Making Sense of Jobs and Employment Data

By Edward Seiler, Ph.D., Vice President, Research and Economic Analysis


Wall Street expectations were running high earlier this month in advance of the Bureau of Labor Statistics (BLS) March 2018 employment report. On the heels of February’s strong numbers and a string of seven straight years of private sector gains, investors projected 185,000 new jobs would be added to payrolls, and the unemployment rate would drop from its 5-month 4.1% plateau to 4.0%.

A Wall Street Journal writer wondered whether booming Elkhart, Indiana, the self-proclaimed RV capital of the world now experiencing labor shortages, and rising home prices and wages, is “a glimpse of what the American economy looks like at full tilt.”[1]

Other economists questioned whether the rapid increases could continue unabated, and while the employment situation continues to improve, could it keep up its sprinter’s pace?

But, the anticipated April 6 report provided some lower than expected numbers—only 103,000 jobs were added in March and the unemployment rate stayed at 4.1% for a sixth consecutive month. Still there is no consensus if the news was good or bad for the economy with varied reactions from different parties.

While economists and politicians continue their debates, we cannot lose sight of the importance of these numbers to NH&RA members. At last month’s National Council of Housing Market Analysts (NCHMA) meeting in Philadelphia, I was fortunate to be on a panel with Bob Lefenfeld of Real Property Research Group and Zack Patton of Enterprise Community Partners. While Bob and Zack ably showed how employment data are used in housing market studies, and in innovative tools (such as Enterprise’s Opportunity 360), I took a look at where the data from the employment situation reports originate from and how to interpret them.

In this article, I expand on my discussion from the Philadelphia panel and provide additional color around the monthly jobs numbers.

The Two Main Monthly Jobs Numbers

The two numbers that many people look out for are the unemployment rate and the change in nonfarm employees (or, payrolls). While these numbers are presented in the same report each month, and are often correlated, they communicate different aspect of the employment situation. Moreover, they are collected from different sources.

Let’s start by looking at the unemployment rate.

The BLS releases six measures of unemployment each month (U-1 through U-6). The genesis for these measures is a monthly survey that BLS conducts in cooperation with the US Census Bureau. This survey, the Current Population Survey (CPS), is a representative sample of the US consisting of about 60,000 households (corresponding to approximately 110,000 individuals).

CPS data is only collected on US residents who are aged 16 or older who do not reside in institutions and who are not on active duty.  The CPS, referred to as the household survey, is helpful for understanding the changing nature of the workforce in terms of age, gender, race, and education.

Explaining the Current Population Survey: The CPS has a state-based sampling design that reflects urban and rural areas, different types of industrial and farming areas, and each state’s major geographic divisions. It is also designed so that we can reliably measure labor force estimates across time to understand month-to-month and year-to-year changes. Sample weighting is used in administering the survey that considers the age, sex, race, ethnicity, and state of residence of the respondents.

CPS asks whether responders are currently working and, if not, whether they have searched for a job in the last four weeks. Those who have stopped looking for work—because they’re retired or because they’re despondent—are considered outside the labor force. The CPS also asks if respondents are working part-time or full-time and their duration of unemployment.

The following table provides an illustration of the household survey data.[2]

Table 1: Employment Status (thousands, rates in %)

The table shows that while the civilian labor force increased by over 1.5 million in the last year (from 160.2 million in March 2017 to 161.8 million in March 2018), the number of employed increased by over 2 million. This has led to unemployment falling from 7.2 million to 6.6 million, corresponding to a 4.1% rate.

The following chart shows the historical unemployment rate since January 2000. Of note is the steady decline over the last seven years from the highs in 2010.


The (official U-3) unemployment rate of 4.1% corresponds to individuals who have actively searched for a job in the last four weeks. Those who have stopped looking for work are considered outside the labor force. It is important however to also account for those who would potentially like to work and are currently not actively searching, or are working part-time but would like to work full-time. To understand why, consider an unemployed person who gives up looking for work because he/she believes the situation is dire. As this person exits the labor force it leads to a decrease in the U-3 unemployment rate.[3]

A Note on BLS Definitions: Individuals marginally attached to the labor force are neither working nor looking for work but indicate that they want and are available for a job and have looked for work sometime in the past 12 months. Discouraged workers, a subset of the marginally attached, have given a job-market related reason for not currently looking for work. Persons employed part time for economic reasons are those who want and are available for full-time work but have had to settle for a part-time schedule.

The BLS therefore defines several broader measures of underutilization. For example, the U-6 unemployment measure includes the total unemployed plus all persons marginally attached to the labor force plus all those employed part time for economic reasons.

I am encouraged that more economists and financial journalists are reporting this broader measure, and that it has gone down from 8.8% in March 2017 to 8.0% this March.

