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Archive for the ‘Macroeconomics’ Category

The Federal Reserve reportedly wants consumer inflation of about 2 percent per year, as measured by the personal consumption expenditures price index, affectionately known as the PCE. By that standard, Fed policy appears too tight, despite near-zero rates and ongoing QE:

PCE Inflation - March 2013

Over the past year, the headline PCE (dashed blue line) has increased only 1.0 percent, and the core PCE (orange line) is up only 1.1 percent. The core PCE strips out often-volatile food and energy prices not, as some wags would have it, because economists don’t drive, eat, or heat their homes, but because the resulting series appears to be a better predictor of future inflation trends (i.e., less noise, more signal).

At the moment, both measures are close together — and far below the Fed’s alleged target.

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By many accounts, Sweden did a great job managing its financial and fiscal crises in the early 1990s. But more than 20 years onward, its unemployment rate is still higher than before the crisis, as noted in a recent commentary by the Cleveland Fed’s O. Emre Ergungor (ht: Torsten Slok):

2013-03-3w

And its labor force participation rate is still lower:

2013-03-4w

Does Sweden’s experience portend similar problems for the United States? Ergungor thinks not. Instead, he attributes this shift to a structural change in Swedish policy that has no direct analog in the United States:

One study of public sector employment policies published in 2008 by Hans-Ulrich Derlien and Guy Peters indicates that for many years, the labor market had been kept artificially tight by government policies that replaced disappearing jobs in failing industries with jobs in the government. The financial crisis was the breaking point of an economic system that had grown increasingly more unstable over a long period of time. It was a watershed event that marked the end of an unsustainable structure and the beginning of a new one. Public sector employment declined from 423,000 in 1985 to 240,000 in 1996 mainly through the privatization of large employers—like the Swedish postal service, the Swedish Telecommunications Administration, and Vattenfall, the electricity enterprise—and it has remained almost flat since then.

With such a large structural change, what came before the crisis may no longer be a reference point for what will come after. Having corrected the root of the problem, the Swedish labor market is now operating at a new equilibrium.

That doesn’t mean smooth sailing for the United States, as he discusses. But it does leave hope that perhaps we do better than Sweden in creating jobs in the wake of a financial crisis.

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The U.S. economy has recovered slowly since the official end of the Great Recession in 2009. Mark Lasky and Charles Whalen of the Congressional Budget Office just released a study asking why. Their answer: two-thirds of the slowness (relative to past recoveries) reflects weak growth in the economy’s potential. The potential labor force, capital stock, and productivity are all growing less rapidly than they did following past recessions. The other third reflects cyclical weakness, particularly in government, housing, and consumer spending.

CBO’s Maureen Costantino and Jonathan Schwabish turned those results into a nifty infographic (click to make larger):

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The fine folks at FRED, the economic data service of the St. Louis Fed, recently added seven new data series showing how various measures of federal debt compare to the economy as a whole, as measured by GDP.

I particularly enjoyed this one, showing the federal debt owned by the Federal Reserve banks.

Quantitative easing gets all the press these days and understandably so given the recent spike in Fed ownership of Treasuries, now equivalent to almost 11 percent of annual GDP. But the chart also reminds us of that brief period early in the financial crisis when the Fed sold lots of Treasuries so it could make loans and buy other assets.

P.S. Anyone know how to get the FRED graph’s vertical axis to start at 0?

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Harvard historian Niall Ferguson goofed on Bloomberg TV yesterday. Arguing that the 2009 stimulus had little effect, he said:

The point I made in the piece [his controversial cover story in Newsweek] was that the stimulus had a very short-term effect, which is very clear if you look, for example, at the federal employment numbers. There’s a huge spike in early 2010, and then it falls back down.  (This is slightly edited from the transcription by Invictus at The Big Picture.)

That spike did happen. But as every economic data jockey knows, it doesn’t reflect the stimulus; it’s temporary hiring of Census workers.

Ferguson ought to know that. He’s trying to position himself as an important economic commentator and that should require basic familiarity with key data.

But Ferguson is just the tip of the iceberg. For every prominent pundit, there are thousands of other people—students, business analysts, congressional staffers, and interested citizens—who use these data and sometimes make the same mistakes. I’m sure I do as well—it’s hard to know every relevant anomaly in the data. As I said in one of my first blog posts back in 2009:

Data rarely speak for themselves. There’s almost always some folklore, known to initiates, about how data should and should not be used. As the web transforms the availability and use of data, it’s essential that the folklore be democratized as much as the raw data themselves.

