if carbon is a bigger problem, our descendants are more likely to have lots of money, technology, and resources to deal with it. If they are poorer, then carbon is likely to be a lesser problem. In finance language, projects with a strong positive beta require a much higher expected return, and a high equity-like discount rate. This consideration drives us to tax less now.

Catastrophes

But, Bob goes on, how do you price catastrophe risk? Though the central tendency of the present value of economic costs of carbon emissions are surprisingly low – even moving all of Florida up to the Georgia border is only money after all, and you have a century to do it – there is a chance that things are much worse.

We’re all thinking about “black swans” and “tail risk” these days. Shouldn’t we pay a bit more carbon tax now, though the best guess is that it’s not a worthwhile investment, as insurance against such tail risks?

The problem is,

Massachusetts Institute of Technology economist Robert Pindyck… argues that too many non-GHG-related low-probability, high-damage scenarios exist. He writes, “Readers can use their imaginations to come up with their own examples, but a few that come to my mind include a nuclear or biological terrorist attack (far worse than 9/11), a highly contagious ‘mega-virus’ that spreads uncontrollably, or an environmental catastrophe unrelated to GHG emissions and climate change.” He concludes that society cannot afford to respond strongly to all those threats.

Indeed. (Fun for commenters: come up with more. Asteroid impact. Banking system collapse. Massive crop failure from virus or bacteria. Antibiotic resistsance….) If we treat all threats this way, we spend 10 times GDP.

It’s a interesting case of framing bias. If you worry only about climate, it seems sensible to pay a pretty stiff price to avoid a small uncertain catastrophe. But if you worry about small uncertain catastrophes, you spend all you have and more, and it’s not clear that climate is the highest on the list.

This thought fits nicely into the modern research on “ambiguity” and “robust control” (for example see Lars Hansen and Tom Sargent’s webpages for a portal). This line of thought often argues that you should pay a lot of attention to unlikely catastrophes, especially when it’s hard to quantify their risks. And Pindyck’s point (as I see it) gets to the central problem with that line of thought: you have to draw an arbitrary circle about which unlikely events you pay a lot of attention to, and which ones you pay no attention to.

If you worry about anvils falling from the sky, maybe you miss the piano falling from the sky. And if you worry about anvils, pianos, dynamite, and so on,  you just don’t get out of bed in the morning.

It’s also related to the tendency people have, in Kahneman and Tversky’s famous analysis, to overweight some small probability events – nuclear reactors, airplane crashes, terrorism – and to ignore others – coal dust, cab crashes on the way to the airport.

The same observation: One of my skepticisims of the current almost exclusive focus on carbon and global warming in the environmental community is that we may miss the real environmental problems. Most of the world breathes awful air and drinks awful water. Climate change is not even on their list of environmental problems. And the environmental effects of social or economic collapse or another war might dwarf warming.

All in all, I’m not convinced our political system is ready to do a very good job of prioritizing outsize expenditures on small ambiguous-probability events.

Alternative investments

Once we reduce things to money, which is what economists do, a bunch of unconventional and unsettling analysis opens up. (This isn’t in Bob’s piece, mea culpa only.) The economic case for cutting carbon emissions now is that by paying a bit now, we will make our descendants better off in 100 years.

Once stated this way, carbon taxes are just an investment. But is investing in carbon reduction the most profitable way to transfer wealth to our descendants?  Instead of spending say $1 trillion in carbon abatement costs, why don’t we invest $1 trillion in stocks? If the 100 year rate of return on stocks is higher than the 100 year rate of return on carbon abatement – likely – they come out better off. With a gazillion dollars or so, they can rebuild Manhattan on higher ground. They can afford whatever carbon capture or geoengineering technology crops up to clean up our messes.

Put that way, though, the first question might be why we are leaving our descendants with $18 trillion of Federal debt, and a bill for $70 trillion or so of unfunded liabilities. Once we reduce the question to investment now to benefit the economic well-being of our descendants, it’s not at all clear that investing in carbon reductions is the best place to put our money.

The greatest thing we can invest in for the economic well being of our 100 year descendants is strong, decades-long  economic growth. Needless to say, the overall economic policy mix and especially the environmental policy mix is not pointing in that direction. A lot of environmental policy actively discourages growth.

Nonlinearities

Bob points out one good case against this analysis. It is possible that carbon abatement is a very special investment with very special state-contingent rate of return.

There is a very small chance that climate effects may not just reduce subsequent growth, but may cause it to plummet catastrophically. Such scenarios require positive feedbacks; for example, warmer temperatures cause the release of methane from the currently permanently frozen tundra, triggering catastrophic warming impacts beyond the ability of future generations to adapt. How should society today rationally price the possibility of such unknown, very-low-probability outcomes in the future?

