My Refusal to Use U.S. Government Data Has Been Extended Indefinitely

RIP Government Data

(click for larger image)

In early 2014 I wrote that I would not use government data again for three more years.  I have now extended that deadline indefinitely.  Neither of the candidates for president inspires more confidence in the data than President Obama.  I have updated the image at the top right of the home page to reflect this fact.  Here’s the updated version →

I will shortly post a companion article about Kai Ryssdal’s failure to understand the issues with government data.




Why I Will Not Use U.S. Government Data for Three More Years

Fake Jobs Are Not Real Jobs

Fake Jobs Are Not Real Jobs

[Update April 20, 2014. This article was featured in James Taranto’s “Best of the Web Today” column in the Wall Street Journal.  Click here to see it.]

[Update May 18, 2014.  In response to a comment from larsschall.com, I have added a paragraph at the end explaining my three year time limit.]

For quite a few years my lovely wife has refused to believe any economic data from the U.S. government.  Until recently, I have been a staunch defender of the statisticians and economists who work in various branches of the government.  The four I use most often are the Bureau of Economic Analysis (Commerce), the Bureau of Labor Statistics (Labor), the Treasury Department, and the Census Bureau (formerly in Commerce, stay tuned).

Much of the data supplied by these departments rely on Census to perform the actual survey work.  Census has the tools for this and they have been in the survey business for a long time.  Unfortunately, that also creates a single point of vulnerability.  As far as anyone can tell, the Obama administration successfully exploited this vulnerability and produced false survey data.  The falsification itself was not at all sophisticated.  One or more Census employees simply made up numbers.  John Crudele of the New York Post has covered this extensively.  In yet another measure of how bad the “news” industry has become, Mr. Crudele remains almost entirely the sole source of this information.

U.S. Government Data Has Been Faked

I have reluctantly concluded that I cannot believe any numbers emanating from the U.S. government.  The purpose of this article is to explain why I will not use U.S. government data for three more years.  The exception is long-term historical data that is harder to fudge. I remain hopeful that the next occupant of the executive branch will restore integrity to the data.

I have compiled Mr. Crudele’s articles into a single 4.7 mb pdf file.  Click here to download it.  I have also compiled a list of headlines and links from the oldest (November 18) to the most recent as of today (December 16).  I will update this post from time to time as Mr. Crudele provides more evidence.

Those who do not believe the Obama administration is corrupt should look at Mr. Crudele’s articles.  Read carefully and keep an open mind.  What’s in there is devastating.  I am personally heartbroken speaking as someone who has used and relied on this data since 1971.

Why Three Years?

Why three years?  That’s the end of the Obama administration, the same administration that moved control of the Census Bureau from the Department of Commerce to the White House.  I did not intend to make any predictions about what is likely to happen after Mr. Obama leaves the White House.  I will re-evaluate my position on this issue at that time.

Bibliography

Census ‘faked’ 2012 election jobs report
http://nypost.com/2013/11/18/census-faked-2012-election-jobs-report/

House probes Census over ‘fake’ results
http://nypost.com/2013/11/19/house-probes-census-over-fake-results/

Census ‘Fake’gate goes back even further
http://nypost.com/2013/11/21/census-fakegate-goes-back-even-further/

False job numbers: Did the White House know?
http://nypost.com/2013/11/23/cooked-census-reported-to-obama-and-rahm/

Get ready for lies and Labor Department statistics
http://nypost.com/2013/12/02/get-ready-for-lies-and-labor-department-statistics/

So much for Census ‘oversight’
http://nypost.com/2013/12/04/so-much-for-census-oversight/

Warning: Jobless rate may be rigged
http://nypost.com/2013/12/07/warning-jobless-rate-may-be-rigged/

Brooklyn Census Bureau also falsified data in 2010
http://nypost.com/2013/12/16/brooklyn-census-bureau-also-falsified-data-in-2010/




The September Jobs Report

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

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

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.




January Unemployment

U.S. Labor Force Participation Rate

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.




U.S. Retail Sales: Moving Markets by Ignoring Error Margins

“Retail sales up 0.3% in February” is what you read in the headlines. In response, U.S. stock markets moved higher. Apparently the markets hope that consumers are finally starting to spend again.  Consumer spending is about 2/3 of total domestic spending, so this is a big deal – if it’s true. Let’s spend a few minutes deconstructing that number.

First, this increase is the “ADVANCE MONTHLY SALES FOR RETAIL TRADE AND FOOD SERVICES” from the Census Bureau.[1] The press release clearly states the margin of error is ±0.5%.  In other words, the 0.3% estimate is meaningless.  All we know with any confidence is that the actual growth rate is likely between –0.2% and +0.8%.  Don’t bet the ranch on this estimate.

Second, and more intriguing, a good part of the February growth was caused by a downward revision in January’s estimate. The advance estimate for January was +0.5% with an error of ±0.5%.  The revised estimate was +0.1% with an error of ±0.3%.  Make January lower and February looks better.  Are the numbers being fudged?  Nah, folks in Washington D.C. would never do that.

Third, these figures are nominal numbers.  While they are adjusted for seasonal variation, they are not corrected for inflation.  Assuming inflation is about 0.2% per month (2.4% per year), the advance estimate for real growth is +0.1%.  Anemic.

According to the Census Bureau press release, the advance estimates are based on a stratified sample of 5,000 retail and food service firms.  The total number of these firms is over 3 million.  While the sample covers 65% of the dollar volume, there’s a reason the margin of error is so high: 65% is quite a distance from 100%.

The chart below gives some perspective.  This is based on inflation adjusted data from the Department of Commerce Bureau of Economic Analysis for January of each year.[2]

U.S. retail sales 1992 - 2010

U.S. retail sales 1992 - 2010


[1] http://www.census.gov/retail/marts/www/retail.html .  Accessed March 13, 2010.

[2] http://bea.gov/national/nipaweb/nipa_underlying/DownSS2.asp?3Place=N#XLS.    Accessed March 13, 2010.