Posts Tagged unemployment rate
April Jobs Report
Posted by TonyLima in Current issues on May 3, 2013
The media are in a kerfuffle over the April jobs report. Lots of jobs created, the unemployment rate fell, what’s not to like?
There’s a reason economics is called the dismal science. Economists have this nasty habit of pointing out the discrepancies between belief and reality. The April report is no exception.
Just for kicks, I’ve dissected the first four months of employment data from BLS. These numbers are all from the current population survey (CPS) so they are consistently sourced. Results are not promising. The reported unemployment rate fell to 7.5% in March. Using just about any other measure that’s reasonable, 7.8% is a better estimate.[1] BUT, if you look at the measure BLS calls “U-6″ things get really bad. What’s U-6? Here’s what BLS says:
Total unemployed, plus all marginally attached workers plus total employed part time for economic reasons, as a percent of all civilian labor force plus all marginally attached workers
Aren’t you happy you asked? For April, 2013, U-6 was 13.9%, up 0.1% from March.
As always, my methods are transparent. Click here to download the Excel workbook that has all the calculations and numbers cited here (and a whole lot more).
[1] OK, since you asked, I did two other calculations. Between January and April 2013, the labor force decreased by 273,000 people. My first calculation added all those folks back in and assumed they would all have been unemployed. You don’t believe that? Frankly, neither do I. So I calculated the net change in those who are not in the labor force but want a job. That’s not the same as “discouraged workers.” If you care about that, e-mail me and I’ll be happy to send you a two-page extract from the BLS “Handbook of Methods” that describes the process in detail.
The Other Cliff — Regulations
Posted by TonyLima in Economic policy, The state of the economy on December 22, 2012
Pending and Proposed Regulations
About two years and nine months ago I wrote an article pointing out the limitations of conventional fiscal policy analysis. To summarize, there is more to fiscal policy than G, TA, and TR (government spending, taxes, and transfer payments for those a little rusty on their macroeconomics). Government regulations also have a significant impact on the economy. Now that the election is behind us, the economy has fallen off the other cliff — regulations. This article will give a few examples, but the main point is in the table above (from the handy government website Regulations.gov on December 22, 2012). Almost 6,000 new regulations have been posted in the last 90 days. Half of those (3,148 to be precise) have been posted since the election. (Click the “Last 90 days” link, then look for the “custom date range” filter and you can play along, too.) If you believe that’s not going to have a significant impact on businesses, then you probably also believe the unemployment rate was under 7 percent last month.
Regulations, Rules, and Hiring, Oh, My
Sometimes the impact of these regulations can be seen easily. For example, the CAFE (corporate average fuel economy) standards imposed on the U.S. auto industry has done as much as anything to distort the auto market. Since CAFE standards do not apply to light trucks, automakers in the U.S. have been pushing them like mad. High margins are maintained with the help of a nifty 25% tariff on imported light trucks. A somewhat offsetting benefit is that some foreign car makers have set up assembly lines in the U.S., increasing U.S. employment. Trust me, this will not offset the harm done by the tariff.
In other cases, the regulations have a less specific impact. Most economists now agree that a significant contribution to the high unemployment rate in the U.S. has been uncertainty over the rules and regulations that will be required by the Patient Affordable Care Act [sic] (ACA) and the Dodd–Frank Wall Street Reform and Consumer Protection Act. Uncertainty means risk and businesses — especially small businesses — are very risk-averse. Some of the impacts are already being seen. For example, one ACA rule says that part-time employees who work less than 30 hours per week are exempt from ObamaCare rules. The result has been entirely predictable: businesses that rely on part-time employees are cutting their hours. One highly publicized example is Papa John’s Pizza. Darden Restaurants owns the Olive Garden and Red Lobster chains. They, too, are moving toward limiting part-time employees to less than 30 hours per week.
And consider the marginal cost of hiring employee number 50. “Businesses with 50 or more full-time workers must pay a $2,000 penalty for each employee, beyond the first 30 workers, who qualifies for subsidies and does not have employer coverage.[1] Part-time workers also count toward the number of employees in the firm (and thus toward the 50-employee threshold), but the government does not penalize firms for not offering them qualifying insurance.” (from the Heritage Foundation, but widely available. Other good articles are here and here.). So hiring employee number 50 carries a potential cost of 20 employees (50-30) times $2,000 per employee fine equals $40,000. That could easily be more than the actual wages paid to the 50th employee. I suspect there will be many firms that will simply stop hiring once they get to 45 employees.
