Monthly Labor Review • February 2008 

BLS Labor Dynamics Data

Zhi Boon, Charles M. 

Carson, and Randy

E. Ilg are economists

in the Office of 

Employment and 

Unemployment 

Statistics, Bureau of 

Labor Statistics (BLS);

R. Jason Faberman,

formerly of BLS, is an 

economist at the Federal Reserve Bank of 

of Philadelphia.

E-mail: Jason.

Faberman@phil.frb.org

Zhi Boon, Charles 

M. Carson, R. Jason 

Faberman, and 

Randy E. Ilg

Three relatively new data sources released by the BLS help analysts

track the rich dynamics underlying the changes in employment

and unemployment; these data add depth and context, and they

ultimately provide a better understanding of movements

in the labor market

Studying the labor market 

using BLS labor dynamics data

Over the past 5 years, the Bureau of 

Labor Statistics (BLS) has released 

three new data products that measure the dynamics of the U.S. labor market. 

These data illustrate the fluid nature of the 

labor market by highlighting the millions of 

jobs that appear or disappear and the millions of individuals who become employed, 

become unemployed, or leave the labor 

force entirely every month.

In 2002, the BLS began releasing data 

from the Job Openings and Labor Turnover Survey (JOLTS). This survey of establishments has collected data since December 2000 on the number of hires, quits, 

layoffs, and job openings businesses have 

each month. In 2003, the BLS began releasing the Business Employment Dynamics 

(BED) data. The BED counts are based on 

6.9 million mandatory reports submitted by 

businesses subject to State Unemployment 

Insurance (UI) programs; these records are 

longitudinally linked over time so that one 

can observe employment changes at the 

establishment level. The BED measures the 

gross number of jobs gained each quarter 

at expanding or opening establishments, as 

well as the gross number of jobs lost each 

quarter at contracting or closing establishments. The BED data are available back to 

1992. Finally, beginning in October 2007, 

the BLS has released seasonally adjusted 

monthly estimates of labor force status 

flows (also known as “gross flows”) from the 

Current Population Survey (CPS), a survey 

best known as the source of the monthly 

unemployment rate. The estimates of labor 

force status flows, which begin in 1990, use 

month-to-month changes in the employment status of individuals to estimate the 

population-level changes in labor force status between being employed, unemployed, 

or out of the labor force.

This article explains how these new data 

on employment dynamics provide a more 

detailed picture of the labor market. It also 

explains how these data—when used in conjunction with existing labor market information, such as the more familiar BLS data on 

employment and unemployment—enhance 

understanding of how the labor market 

functions and how it changes with the business cycle. The main point of the study is 

that these data add context to the observed 

changes in the labor market and help answer 

questions that the more traditional employment data cannot address. By providing a 

deeper understanding of movements in the 

labor market, this information can aid analysts and policy makers alike.
BLS Labor Dynamics Data

 Monthly Labor Review • February 2008

Why study labor dynamics?

Most observers of the U.S. labor market are familiar with 

the standard gauges used to measure its health, such as 

employment growth and the unemployment rate. Every 

month, these estimates provide a useful measure of the 

overall health of the labor market, and consequently they 

are closely watched by analysts and others. Data on the 

underlying labor dynamics are useful because they add 

depth to these standard measures. For example, knowing that employment grew by 150,000 jobs or that the 

unemployment rate fell by 0.2 percentage point provides 

a reasonable sense of overall labor market health, but for 

those looking to make policy, financial, or other economic 

decisions, this information leaves key questions related to 

how these changes came about unanswered.

