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Nearly 11% of the workforce is out of work with no reasonable chance of getting called back to a prior job



Key takeaways:

  • In May, the official unemployment rate was 13.3%. However, the unemployment rate that takes into account all those who are out of work as a result of the virus was 19.7%, and the unemployment rate that includes only those who are out of work and don’t have a reasonable chance of being called back to a prior job was 10.7%.
    • The official unemployment rate was 13.3% in May. However, if you consider not just the 21.0 million officially unemployed, but all 32.5 million workers who are either officially unemployed or otherwise out of work as a result of the virus, that jumps to 19.7%. That is nearly one in five workers.
    • Of the 32.5 million workers who are either officially unemployed or otherwise out of work because of the virus, 11.9 million workers, or 7.2% of the workforce, are out of work with no hope of being called back to a prior job; 5.7 million workers, or 3.5% of the workforce, are out of work and expect to get called back to a prior job but likely will not; and 14.8 million workers, or 9.0% of the workforce, are out of work and can reasonably expect to be called back. That means the share of the workforce that is out of work and has no reasonable chance of being called back to a prior job is 10.7% (7.2% + 3.5%).
  • All three of these unemployment rates are extremely elevated across all demographic groups. However, the highest rates are found among Black and brown workers, women, and particularly Hispanic, Asian, and Black women. Young workers and workers with lower levels of education have also been hit disproportionately hard.
  • It is important to note that the prospect of even those who can reasonably expect to be called back to a prior job actually getting called back will require Congress to act. For example, if Congress doesn’t extend the extra $600 in weekly unemployment insurance payments, that will cost us 5.1 million jobs over the next year, and if it doesn’t provide fiscal aid to state and local governments to fill in their budget shortfalls, it will cost another 5.3 million jobs by the end of 2021.

In May, the unemployment rate declined to 13.3% from 14.7% in April. That improvement was welcome news, but aside from April, the 13.3% unemployment rate in May was higher than anything we’ve seen since the Great Depression.

And, the unemployment rate is not reflecting all coronavirus-related job losses. In May, 21 million workers were counted as officially unemployed. But there were another 4.9 million workers who were out of work because of the virus but who were being misclassified—they had been furloughed and should have been counted as unemployed and on temporary layoff, but were instead counted as “employed but not at work.” If those workers had been correctly counted as being on furlough instead of employed, the unemployment rate would have been 16.4% in May instead of 13.3%. (This misclassification has gotten a lot of attention, with some suggesting that the Bureau of Labor Statistics (BLS) is cooking the books. That is not the case; BLS was extremely transparent and consistent with their treatment of the data.)

Another group of workers who are left out of the official unemployment rate are those who are out of work as a result of the virus but are not actively seeking work. As is always the case, for a jobless worker who is not on furlough to be counted as unemployed, they must be actively seeking work. Today, that remains impossible for many. I estimate that in May, there were 6.6 million workers who were out of work as a result of the virus but who were being counted as dropping out of the labor force because they weren’t actively seeking work. I arrive at that figure by assuming that the February labor force participation rate (63.4%) is what the May labor force participation rate (LFPR) would have been if the pandemic had not occurred. (Note, this is likely somewhat understating what the LFPR would have been in May without the pandemic since the LFPR had been rising slightly in the year prior to the virus—from 63.1% in February 2019 to 63.4% in February 2020.) Then I multiply the February 2020 LFPR by the May population (age 16+) to estimate what the size of the labor force would have been in May if the coronavirus hadn’t happened, yielding 164.8 million. I then subtract from that the actual May labor force, 158.2 million. The result, 6.6 million, is the number of workers who would have been in the labor force in May if the pandemic hadn’t happened, but, instead, are out of work and not actively seeking work.

Putting that all together—the 21.0 million officially unemployed, the 4.9 million unemployed who are being misclassified as “employed, not at work,” and the 6.6 million who have dropped out of the labor force as a result of the virus—that’s 32.5 million workers who are officially unemployed or are otherwise out of work as a result of the virus. If they had all shown up as unemployed, the unemployment rate would have been 19.7% in May instead of 13.3%. That’s an improvement from the same figure in April, which was 23.5%, but it is still mind-bogglingly high—nearly one in five workers are out of work.

