Initial Reaction
Today’s employment report shows a wild miss in the expected number of jobs. The Econoday consensus estimate was 175,000 and ADP expected 263,000.
Instead, the BLS reported an increase of 98,000. Economists did what they usually do in such situations: blame the weather.
“Throw ADP out, it was the weather in March! Or at least the Category 3 storm that swept the Northeast may explain a much weaker-than-expected 98,000 increase in March nonfarm payrolls. This compares with Econoday’s consensus for 175,000 and a low estimate of 125,000” says Econoday.
“The big storm hit during the sample week of the employment report and apparently delayed new hiring, or at least that will be the takeaway from the report,” added Econoday.
That aside, the internals of the report as measured by the household survey were actually very good. but revisions to the establishment survey weren’t.
Revisions
The change in total nonfarm payroll employment for January was revised down from +238,000 to +216,000, and the change for February was revised down from +235,000 to +219,000. With these revisions, employment gains in January and February combined were 38,000 less than previously reported. Monthly revisions result from additional reports received from businesses since the last published estimates and from the recalculation of seasonal factors. Over the past 3 months, job gains have averaged 178,000 per month.
Let’s dive into the details in the BLS Employment Situation Summary, unofficially called the Jobs Report.
BLS Jobs Statistics at a Glance
- Nonfarm Payroll: +98,000 – Establishment Survey
- Employment: +472,000 – Household Survey
- Unemployment: -326,000 – Household Survey
- Involuntary Part-Time Work: -151,000 – Household Survey
- Voluntary Part-Time Work: -50,000 – Household Survey
- Baseline Unemployment Rate: -0.2 to 4.5% – Household Survey
- U-6 unemployment: -0.3 to 8.9% – Household Survey
- Civilian Non-institutional Population: +168,000
- Civilian Labor Force: +145,000 – Household Survey
- Not in Labor Force: +23,000 – Household Survey
- Participation Rate: +0.0 to 63.0 – Household Survey
Employment Report Statement
The unemployment rate declined to 4.5 percent in March, and total nonfarm payroll employment edged up by 98,000, the U.S. Bureau of Labor Statistics reported today. Employment increased in professional and business services and in mining, while retail trade lost jobs.
Unemployment Rate – Seasonally Adjusted
Nonfarm Employment Change from Previous Month
Nonfarm Employment Change from Previous Month by Job Type
Hours and Wages
Average weekly hours of all private employees were steady at 34.4 hours. Average weekly hours of all private service-providing employees were steady at 33.2 hours. Average weekly hours of manufacturers fell 0.2 hours to 40.6 hours.
Average hourly earnings of private workers rose $0.04 to $21.90. Average hourly earnings of private service-providing employees rose $0.04 to $21.69. Average hourly earnings of manufacturers rose $0.05 to $20.69.
For a discussion of income distribution, please see What’s “Really” Behind Gross Inequalities In Income Distribution?
Birth Death Model
Starting January 2014, I dropped the Birth/Death Model charts from this report. For those who follow the numbers, I retain this caution: Do not subtract the reported Birth-Death number from the reported headline number. That approach is statistically invalid. Should anything interesting arise in the Birth/Death numbers, I will comment further.
Table 15 BLS Alternate Measures of Unemployment
Table A-15 is where one can find a better approximation of what the unemployment rate really is.
Notice I said “better” approximation not to be confused with “good” approximation.
The official unemployment rate is 4.5%. However, if you start counting all the people who want a job but gave up, all the people with part-time jobs that want a full-time job, all the people who dropped off the unemployment rolls because their unemployment benefits ran out, etc., you get a closer picture of what the unemployment rate is. That number is in the last row labeled U-6.
U-6 is much higher at 8.9%. Both numbers would be way higher still, were it not for millions dropping out of the labor force over the past few years.
Some of those dropping out of the labor force retired because they wanted to retire. The rest is disability fraud, forced retirement, discouraged workers, and kids moving back home because they cannot find a job.
Strength is Relative
It’s important to put the jobs numbers into proper perspective.
- In the household survey, if you work as little as 1 hour a week, even selling trinkets on eBay, you are considered employed.
- In the household survey, if you work three part-time jobs, 12 hours each, the BLS considers you a full-time employee.
- In the payroll survey, three part-time jobs count as three jobs. The BLS attempts to factor this in, but they do not weed out duplicate Social Security numbers. The potential for double-counting jobs in the payroll survey is large.
Household Survey vs. Payroll Survey
The payroll survey (sometimes called the establishment survey) is the headline jobs number, generally released the first Friday of every month. It is based on employer reporting.
The household survey is a phone survey conducted by the BLS. It measures unemployment and many other factors.
If you work one hour, you are employed. If you don’t have a job and fail to look for one, you are not considered unemployed, rather, you drop out of the labor force.
Looking for jobs on Monster does not count as “looking for a job”. You need an actual interview or send out a resume.
These distortions artificially lower the unemployment rate, artificially boost full-time employment, and artificially increase the payroll jobs report every month.
Final Thoughts
The establishment survey and the household survey have been way out of sync for a long time. The gap narrowed for the second month. Last month, employment rose by 447,000. This month employment rose by 472,000.
A year ago there were 151,301,000 employed. Today there are 153,000,000 employed. That’s equates to 141,583 per month, solid but not exceptional growth.
Regardless, one has to laugh at economists who cannot predict the weather, even in arrears, until economic reports come out.
Mike “Mish” Shedlock
Trading places. Lets have the economists do the weather forecasts and have the weather persons do the economic forecasts for a while. “You don’t need to be an economist to know which way the wind is blowing”
“Regardless, one has to laugh at economists who cannot predict the weather, even in arrears, until economic reports come out.”
…
So true … but you can kiss off any chance of ever being a guest on CNBC …
“The big storm hit during the sample week of the employment report and apparently delayed new hiring, or at least that will be the takeaway from the report,” added Econoday.
…
2 things
1) NYC was in the bulls-eye … till storm shifted west … and Binghamton took the brunt
2) from report:
“Typically, it is not possible to precisely quantify the effect of extreme weather on
payroll employment estimates. In order for severe weather conditions to reduce
employment estimates, employees have to be off work without pay for the entire pay
period. Employees who receive pay for any part of the pay period, even 1 hour, are
counted in the payroll employment figures.”
True but what if businesses shut down for a day or two in a week because of a big snow storm (even one that’s predicted on TV but fizzles out)? Job interviews that would have happened get pushed to next week. Job starts might get pushed. A few thousands of jobs that shift out a week or two just when the survey is being conducted might distort the figure.
I think the employment figures are based on when you start work (go on the payroll), not when you have your interview.
Excellent comments as usual Tony
98,000, great again?
Another likely culprit – Easter.
Last year early (march) … this year mid April … doubt retail would be -30K if Easter early,
I blame the economists.
After decades of regular misses (often big misses), one might think their accuracy would improve or they would admit defeat and stop issuing random guesses.
This just highlights the problem when academics are employed with no real world accountability. If they are right or wrong, they don’t get fired or even reprimanded, they just get cost of living increases and eventually a promotion by way of attrition / seniority.
The “senior” economists end up being the ones that had no better job prospects…
Hiring is definitely slowing down. I applied for a job in January. The headhunter called me within 24 hours. Within 24 hours of that the hiring manager wanted to set up a phone screen. 2 hours before the phone screen the hiring manager called the headhunter to cancel the phone screen because the funding for the position had not been approved. It’s been over 2 months and the budget has not been approved. While I was waiting for that position to get funding, I noticed fewer and fewer jobs being posted.
The jobs number was NOT affected by the weather.