When the economy adds 150,000 jobs, it represents 

a net gain summed over millions of businesses simultaneously expanding, contracting, starting up or closing 

down each month. Some businesses have hired new employees, others have let workers go or have had workers 

quit, and others still have had some mix of workers starting work and separating from employment. As a result, 

there are several ways the economy can generate a net 

gain of 150,000 jobs. For example, there could be a rise 

in job creation that outpaces an increase in job losses. On 

the other hand, there could be a fall in job loss that is 

steeper than a decline in job gains. One could think of 

many possible scenarios. The policy-related and financial 

decisions related to each of these scenarios can be quite 

different. The first scenario paints a picture of increased 

employment coupled with increased turbulence, while 

the second scenario implies employment gains coupled 

with a decline in labor market churning. The gross job 

gains and gross job losses statistics of the BED capture 

exactly these types of flows, thereby giving some context 

to the dynamic environment in which jobs are added or 

lost during a given period.

Labor market analysts might also be interested in 

knowing about the movement of workers into and out 

of those jobs. While this is related to the gains and losses 

of jobs, this is a slightly different question to ask, and requires different tools to answer. Returning to the example 

of a net gain of 150,000 jobs, did such a gain come about 

through a relative increase in hiring or a relative decline 

in workers separating from their jobs? Of those who 

separated, how many were laid off and how many chose 

to quit? A period of high turnover with a lot of quits is 

obviously much different from a period of high turnover 

with many layoffs. The data on labor turnover from the 

JOLTS program provide answers to these questions. 

Just as multiple scenarios can generate a gain of 150,000 

jobs, multiple scenarios can cause a 0.2-percentage point 

decline in unemployment. Each month, millions of people 

move into and out of unemployment, as well as into and 

out of the labor force (the sum of the employed and the 

unemployed) altogether. Because the unemployment rate 

is defined as the number of unemployed persons divided 

by the number of people in the labor force, it can decline 

in several different ways. The most obvious way that the 

unemployment rate can decline is for the number of unemployed persons to decline. However, this, too, can occur 

either because of a drop in recently unemployed individuals 

(that is, a drop in the flows into unemployment) or because 

of a rise in the number of unemployed persons who find a 

job or drop out of the labor force entirely (that is, a rise in 

the flows out of unemployment). The unemployment rate 

can also decline because of a rise in the number of employed individuals. The economic and policy implications 

of each change are quite different. The labor force status 

flows data from the CPS quantify the flow of people into 

and out of each of the major labor market states: employed, 

unemployed, and not in the labor force. These flows data 

provide analysts with critical information on the detailed 

changes in the labor market in a given month.

Labor dynamics data from the BLS

Job Openings and Labor Turnover Survey. The Job Openings and Labor Turnover Survey (JOLTS) is an establishment 

survey that publishes monthly data on job openings, as 

well as monthly and annual data on hires and separations, 

by major industry and region.1 The survey samples about 

16,000 establishments. It covers all nonfarm employment 

and is benchmarked to the BLS Current Employment Statistics (CES) survey, which is commonly referred to as “the 

payroll survey.”

Job openings are a count of the number of vacancies on 

the last business day of the month. They provide a measure 

of unmet labor demand. Hires are all additions to the payroll for the month. Similarly, total separations are all subtractions from the payroll for the month. The JOLTS distinguishes between three types of separations: quits (generally 

voluntary separations), layoffs and discharges (generally 

involuntary separations), and other separations (such as 

transfers and retirements). Hires and separations are commonly referred to as “worker flows,” because they measure 

the movement of workers across business establishments. 

These flows are presented as rates and are calculated by 

dividing each by employment for the month.
Monthly Labor Review • February 2008 

Business Employment Dynamics. The Business Employment Dynamics (BED) data series is a virtual census of 

the U.S. private sector. It includes all establishments 

covered by State unemployment insurance (UI) programs—about 6.9 million in 2006—with each establishment longitudinally linked so that its employment 

history can be tracked by BLS.

2

 Each quarter, these data 

include gross job gains and gross job losses by major 

industry, employer size class, and by State. Gross job 

gains are the sum of increases in employment from expansions at existing businesses and the addition of new 

jobs at opening businesses. Gross job losses are the sum 

of decreases in employment from contractions at existing businesses and the loss of jobs at closing businesses. 