How would that democratization work? One approach would be to create metadata for key economic data series. Just as your camera attachs time, date, GPS coordinates, and who knows what else to each digital photograph you take, so could each economic data point be accompanied by a field identifying any special issues and providing a link for users who want more information.

When Niall Ferguson calls up a chart of federal employment statistics at his favorite data provider, such metadata would allow them to display something like this:

 

Clicking on or hovering over the “2″ would then reveal text: “Federal employment boosted by temporary Census hiring; for more information see link.” And the stimulus mistake would be avoided.

I am, of course, skimming over a host of practical challenges. How do you decide which anomalies should be included in the metadata? When should charts show a single flag for metadata issues, even when the underlying data have it for each affected datapoint?

And, perhaps most important, who should do this? It would be great if the statistical agencies could do it, so the information could filter out through the entire data-using community. But their budgets are already tight. Failing that, perhaps the fine folks at FRED could do it; they’ve certainly revolutionized access to the raw data. Or even Google, which already does something similar to highlight news stories on its stock price charts, but would need to create the underlying database of metadata.

Here’s hoping that someone will do it. Democratizing data folklore would reduce needless confusion about economic facts so we can focus on real economic challenges. And it just might remind me what happened to federal employment in early 2009.

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My recent post on government size prompted several readers to ask a natural follow-up question: how has the government’s role as employer changed over time?

To answer, the following chart shows federal, state, and local employment as a share of overall U.S. payrolls:

In July, governments accounted for 16.5 percent of U.S. employment. That’s down from the 17.7 percent peak in early 2010, when the weak economy, stimulus efforts, and the decennial census all boosted government’s share of employment. And it’s down from the levels of much of the past forty years.

On the other hand, it’s also up from the sub-16 percent level reached back in the go-go days of the late 1990s and early 2000s.

Employment thus tells a similar story to government spending on goods and services: if we set the late 1990s to one side, federal, state, and local governments aren’t large by historical standards; indeed, they are somewhat smaller than over most of the past few decades. And they’ve clearly shrunk, in relative terms, over the past couple of years. (But, as noted in my earlier post, overall government spending has grown because of the increase in transfer programs.)

P.S. Like my previous chart on government spending, this one focuses on the size of government relative to the rest of the economy (here measured by nonfarm payroll employment). Over at the Brookings Institution’s Hamilton Project, Michael Greenstone and Adam Looney find a more severe drop in government employment than does my chart. The reason is that they focus on government employment as a share of the population, while my chart compares it to overall employment. That’s an important distinction given the dramatic decline in employment, relative to the population, in recent years. 

P.P.S. As Ernie Tedeschi notes, this measure doesn’t capture government contractors. So any change in the mix of private contractors vs. direct employees will affect the ratio. This is another reason why focusing on spending metrics may be better than employment figures.

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Politicians and pundits constantly debate the size of government. Is it big or small? Growing or shrinking?

You might hope these simple questions have simple answers. But they don’t. Measuring government size is not as easy as it sounds. For example, official statistics track two different measures of government spending. And those measures tell different stories:

The blue line shows how much federal, state, and local governments directly contribute to economic activity, measured as a share of overall gross domestic product (GDP). If you’ve ever taken an intro economics class, you know that contribution as G, shorthand for government spending. G represents all the goods and services that governments provide, valued at the cost of producing them. G thus includes everything from buying aircraft carriers to paying teachers to housing our ambassador in Zambia.

At 19.5 percent of GDP, G is down from the 21.5 percent it hit in the worst days of the Great Recession. As Catherine Rampell of the New York Times pointed out last week, it’s also below the 20.3 percent average of the available data back to 1947. For most of the past 65 years, federal, state, and local governments had a larger direct economic role producing goods and services than they do today.

There’s one notable exception: today’s government consumption and investment spending is notably larger than it was during the economic boom and fiscal restraint of the late 1990s and early 2000s. From mid-1996 to mid-2001, government accounted for less than 18 percent of GDP. Relative to that benchmark, government is now noticeably larger.

The orange line shows a broader measure that captures all the spending in government budgets—all of G plus much more. Governments pay interest on their debts. More important, they make transfer payments through programs like Social Security, Medicare, Medicaid, food stamps, unemployment insurance, and housing vouchers. Transfer spending does not directly contribute to GDP and thus is not part of G. Instead, it provides economic resources to people (and some businesses) that then show up in other GDP components such as consumer spending and private investment.

