unemployment – Page 3 – Donald Marron

1.1 Million More Jobs Lost

Today’s jobs report was weak across the board: September payrolls fell by 263,000, the unemployment rate rose to 9.8%, the underemployment rate (U-6) rose to 17.0%, and average weekly hours fell to 33.0, tying the record low set in June.

The Bureau of Labor Statistics also reported that payrolls declined by 13,000 more in July and August than it had previously estimated.

And if that weren’t enough, BLS also estimates the number of jobs back in March was actually 824,000 lower than previously reported (this is an estimate of the “benchmark revision” that BLS will make to the data early next year).

Putting these figures together, we find that the number of jobs has now declined by 1.1 million (263,000 + 13,000 + 824,000) more than we previously knew.

I have always found it frustrating that the BLS reports an estimate of the benchmark revision each October, but doesn’t incorporate that revision until the following February. That means that many analysts will be using incorrect data over the next few months.

If you want to know the number of jobs lost during the recession, for example, you might think you could get that number by clicking over to the BLS and comparing the number of jobs in September 2009 to the number of jobs in December 2007. That comparison would show total job losses of 7.2 million. Based on today’s estimate of the benchmark revision, however, it’s likely that the actual figure is more than 8.0 million.

Update: The original post had a typo for the average weekly hours; as noted above, the correct figure is 33.0, not 30.0.

Insight on Google and Unemployment

In a series of posts (here, here, and here), I have expressed concern that Google directs its users to what I think is the “wrong” measure of unemployment. For example, if you search for “unemployment rate United States” today, it will tell you that the U.S. unemployment rate in August was 9.6%, when the actual figure is 9.7%.

This discrepancy arises because Google directs users to data that haven’t been adjusted for seasonal variations. Almost all discussions of the national economy, however, use data that have been seasonally-adjusted. Why? Because seasonally-adjusted data (usually) make it easier to figure out what’s actually happening in the economy. The unemployment rate always spikes up in January, for example, because retailers lay off their Christmas help. But that doesn’t mean that we should get concerned about the economy every January. Instead, we should ask how the January increase in the unemployment rate compares to a typical year. That’s what seasonal adjustment does.

My concern about Google’s approach is that many (if not most) data users know nothing about seasonal adjustment. They simply want to know what the unemployment rate is and how it has changed over time. Directing those users to the non-seasonally-adjusted data thus seems like a form of search malpractice.

I’ve wondered why Google has chosen this approach, and thus was thrilled when reader Jonathan Biggar provided the answer in a recent comment. Jonathan writes:

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Google and Me

A strange this happened last week: Google misplaced my blog.

I’ve run all the usual diagnostics, and I can confirm that Google still knows that my blog exists. But it no longer appears in any of the searches – e.g., “natural gas price”, “unemployment”, “budget deficit”, or “brooke boemio” – that used to help new readers find posts on my site.

Things are so bad, in fact, that my blog doesn’t even come up when you search for “donald marron”. I feel an existential crisis coming on.

I presume this is just the result of some obscure algorithm tweak and that, over time, my posts will reappear in the ranks of the Google-worthy. But it’s fun to imagine that Google is mad at me for my posts criticizing the way it reports unemployment data.

I just checked and, no surprise, Google is still reporting the wrong data. If you search for “unemployment rate”, Google will tell you that the U.S. unemployment rate was 9.6% in August, when in fact it was 9.7%. Why the difference? Because Google is reporting an obscure measure of unemployment, not the one used by 99% of the world.

More Stimulus Spending Than Originally Projected

Lots of budget news this morning, with the release of the newest projections from the Office of Management and Budget and the Congressional Budget Office.

One headline is that spending on the stimulus will be higher than expected. As reported by Lori Montgomery at the Washington Post (ht EconomistMom):

The $787 billion economic stimulus package President Obama signed earlier this year is likely to cost “tens of billions of dollars” more than expected, helping to drive projections for next year’s budget deficit to $1.5 trillion, White House budget director Peter Orszag told reporters.

With unemployment climbing, costs for a variety of stimulus programs are running higher than anticipated, Orszag said, including expanded unemployment benefits, food stamps and energy grants. In an interview embargoed for release Tuesday morning, Orszag said he could not estimate the overall cost of the package, but he called Republican estimates of $900 billion “slightly high.”