The BED data include job gains and losses for all four 

types of employment changes. Employment changes 

in the BED are measured from the third month of one 

quarter to the third month of the next quarter. The net 

change in employment is the difference between the 

gross number of jobs gained and the gross number of 

jobs lost.

Gross job gains and losses are often referred to as “job 

flows,” because they measure changes in the number of 

positions rather than the actual movement of workers. 

Finally, gross job gains and losses are expressed as rates, 

calculated by dividing by the average of the previous and 

current quarter’s third-month employment.3

CPS Labor force status flows. The labor force status flows 

data are derived from the Current Population Survey 

(CPS), a monthly sample survey of approximately 60,000 

households.4 Each month, the CPS is administered to 

about three-quarters of the households that were also 

in the survey during the previous month. (The other 

one-fourth consists of new households.) The monthto-month overlap allows the BLS to track individuals 

who change labor force status from one month to the 

next. The dynamic “flows” of these individuals underlie 

changes observed in the official labor force stock estimates published by BLS (employment, unemployment, 

and not in the labor force). Gross flow estimates are 

available for the total working-age population (age 16 

and over) and separately for men and women.

In a given month, a person is in one of three labor 

force states: employed (E), unemployed (U), or not in 

the labor force (N). The following month, the person 

could either have the same status or change to one of 

the other two states. Thus, one can express the complete 

set of labor market gross flow possibilities with the following 3 x 3 matrix:

 Status in current month

 Not in 

Status in prior month Employed Unemployed labor force

Employed................. EE EU EN

Unemployed............. UE UU UN

Not in the labor force NE NU NN

The notation of the matrix is such that the first letter of 

each flow denotes the labor force status of an individual in 

the previous month, and the second letter of each flow denotes the state of an individual in the current month. The 

diagonal elements, EE, UU, NN (shown in bold), represent 

individuals who did not change their labor force status 

over the month.

The flows into employment, listed in the first column, 

represent all individuals who remained employed, but not 

necessarily with the same employer, over the month (EE); 

the number of unemployed persons who became employed (UE); and the number of persons previously not in 

the labor force who became employed (NE). The flows into 

unemployment, listed in the second column, represent the 

number of employed who become unemployed (EU), the 

number of unemployed who remained unemployed from 

the previous month (UU), and the number of individuals not in the labor force who became unemployed (NU). 

Finally, the flows out of the labor force, listed in the third 

column, represent the number of previously employed 

individuals who leave the labor force (EN), the number 

of previously unemployed individuals who leave the labor 

force (UN), and the number of individuals who remained 

out of the labor force (NN). 

Note that the CPS labor force status flows data do not 

provide insight into how or why individuals change their 

labor force status. For example, among EN flows, the data 

do not distinguish between persons who drop out of the 

labor force voluntarily or involuntarily. They do not identify whether flows out of employment (EN or EU) represent quits, layoffs, or other separations; they do not identify whether those who enter the labor force (NE or NU) 

are new entrants or re-entrants; and they do not identify if 

those who quit looking for work (UN) do so because they 

are discouraged over job prospects.5

The most interesting estimates for studying labor dynamics are the gross flows not on the matrix’s diagonal (UE, 

NE, EU, NU, EN, UN). The gross flow statistics from the CPS

have actually been available in some form intermittently 

since 1948. Unlike previous versions, however, the current 

labor force status flows data are available on a seasonally 

adjusted basis and have flow estimates that are compatible 

with the monthly stock estimates published each month.6
BLS Labor Dynamics Data

 Monthly Labor Review • February 2008

Like the JOLTS estimates, the CPS labor force status flows 

can be referred to as “worker flows,” because they measure 

the movements of actual workers. One can express these 

flows as rates in several different ways, depending on the 

specific question one wants to answer. The more common 

gross flow rates used are expressed as percentages of the 

population, of the labor force, of employment, or of their 

original stock’s level. 