Finally, consider the impact of the 2.3% tax on medical device sales in the U.S. scheduled to go into effect January 1. Medical device companies have announced layoffs as a direct result of this tax. Stryker Corp. will lay off about 100 workers at their Kalamazoo, Michigan offices and about 1,000 worldwide. I’ve written about this a couple of times before (here and here). It’s a shame that many so-called economists couldn’t manage to predict this.
Conclusion
Ironically, the ACA may actually reduce the unemployment rate. By cutting hours, businesses may well need more employees. But the underemployment rate is already intolerably high and will undoubtedly rise. Perhaps we need to revise Arthur Okun’s misery index (the sum of the unemployment rate and the inflation rate). I propose something simple: the sum of the unemployment rate, the inflation rate and half the difference between the underemployment rate and the unemployment rate. Details on this Enhanced Misery Index (EMI, as if we needed another TLA) will be forthcoming in a future article.
————-
[1]The portion of the health care law on the employer mandate explicitly states that firms with more than 50 employees are required to offer “full-time employees (and their dependents) the opportunity to enroll in minimum essential coverage under an eligible employer sponsored plan.” The Department of Treasury, however, has issued a proposed rule linking both the affordability of employer-sponsored insurance and compliance with the individual mandate to single coverage only. Since the employer is not penalized unless an employee enrolls in the exchanges, it is possible that if this proposed rule is adopted, employers will either drop family coverage or be indifferent to the affordability of the workers’ family coverage. Alternatively, the government may ultimately require employers to provide family coverage to workers with dependents. See Patient Protection and Affordable Care Act, Public Law 111-148, § 4980H.
The September Jobs Report
Posted by TonyLima in Current issues, Labor Market Issues 2000 to 2012 on October 14, 2012
It’s been nine days since the September jobs report was released by the Bureau of Labor Statistics. I’ve been working on a much longer article, but decided to post this abbreviated version to pull together some analysis.
Introduction
Did the U.S. economy really gain 873,000 jobs in September, 2012? Was the unemployment rate really 7.8%? Economists have reacted to these numbers with a peculiar mixture of disbelief and defensiveness. No sane economist believes these numbers represent the current state of the U.S. economy. A quick-and-dirty estimate says that real GDP would have to grow at a 4 – 5% annual rate to add that many jobs. Actual GDP growth in recent quarters has been below 2.5%.
U.S. Employment
But, at the same time, we economists are vehemently defending the statisticians and economists at the Bureau of Labor Statistics (BLS). (Technical note: we should also be defending the Census Bureau because those folks conduct the “household survey” under contract from BLS. Technically the household survey is called the current population survey, CPS, while the establishment survey is called current employment statistics, CES.)
Before going any further, I have to say that there’s a good chance that the 873,000 increase in jobs is simply a statistical fluke. Remember, total employment is estimated using a sample of 60,000 households. There is a large margin of error. More details are in the next section of this paper where I look at the numbers and analyze this possibility.
The purpose of this report is to reconcile those two conflicting viewpoints: the jobs number seems unbelievable, but I remain fully confident in the integrity of the number wonks at BLS. And there is also a contribution from the vagaries of the seasonal adjustment process the BLS uses, specifically the treatment of those between ages 20 and 24. (For those who are interested, Catherine Rampell has an excellent discussion in her blog at the New York Times website (may be behind a paywall). I have included Ms. Rampell’s numbers with a few additions as the last worksheet in the Excel workbook for this report.)
A Quick Look at the Numbers
Before heading into the analysis, I have to mention a few facts about the data. Since January, 2002 the month-to-month change in employment has had a standard deviation of 356,510 and a mean of only 56,820. This is a very imprecise number with huge month-to-month volatility. It has been alleged that the 853,000 employment increase in September, 2012 was the largest increase in 29 years. Not according to the data: since January, 2002 (and including September, 2012) there have been nine months when employment increased by more than 500,000 and three months in which employment gained more than 750,000 (January, 2012, +847,000 and January, 2003 with a whopping +991,000). At best, this is the largest increase in 108 months. The point is that this number moves all over the place. We shouldn’t take the +873,000 figure any more seriously than, say, the job loss of 1,141,000 in January, 2009.
Month-to-Month Change in U.S. Employment
If you want to stop reading right now, that’s fine with me. But I think you may find parts of this revealing and/or instructive. Some parts may even be mildly entertaining.