The following chart provides these two unemployment rates—the official rate and the rate that takes into account the officially unemployed and others who are out of work as a result of the virus—by gender, race/ethnicity, education, and age. The rates are incredibly high across the board, but job losses have been particularly stark among Black and brown workers. Historically higher unemployment rates and lower liquid savings make job losses even more devastating for Black workers and their families. Unemployment rates in May were also extremely high among women, and especially Hispanic, Asian, and Black women. Furthermore, the unemployment rate is higher for workers with lower levels of educational attainment, though even among those with advanced degrees, nearly one in 10 are either unemployed or out of work as a result of the virus. The figure also shows that young people have been hit especially hard in this pandemic recession, with more than a third of 16–23 year-olds either officially unemployed or otherwise out of work as a result of the virus. Those graduating right now are in a particularly difficult situation, as they are experiencing extremely limited job opportunities but do not qualify for unemployment insurance, even under the expansive definitions of the CARES Act. Congress should institute a Jobseeker’s Allowance to address this issue.

Figure A

Some are saying that because rehiring took place in May and the unemployment rate improved, perhaps more aid from Congress isn’t needed because workers will just return to their old jobs. This logic could not be more misguided. Of the 32.5 million workers who are either officially unemployed or otherwise out of work because of the virus, only 14.8 million workers (or 45.6%) can reasonably expect to be called back to a prior job, which means 17.6 million (or 54.4%) cannot. That calculation is the result of the following steps:

  1. The survey the unemployment data are from asks unemployed workers who lost a job if they expect to return to work. Of the 21.0 million officially unemployed in May, 15.3 million expect to be called back to their old job, which means 5.6 million of the officially unemployed do not expect to be recalled to a former job (numbers don’t sum to the total due to rounding). Further, I assume that all of the 4.9 million unemployed who are being misclassified as “employed, not at work” expect to be called back to their old job, and that none of the 6.6 million who have dropped out of the labor force as a result of the virus expect to be called back. That means that of the 32.5 million workers who are either officially unemployed or otherwise out of work because of the virus, 20.2 million expect to be called back, and 12.2 million do not.
  2. However, it is likely that many of those who expect to be called back to their jobs will find that those furloughs have turned into permanent layoffs. First, BLS adopted an unusually broad definition of temporary layoff with respect to the coronavirus. Typically, to be classified as unemployed on temporary layoff, a person has to either have been given a date to return to work by their employer or expect to be recalled to their job within 6 months. However, if an unemployed person expects to be recalled to their job but, because of the coronavirus, they are not sure whether they will be recalled within six months, their response was counted as a “yes” (they expect to be called back within six months), rather than “don’t know.” BLS reports that “this unusual step was taken as part of an attempt to classify people who were effectively laid off due to pandemic-related closures among the unemployed on temporary layoff.” (See Question 8 here.)

    Further, it is likely that many workers who were explicitly told they would be called back will ultimately find that their temporary layoff was actually a permanent layoff. Businesses may have told the workers they were laying off that they were going to call them back even if they were unsure they would be able to, because it was an easier message to deliver. Or, businesses may have felt confident that they were going to call back their workers at the time of the job separation, but underestimated the financial strain they would face and will end up either going out of businesses or only needing to call back a fraction of the workers they furloughed. Historically, only 71.7% of workers on temporary furlough return to their jobs. On the other hand, 13.4% of laid-off workers who expect that their layoff is permanent are actually recalled. (These shares are found in Table II and the surrounding discussion in a 1990 paper by Larry Katz and Bruce Meyer, “Unemployment Insurance, Recall Expectations, and Unemployment Outcomes.”) It is unclear the extent to which this historic experience will be applicable in the current crisis, but these estimates nevertheless provide a rough sense of what we might expect. BLS data show that 2.3 million unemployed workers report being permanently laid off (unemployed workers who were not on temporary layoff but, for example, were not laid off because they are new entrants or reentrants to the labor market, or they voluntarily quit their job, are not included in this figure). If 13.4% of the 2.3 million unemployed workers who report being permanently laid off are in fact recalled, that is 308,000 workers who thought they were permanently laid off who will ultimately be recalled. Subtracting 308,000 from the 12.2 million calculated in step 1 that do not expect to be called back to a prior job yields 11.9 million workers who have essentially zero chance of being called back.

