Jack Dunn - Reclaiming Common Sense

The January Jobs Report, or Employment Situation Report, garnered headlines elsewhere because of a spike in wages. The media had been clamoring for an increase in hourly earnings for an extended period of time. When an increase in wages was received (or noticed) it was the "end of the world as we know it." The thought was that we would see dire consequences if gasoline prices rose. Would people chose filling their cars versus filling their bellies? What if wages started to rise? What if people had more money to spend on more things?  What if inflation is okay? What if people are being lured back into the workforce with higher wages? What we know is that the March 2018 Jobs report was better than the March 2017 Jobs Report. What we know is that President Trump has added more full-time jobs than any of the two term Presidents since, and including, President Reagan. He has had the "best first fourteen months in office" of five Presidents. Is this growth being seen because people are desperate or because wages are rising?


Digging into the data is easy. When the report is released various analysts run to a multitude of tables. The "A" tables are the Household Data, or the Current Population Survey (CPS) data. this data measures jobs, the number unemployed, and the workforce population. From this data we can calculate the unemployment rate and the participation rate. The "B" tables, the Establishment Data, or Current Employment Statistics (CES) data, measures workers and wages.The data that is published in the Jobs Report is a mix of seasonally adjusted (SA) and non-seasonally adjusted (NSA) data. The seasonal factors used to convert the NSA data to the SA data change by category, month, and year. The NSA data has advance values, preliminary values, and "final" values. Sometimes, as with this past January, the "final" data is revised. The problem is that not all data has its NSA values published, such as the Gross Domestic Product data.  The "B" tables only contain the SA wage data. You have to go to the CES website and download the data.Of course, the data is not available if you use Google, Bing, or Firefox to download the data, you have to use Microsoft Explorer.  ( does anybody use Bing?)


Income is a function of hours worked and wages paid per hour. The seasonally adjusted data showed that the average hourly private sector wage increased from March 2017 by 3.14 . This information can be found in table  B-3.  The annual wage inflation can be calculated by comparing the private sector wage for March 2017 with March 2018. This information was analyzed last week and posted on Twitter.

  • Total Private Sector - 3.31%
  • Goods Producing 3.21%
  • Private Service Producing 3.14%
  • Leisure and Hospitality - Lowest Wage - still up 3.39%
  • Utilities - Best Wage - Only up 1.43%

The hours worked data can be found in table B-7. Hours have been increasing over time. All sectors, except Professional Business services have added seasonally adjusted hours since March 2017. The goods Producing Sector has been, and is, working overtime, literally and figuratively. Private Service providing workers have been working under 35 hours a week, as a whole. Note that the Utilities sector is working over 42 hours a week and the Leisure and Hospitality Sector is working working the fewest hours at under 25 hours a week. If the number of jobs is multiplied by the average weekly wages and that is multiplied by 52 weeks then we can find the total wages earned by sector. If we calculate the wages earned during March 2017 and March 2018 we can calculate the growth rate. The problem is that the data published in the B-3 Table is seasonally adjusted. If you multiply seasonally adjusted data by seasonally adjusted data you receive "garbage" because the seasonal factors are being multiplied by each other.


Digging into the data isn't easy. It rarely is easy. You have to go to the CES website and tab on the database button. Yen have to select the category (categories) that you want, the sectors that you want, and that you want the seasonally adjusted or non-seasonally adjusted data, or both. If you want the data for a given month you have to download all of the data and work with Excel for a while.


Did wages increase by 2% or 3% or 6%? It depends on your sector how much your weekly wage has increased over last March. All sectors saw wages increase by over 2%. The largest growth was seen in the Financial Activities (Fina Act), Mining and Logging (M/L,) and Leisure and Hospitality (LAH) Sectors.


Did gross Income Increase by 1.5%, 4% or 14%? Again, how much you may make this year, based on the March Weekly Average, varies by industry. It is also important to note that how much each industry receives in weekly average wages varies from month to month and year to year. The highest paid sectors may remain the highest paid sectors and the lowest paid sectors may still be the lowest paid sectors. If we annualize the earnings then Mining and Logging "saw" the  largest gains and LAH saw the smallest gains.


We see a similar pattern with the seasonally adjusted wages. One thing that you will notice when comparing the data is that there are differences between the number of people working in each sector and there are differences in the wages. If you compare both tables you will see that both wages are on track for a 5% growth, based on the March wage levels.


Jobs are up. Wages are Up. Unemployment is Down. Gross Income is improving over last year. Who is doing better than the others?  This column will publish articles on the sector data, the data as broken down by Men and Women working full-time an part-time jobs, and breaking down the data by age and multiple job workers. There is considerable data to digest from the Employment Situation Report.


It's the economy.