Statistical Issues and Seasonal Adjustment: Half the Gain
There have been steady changes in the number of people ages 20 − 24 who are employed each September. According to Ms. Rampell, since 1948 employment in this group fell by an average of 398,000 in September. In September, 2012, employment of these folks increased by 101,000. After processing with the standard seasonal adjustment software, the actual seasonally adjusted increase was 368,000, about 42% of the total increase in September. That leaves 853,000 − 368,000 = 485,000 new jobs still to be explained. Read on.
Note, however, that the 485,000 figure is well within 1.5 standard deviations of the mean since 2002. That’s a bit more evidence that the number is simply a statistical fluke.
Before going further, it’s important to understand how things are measured. Much of the following is from the Bureau of Labor Statistics’ Handbook of Methods. (On the BLS website, the handbook is available chapter-by-chapter as separate web links. Click here to download a copy as a single pdf file. And, as always, my methodology is transparent. Click here to download the Excel workbook with the gruesome details. This is an Excel 2011 workbook.)
Definitions
An individual in the CPS sample is employed if, “during the reference week, (1) did any work at all as paid employees, worked in their own business or profession or on their own farm, or worked 15 hours or more as unpaid workers in a family-operated enterprise; and (2) all those who did not work but had jobs or businesses from which they were temporarily absent due to illness, bad weather, vacation, childcare problems, labor dispute, maternity or paternity leave, or other family or personal obligations—whether or not they were paid by their employers for the time off and whether or not they were seeking other jobs. Each employed person is counted only once, even if he or she holds more than one job. Included in the total are employed citizens of foreign countries who are residing in the United States, but who are not living on the premises of an embassy. Excluded are persons whose only activity consisted of work around their own home (such as housework, painting, repairing, and so forth) or volunteer work for religious, charitable, and similar organizations.” (BLS Handbook of Methods, chapter 1, p. 6)
An individual who did one hour of work for pay during the reference week counts as employed. The “reference week” is the week of the month that includes the 12th day.
Individuals in the sample are unemployed if they “1) had no employment during the reference week; 2) were available for work, except for temporary illness; and 3) had made specific efforts, such as contacting employers, to find employment sometime during the 4-week period ending with the reference week. Persons who were waiting to be recalled to a job from which they had been laid off need not have been looking for work to be classified as unemployed.”
This definition, of course, creates the “discouraged worker” phenomenon, along with its impact on the unemployment rate. (Those interested should read my blog post about the labor force participation rate.)
The labor force is the sum of the number of people employed and the number of people unemployed. The unemployment rate is the number unemployed divided by the labor force. So simple, yet with much hidden complexity.
Now that you understand who is employed, who is unemployed, and who is not in the labor force, let’s turn our attention to sampling methodology.
BLS – Census Methodology
There are 60,000 households surveyed each month by the Census Bureau for the Current Population Survey (CPS, usually called the “household survey.”) That translates into 155,400 individuals using the Census figure of 2.59 people per household. Of those 155,400 individuals, 78.79% will be age 16 or over. Even though Census questions those age 15, the only data reported for purposes of the jobs report is on those 16 and over. With an unemployment rate of 8.11%, we expect 9,932 individuals in the household survey to be unemployed.
Now set a target unemployment rate, say 7.8%. That implies 9,551 of those surveyed need to be unemployed, a decrease of only 381 people compared to the 7.11% unemployment rate. Scary, isn’t it? Such are the vagaries of projecting a relatively small sample onto a large population. (BLS and Census know this. There are warnings all over their websites and in the BLS Handbook.)
Census conducts the survey during the week of the month that contains the 19th of that month. Respondents are asked about their employment status for the preceding week, the week that includes the 12th. There is a rather complicated pattern of rotation in and out of the sample.
“Rotation of sample. Part of the sample is changed each month. Each monthly sample is divided into eight representative subsamples or rotation groups. A given rotation group is interviewed for a total of 8 months, divided into two equal periods. The group is in the sample for 4 consecutive months, leaves the sample during the following 8 months, and then returns for another 4 consecutive months. In each monthly sample, 1 of the 8 rotation groups is in the first month of enumeration, another rotation group is in the second month, and so on. (The rotation group in the fifth month of enumeration is returning after an 8-month break.) Under this system, 75 percent of the sample is common from month to month and 50 percent is common from year to year for the same month. This procedure provides a substantial amount of month-to-month and year-to-year overlap in the sample, thus yielding better estimates of change and reducing discontinuities in the series of data without burdening sampled households with an unduly long period of inquiry.” (BLS Handbook of Methods, chapter 1, p. 7)
Conclusion
There’s a reason economists like me make a fairly good living. We’re willing to dig into the numbers and the underlying assumptions. If you found this persuasive and/or interesting, you may have the economist gene.