The $900 billion estimate that Peter mentions is reported in this letter from former CBO Director Doug Holtz-Eakin to Republican House Leader John Boehner.

The CBO also addresses this issue in its report (box on pp. 10-11). The box discusses lots of pesky nuances about budget accounting and the timing of payments. Perhaps the most interesting observation, consistent with the OMB quote above, is that:

The higher-than-expected unemployment rate has led CBO to raise its estimates of spending in 2009 for ARRA [i.e., stimulus] provisions that affect unemployment compensation (by $7 billion) and Medicaid (by $1 billion).

In other words, the weaker economy has added $8 billion to stimulus spending in fiscal 2009 alone with, presumably, more to come in fiscal 2010.

These developments further complicate the challenging task of tracking the stimulus.

Google Is Still Wrong About Unemployment

Everyone who follows the U.S. economy closely knows that the unemployment rate was 9.4% in July, down 0.1% from June.

Everyone, that is, except Google.

If you ask Google (by searching for “unemployment rate United States“), it will tell you the unemployment rate in July was 9.7%.

What’s going on? Well, it turns out that Google is directing users to the wrong data series. As I discussed last month, almost everyone who talks about unemployment is using (whether they know it or not) data that have been adjusted to remove known seasonal patterns in hiring and layoffs (e.g., many school teachers become unemployed in June and reemployed in August or September). Adjusting for such seasonal patterns is standard protocol because it makes it easier for data users to extract signals from the noisy movements in data over time.

For unknown reasons, Google has chosen not to direct users to these data. Instead, Google reports data that haven’t been seasonally adjusted and thus do not match what most of the world is using.

This is troubling, since I have high hopes for Google’s vision of bringing the power of search to data sets. The ability of users to find and access data lags far behind their ability to find and access text. I am hopeful that Google will solve part of this problem.

But data search is not about mindlessly pointing users to data series. You need to make sure that users get directed to the right data series. So far, Google is failing on that front, at least with unemployment data.

P.S. As I discussed in a follow-up post last month, Wofram Alpha has an even more ambitious vision for making data — and computation — available through search. I like many of the things Alpha is trying to do, but they are lagging behind Google in several ways. For example, as I write this, they haven’t updated the unemployment data yet to reflect the new July data. (Click here for Alpha results.)

Bing isn’t trying yet.

Latest Data on Transfers and Income

In a series of posts (most recent here), I’ve documented that Americans are getting an increasing portion of their income from the government.

BEA released new data on incomes a couple weeks ago, including revisions back to 1995. These data reinforce the story I’ve described in my previous posts:

Transfers accounted for 17.3% of personal income in June. That’s the second highest in history, topped only by the 18.2% recorded in May, when transfers were boosted by one-time payments from this year’s stimulus act:

The increasing importance of transfers reflects both short-run developments and long-run trends. In the past year, the importance of transfers has grown because of (a) weakness in other forms of income, (b) the natural expansion of transfers due to economic weakness (e.g., increases in unemployment insurance payments), and (c) policies to expand benefits (e.g., as an attempt at stimulus). Over the longer run, however, the growth of transfers has been driven by the expansion of entitlement programs.

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A Less-Bad Jobs Report

The headlines in today’s jobs report were better than expected:

Payrolls fell by “only” 247,000 in July, somewhat smaller than the 325,000 that analysts had anticipated.
The unemployment rate ticked down to 9.4%.

If you dig into the numbers a bit further, you find some other encouraging nuggets:

Job losses in May and June were 43,000 smaller than BLS had previously estimated.
The average work week ticked up from 33.0 hours in June to 33.1 hours in July. That may seem like a small change, but it’s a good sign that hours have bounced off the record low recorded in June.
Average hourly earnings increased 0.2%. Again not a huge change, but clearly pointing in the right direction.
The U-6 measure of unemployment, which includes workers who are discouraged or working part-time for economic reasons, declined from 16.5% to 16.3%:

Losing 247,000 jobs is not a good month in the job market. But it is the best month since last August, before the fall of Lehman.

Health Insurance and Labor Markets

Health insurance is not just a health issue. It’s also a jobs issue. Why? Because about 60% of non-elderly Americans get their health insurance through an employer or a labor union. As a result, health insurance and employment are closely related.