  3. If, as described in the prior step, only 71.7% of workers who do expect to be called back are called back, that means 28.3% will not be called back even though they expect to. That in turn would imply that of the 20.2 million workers who are out of work but expect to be called back to their prior job, 5.7 million will not be called back, and 14.5 million will. Adding to that 14.5 million the 308,000 workers calculated in the previous step who thought they were permanently laid off who are likely to get recalled, that is 14.8 million workers who can reasonably expect to be called back.
  4. Putting this all together means that of the 164.8 million workers who are either in the labor force or who have dropped out of the labor force as a result of the virus, 11.9 million workers, or 7.2%, are out of work with no hope of being called back to a prior job; 5.7 million workers, or 3.5%, expect to get called back to work but likely will not; and 14.8 million workers, or 9.0%, may reasonably expect to be called back. In other words, even if all workers who can reasonably expect to be called back to their prior jobs were called back, the share of the workforce out of work would still be 10.7% (7.2% plus 3.5%), higher than the highest unemployment rate of the Great Recession.

The following chart provides, overall and by demographic, the breakdown from step 4 (namely, the share of the workforce that is out of work with no chance of being called back to a prior job, the share of the workforce that is out of work and expects to get called back to their prior job but likely will not, and the share of the workforce that is out of work and can reasonably expect to be called back). The sum of the first two segments in each bar is the share of the workforce that is out of work and has no reasonable expectation of being called back to work. Overall, that figure is 10.7%, and is extremely high across the board, but it is particularly high among Black and brown workers, women, and especially Hispanic, Asian, and Black women. It is also particularly high among young workers and among workers with low levels of education.

Figure B

Figure B

It’s worth noting that the prospect of even those who can reasonably expect to be called back to a prior job actually getting called back will require Congress to act. If Congress provides enough aid to state and local governments, individuals, and businesses so that confidence and demand are high as the economy reopens, and puts in place public health measures and child care measures that make a successful reopening possible, then those furloughed workers will likely be needed by their former employers to meet demand, and will be called back. But if not, many won’t, and we will face sustained, extremely high unemployment.

Congress needs to extend the unemployment provisions in the CARES Act, including extending the across-the-board $600 increase in weekly benefits. Opponents of the policy say that the extra benefits disincentivize people from returning to work. However, cutting off the extra money so that people must exist on our very stingy regular state benefits will not work to incentivize people to return to work when safe jobs aren’t available. Instead, what we will see is millions who can’t find work being forced to dramatically cut back their spending. That will not only cause an enormous amount of human suffering, but it will also hamstring the recovery. We estimate that allowing the $600 to expire at the end of July will cost us 5.1 million jobs over the next year.

We must also provide a huge amount of aid to state and local governments. Without it, the recovery from this recession will be delayed for years. We estimate that state and local governments face budget shortfalls on the order of $1 trillion by the end of 2021 and if the federal government doesn’t fill that in, it will cost 5.3 million jobs—in both the public and private sector—by the end of 2021.

And we can’t turn off federal relief too early. The expiration of relief provisions should be tied to economic conditions. Assigning arbitrary end dates to provisions to sustain the economy makes no sense when we could easily have provisions phase out as the unemployment rate or the employment-to-population ratio are restored to near pre-virus levels. Using automatic stabilizers would not be any more expensive than the cumulative cost of multiple extensions—but it would prevent destructive lapses in critical programs while Congress negotiates extensions, and it would alleviate corrosive uncertainty by giving businesses, states, localities, and households confidence around budgeting and planning. And if projections are wrong and jobs roar back until we are at near pre-recession levels much more quickly than expected? That would be great news, and with automatic stabilizers, aid would simply turn off because it would no longer be needed.

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Reclaiming freedom



We might be seeing a significant political change, with the left reclaiming freedom and anti-statism from the right.