Rounding the Unemployment Rate
Posted by TonyLima in Current issues on August 5, 2012
President Obama’s chief economic adviser Alan Krueger has gained a certain bit of infamy for rounding the unemployment rate: ”More precisely, the rate rose from 8.217% in June to 8.254% in July,”Krueger wrote on the official White House blog, adding: “Acting BLS Commissioner John Galvin noted in his statement that the unemployment rate was ‘essentially unchanged’ from June to July.”
This is stupid. There are good reasons the unemployment rate is only reported to one decimal place. Even with a sample of 60,000, there is a statistical estimation error. (See below for a more complete description from the Bureau of Labor Statistics. Contrary to popular opinion, claims for unemployment benefits are not used because those figures ignore unemployed people whose benefits have run out.) Prof. Krueger should know better. (Of course, he is infamous as the co-author of a badly flawed paper that purported to show increasing the minimum wage lowered the unemployment rate.[1])
This blog is about data. So let’s look at some recent allegations and see how they stack up. (As always, my methodology and data are transparent. Click here to download an Excel workbook containing everything I’ve used to support this post.)
One claim is that the unemployment rate would have been much higher if discouraged workers had been included. Discouraged workers are:
“Persons not in the labor force who want and are available for a job and who have looked for work sometime in the past 12 months (or since the end of their last job if they held one within the past 12 months), but who are not currently looking because they believe there are no jobs available or there are none for which they would qualify.”[2]
In June, 2012 there were 821,000 discouraged workers. That figure increased to 852,000 in July. Here’s a summary of the unemployment rates:
|
|
Jun-12 |
Jul-12 |
|
Unemployment rate as reported |
8.217% |
8.254% |
|
Unemployment rate including discouraged workers |
8.700% |
8.755% |
So including discouraged workers raises the unemployment rate by about 0.5 percentage points.
But there’s a second category of interest under the heading “Not in labor force.” That is “marginally attached workers” defined as:
“Persons not in the labor force who want and are available for work, and who have looked for a job sometime in the prior 12 months (or since the end of their last job if they held one within the past 12 months), but were not counted as unemployed because they had not searched for work in the 4 weeks preceding the survey. Discouraged workers are a subset of the marginally attached.”[3]
That’s quite a mouthful. Let me summarize. Marginally attached workers are really, really discouraged workers. If we include marginally attached workers, the picture gets considerably worse:[4]
|
|
Jun-12 |
Jul-12 |
|
Unemployment rate as reported |
8.217% |
8.254% |
|
Unemployment rate including marginally attached workers |
9.662% |
9.726% |
Look, folks, unemployment rates above 8% are simply unacceptable. The government screwed up the first stimulus by not shoveling the spending out the door fast enough. They then proceeded to issue so many new regulations (including those issued, proposed, and feared) that businesses have no idea what the future cost of new employees will be. Meanwhile, the Obama administration insists on increasing taxes on those with incomes over $250,000 per year. Best estimates are that the proposed new taxes would raise between $35.4 and $37.1 billion.[5] This amount is pocket lint compared to our $1,500 billion budget deficit. (If you’re looking for an explanation of the difference between the budget deficit and the government debt, here’s something I wrote a while back.) Talk about fiddling while the economy burns.
I’ve said it before and it bears repeating: an unemployment rate over 8 percent is no time to raise taxes. Anybody’s taxes. Period. The Democrats should get over their obsession with “fairness” and admit that the tax increase they’re insisting on isn’t worth squat.
[1] Card, David; Krueger, Alan B., “Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania.” Economics of Labor and Employment Law. Volume 2., 2007, pp. 5-26, Elgar Reference Collection. Economic Approaches to Law, vol. 12.. Cheltenham, U.K. and Northampton, Mass.: Elgar
[2] http://www.bls.gov/bls/glossary.htm/#D Accessed August 5, 2012.
[3] http://www.bls.gov/bls/glossary.htm/#M Accessed August 5, 2012.
[4] Being careful, of course, to not double-count discouraged workers.
