Just a bit about how the stats are developed.
From the people that generate the stats:
Frame and sample selection
The LDB is the universe from which CES draws the establishment survey sample. The LDB contains data on the roughly 9 million U.S. business establishments covered by UI, representing nearly all elements of the U.S. economy. The Quarterly Census of Employment and Wages (QCEW) program collects these data from employers on a quarterly basis in cooperation with Labor Market Information Agencies (LMIs). The LDB contains employment and wage information from employers, as well as name, address, and location information. It also contains identification information such as UI account number and reporting unit or worksite number.
The LDB contains records of all employers covered under the UI tax system. That system covers 97 percent of all employment within the scope of CES in the 50 States, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands. There are a few sections of the economy that are not covered by the QCEW, including the self-employed, unpaid family workers, railroads, religious organizations, small agricultural employers, and elected officials. Data for employers generally are reported at the worksite level. Employers who have multiple establishments within a State usually report data for each individual establishment. The LDB tracks establishments over time and links them from quarter to quarter.
The Total private and Government portions of the CES sample are selected using two different methods. Private establishments in the CES sample frame are stratified by State, industry, and size. Stratification groups population members together for the purpose of sample allocation and selection. The strata, or groups, are composed of homogeneous units. With 13 industries (treating Manufacturing as one industry and not including Government) and 8 size classes, there are 104 total allocation cells per State. The sampling rate for each stratum is determined through a method known as optimum allocation. Optimum allocation minimizes variance at a fixed cost or minimizes cost for a fixed variance. Under the CES probability design, a fixed number of sample units for each State is distributed across the allocation strata in such a way as to minimize the overall variance, or sampling error, of the total State employment level. The number of sample units in the CES probability sample was fixed according to available program resources. The optimum allocation formula places more sample in cells for which data cost less to collect, cells that have more units, and cells that have a larger variance.
The CES Government sample is not part of the program's probability-based design. CES is able to achieve a very high level of universe employment coverage in Government industries by obtaining full payroll employment counts for many government agencies, eliminating the need for a probability-based sample design. Government estimates are combined with the Total private estimates to obtain values for Total nonfarm.
Annual sample selection helps keep the CES survey current with respect to employment from business births and business deaths. In addition, the updated universe files provide the most recent information about industry, size, and metropolitan area designation. Each year the CES sample is drawn from the first quarter Longitudinal Database (LDB) data in the fall of that year. A birth update is added in the early summer from the third quarter of the previous year. CES enrollment efforts begin immediately after a sample is selected, and collection generally begins in the first month after enrollment. At least a full year passes between the sample draw and sample implementation. CES produces estimates using the new sample units for all industries for the first time in early February of each year. Starting with January estimation, the new sample is used for the first time to estimate November third preliminary estimates of the previous year, December second preliminary estimates of the previous year, and January to October of the current year’s first, second, and third release estimates. The same sample is used for November first and second preliminary and December first preliminary estimates of that year.
After all out-of-scope records are removed, the sampling frame is separated into allocation cells. Within each allocation cell, units are grouped by metropolitan statistical area (MSA), and these MSAs are sorted by the size of the MSA, defined as the number of UI accounts in that MSA. As the sampling rate is uniform across the entire allocation cell, implicit stratification by MSA ensures that a proportional number of units are sampled from each MSA. Some MSAs may have too few UI accounts in the allocation cell; these MSAs are collapsed and treated as a single MSA.
Permanent Random Numbers (PRNs) are assigned to all UI accounts on the sampling frame. As new units appear on the frame, random numbers are assigned to those units as well. As records are linked across time, the PRN is carried forward in the linkage. Within each selection cell, the units are sorted by PRN, and units are selected according to the specified sample selection rate. The number of units selected randomly from each selection cell is equal to the product of the sample selection rate and the number of eligible units in the cell plus any carryover from the prior selection cell. The result is rounded to the nearest whole number. Carryover is defined as the amount that is rounded up or down to the nearest whole number.
As a result of the cost and workload associated with enrolling new sample units, all units remain in the sample a minimum of two years. To ensure all units meet this minimum requirement, CES has established a "swapping in" procedure. The procedure allows units to be swapped into the sample that were newly selected during the previous sample year and not reselected as part of the current probability sample. The procedure removes a unit within the same selection cell and places the newly selected unit from the previous year back into the sample. Approximately 68 percent of the CES sample for the private industries overlaps from the previous sample to the current sample.
That is enough for here. There is more available. I guess that some don't think they know what they are doing. But that is because they don't like the answer. It used to happen to me at work, people that didn't like my answers told others that I didn't know what I was doing.