However, this is not the whole story. Unemployment rates are down yet people feel economically disadvantaged. I think that there are many reasons for this. I highlight three:

  1. One must drill-down within these rates to get a clearer picture. For example, drilling-down by educational attainment shows that the unemployment rate in March 2018 for people at least 25 years old with a bachelor’s degree (or higher) was only 2.2%, while for those at least 25 years old with no high school diploma it was more than double at 5.5%.
  2. While the 5.5% rate is lower than it has been for a long time, and is approaching the (hypothetical) level that economists refer to as the “natural rate of unemployment,”[4] there is still room for improvement that would lead to upward pressure on wages.
  3. Many forms of underemployment are hard to measure. Consider geographically constrained individuals who can only find (local) positions that do not utilize their skills to capacity. Since it is often harder to move if one owns a home than if one rents, homeownership may contribute to underemployment. Underemployment is hard to quantify in the CPS, yet impacts wellbeing.

Unemployment rates are thus important to study, but don’t provide a full picture. Market analysts also need to understand which sectors of the economy are hiring, the number of hours being worked, and workers’ earnings. This is where a second survey, often referred to as the establishment survey, comes into play. This survey helps reveal which industries are growing and which are shrinking.

BLS collects data on who is working through the Current Employment Statistics (CES) program. This program produces detailed industry estimates of employment, hours, and earnings of workers on nonfarm payrolls. Moreover, in addition to CES national estimates, the CES “State and Metro Area” produces data for all 50 States, DC, Puerto Rico, the Virgin Islands, and about 450 metropolitan areas and divisions.

Each month, CES surveys approximately 149,000 businesses and government agencies, representing 651,000 individual worksites.[5]

One of the main CES outputs is the monthly change in payrolls (Chart 2). This measure provides insights into the current economic situation–it represents the number of jobs added or lost in an economy. Increases indicate that businesses are hiring and may be growing. Moreover, the CES indirectly reveals future trends since those who are newly employed have increased personal incomes and hence disposable incomes, thus fostering further economic expansion.

Employment data from the establishment survey is illustrated in Table 2. The table shows that between March 2017 and March 2018 construction payrolls increased from 6.92 million to 7.15 million, weekly hours worked in construction increased from 38.8 to 39.2 on average, and average hourly construction earnings rose from $28.60 to $29.43 over this period.

Table 2: Establishment Survey Selected Data

It is instructive to add color to these data by looking at the economic fundamentals—growth in supply and demand. Comparing the total number of construction workers prior to and during the housing crisis to the employment situation today, we see that the total number of workers (at the height of the boom) in late 2006 reached 7.7 million, fell to 5.5 million by the end of 2010 and been gradually trending upward since. We are now approaching 7.2 million construction workers.

Together with the growth in supply, there is evidence of increasing demand. The National Association of Home Builders and Wells Fargo compile a Housing Market Index (HMI) that summarizes three aspects of housing demand: current market conditions for the sale of new homes, market conditions for the sale of new homes in the next six months, and the traffic of prospective new home buyers. The HMI is at levels not seen in 20 years—indicating that demand has also grown and is high.

If growth in demand is outstripping growth in supply (indicating a shortage of workers), we would expect rising earnings for construction workers. Chart 3 shows that this is indeed the case.

Rising construction costs are a concern for the NH&RA community. Understanding the trends in employment data for construction labor (based on the CES) provides valuable market information. Likewise, drilling-down on other aspects of the CES and CPS data can increase our understanding of local labor markets and employment trends for tenants and employees (e.g., property maintenance staff). Understanding the origin of these statistics will enhance effective use of the numbers.

In Closing

The monthly Employment Situation report contains data from two national surveys—the household Current Population Survey and the establishment Current Employment Statistics. One of the appealing aspects of both surveys is that they provide data that on all states and reflect urban and rural areas, different types of industrial and farming areas, and the major geographic divisions. In addition, even though the surveys are administered monthly, the data can be reliably used to examine month-to-month and year-to-year change. The data also considers the age, sex, race, ethnicity, and state of residence.

Taking these things together, the aggregate data are suitable sources of data for us to utilize as affordable housing professionals. Furthermore, given the survey designs, the data can be readily used to drill-down to specific locations and markets. Thus, their appeal for housing market studies and other NH&RA member activities.

While there are services that are automating the use of these data for specific geographies, it is my hope that this paper has helped shed light on the genesis of the data and how to interpret the numbers they provide.


[2] This table is a part of Table A-1 provided by BLS in its April 6, 2018 release. Our focus here is on seasonally adjusted (SA) data. Data are subject to fluctuations due to seasonality in weather, holidays, and the opening and closing of schools. SA data is adjusted to offset these effects. Also note that one can drill down into these data on many dimensions (e.g., age, race, geography). This makes the data an ideal input for local market reports.

[3] If there were two unemployed people and a total civilian labor force of 20 the unemployment rate is 10%. If one of these unemployed workers leaves the labor force, the unemployment rate would fall to 5.3% (= 1 in 19). Is this halving of the unemployment rate necessarily a good thing?

[4] This is where the only unemployment is due to the natural comings and goings of people from jobs, and economists would consider the labor market in equilibrium. The Congressional Budget Office pegs this at around 5.2%.

[5] Like CPS, the CES has all the desired properties of a well-designed survey.