In my investment context, reducing carbon emissions now has a very special property that alternative ways of investing money don’t have – it turns off this low probability but huge negative-return scenario.

That’s a good point – but it means the entire case for a strong carbon tax now relies on how likely such extreme nonlinearity is.

Economics after all? 

I suspect this sort of analysis will be profoundly unsettling – how about infuriating – to people who worry about carbon and other greenhouse gases. It’s not just about money, I suspect they might say, it’s not about giving our descendants wealth; it’s about giving them a healthy planet. The economist might say, so what’s that worth to you? Some finite number, no? Sure, we inundate Florida, but our descendants are $100 trillion richer, so they can afford to rebuild Florida on higher ground. Problem solved with $90 trillion extra in the bank. Somehow I doubt Greenpeace will go back to saving whales even if that argument were decisively proved.

As much of a died-in-the wool economist as I am, I have to admit some sympathy. (Or maybe “ambiguity?”) Consider species extinction. Our short time on Earth coincides with a greater mass extinction than the asteroid that killed off the dinosaurs. And the extinction rate is not abating.

Now, I can’t point to an economic cost, and people who hold up development projects to save some small species have a hard time doing the same. The best arguments I have read (admittedly not an expert) is of the sort that there might be some snake in the rain forest has a medically useful venom. More generally, “biodiversity is good.” These is again, the  small probability of huge but unquantifiable benefit option-value argument.

Really, is that the best we can do when staring at the K-T boundary, and realizing that future alien geologists will see a more dramatic layer, with far more interesting chemistry, where we lived? The feeling nags that it can’t be a good thing for us to move on from the dinosaurs to see if we can beat the Permian-Triassic extinction in the spectacular-geology department. (Global warming is a is a tiny component of extinction – we got megafauna with spears.) I welcome suggestions on how to voice this view in economic terms.

Perhaps systematically worrying about small and unquantifiable probability events isn’t such a bad thing. But paying attention to vague unquantifiable worries leads to a lot of stupidity, like banning genetically modified crops.

Back to carbon taxes

With all that in mind, where do I stand on carbon taxes? Usually, when something is this muddy, it means we’re asking the wrong question, and I think that’s the case here.

I think we’re way too focused on the amount of the tax and way too unfocused on its operation.

I think we should be talking about a carbon tax in place of  all the rest of our rather calamitous energy policy. Subsidies for windmills, for rich people to buy Tesla cars, HOV lanes, fuel economy standards, subsidies for photovoltaic roofs, tax credit for energy efficient appliances, certified buildings, ethanol, high speed trains, low speed trains, and on and on. Throw out the whole department of energy, the EPA’s ability to regulate climate emissions, and every other nagging energy regulation, and give us a carbon tax instead (and real-time tolling to eliminate congestion). Set the level of the carbon tax at the cost of all this other junk, and achieve better results at a fraction of the cost.

The first-order issue is the monstrous inefficiency and increasing corruption of our energy regulation. Get the clean carbon-tax system in place, then we can talk about the level of the tax. In that world, a tax rate twice or even three times too high will have much fewer distortions than what we have now, and will produce both better growth and a cleaner environment.

Alas, as with the consumption tax and any other perfectly obvious policy, we can’t seem to trust that the deal will be kept.

The Value of Public Sector Pensions

The unfunded promises of public sector pensions are in the news, with the Detroit bankruptcy. Josh Rauh at Stanford and Hoover has a nice blog post on the subject titled “Public Sector Pensions are a National Issue”. (Josh and Robert Novy-Marx wrote a very influential paper (ssrn manuscript) alerting us to the size of the state and local pension bomb.)

Josh’s baseline number for the value of underfunded pensions: $4 trillion. Why so big, and why is this a surprise? Because many governments calculate their funding by assuming they will earn 8% per year. Discounting a riskless liability (pensions) at a risky rate is a basic error in finance. It’s made all the time. University presidents are notorious for demanding their endowments “reach for yield” in order to “make our rate of return targets.”

Reading this piece sparks a few thoughts about the risks posed by pensions and other unfunded liabilities.

Let’s report risks

How to make the error clearer? Perhaps focusing on present values and arguing about discount rates obfuscates the issue. Let’s talk about risk. Maybe it would clear things up if pensions had to report a “shortfall probability” or “value at risk” calculation like banks do. OK, you are assuming an 8% discount rate because you’re investing in stocks. What’s the chance that your investments will not be enough?   Coincidentally, when I saw Josh’s piece I was putting together a problem set for my fall class that illustrates the issue well.