How the data relate to each other

At first glance, it might appear that the JOLTS, BED, and 

CPS gross flow data essentially measure the same basic 

economic phenomena, but each series measures a different and distinct aspect of labor market dynamics. Exhibit 

1 highlights the differences in measurement and concepts 

between the three data sources. Both the JOLTS and BED

data are based on establishments, while the CPS data are 

based on household information. The JOLTS and CPS report 

monthly data, while the BED reports quarterly. The data 

also differ in their coverage, timeliness, detail, and periods 

covered. More importantly, each series is conceptually different, with BED focusing on the perspective of businesses, 

CPS focusing on the perspective of individuals, and JOLTS

focusing on workers at businesses.

Both the JOLTS and CPS data measure worker flows. 

The JOLTS data does so from the establishment viewpoint, 

measuring the number of workers each month who are 

hired, who are laid off, who quit, or who separate in some 

other way. The CPS data measure worker flows from the 

individual’s viewpoint, measuring the number of workers who change their status between being employed, 

unemployed, or out of the labor force. The two sources 

complement each other well. For example, assume that 

the number of quits rises in the JOLTS data. To infer the 

implications of such a rise, it would be useful to know 

where these workers went. The CPS data address this question by reporting the number of workers who move from 

employment to either unemployment or out of the labor 

force entirely. It is possible that neither gross flow measure would change, suggesting that those who quit found 

new jobs quickly and remained in the pool of employed 

persons.7

The BED data measure job flows. The BED calculates the 

net change in jobs at each establishment over the reference period. Establishments that add workers on net either opened or expanded, and those that lose workers on 

net either closed or contracted. One can think of these 

job flows as a subset of worker flows, because even an 

establishment-level net change will mask turnover that 

occurs within the period. For example, if a worker quits 

and is quickly replaced during the same reference period, 

no job gain or loss will be observed in the BED data. In 

the JOLTS data, on the other hand, a quit and a hire would 

be observed.8 Compared with the other data sources, this 

fact makes the BED data somewhat more appropriate for 

analyzing the business side of the labor market, because it 

ignores much of the routine labor market churning and 

focuses on the reallocation of actual jobs in the labor market. Similarly, the CPS is more appropriate for analyzing 

the worker side of the market, because it measures the 

flow of individuals into and out of unemployment as well 

as into and out of employment. The JOLTS data on hires 

and separations lie somewhere in between, measuring 

employed workers but giving a more complete picture of 

their movements in and out of different businesses.

Graphical examples help to illustrate the different labor dynamics concepts each data source measures. Exhibit 

2 depicts some relatively common employment changes 

during both recessions and expansions. The hypothetical example shows two establishments. Establishment A 

faces difficult business conditions and must contract its 

workforce as a result. Establishment B has been doing 

well financially and is planning to expand. Establishment 

A is forced to lay off half of its eight workers. In addition, 

another worker from establishment A quits after learning that establishment B is hiring and accepts a position 

there. Of the four laid-off workers, three immediately 

start searching for new work and thus are counted as unemployed. The fourth decides not to actively search for 

work and drops out of the labor force. Under this scenario, 

even though establishment B is doing well, it must still 

deal with the routine turnover of workers. Of its original 

six workers, suppose one longtime employee retires and 

another quits because of family responsibilities at home. 

Thus, in order to expand, establishment B will need to 

hire additional workers as well as replace the two who left. 

Establishment B would hire four new workers: the one 

worker who was previously at establishment A and three 

recent college graduates who just entered the labor force.