I'm prompted to say this by the Black Lives Matter slogan, "defund the police" which invites us to see the state as an oppressor. As Grace Blakeley recently tweeted:

People know that the state is fucking them over just as much as their boss or landlord – in fact, it’s helping their boss and landlord fuck them over even more…Rather than saying ‘just give more state power to the goodies (us)’ we need to start saying ‘put power where it belongs – in the hands of working people’.

If we read this alongside the disappearance of right-libertarians (some of whom discovered that they like racism and inequality more than small government) and emergence of big government Toryism, we see a big change from a few years ago. Back then, it was the right who called for a smaller state and much of the left that wanted a bigger one. Now it is, if anything, the opposite*.

In one sense this is a return to normality. Historically, advocates of freedom were opponents of the existing order, such as Tom Paine, John Stuart Mill and – yes – Adam Smith**. And, of course, Marxists have long regarded the state as "a committee for managing the common affairs of the whole bourgeoisie" and looked forward to it withering away.

Which poses the question: why are things now changing (back)?

One reason is that the left has learned that states are indeed often repressive. I'm thinking here not just of police killings but of the social murder that is austerity and tough benefit sanctions, and the forced deportations of black Britons (something still going on).

Secondly, they've learned that, as Grace says, it is not good enough to "give more state power to the goodies". Yes, New Labour did make significant achievements in tax credits, Sure Start and better funding of schools and the NHS. But many of these have been reversed by the Tories in the subsequent decade. The left cannot pin its hopes merely on winning temporary (and partial) control of the state.

Thirdly, changes within capitalism have changed the state. Of course, capital (pdf) has always wielded power over governments. But there was a time when this was relatively benign. In the post-war war mass production Fordist capitalists needed a mass market and hence an affluent working class. Extractive finance capital, though, doesn't. It needs cheap and plentiful money which fiscal austerity helps provide. General Motors needed a large well-paid working class; Goldman Sachs, not so much. This means there is now more tension between the needs of working people and the function of the state than there used to be.

All of which poses the question. What would anti-statist leftism look like?

Many of you might think the slogan "defund the police" goes too far. No matter: we don't know what's right unless we know what's too much. And what is right – as Elinor Ostrom showed – is that the police should be small and locally accountable. Also, there's a strong case for decriminalizing drugs, in part because it removes a pretext for the police to harass black people.

A high universal basic income would also expand freedom, not just by removing the harsh conditionality of Universal Credit, but also by giving us the freedom to reject exploitative labour or to drop out of the labour market to care for others or to train for better work. As Guy Standing says (pdf), "basic Income’s emancipatory value exceeds its monetary value."

Also, left-libertarianism must empower local communities, and embrace the community wealth-building advocated by Martin O'Neil and Joe Guinan and pioneered by Preston council. In weakening the power of central government, localization mitigates the damage done by Tory austerity. And it also gives local people more republican freedom – the freedom to collectively control more of their own lives.

There's something else, which the Black Lives Matter movement is also highlighting. It's that slavery teaches us something about economics. As Peter Doyle shows in a brilliant paper (pdf), markets produce incentives to undermine others' agency. Although slavery is the most extreme example of this we also see it in everyday capitalist labour markets. As Marx said, when we they start work workers leave behind the realm of equality and freedom and become mere factors of production. Left-libertarianism would put in place institutions to resist this and expand the realm of genuine agency. This would comprise worker coops and more local say over public services.

I say all this not to offer detailed blueprints: Marx was right to be sceptical of these. Instead, the point is that the left can and should pick up the cause of freedom now that the right has abandoned it.

* We mustn't be misled by the right's loud assertion of a right to free speech. What they are really proclaiming is the "right" to spout rubbish without any comeback, which is an altogether different matter.

** If you think the Adam Smith Institute is a representative guide to Smith's thinking, the wallet inspectors would like to meet you.

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The Surplus Process



How should we model surpluses and deficits? In finishing up a recent articleand chapter 5 and 6 of a Fiscal Theory of the Price Level update, a bunch of observations coalesced that are worth passing on in blog post form.