Here is the distribution of how much money you will have in 1, 5, 10, and 50 years if you invest in stocks at 6% mean return, 20% standard deviation of return. I added the mean in black, the median (50% of the time you earn more, 50% less) and the results of a 2% risk free investment in green. (The geometric mean return is 4% in this example.)

(Note: there is a picture here. I’ve noticed this blog is getting reposted here and there in text-only form. Go to the original if you want the pictures)

The mean return looks pretty good. After 50 years, you get $20 for every dollar invested, or contrariwise an accountant discounting a promise to pay $20 of pensions in 50 years reports that the present value of the debt is only $1. But you can see that stock returns (these are just plots of lognormal distributions) are very skewed. The mean return reflects a small chance of a very large payoff.

In these graphs the chance of a shortfall is 54, 59, 62, and 76% respectively. As horizon increases, you are almost guaranteed not to make the projected (mean) return! The median returns – with 50% probability of shortfall, in red – are a good deal lower. And the modal “most likely” return is below the riskfree rate in each case.

How is it that people get this so wrong? Let’s look at the distribution of annualized returns in each case. Remember, these are exactly the same situations, we’re just reporting a different number.

In these pictures, the distribution of annualized returns is symmetric, the mean and median are the same, and the distributions get narrower and narrower for longer horizons.

Comparing the two graphs, you see that annualized returns are profoundly misleading about the risks you’re taking. Annualized returns have a standard deviation that goes down at the square root of horizon. But the actual return has a standard deviation that goes up at the square root of horizon, and exponentiating makes it skewed with the larger and larger chance of underperformance. Money matters, not annualized returns.

So as usual, when arguments are getting nowhwere, perhaps we need to shift the question: please report your shortfall probabilities. And your plans for what you do with shortfalls.

In  many of those cases, the plan for shortfall  comes down to “the Federal Government bails us out” (or ERISA bails out private plans.) Well, if that’s true, then we have a different and interesting discounting question. Maybe 8% is the right number if someone else pays the losses!

Finance also teaches us to think about “state contingent payoffs.” What does the whole world look like in the bad events? If cities and states can’t pay their pensions, this very likely because stocks have performed badly, and because we’ve had 20 years of sclerotic growth, no growth in tax revenues, to fund the pensions. Stock returns are not uncorrelated with other aspects of state, municipal, and corporate finance. Investing in stocks to fund pensions is like selling fire insurance on your house, rather than buying it. If the house burns down, then you pay the insurance company.

What debt really matters?

Even $4 trillion is not all that huge in the grander scheme of things.  The official Federal debt is $18 trillion. But if you add the present value of unfunded pensions, social security, medicare, Obamacare, and so on you can get numbers like $50 trillion or more. Which, it should be perfectly obvious, are not going to get paid, especially if we stay on the current slow growth trajectory.  But how important is this present-value observation?  Should we routinely add up all the unfunded promises, discount them properly using the Treasury yield curve, and report the grand total?

I worry most about runnable debt. Promises to pay people trillions in the far off future are a different thing than rolling over marketable debt every year. If it looks likely we won’t be able to pay pensions in 20 years, there’s not all that much pensioners can do about it. If it looks like we won’t pay off formal short-term debt, markets can fail to roll over, leading to an immediate financial crisis.

So, much as I value Josh’s calculation, and zinging those who want to minimize the necessity of ever paying off debt, it does seem there is a difference between marketable debt that needs to be rolled over every year and promises to pensioners and social security that may eventually be defaulted on, but can’t cause an immediate crisis.

The cash flows do matter. If the government has promised to make pension and other payments that on a flow basis drain all its revenues, something has to give. As it has in Detroit.

A too-clever thought

A good response occurred to me, to those cited by Josh who want to argue that underfunding is a mere $1 trillion. OK, let’s issue the extra $1 trillion of Federal debt. Put it in with the pension assets. Now, convert the pensions entirely to defined-contribution. Give the employees and pensioners their money now, in IRA or 401(k) form. If indeed the pensions are “funded,” then the pensioners are just as well off as if they had the existing pensions. (This might even be a tricky way for states to legally cut the value of their pension promises)

I suspect the other side would not take this deal. Well, tell us how much money you think the pension promises really are worth – how much money we have to give pensioners today, to invest just as the pension plans would, to make them whole. Hmm, I think we’ll end up a lot closer to Josh’s numbers.

Details

I used a geometric Brownian process, dp/p = mu dt + sigma dt with mu = 0.06 (6%) and sigma = 0.20 (20%). The T year arithmetic return is then lognormally distributed R_T = exp( mu - 1/2sigma^2)T + sigma root T e) with e~N(0,1). It has mean E(R_T) = exp(mu*T)=exp(0.06*T), median exp[mu-1/2sigma^2)T] = exp(0.04*T) and mode exp[(mu-3/2*sigma^2)T] = exp(0)=1.