How is this all reflected in the data? In JOLTS, there 

would be 4 hires (all at establishment B) and 7 separations (4 layoffs and 1 quit at establishment A, and 1 quit 

and 1 “other separation” at establishment B). In the BED

data, there would be 2 job gains (the net gain at establishment B) and 5 job losses (the net loss at establishment 

A). In the CPS data, there would be 3 workers going from 

employment to unemployment (the 3 layoffs at establishment A), 3 workers leaving employment and dropping out 

of the labor force entirely (the 1 layoff at establishment 
Monthly Labor Review • February 2008 

A, plus the retirement and quit at establishment B), and 3 

workers entering the labor force and immediately becoming 

employed (the 3 college graduates hired at establishment 

B). The worker who switched from establishment A to establishment B never became unemployed, so that worker’s 

status would not change in the CPS data—such a worker 

would be counted as part of the employment-to-employment (EE) flow. The monthly BLS Employment Situation 

news release would report a decline in employment of 3 

payroll jobs and an increase of 3 in the number of unemployed persons, with no change in the labor force. As this 

example shows, though, these aggregate level numbers do 

not describe all of the activity occurring in the labor market. 

There are many dynamics in this example: of the 17 workers in the two establishments, 10 had some change in their 

work status. The JOLTS data would show that 4 people were 

hired while 7 separated from their jobs. The BED data would 

show that 2 new jobs were created while 5 others were lost. 

Finally, the CPS data would show that 3 people flowed into 

the employment pool, while 6 others flowed out.

Exhibit 1.

Data characteristics Job Openings and 

Labor Turnover (JOLTS)

Business Employment 

Dynamics (BED)

Data source Survey of roughly 16,000 Virtual census of establishments Six of the eight rotation groups

 establishments from UI administrative records of the Current Population

 Survey; represents roughly

 45,000 households

Coverage All nonfarm employment All private employment Individuals aged 16 and over

Frequency Monthly Quarterly Monthly

Related data sources Survey of employment Longitudinal data based on the Gross flow data based on

 benchmarked to the Current Quarterly Census of continuous respondents in the

 Employment Statistics (CES) Employment and Wages Current Population Survey

 (QCEW) (CPS)

Timeliness Available approximately 2 Available approximately Available approximately 1

 months after the end of the 8 months after the reporting week after the end of the 

 reporting month quarter reporting month

History Data available from December Data available from 1992Q3 Data available from 

 2000 January 1990

Data elements Total number of Job Openings Total number of Gross Job Total number of individuals

 on the last business day of the Gains at Expanding and moving between two of the

 month Opening establishments three labor market states:

 Total number of Hires during Total number of Gross Job Employment, Unemployment, 

 the month Losses at Contracting and and Out of the Labor Force

 Total number of Separations Closing establishments (the total number moving from

 (disaggregated into Quits, unemployment to employment, 

 Layoffs and Discharges, and from employment to out

 Other Separations) during the of the labor force, and so on)

 month

Detail available Data available for major (2-digit Data available for major Data available by sex

 NAICS) industries and for four (2-digit NAICS) industries, 

 geographic regions by size class of the employer, 

 and by State

Current Population 

Survey (CPS) labor force 

status flows

Summary of BLS labor dynamics data
BLS Labor Dynamics Data

  Monthly Labor Review • Februar  20

What the data show

The preceding example highlights some common changes 

that occur in the labor market. Together, the three data 

sources show dynamics that represent millions of jobs 

and workers in every measurement period. In an average 

month during periods covered by the CPS and JOLTS data, 

more than 14 million individuals, or 6.9 percent of the 

working-age population, will change their labor force status in some way. More than 4 million will be hired and 

about as many will separate from their jobs. In a given 

quarter, more than 15 percent of all jobs will reallocate 

across different establishments. In other words, the flows 

of workers and jobs in any given period are quite large.

Consider the JOLTS estimates, for example. Chart 1 

presents the JOLTS monthly estimates of hires and separations as a percent of employment, and the job openings 

estimates as a percent of employment plus job openings 

(the total number of positions available). All flows move 

in accordance with the business cycle, but they also remain 

relatively high throughout its duration. For example, even 

at its lowest point, the hiring rate still represents more 

than 3 percent of employment (about 4 million workers), and even when hiring is strong, the rate of layoffs 

and other separations account for at least 1.3 percent of 

employment (about 2 million workers). Quits consistently 

account for between 1.5 and 2.0 percent of employment, 

implying that they are the more common type of separation, while the job openings rate fluctuates considerably 

between 2.0 and 3.5 percent of all positions.