[5] Tax Policy Institute (data from Joint Committee on Taxation, U.S. Congress). Available at http://taxpolicycenter.org/numbers/displayatab.cfm?Docid=3463&DocTypeID=5 accessed August 5, 2012. Also included in the Excel workbook for this entry.
January Unemployment
Posted by TonyLima in Current issues, The state of the economy on February 3, 2012
U.S. Labor Force Participation Rate
The January unemployment rate was released this morning. Let’s get one thing out of the way right now. Last month I forecast 8.7% for January. The actual was 8.3%. “Forecasting is difficult, especially when it’s about the future.” – Nils Bohr
Economics is known as the dismal science. You’re about to learn why. How can a 0.2 percentage point decline in the unemployment rate be bad news? Read on.
First, every January the BLS updates their data for the civilian non-institutional population to align their data with information from the Census Bureau and other sources. Guess what? The bump to population was 1,685 thousand. At the same time the civilian labor force increased by 508 thousand. The labor force participation rate fell to 63.73%, the lowest level since 1979.
So apparently there were about 1.7 million folks that BLS thought were dead that were, in fact, alive. Some have argued that the decrease in the labor force participation rate is partly caused by the retirement of baby boomers. I wish. Everyone I know born after World War II is still working or looking for work.
Let’s look at changes between December, 2011 and January, 2012. The number of people unemployed fell by 339 thousand. Good news. And the number employed rose by 847 thousand, also good news. But 1,177 thousand people dropped out of the labor force. The employment – population ratio has remained virtually constant at 58.5% for the last three months. That means the gyrations between employment, unemployment, and labor force dropouts are just about offsetting each other.
When the unemployment rate drops mainly because an additional million people have left the labor force and population estimates are revised … well, let’s just say this report is not the sign of a healthy economy.
As always my work is an open book. Click here for the most recent Excel workbook.
December Unemployment Rate
Posted by TonyLima in The state of the economy on January 6, 2012
The December unemployment rate was released this morning. The measured rate dropped to 8.5%. As always, a good part of this drop was caused by the ongoing decline of the number of workers in the labor force. The labor force participation rate dropped sharply to 64.1%. This is the lowest participation rate since 1983′s 64.0%. Anyone who argues that the drop in the unemployment rate signals an improving economy should be forced to recycle their Ph.D. in economics into aluminum beer cans. The graph below tells the gruesome story.
U.S. Labor Force Participation Rate
Unemployment Rates Revised for 2011
In other news, the Bureau of Labor Statistics issued revisions to the unemployment rate for the twelve months in 2011. The table below is from the BLS employment report.
|
Month |
As first computed |
As revised |
Change |
| January |
9.0 |
9.1 |
+0.1 |
| February |
8.9 |
9.0 |
+0.1 |
| March |
8.8 |
8.9 |
+0.1 |
| April |
9.0 |
9.0 |
0.0 |
| May |
9.1 |
9.0 |
-0.1 |
| June |
9.2 |
9.1 |
-0.1 |
| July |
9.1 |
9.1 |
0.0 |
| August |
9.1 |
9.1 |
0.0 |
| September |
9.1 |
9.0 |
-0.1 |
| October |
9.0 |
8.9 |
-0.1 |
| November |
8.6 |
8.7 |
+0.1 |
As I wrote last month, the November unemployment rate seemed too low. Frankly, however, I’d chalk that up to a lucky guess rather than any particular skill on my part.
As my fellow economist Dean Baker (co-director, Center for Economic Policy Research) noted in his Twitter feed (@DeanBaker13), some 42,000 of the new jobs were courier jobs, presumably seasonal hiring by FedEx, UPS, and other companies whose business increases sharply during December. However, the unemployment rate and most other statistics are seasonally adjusted. Let’s see if we can sort this out. (Even the BLS commented on this in their report, stating “Employment in transportation and warehousing rose sharply in December (+50,000). Almost all of the gain occurred in the couriers and messengers industry (+42,000); seasonal hiring was particularly strong in December.” The actual change from November to December in courier employment was an increase of 85,900 workers. The 42,200 figure cited by Baker uses the seasonally adjusted (SA) numbers. The 85,900 figure uses data that is not seasonally adjusted (NSA). Allow me a small digression.