Background: The real value of nominal government debt equals the present value of real primary surpluses, [ frac{B_{t-1}}{P_{t}}=b_{t}=E_{t}sum_{j=0}^{infty}beta^{j}s_{t+j}. ] I ‘m going to use one-period nominal debt and a constant discount rate for simplicity. In the fiscal theory of the price level, the (B) and (s) decisions cause inflation (P). In other theories, the Fed is in charge of (P), and (s) adjusts passively. This distinction does not matter for this discussion. This equation and all the issues in this blog post hold in both fiscal and standard theories.

The question is, what is a reasonable time-series process for (left{s_{t}right} ) consistent with the debt valuation formula? Here are surpluses

The blue line is the NIPA surplus/GDP ratio. The red line is my preferred measure of primary surplus/GDP, and the green line is the NIPA primary surplus/GDP.

The surplus process is persistent and strongly procyclical, strongly correlated with the unemployment rate.  (The picture is debt to GDP and surplus to GDP ratios, but the same present value identity holds with small modifications so for a blog post I won’t add extra notation.)

Something like an AR(1) quickly springs to mind, [ s_{t+1}=rho_{s}s_{t}+varepsilon_{t+1}. ] The main point of this blog post is that this is a terrible, though common, specification.

Write a general MA process, [ s_{t}=a(L)varepsilon_{t}. ] The question is, what’s a reasonable (a(L)?) To that end, look at the innovation version of the present value equation, [ frac{B_{t-1}}{P_{t-1}}Delta E_{t}left( frac{P_{t-1}}{P_{t}}right) =Delta E_{t}sum_{j=0}^{infty}beta^{j}s_{t+j}=sum_{j=0}^{infty}beta ^{j}a_{j}varepsilon_{t}=a(beta)varepsilon_{t}% ] where [ Delta E_{t}=E_{t}-E_{t-1}. ] The weighted some of moving average coefficients (a(beta)) controls the relationship between unexpected inflation and surplus shocks. If (a(beta)) is large, then small surplus shocks correspond to a lot of inflation and vice versa. For the AR(1), (a(beta)=1/(1-rho_{s}beta)approx 2.) Unexpected inflation is twice as volatile as unexpected surplus/deficits.

(a(beta)) captures how much of a deficit is repaid. Consider (a(beta)=0). Since (a_{0}=1), this means that the moving average is s-shaped. For any (a(beta)lt 1), the moving average coefficients must eventually change sign. (a(beta)=0) is the case that all debts are repaid. If (varepsilon_{t}=-1), then eventually surpluses rise to pay off the initial debt, and there is no change to the discounted sum of surpluses. Your debt obeys (a(beta)=0) if you do not default. If you borrow money to buy a house, you have deficits today, but then a string of positive surpluses which pay off the debt with interest.

The MA(1) is a good simple example, [ s_{t}=varepsilon_{t}+thetavarepsilon_{t-1}% ] Here (a(beta)=1+thetabeta). For (a(beta)=0), you need (theta=-beta ^{-1}=-R). The debt -(varepsilon_{t}) is repaid with interest (R).

Let’s look at an estimate. I ran a VAR of surplus and value of debt (v), and I also ran an AR(1).

Here are the response functions to a deficit shock:

The blue solid line with (s=-0.31) comes from a larger VAR, not shown here. The dashed line comes from the two variable VAR, and the line with triangles comes from the AR(1).

The VAR (dashed line) shows a slight s shape. The moving average coefficients gently turn positive. But when you add it up, those overshootings bring us back to (a(beta)=0.26) despite 5 years of negative responses. (I use (beta=1)). The AR(1) version without debt has (a(beta)=2.21), a factor of 10 larger!

Clearly, whether you include debt in a VAR and find a slightly overshooting moving average, or leave debt out of the VAR and find something like an AR(1) makes a major difference. Which is right? Just as obviously, looking at (R^2)   and t-statistics of the one-step ahead regressions is not going to sort this out.

I now get to the point.

Here are 7 related observations that I think collectively push us to the view that (a(beta)) should be a quite small number. The observations use this very simple model with one period debt and a constant discount rate, but the size and magnitude of the puzzles are so strong that even I don’t think time-varying discount rates can overturn them. If so, well, all the more power to the time-varying discount rate! Again, these observations hold equally for active or passive fiscal policy. This is not about FTPL, at least directly.