Chart 2 depicts the gross job gains and gross job losses 

estimates from the BED. The estimates are broken out by 

type of employment change (such as expansions, contractions, openings, and closings) and are expressed as rates, 

calculated by dividing the job flows by the average of the 

current and previous quarters’ employment. The combined 

gross job gains and losses each averaged about 7.5 percent 

of employment (nearly 8 million jobs) per quarter over 

the 1992–2006 period. Most gains occurred at expanding 

establishments, while most losses occurred at contractExhibit 2. An example of employment dynamics

What occurs in the labor market:

Establishment A 

What it looks like in the data:

	JOLTS:	4 layoffs and 1 quit at establishment A, 4 hires, 1 quit and 1 other separation at establishment B.

	 BED:	 5 jobs lost at establishment A, 2 jobs gained at establishment B.

	 CPS:	 3 workers move from employment to unemployment, 3 workers move from employment to out of

	 	 the labor force, and 3 workers move from out of the labor force to employment (the 1 job-to-job

	 	 transition is not captured in the data).

Employment Situation Report:

A net loss of 3 payroll jobs and an increase in unemployment of 3 individuals.

Laid off and unemployed

Laid off and leaves the labor force

Quits for job at establishment B

Retires

Quits and leaves

the labor force

Establishment B 

Hired from establishment A

Enters the labor force
Monthly Labor Review • February 2008 

Chart 1. JOLTS monthly job openings and labor flows, seasonally adjusted, nonfarm employment

4.0

3.5

3.0

2.5

2.0

1.5

1.0

Percent

	Dec	 Jun	 Dec	 Jun	 Dec	 Jun	 Dec	 June	 Dec	 Jun	 Dec	 Jun	 Dec

	2000	 2001	 2001	 2002	 2002	 2003	 2003	 2004	 2004	 2005	 2005	 2006	 2006

Percent

Hires

Layoffs and other separations

Quits

Job openings

4.0

3.5

3.0

2.5

2.0

1.5

1.0

NOTE: Rates are percent of monthly employment. Job opening rate is percent of vacancies + employment

Chart 2. BED quarterly job flow rates, seasonally adjusted, private employment

7.0

6.0

5.0

4.0

3.0

2.0

1.0

Percent

	1992	 1994	 1996	 1998	 2000	 2002	 2004	 2006

Percent

Job gains at expansions

Job losses at contractions

Job gains at openings

Job losses at closings

7.0

6.0

5.0

4.0

3.0

2.0

1.0
BLS Labor Dynamics Data

10 Monthly Labor Review • February 2008

ing establishments. Gains at opening establishments and 

losses at closing establishments each averaged less than 2 

percent of employment. Additionally, gross job gains and 

loss rates tended to be higher prior to the 2001 recession.

Table 1 presents the monthly averages of the CPS labor 

force status flows data, both in levels and as percentages 

of the population, labor force, and the original “stock” or 

labor force category (employment, unemployment, or out 

of the labor force). Between 1990 and 2006, the largest 

flows were between employment and out of the labor 

force, averaging about 7.0 million workers going either 

into or out of each labor market status each month. Flows 

between employment and unemployment are smaller, 

averaging around 3.9 million individuals per month. An 

even smaller number of individuals, on average, move between unemployment and out of the labor force. Of the 

three stocks, unemployment exhibits the greatest amount 

of churning, relatively speaking. On average, 27 percent of 

the unemployed in a given month get a job the following 

month, while 22 percent drop out of the labor force.

Charts 3 and 4 depict the flows into and out of employment and unemployment, respectively, over time. 

