Tag: Employment

Niall Ferguson’s Mistake Makes the Case for Metadata

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.

Has the Government Been Growing or Shrinking? Employment Edition

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.

Weak Employment in One Chart

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.

The Rising Risk of Social Unrest

The risk of social unrest is on the rise around much of the world, according to polling data summarized in the International Labour Organization’s latest World of Work Report (ht: Tortsen Slok).

The ILO estimates that the risk of unrest has risen the most in advanced economies over the past five years, followed by the Middle East & North Africa and South Asia:

With people in the streets from Athens to Oakland, the ILO clearly has a point about the advanced economies.

And what factors contribute to a rising risk of unrest? The ILO pegs six, all of which sound familiar:

• Income inequality and perception of injustice: Perception of economic and social disparities, and increasing social exclusion, is said to have a negative impact on social cohesion and tends to lead to social unrest (Easterly and Levine, 1997).

• Fiscal consolidation and budget cuts: Austerity measures have led to politically moti- vated protests and social instability. This has been the case in Europe for many years, from the end of the Weimar Republic in the 1930s to today’s anti-government demonstrations in Greece (Ponticelli and Voth, 2011), but has also been a feature in developing countries, especially in over-urbanized zones, where protests have arisen following the implementation of austerity programmes imposed by the International Monetary Fund or the World Bank (Walton and Ragin, 1990). Meanwhile, societies that are more indebted tend to have higher levels of social unrest (Woo, 2003).

• Higher food prices: In addition to collective frustrations regarding the democratic process, rising food prices were also central to the developments associated with the Arab Spring (Bellemare, 2011).

• Heavy-handedness of the State: In countries where the State has resorted to excessive use of force (police and military) to tackle social upheavals instead of focusing on the actual causes of unrest, such actions have often exacerbated the situation (Justino, 2007).

• Presence of educated but dissatisfied populace: Countries with large populations of young, educated people with limited employment prospects tend to experience unrest in the form protests (Jenkins, 1983; Jenkins and Wallace, 1996). This has been the case recently in many southern European countries, such Greece and Spain.

• Prevalence of mass media: Past studies have highlighted the impact of radio on the organization of demonstrations, and clearly the use of the Internet (e.g. through the use of Facebook and Twitter) have played a role in recent incidences of unrest.