1) The correlation of deficits and inflation. Reminder, [ frac{B_{t-1}}{P_{t-1}}Delta E_{t}left( frac{P_{t-1}}{P_{t}}right) =a(beta)varepsilon_{t}. ] If we have an AR(1), (a(beta)=1/(1-rho_{s}beta)approx2), and with (sigma(varepsilon)approx5%) in my little VAR, the AR(1) produces 10% inflation in response to a 1 standard deviation deficit shock. We should see 10% unanticipated inflation in recessions! We see if anything slightly less inflation in recessions, and little correlation of inflation with deficits overall. (a(beta)) near zero solves that puzzle.

2) Inflation volatility. The AR(1) likewise predicts that unexpected inflation has about 10% volatility. Unexpected inflation has about 1% volatility. This observation on its own suggests (a(beta)) no larger than 0.2.

3) Bond return volatility and cyclical correlation. The one-year treasury bill is (so far) completely safe in nominal terms. Thus the volatility and cyclical correlation of unexpected inflation is also the volatility and cyclical correlation of real treasury bill returns. The AR(1) predicts that one-year bonds have a standard deviation of returns around 10%, and they lose in recessions, when the AR(1) predicts a big inflation. In fact one-year treasury bills have no more than 1% standard deviation, and do better in recessions.

4) Mean bond returns. In the AR(1) model, bonds have a stock-like volatility and move procyclically. They should have a stock-like mean return and risk premium. In fact, bonds have low volatility and have if anything a negative cyclical beta so yield if anything less than the risk free rate. A small  (a(beta)) generates low bond mean returns as well.

Jiang, Lustig, Van Nieuwerburgh and Xiaolan recently raised this puzzle, using a VAR estimate of the surplus process that generates a high (a(beta)). Looking at the valuation formula [ frac{B_{t-1}}{P_{t}}=E_{t}sum_{j=0}^{infty}beta^{j}s_{t+j}, ] since surpluses are procyclical, volatile, and serially correlated like dividends, shouldn’t surpluses generate a stock-like mean return? But surpluses are crucially different from dividends because debt is not equity. A low surplus (s_{t}) raises  our estimate of subsequent surpluses (s_{t+j}). If we separate out
 [b_{t}=s_{t}+E_{t}sum_{j=1}^{infty}beta^{j}s_{t+j}=s_{t}+beta E_{t}b_{t+1}  ] a decline in the “cashflow” (s_{t}) raises the “price” term (b_{t+1}), so the overall return is risk free. Bad cashflow news lowers stock pries, so both cashflow and price terms move in the same direction. In sum a small (a(beta)lt 1) resolves the Jiang et. al. puzzle. (Disclosure, I wrote them about this months ago, so this view is not a surprise. They disagree.)

5) Surpluses and debt. Looking at that last equation, with a positively correlated surplus process (a(beta)>1), as in the AR(1), a surplus today leads to  larger value of the debt tomorrow. A deficit today leads to lower value of the debt tomorrow. The data scream the opposite pattern. Higher deficits raise the value of debt, higher surpluses pay down that debt. Cumby_Canzoneri_Diba (AER 2001) pointed this out 20 years ago and how it indicates an s-shaped surplus process.  An (a(beta)lt 1) solves their puzzle as well. (They viewed (a(beta)lt 1) as inconsistent with fiscal theory which is not the case.)

6) Financing deficits. With (a(beta)geq1), the government finances all of each deficit by inflating away outstanding debt, and more. With (a(beta)=0), the government finances deficits by selling debt. This statement just adds up what’s missing from the last one. If a deficit leads to lower value of the subsequent debt, how did the government finance the deficit? It has to be by inflating away outstanding debt. To see this, look again at inflation, which I write [ frac{B_{t-1}}{P_{t-1}}Delta E_{t}left( frac{P_{t-1}}{P_{t}}right) =Delta E_{t}s_{t}+Delta E_{t}sum_{j=1}^{infty}beta^{j}s_{t+j}=Delta E_{t}s_{t}+Delta E_{t}beta b_{t+1}=1+left[ a(beta)-1right] varepsilon_{t}. ] If (Delta E_{t}s_{t}=varepsilon_{t}) is negative — a deficit — where does that come from? With (a(beta)>1), the second term is also negative. So the deficit, and more, comes from a big inflation on the left hand side, inflating away outstanding debt. If (a(beta)=0), there is no inflation, and the second term on the right side is positive — the deficit is financed by selling additional debt. The data scream this pattern as well.