Since the monthly series of these flows can be quite 

“noisy,” in a statistical sense, the estimates are presented as 

quarterly sums of the monthly data expressed as percentages of the labor force. Chart 3 shows that employment 

inflows (UE + NE) and employment outflows (EU + EN) 

exhibit small movements over time and both consistently 

represent about 12 percent of the labor force. Outflows 

exceed inflows during both recessionary periods, so employment falls. Chart 4 shows unemployment inflows (EU

+ NU) and unemployment outflows (UE + UN), again, as 

percentages of the labor force. These flows exhibit more 

cyclical variation over the period, ranging from 6.4 to 9.4 

percent, and they tend to track each other closely, with 

inflows into unemployment exceeding outflows during 

economic downturns.

Worker and job flows vary in the cross section as well as 

over time. For example, the JOLTS and BED data in table 2 

show that worker and job flows differ widely across major 

industries. Industries such as natural resources and mining, construction, and leisure and hospitality tend to have 

a high turnover of workers, as well as a high reallocation of 

jobs, while industries such as manufacturing and wholesale trade tend to have low levels of both. In addition, as 

the CPS data in table 3 shows, during the sample period 

used in this study, worker flow patterns differ by sex. Men 

account for more than half of the labor force, but women 

account for the majority of labor force dynamics, exhibiting higher flow rates into and out of both employment 

and unemployment.

Labor dynamics and the business cycle

These new data sources complement each other and provide a better understanding of the labor market. This is 

especially true when studying these changes over the business cycle. The CPS seasonally adjusted labor force status 

flows data go back to 1990, covering the last two recessions, 

while the BED data begin after the 1990–91 recession.9 The 

JOLTS data begin just before the start of the 2001 recession. 

Thus, the 2001 recession is the only one for which movements in all three surveys together can be compared. 

Chart 5 shows the movements of payroll employment 

growth (from the CES) and the unemployment rate (from 

the CPS) on a quarterly basis since 1990. In each recession, 

employment growth dropped sharply and remained negative for several quarters after the recession ended. FollowTable 1. Labor force status flows, average monthly estimates, CPS data, 1990–2006

Labor force flows Number of individuals 

(in thousands)

Percent of 

population

	Employed to unemployed (EU) .......................	 1,821	 0.9	 1.3	 1

	Employed to not in labor force (EN) ................	 3,561	 1.7	 2.6	 2

	Unemployed to employed (UE) .......................	 2,035	 1.0	 1.5	 27.4

	Unemployed to not in labor force (UN)............	 1,642	 .8	 1.2	 22.1

	Not in labor force to employed (NE)................	 3,398	 1.6	 2.5	 4

	Not in labor force to unemployed (NU)............	 1,832	 .9	 1.3	 2

Percent of 

labor force

Percent of

original stock
Monthly Labor Review • February 2008 11

Chart 4. CPS unemployment flows: quarterly sums, percent of the labor force

10.0

9.0

8.0

7.0

6.0

Percent

1990	 1992	 1994	 1996	 1998	 2000	 2002	 2004	 2006

Flows into unemployment

Flows out of unemployment

10.0

9.0

8.0

7.0

6.0

Percent

Chart 3. CPS employment flows: quarterly sums, percent of the labor force

14.0

13.0

12.0

11.0

10.0

Percent

1990	 1992	 1994	 1996	 1998	 2000	 2002	 2004	 2006

14.0

13.0

12.0

11.0

10.0

Percent

Flows into employment

Flows out of employment
BLS Labor Dynamics Data

12 Monthly Labor Review • February 2008

ing the 2001 recession, employment continued to contract 

until the middle of 2003. The unemployment rate rose 

during both recessions and did not peak until after they 

had officially ended. The unemployment rate declined over 

a long period from 1993 to 2001. After the 2001 recession, 

the unemployment rate did not rise nearly as high as it did 

following the 1990–91 recession.

Comparing these data to the gross flows data in chart 

4, one can see that the unemployment stock and the unemployment flows exhibited very similar patterns. When 

unemployment was high, the flow of people moving into 

and out of the unemployment pool was high as well. By 

definition, when unemployment inflows exceed outflows, 

the unemployment rate rises, and one can observe that this 

happened during and immediately following both recessions. Note that it takes only relatively small differences 

between inflow and outflow rates to generate large changes 

in the unemployment rate.