Seasonal Adjustment
Most monthly and quarterly data is seasonally adjusted. The idea is to adjust for regular cyclical changes that occur every year. Two big causes of seasonality are holidays (Christmas, Kwanzaa, Hanukkah) and, well, the season. Ice cream sales rise in the summer. More products are shipped in November and December. Seasonal adjustment is designed to remove the regular changes that occur every year. These days seasonal adjustment is tricky because of the rapid changes in technology, demographics, and the economy itself. So the real question is how the difference between the seasonally adjusted and not seasonally adjusted figures for December, 2011 compare with historical data. I’ll add a technical note at the end of this post to explain how to find the exact data.
There’s another issue that came up looking at the data. The difference between the NSA and SA figures for December rose sharply beginning in 2006. The average difference between 2001 and 2005 was 15,620. From 2006 to 2011 the average was 40,200. Thus the NSA – SA figure more than doubled on average starting in 2006.
Statistical Results
Before I go any further, if you want the data, click here to download an Excel 2003 workbook. The last tab includes data sources and an explanation of how to extract this data from the bls.gov website.
What we really want to determine is whether the 60,900 difference between NSA and SA in December, 2011 is statistically different from the average. To do this we use a t-test. Calculating the standard deviation, then calculating (December – average)/standard deviation gives us a t-statistic. (Yes, I calculated the sample standard deviation.) Using data from 2006 – 2011 the t-statistic is 1.68. Not statistically significant at the five percent level. According to Stat Trek online the actual significance level is about 7.74%. Nice grey area result. (Naturally, using the entire sample period 2001 – 2011, the t-statistic improves to 2.06. Until someone can explain what happened in 2006, I’m sticking to 1.68.) For the masochists who like to see the numbers, here they are:
| Dec. year | Dec. SA (year) | Dec. NSA | Diff |
| 2011 | 567.80 | 628.70 | 60.90 |
| 2010 | 573.60 | 623.70 | 50.10 |
| 2009 | 561.30 | 594.70 | 33.40 |
| 2008 | 562.70 | 595.40 | 32.70 |
| 2007 | 588.00 | 620.80 | 32.80 |
| 2006 | 590.70 | 622.00 | 31.30 |
| 2005 | 579.70 | 591.10 | 11.40 |
| 2004 | 562.30 | 572.60 | 10.30 |
| 2003 | 542.60 | 568.00 | 25.40 |
| 2002 | 563.80 | 580.10 | 16.30 |
| 2001 | 577.50 | 592.20 | 14.70 |
| Average (2001-2005) | 15.62 | ||
| Average (all) | 27.91 | ||
| StdDev (all) | 15.98 | ||
| Average (2006-2011) | 40.20 | ||
| StdDev (2006-2011) | 12.35 | ||
| t (2011 – average all) | 2.06 | ||
| t (2011 – average 2006 and later) | 1.68 |
Another way of looking at this issue is to compare job gains from November to December with job losses from December to January. We’ll have to wait another month to get the full comparison for this season, but here’s the seasonally adjusted data from 2006 – 2010:
| Dec. year | Diff Jan – Dec SA | Diff Dec – Nov SA |
| 2011 | 42.20 | |
| 2010 | -48.70 | 46.30 |
| 2009 | -40.80 | 30.10 |
| 2008 | -5.30 | 13.40 |
| 2007 | -4.10 | 7.00 |
| 2006 | -8.40 | 1.30 |
For the last two years job losses in January have been greater than job gains in December. And remember, these are seasonally adjusted data. Unless the labor force continues to shrink at an alarming rate, the unemployment rate for January should tick up to about 8.7%. Remember, you read it here first.
One more item of note. The NSA – SA difference in December, 2010 was 50,100. In the four years before that, the difference was in the neighborhood of 35,000. Something is going on here. If I had to guess, I’d speculate that it’s the ongoing steady increase in online shopping. But wait — these are courier services, not UPS and FedEx. I look forward to comments from those smarter (and/or more imaginative) than me to clarify this mystery.
Note on Retrieving BLS Data
Start at http://www.bls.gov/data. Select the link to Employment data, then select the multi-screen data search column in the “Employment, Hours, and Earnings – National” row. On the next screen, check both the seasonally adjusted and not seasonally adjusted boxes, then click next form. Scroll down the “Supersector” list box until you see sector 43: Transportation and Warehousing. Click that, then next form. In the Datatype list box, click All Employees, Thousands, then click next form. Scroll down the Industry list box until you find 434920000 Couriers and messengers. Click that, then next form. The list box should have two series in it: CES4349200001 and CEU4349200001. CES is the seasonally adjusted data and CEU is not seasonally adjusted. Click retrieve data, then download the two Excel files that are generated.