7) And, perhaps most of all, when the government sells debt, it raises revenue by so doing. How is that possible? Only if investors think that higher surpluses will eventually pay off that debt. Investors think the surplus process is s-shaped.

All of these phenomena are tied together.  You can’t fix one without the others. If you want to fix the mean government bond return by, say, alluding to a liquidity premium for government bonds, you still have a model that predicts tremendously volatile and procyclical bond returns, volatile and countercyclical inflation, deficits financed by inflating away debt, and deficits that lead to lower values of subsequent debt.

So, I think the VAR gives the right sort of estimate. You can quibble with any estimate, but the overall view of the world required for any estimate that produces a large (a(beta)) seems so thoroughly counterfactual it’s beyond rescue. The US has persuaded investors, so far, that when it issues debt it will mostly repay that debt and not inflate it all away.

Yes, a moving average that overshoots is a little unusual. But that’s what we should expect from debt. Borrow today, pay back tomorrow. Finding the opposite, something like the AR(1), would be truly amazing. And in retrospect, amazing that so many papers (including my own) write this down. Well, clarity only comes in hindsight after a lot of hard work and puzzles.

In more general settings (a(beta)) above zero gives a little bit of inflation from fiscal shocks, but there are also time-varying discount rates and long term debt in the present value formula. I leave all that to the book and papers.

(Jiang et al say they tried it with debt in the VAR and claim it doesn’t make much difference.  But their response functions with debt in the VAR, at left,  show even more overshooting than in my example, so I don’t see how they avoid all the predictions of a small (a(beta)), including a low bond premium.)

A lot of literature on fiscal theory and fiscal sustainability, including my own past papers, used AR(1) or similar surplus processes that don’t allow (a(beta)) near zero. I think a lot of the puzzles that literature encountered comes out of this auxiliary specification. Nothing in fiscal theory prohibits a surplus process with (a(beta)=0) and certainly not (0 lt a(beta)lt 1).


Jiang et al. also claim that it is impossible for any government with a unit root in GDP to issue risk free debt. The hidden assumption is easy to root out. Consider the permanent income model, [ c_t = rk_t + r beta sum beta^j y_{t+j}] Consumption is cointegrated with income and the value of debt. Similarly, we would normally write the surplus process [ s_t = alpha b_t + gamma y_t. ] responding to both debt and GDP. If surplus is only cointegrated with GDP, one imposes ( alpha = 0), which amounts to assuming that governments do not repay debts. The surplus should be cointegrated with GDP and with the value of debt.  Governments with unit roots in GDP can indeed promise to repay their debts.

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"The Market Was Made for Man, Not Man for the Market": Time to Ramp Up Direct Cash Payments



The need for large redirections of financial flows to avoid large increase in poverty during this coronavirus plague is large. The need for substantial top-ups to spending flows in view of the large jump in savings rates triggered by the arrival of coronavirus is large. The U.S. government continues to be able to borrow at unbelievable terms—terms so unbelievable that, when the accounting is done correctly, a larger national debt is not a drag on the funds the government has available for its other missions but rather a source of current cash flow.

(Why? Because in real population-adjusted terms, people are not charging the government interest on its debt but are instead paying the government to keep their money safe, but that is a discussion for another time.)