As lawmakers consider changes to our system of health insurance, they should therefore keep an eye on the potential implications for jobs and wages. To help them do so, the Congressional Budget Office yesterday released a very helpful brief (see also the accompanying blog entry) that discusses many of the linkages between health insurance and the labor market.

Among other things, CBO reiterates a point I’ve made previously: that the costs of health insurance are ultimately born by workers through lower wages and salaries:

Although employers directly pay most of the costs of their workers’ health insurance, the available evidence indicates that active workers—as a group—ultimately bear those costs. Employers’ payments for health insurance are one form of compensation, along with wages, pension contributions, and other benefits. Firms decide how much labor to employ on the basis of the total cost of compensation and choose the composition of that compensation on the basis of what their workers generally prefer. Employers who offer to pay for health insurance thus pay less in wages and other forms of compensation than they otherwise would, keeping total compensation about the same.

CBO then goes on to discuss a range of potential policies, including ones that would impose new costs on employers. Such policies might require employers to provide health insurance to their workers (an employer mandate), for example, or might levy a fee on employers who don’t provide health insurance (play or pay). CBO concludes that, consistent with the argument above, employers would generally pass the costs of such measures on to their employees through lower wages and salaries. Such adjustments won’t happen instantly, so there may be some short-term effect on employment, but over time the cost will primarily be born by workers through lower compensation.

One exception, however, would be workers who currently earn low wages. As noted on the blog:

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Wolfram Alpha, Unemployment, and the Future of Data

I’ve received a number of helpful responses to my post about the strengths and weaknesses of Google’s efforts to transform data on the web. Reader DD, for example, reminded me that I ought to run the same test on Wolfram Alpha, which I briefly mentioned in my post on Google’s antitrust troubles.

Wolfram Alpha is devoting enormous resources to the problem of data and computation on the web. As described in a fascinating article in Technology Review, Wolfram’s vision is to curate all the world’s data. Not just find and link to it, but have a human think about how best to report it and how to connect it to relevant calculation and visualization techniques. In short:

[Wolfram] Alpha was meant to compute answers rather than list web pages. It would consist of three elements, honed by hand …: a constantly expanding collection of data sets, an elaborate calculator, and a natural-language interface for queries.

That is certainly a grand vision. Let’s see how it does if I run the same test “unemployment rate United States” I used for Google:

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Google, Unemployment, and the Future of Data

Google may eventually solve the problem of finding data on the web. Too bad its first effort reports the wrong numbers for unemployment.

Since leaving public service, I have occasionally pondered whether to start a company / organization to transform the way that data are made available on the web. The data are out there, but they remain a nuisance to find, a nuisance to manipulate, and a nuisance to display. I cringe every time I have to download CSV files, import to Excel, manipulate the data (in a good sense), make a chart, and fix the dumb formatting choices that Excel makes. All those steps should be much, much easier.

There are good solutions to many of these problems if you have a research assistant or are ready to spend $20,000 on an annual subscription. With ongoing technology advances, however, there ought to be a much cheaper (perhaps even free) way of doing this on the net. With some good programming, some servers, and careful design (both graphic and human factors), it should be possible to dis-intermediate research assistants and democratize the ability to access and analyze data. At least, that’s my vision.

Many organizations have attacked various pieces of this problem, and a few have even made some headway (FRED deserves special mention in economics). But when you think about it, this is really a problem that Google ought to solve. It has the servers, software expertise, and business model to make this work at large scale. And with its launch of a search service for public data it has already signaled its interest in this problem.

As a major data consumer, I wish Google every success in this effort. However, I’d also like to use their initial effort, now almost three months old, as a case study in what not to do.

Google’s first offering of economics data is the unemployment rate for the United States (also available for the individual states and various localities). Search for “unemployment rate united states” and Google will give you the following graph:

Your first reaction should be that this is great. With absolutely no muss and no fuss, you have an excellent (albeit sobering) chart of the unemployment rate since 1990. I would add myriad extensions to this – e.g., make it easier to look at shorter time periods, allow users to look at the change in the unemployment rate, rather than the level, etc. – but the basic concept is outstanding.

Unfortunately, there is one major problem: That’s the wrong unemployment rate.

Click over to the Bureau of Labor Statistics, open a newspaper (remember them?), or stay right here on my blog – all of them will tell you that the unemployment rate in June was 9.5% not 9.7%.

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