Mankiw on the 1%

Greg Mankiw has an intereting new article draft, titled “Defending the 1%”  It’s mistitled really, as the main point I got out of it is the more interesting question, “Can transfers really help the bottom 50%?”

It’s a very well written (as one would expect) and survey of economic issues surrounding the idea of greatly expanded taxation of upper income people to fund transfers. Go read it, I won’t do it justice in a summary.

As Greg notes, much of the success of the 1% is not rent-seeking, nor inherited wealth, but entrepreneurs who innovated and got spectacularly wealthy in the process.

It’s not clear how Steve Jobs getting hugely rich hurts the rest of us. (Greg makes a few jabs at financial profits, but readers of this blog know that’s a more nuanced issue.) It’s not clear how any of us even know if Jobs had $100 million, $1 billion, or $1 Gazillion when he died, though it makes a huge difference to measured inequality.  And I like Greg’s emphasis that it doesn’t make much philosophical or moral sense to draw national borders around income-transfer moral philosophy.  Look for the kidney story too.

Greg chose not to argue with the very tricky measurement issues, instead just quoting Pikkety and Saez’ numbers.  That’s a good issue for another day – other measures give very different results.

One of Greg’s main points is that our inequality is the result of an interplay between supply and demand for talented skilled people.

I am more persuaded [than by Stiglitz] by the thesis advanced by Claudia Goldin and Lawrence Katz (2008) in their book The Race between Education and Technology. Goldin and Katz argue that skill biased technological change continually increases the demand for skilled labor. By itself, this force tends to increase the earnings gap between skilled and unskilled workers, thereby increasing inequality. Society can offset the effect of this demand shift by increasing the supply of skilled labor at an even faster pace, as it did in the 1950s and 1960s. In this case, the earnings gap need not rise and, indeed, can even decline, as in fact occurred. But when the pace of educational advance slows down, as it did in the 1970s, the increasing demand for skilled labor will naturally cause inequality to rise. The story of rising inequality, therefore, is not primarily about politics and rent-seeking but rather about supply and demand.

Having stated it this way, I’m disappointed Greg didn’t explore supply more. Why is it that America has not responded this time by increasing the supply of skilled workers? The obvious suspects are easy to name, and do not bode well for the left’s suggestion that permaent confiscatory taxation plus transfers are the answer to the “problem.”

Greg does a good job of painting the standard incentive problem with tax and transfer redistribution. However, he states it in its classic, static form. More transfers means less work effort. In reality, hours of work don’t really respond that much, as there are only so many hours in a day and income and substitution effects offset. To make this come alive, we need to think harder about the margin of working vs. not working.

And investing. Here the two points come together, and I don’t think Greg’s article nor the literature put the pieces in one place. We need a dynamic perspective. If inequality comes from a mismatch between supply and demand for skill, then keeping the incentives in place to acquire skill is vital. If there is a strong income-based transfer scheme in place, yes, there  is less incentive to work overtime. And yes, there is less incentive to work at all at least legally. But most of all, there is less incentive to go to school, to pick hard courses (face it, art history is a lot more fun than python and Java 101), pursue expensive advanced graduate education or innovate. One can imagine a spiral, or inequality laffer curve: Demand for skill outpaces supply, inequality rises, we put in place an income based transfer scheme, less people acquire skils, inequality rises…

Greg has a great section, “listening to the left” which I will now invite as well. Forget about the 1%. Pretend wealth grows on trees. Let’s just think of the fortunes of the bottom 50%. Can we actually help them? Is there any historical precednent of a successful society that pays large means-tested amounts to young and working-age men and women, without destroying their incentives to gain skills and become middle class, to say nothing of the next Steve Jobs?

Social security doesn’t count; the question is sending checks to young, healthy, but low-skilled working age people.  Short-term doesn’t count. I want to know of an instance in which, maintained over a generation or two, such a system did anything more than perpetuate an unskilled largely dysfuncitonal underclass, which achieved much more than reliably voting for politicians who endorse its transfers. (The model “send money to Democratic voters” does explain the proposed policies pretty well!) The reputed wonders of living in Sweden or other welfare states don’t count: their benefits are in kind, and not means tested.

It’s easy to come up with incentive-destruction horror stories, American welfare, European dole, and so on.  Small cash transfers coupled with restricted educational opportunities and large labor market wedges, as faced by refugees and many European immigrants, seem particularly destructive. Tom Sowell writes whole books of examples.  But it’s too easy to listen to the choir. To those of you advocating large cash transfers, when has this ever worked?   I'm curious to hear a clear historical precedent for the policies you advocate for the US.