Moreover, a plan to have the government top off spending flows by whatever large amount is necessary to immediately return to full employment is moderately conservative, and the only effective way to give American businesses their proper chance to adjust and survive the coronavirus plague. It is, as John Maynard Keynes wrote back in 1936:

moderately conservative… [to] enlarge… the functions of government… [to include] the task of adjusting to one another the propensity to consume and the inducement to invest…. [It is] the condition of the successful functioning of individual [entrepreneurial] initiative. For if effective demand is deficient, not only is the public scandal of wasted resources intolerable, but the individual enterpriser who seeks to bring these resources into action is operating with the odds loaded against him. The game of hazard which he plays is furnished with many zeros, so that the players as a whole will lose if they have the energy and hope to deal all the cards…. [Success then requires] courage and initiative… supplemented by exceptional skill or unusual good fortune. But if effective demand is adequate, average skill and average good fortune will be enough… [thus] preserving [both] efficiency and freedom…

Our financial flows and property orders are a societal accounting system to guide and manage our collective societal division of labor. If dotting the i’s and crossing the t’s in this societal accounting system produces mass unemployment, the right response is to adjust it to produce full employment and then reconcile the accounting entries, not to watch employment fall and then sit around with our thumbs up our butts wondering what to do.

After all, the market was made for man, not man for the market—wasn’t it?:


Olugbenga Ajilore,​ Mark Blyth,​ J. Bradford DeLong,​ Susan Dynarski,​ Jason Furman,​ Indivar Dutta-Gupta,​ Teresa Ghilarducci,​ Robert Gordon, ​Samuel Hammond, Darrick Hamilton,​ Damon Jones, ​Elaine Maag, Ioana Marinescu,​ Manuel Pastor,​ Robert Pollin,​ Claudia Sahm, & al.: Open Letter from economists on Automatic Triggers for Cash Stimulus Payments We urge policymakers to use all the tools at their disposal to avoid further preventable harm to people and the economy, including​ ​recurring direct stimulus payments, lasting until the economy recovers. The widespread uncertainty created by the COVID-19 pandemic and recession calls for a multifaceted response​ ​that includes automatic, ongoing programs and policies including more direct cash payments to families; extended and enhanced unemployment benefits; substantial aid to state and local governments; stronger SNAP benefits; robust child care funding and more. These programs and policies will hasten the economic recovery far more effectively if they stay in place until economic conditions warrant their phaseout. ​Direct cash payments are an essential tool that will boost economic security, drive consumer spending, hasten the recovery, and promote certainty at all levels of government and the economy–for as long as necessary…

The economic pain is widespread and the need for immediate, bold action is clear. ​The pain from this crisis is undeniable. The unemployment rate is already ​dwarfing​ peak levels from the Great Recession, with ​higher levels​ of unemployment for Black and Latinx workers; GDP is expected to shrink by ​11 percent​ during the second quarter of this year; and ​27 million​ Americans have likely lost their health insurance along with their jobs. Much is still unknown, but it is clear at this point this recession will require significant and sustained stimulus policies that are responsive to the health of the economy. We agree with economists from ​across​ the ​political spectrum​ that concerns about debt and deficit should not get in the way​ of taking appropriately strong measures to stem the downturn now.

Regular, lasting direct stimulus payments will boost consumer spending, driving the economic recovery and shortening the recession. ​Right now, most Americans are just trying to keep their heads above water. The first round of economic impact payments were a lifeline that helped some get by for a few weeks—​early research​ shows that people are spending the stimulus checks quickly and on essentials—but the worst is not over. Consumer spending accounts for about two-thirds of GDP, so reviving the economy will require sustained efforts to strengthen it. Even after businesses start to re-open and jobs begin to come back, there will be ​significant economic fallout​, and demand will continue to lag if people don’t have money to spend. Regular direct stimulus payments tied to economic indicators will help families stay afloat and drive economic activity.

Automatic stabilizers ensure relief for as long as it is needed, promoting a strong recovery and efficient government. ​Many economists believe our response to the Great Recession was ​too small​ and ​too brief​, slowing the recovery and causing preventable harm particularly to low-income people. Cash assistance is an important element of economic aid, injecting resources through direct stimulus payments and ​refundable tax credits​ into low- and middle-income households that need help and are ​likely​ to spend it. That will start a chain reaction to boost local businesses and increase economic activity. Continuing recurring payments until there is reliable evidence of an economic recovery—such as low and declining unemployment—will promote certainty for all sectors of the economy and for state and local governments and federal agencies.
With many unknowns, it is critical to enact policies that will help promote a robust, sustained, racially equitable recovery and will stay in place until Americans are back on their feet.

.#coronavirus #equitablegrowth #highlighted #macro #publichealth #2020-07-07

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