There’s probably an easier way to get this data, but I’ve spent enough time trying to figure out how the BLS hides data.
Yet Another Downward Revision
Posted by TonyLima in Current issues on December 23, 2011
As predicted here, the “third” estimate of third-quarter U.S. GDP saw yet another downward revision. Recall the “advance” estimate was 2.5% growth, while the “second” estimate was 2.0%. (Translation: the “advance” estimate is the preliminary estimate, the “second” is the revised estimate, and the “third” is the final estimate.)
A growth of 2.5% is about what it takes to keep the unemployment rate constant. A 2.0% growth rate is all right, but pretty anemic. The 1.8% growth announced today is very anemic.
Given the very low rate of real growth, why did the unemployment rate drop in November? The answer I posted three weeks ago was the decrease in the size of the labor force as discouraged workers stop looking for work, reducing the number of unemployed. That explanation looks even more plausible in light of the slow growth of the third quarter GDP.
This is from the BEA website (edited slightly and put into a real table for easy pasting into Excel).
“Revisions
The third estimate of the third-quarter increase in real GDP is 0.2 percentage point, or $6.2 billion, lower than the second estimate issued last month, primarily reflecting a downward revision to personal consumption expenditures that was partly offset by an upward revision to private inventory investment. (Figures are percent change from preceding quarter.)
| Advance Estimate | Second Estimate | Third Estimate | |
| Real GDP |
2.5 |
2.0 |
1.8 |
| Current-dollar GDP |
5.0 |
4.6 |
4.4 |
| Gross domestic purchases price index |
2.0 |
1.9 |
2.0” |
Source: http://www.bea.gov/newsreleases/national/gdp/gdpnewsrelease.htm
Unemployment Drops to 8.6% — Can the News Really Be That Good?
Posted by TonyLima in The state of the economy on December 3, 2011
This morning the Bureau of Labor Statistics released the employment report for November. The good news is that the unemployment rate fell to 8.6%. Wow. But all is not rosy as we’ll see.
The headlines said the private sector added 140,000 jobs in November, but that was offset by a loss of 20,000 government jobs. Net gain: 120,000 jobs. Oh, really? Allow me a brief digression.
The BLS actually does two different surveys. The unemployment rate is based on the household survey, a large sample of U.S. households. But the jobs numbers cited in the headlines are from the establishment survey which surveys business and government. The two surveys often diverge, particularly during periods when unemployed workers are hanging out their own consulting shingles. The household survey includes these new businesses, but the establishment survey doesn’t know those new businesses exist (yet).
So let’s take a closer look at the household survey results. (Anyone who wants to play with the data should e-mail me for an Excel workbook containing seven of the BLS tables as well as a couple of tables I created for this blog.)
The number of people unemployed fell by 594,000. Of that, 315,000 were people who dropped out of the labor force. The civilian labor force fell from 154,198,000 to 153,883,000. According to the household survey, the number of people employed rose by 278,000. The sum of those two numbers (315,000 + 278,000) is equal to the change in unemployment (593,000, compared with the reported figure of 594,000, a difference most likely caused by rounding error).
Today the U.S. labor force participation rate is at the lowest level since the mid-1980s. Is it good news that so many people have given up looking for work? Some have taken early retirement, others have moved in with their families or friends. An 8.6% unemployment rate is good news, but not nearly as good as the headline writers would have you believe.
For the year 2010 the labor force participation rate was 64.7%. In November, that figure dropped even further to 64.0%. Remember, real GDP is equal to the number of workers times average worker productivity. The current increases in U.S. output are largely being fueled by huge productivity increases. As the U.S. moves increasingly toward a service producing information economy, the productivity of educated people will continue to soar. The question of what happens to the rest of the population remains unanswered.
U.S. Labor Force Participation Rate
Nine Point Eight! Are You Convinced Yet?
Posted by TonyLima in The state of the economy on December 3, 2010
by Tony Lima
December 3, 2010
“President Obama had scheduled a speech about the economy this morning, but instead he went to Afghanistan.”[1] No wonder. If I was president I wouldn’t want to be in the country today either.
Today the November labor market report was released. The, um, highlight was the unemployment rate: 9.8%. Corporate profits are soaring and the economy is growing, albeit slowly. So where are the jobs?