This broader measure of government spending is much larger than G alone. In 2011, for example, government spending totaled $5.6 trillion, about 37 percent of GDP. But only $3.1 trillion (20 percent of GDP) went for goods and services. The other $2.5 trillion (17 percent) covered transfers and interest.

Like G, this broader measure of government has declined since the (official) end of the Great Recession. Since peaking at 39 percent in the second quarter of 2009, it has fallen to 36 percent in the second quarter of 2012.

Also like G, this measure has grown since the boom of the late 1990s and early 2000s. In the middle of 2000, government spending totaled just 30 percent of GDP, a full 6 percentage points less than today.

The two measures thus agree on recent history: government has shrunk over the past three years as the economy has slowly recovered from the Great Recession and government policy responses have faded. But government spending is still notably larger than at the turn of the century.

The story changes, however, if we look further back in time. Although governments spent more on goods and services in the past, total spending was almost always lower. Since 1960, when data on the broader measure begin, total government spending has averaged about 32 percent. It never reached today’s 36 percent until 2008, when the financial crisis began in earnest.

Much of the recent increase in overall spending is due to the severity of the downturn. But that’s not the only factor. Government’s economic role has changed. As recently as the early 1960s, federal, state, and local governments devoted most of their efforts to providing public goods and services. Now they devote large portions of their budgets to helping people through cash and in-kind transfers—programs like Medicare and Medicaid that were created in 1965 and account for much of the growth in the gap between the orange and blue lines.

Government thus has gotten bigger. But it’s also gotten smaller. It all depends on the time period you consider and the measure you use.

P.S. Keep in mind that this discussion focuses on a relative measure of government size—the ratio of government spending to the overall economy—not an absolute one. Government thus expands if government spending grows faster than the economy and contracts if the reverse is true.

P.P.S. Measuring government size poses other challenges. Eric Toder and I discuss several in our paper “How Big is the Federal Government?” Perhaps most important is that governments now do a great deal of spending through the tax code. Traditional spending numbers thus don’t fully reflect the size or trend in government spending. For more, see this earlier post.

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The economy grew at a tepid 1.5% annual rate in the second quarter, according to the latest BEA estimates. That’s far below the pace we need to reduce unemployment.

Weak growth was driven by a slowdown in consumer spending and continued cuts in government spending (mostly at the state and local level), which overshadowed rapid growth in investment spending on housing–yes, housing–and equipment and software:

Housing investment expanded at almost a 10% rate in the second quarter, its fifth straight quarter of growth. Government spending declined at a 1.4% rate, its eighth straight quarter of decline.

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Another weak jobs report with payrolls up only 80,000, unemployment stuck at 8.2 percent, and underemployment ticking up to 14.9 percent.

But the real news continues to be how far employment has fallen. As recently as 2006, more than 63 percent of adults had a job. Today, that figure is less than 59 percent:

With the exception of the past several years, you’ve got to go back almost three decades to find the last time that so few Americans were employed (as a share of the adult population).

The stunning decline in the employment-to-population ratio (epop to its friends) reflects two related factors. First, the unemployment rate has increased from less than 5 percent to more than 8 percent. That accounts for roughly half the fall in epop. The other half reflects lower labor force participation. Slightly more than 66 percent of adults were in the labor force back them, but now it’s less than 64 percent.

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Financial repression and extractive institutions are two of the big memes in international economics today.

Financial repression occurs when governments intervene in financial markets to channel cheap funds to themselves. With sovereign debts skyrocketing, for example, governments may try to force their citizens, banks, and others to finance those debts at artificially low interest rates.

Extractive institutions are policies that attempt to redirect resources to politically-favored elites. Classic examples are the artificial monopolies often granted by governments in what would otherwise be structurally competitive markets. Daron Acemoglu and James Robinson have recently argued that such institutions are a key reason Why Nations FailInclusive institutions, in contrast, promote widely-shared prosperity.

Over at Bronte Capital, John Hempton brings these two ideas together in an argument that Chinese elites are using financial repression to extract wealth from state-owned enterprises. In a nutshell, he believes Chinese authorities have artificially lowered the interest rates that regular Chinese citizens earn on their savings (that’s the repression), and have directed these cheap funds to finance “staggeringly unprofitable” state enterprises that nonetheless manage to spin out vast wealth for connected elites and their families.

I don’t have the requisite first-hand knowledge to judge his hypothesis myself. But both his original post and recent follow-up addressing feedback are worth a close read.

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