The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. P-7508369, Disclosure Review Board (DRB) approval number: CBDRB-FY23-0422).

The BDS data measure the net change in employment at the establishment level. These changes come about in one of four ways. A net increase in employment can come from either opening establishments or expanding establishments. A net decrease in employment can come from either closing establishments or contracting establishments.

Gross job gains include the sum of all jobs added at either opening or expanding establishments. Gross job losses include the sum of all jobs lost in either closing or contracting establishments. The net change in employment is the difference between gross job gains and gross job losses.

The formal definitions of employment changes are as follows:

• Job Creation (JC) – Job creation is the sum of all employment gains from expanding establishments from year t–1 to year t including establishment startups. Note that the contribution of firm births can be measured by using the job creation from establishments with firm age equal to zero.
• Job Destruction (JD) – Job destruction is the sum of all employment losses from contracting establishments from year t–1 to year t including establishments shutting down.

Some simple identities are useful to note to interpret and use these statistics. Let E_it be employment in year t for establishment i. Define establishment–level employment growth as follows:

g_it = (E_it – E_it–1) / X_it

where

X_it = 0.5 * (E_it + E_it–1)

This growth rate measure has become standard in analysis of establishment and firm dynamics because it shares some useful properties of log differences but also accommodates entry and exit (see Davis, Haltiwanger and Schuh [1996], and Tornquist, Vartia, and Vartia [1985]). The above definitions of JC and JD for establishments classified in group s (e.g., a firm size, firm age category) are given by:

The net change in employment for establishments in group s satisfies the following identity:

For growth rates, the analagous relationships are given by:

where

The latter variable X_st denotes the sum of average employment over a consecutive two–year period and as is clear from the above it is simple to convert the changes to rates by dividing the relevant measures by this variable. Note that in general the variable X_st for a particular classification is not equal to the simple average of the employment variable using the current and prior year since establishments are assigned the characteristics of the firm that owns the establishment in t and this may have changed from year t–1 to year t.

The employment measure used for the tabulations is the number of employees at the establishment for the payroll period including March 12. As such, all growth rates are based on March–to–March changes and the tabulations for a given year are the changes from the prior year to the current year. An establishment opening or entrant is an establishment with positive employment in the current year and zero employment in the prior year. An establishment closing or exit is an establishment with zero employment in the current year and positive employment in the prior year. The vast majority of establishment openings are true greenfield entrants. Similarly, the vast majority of establishment closings are true establishment exits (i.e., operations ceased at this physical location). However, there are a small number of establishments that temporarily shutdown (i.e., have a year with zero employment) and these are excluded from the counts of establishment openings and closings.

In the released series, the job flow measures are provided in terms of both level changes (e.g., the number of jobs) as well as rates using the above denominator as described above to convert level changes to rates. In addition, the number of establishments in each of the categories of change (openings, closings, continuers) and the classifications (e.g., firm size, firm age, etc.) is provided which permits tracking the gross and net flows of the number of establishments. The decomposition into openings, closings and continuers permits decomposing gross job creation into the component from continuing establishments that are expanding and establishment openings and decomposing gross job destruction into the component from continuing establishments that are contracting and establishment closings.

It is critical to emphasize that the BDS contains measures of net and gross flows of establishments and jobs at the establishment level. All establishments are, however, linked to their parent firm so that the net and gross flows of establishments and jobs can be categorized by the characteristics of the parent firm. In particular, establishments are classified by both the size of the parent firm and age of the parent firm as defined below. This enables quantifying the contribution of firms by firm size and firm age in terms of establishment and job net and gross flows. For example, and of particular interest, the contribution of firm startups to the net and gross flows of establishments and jobs can be ascertained by using the tabulations of firm age zero. As described in detail on the BDS page here, establishments are assigned a firm age based upon the age of the parent firm. The age of the parent firm is based on the age of the oldest establishment in the firm. A firm age of zero represents a firm where all establishments in the firm are entrants in that year –– hence it is a new firm. By construction, tabulations of firm age zero represent establishment entrants that are part of a new firm. Most new firms are single–unit firms.

The BDS has adapted the disclosure avoidance method of the County Business Patterns (CBP) in using Hybrid Balanced Multiplicative Noise Infusion.  CBP has been released with noise-infusion since 2007; see the CBP methodology webpage here.

This disclosure avoidance system perturbs data values for each establishment prior to tabulation by applying a random noise multiplier to the magnitude data (i.e., characteristics such as number of employees) of these establishments. These noise multipliers are longitudinally consistent, that is, the same multiplier is used each year the establishment’s data is published and are consistent with the CBP's multipliers.  As the distribution of noise is symmetric around one, most cells will be less perturbed than the underlying establishments within them.

Please see Massell, P B, and J M Funk. 2007. “Recent Developments in the Use of Noise for Protecting Magnitude Data Tables: Balancing to Improve Data Quality and Rounding That Preserves Protection.” In Proceedings of the 2007 FCSM Research Conference.

https://nces.ed.gov/FCSM/pdf/2007FCSM_Massell-IX-B.pdf

In addition to noise infusion, cells with fewer than three firms are suppressed with a publication flag 'D'. In addition, cells with identified data quality concerns are suppressed with a publication flag 'S'. Cells that are "structurally missing" or "structurally zero" are indicated with a publication flag 'X'. Finally, rate cells that cannot be calculated are indicated with a publication flag 'N'.

Because the BDS tabulations are based on a combination of administrative and survey-collected data, rather than a probability sample, sampling error cannot be measured for the BDS. Nonsampling error, however, still exists. Nonsampling errors can occur for many reasons, such as the employer submitting corrected employment data after the end of the year as well as late filers. Other sources of error include typographical errors made by businesses when providing information.  Changes in administrative data sometimes create complications for the linkage process. The LBD addresses these issues in detail in order to avoid overstating openings and closings while understating expansions and contractions.  The BDS data series are subject to periodic minor changes based on corrections in LBD records due to updates coming from new BR files (e.g., late filers are no longer considered deaths).

Important Note: The BDS uses longitudinal information on firms and establishments to generate measures of business dynamics and job flows. Since information from multiple years is used to produce a statistic for any given year, having more years of data surrounding the year in question improves the quantity and quality of information used to generate the statistics. Thus, less information is available to generate the last year(s) of any given BDS release. Measures of job flows from firm and establishment births are especially sensitive to this source of measurement error and accordingly are more likely to be revised in subsequent releases.

• Davis, Steven J.,  Haltiwanger, John C., and Schuh, Scott.  1996.  Job Creation and Destruction.  Cambridge, Massachusetts:  The MIT Press.
• Jarmin, Ron S. and Javier Miranda. 2002. "The Longitudinal Business Database" Center for Economic Studies Discussion Paper CES–WP–02–17.
• Tornquist, Vartia, and Vartia.  1985.  “How Should Relative Changes Be Measured?”.  The American Statistician 39(1):  43-46.