Let’s review my earlier posts, specifically March 27. [2] There I analyzed the impact of the health care bill on the economy. My summary conclusion: the health care bill included tax increases of about $32 billion. Excerpts are at the end of this post. Those tax increases have pretty much kicked in. (The exception is the increased tax revenue that will supposedly be captured by requiring businesses to file 1099 forms for any firm or individual with whom it does more than $600 per year in business.) What my earlier article didn’t focus on was the uncertainty created by the health care bill and the financial reform bill.
Taken together, these two laws will require writing about 600 new rules. Many of these rules will impact the cost of employees. And businesses don’t know what the rules will be. Small businesses, in particular, are flat-out scared – nervous about future unknown liabilities for employees, worried about the expiration of the Bush tax cuts, and generally just worried about the prospects for their futures. Would you hire new employees in this environment? When, at every turn, the president or a member of his staff demonize businesses? When decisions made in Washington, D.C. have a distinct “shoot from the hip first, ask questions later” flavor?
Neither would I.
Excerpts from my March 27 post:
“So here we are 45 years later. The economy is in a deep recession. If we’ve learned one thing since John Maynard Keynes published The General Theory of Employment, Interest, and Money (1936) it’s this: don’t raise taxes during a recession.
Yet that’s exactly what the recently-passed health care bill does. To support the accounting fiction that the government budget deficit will be reduced, many of the taxes and fees begin during the next two years. The majority of benefits don’t kick in until 2014. Is this yet another instance of presidential ego trumping sound economic policy?
As of March 27, various corporations have announced they will recast their earnings to reflect the fact that healthcare prescription benefits offered under their employees’ insurance plans will no longer be tax deductible. According to the Wall Street Journal article cited in the footnote, “Mr. Zion of Credit Suisse estimated in a report this week that companies in the S&P 500 index will rack up a combined $4.5 billion charge due to the change in the value of the tax asset.” That’s the equivalent of a $4.5 billion tax increase.
Let’s consider another small part of the new taxes. Beginning in 2012 there will be additional taxes imposed on individuals with wage income over $200,000 ($250,000 for married couples filing joint returns). There are two parts to these taxes. First, an additional tax of 0.9% will be levied on wages and salaries in excess of $200,000 ($250,000). Using IRS data for 2007 together with some educated guesses, total income above $200,000 was about $1,382,126,976,000. That implies a tax increase of about $12,439,000,000.
The second tax extends Medicare taxes to cover “Modified Gross Income.” Basically, modified gross income is wages and salaries plus interest. The phrase “exempt from taxes” refers to the exemption of non-employment income from Social Security and Medicare taxes. The purpose of this clause is to extend the 3.8% Medicare tax to cover all interest earned by anyone making over $200,000 ($250,000). … For the year 2007, that total for households with income above $200,000 was $196,513,160,000. The total tax increase for that year would have been $19,906,642,864. Call it $20 billion, bringing the total tax increase to $32 billion.
My conclusion is simply this: despite the fiscal stimulus (much of which still remains unspent), the U.S. economy will continue in recession through 2013. At best we can expect sluggish growth. The tax increases in the health care bill combined with the expiration of many of the Bush tax cuts in 2011 are two factors. But there’s even more. Fiscal policy is as much about expectations as actual changes in tax rates and government spending. Right now businesses and individuals expect higher taxes to continue for the duration of the current administration. Therefore I expect the recession to continue at least until November, 2012 and possibly even longer.”
[1] Heard on NPR’s Morning Edition December 3, 2010.
[2] http://gonzoecon.com/2010/03/the-health-care-bill-disaster-for-the-economy/
Puzzling Bernanke Quote
Posted by TonyLima in The state of the economy on August 3, 2010
Tony Lima
August 3, 2010
Headline from today’s New York Times: “Bernanke Says Rising Wages Will Lift Spending” (August 3, page B7).
“Will?”
Parsing this quote is a task probably left to Talmudic scholars or others wiser than me. But let’s consider some possibilities.
1. “If wages rise, then spending will also rise.” I don’t think there’s much doubt about that. The only issue is the assumption that wages will rise.
2. “The Fed is forecasting that wages will rise. That will cause spending to rise.” This seems closes to Dr. Bernanke’s point. And the Fed has very, very good economic forecasters. But there are two factors weighing against an increase in wages. First, the unemployment rate remains high. Rising wages in the face of an excess supply of labor has happened before — notably during the Great Depression — but I don’t think it’s something that should be assumed to happen regularly. Second, various government policies that mandate new benefits for employees are likely to keep unemployment high for a long time.
3. “I need to say something today to bolster confidence in the economy.” Probably also true.
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