The information presented in charts 6 and 7 provides a 

clearer picture of the relationship between the movements 

of worker and job flows from the JOLTS, BED and CPS gross 

flows data. Chart 6 depicts the flows into employment 

Table 2. Worker and job flow estimates by major industry, JOLTS and BED data, January 2001–June 2006

Industries

Job 

openings

JOLTS monthly estimates, 

percent of employment

Layoffs 

and other 

separations

Hires Gross job 

gains

Natural resources and mining .................................	 1.4	 3.2	 1.4	 1.7	 17.1	 17.0

	Construction............................................................	 1.7	 5.6	 2.2	 3.4	 11.7	 11.4

	Manufacturing .........................................................	 1.6	 2.3	 1.2	 1.5	 3.9	 4.8

	Wholesale trade ......................................................	 1.8	 2.4	 1.3	 1.2	 5.7	 5.7

	Retail trade..............................................................	 2.3	 4.5	 2.7	 1.7	 7.0	 6.9

	Transportation, warehousing, and utilities...............	 1.9	 3.0	 1.4	 1.6	 5.3	 5.4

	Information ..............................................................	 2.4	 2.2	 1.4	 1.0	 5.2	 6.1

	Financial activities ...................................................	 2.5	 2.3	 1.3	 .9	 5.8	 5.6

	Professional and business services........................	 3.4	 4.6	 2.1	 2.1	 8.5	 8.4

	Health and education ..............................................	 3.5	 2.7	 1.5	 .9	 4.8	 4.2

	Leisure and hospitality ............................................	 3.3	 6.5	 4.0	 2.2	 9.4	 9.2

	Other services .........................................................	 2.3	 3.3	 2.0	 1.3	 7.9	 7.9

	Government ............................................................	 1.8	 1.5	 .6	 .6	 ...	 ...

BED quarterly data, 

percent of average 

employment

Gross job 

losses Quits

Table 3. Labor force status flows by gender, average monthly estimates, CPS data, 1999–2006

Labor force flows Number of individuals 

(in thousands)

Percent of total 

labor force

 Men

	Employment inflows (UE + NE) ................................ 2,611	 1.9	 3

	Employment outflows (EU + EN)............................... 2,586	 1.9	 3.5

	Unemployment inflows (EU + NU)............................. 1,898	 1.4	 2.6

	Unemployment outflows (UE + UN)........................... 1,911	 1.4	 2.6

	Employment inflows (UE + NE) ................................. 2,822	 2.0	 4.4

	Employment outflows (EU + EN)............................... 2,796	 2.0	 4.4

	Unemployment inflows (EU + NU)............................ 1,755	 1.3	 2

Unemployment outflows (UE + UN)........................... 1,766	 1.3	 2.8

Percent of gender’s

labor force
Monthly Labor Review • February 2008 1

(hires, gross job gains, and employment inflows, respectively), while chart 7 shows the flows out of employment 

(separations, gross job losses, and employment outflows, 

respectively). The monthly JOLTS and CPS flow data are 

summed for each quarter to make them comparable to the 

quarterly BED data. For consistency, all flows are expressed 

as percentages of the average of the current and previous 

periods’ employment.10 In addition, the JOLTS job openings rate (measured at their level as of the beginning of the 

quarter) is included in chart 6. Chart 7 presents the JOLTS

separations rate broken out into quits and layoffs plus all 

other separations.

Chart 6 shows that hiring and gross job gains declined 

during the 2001 recession. Hiring had a particularly large 

drop during the recession and did not rebound until mid2003. By the end of 2004, the hiring rate had returned 

to its prerecession levels. Job openings followed a similar 

pattern, although they were still somewhat below their 

prerecession level at the end of 2006. The rate of gross job 

gains, which was fairly steady in the last 18 months of the 

1990s, began to decline in the first half of 2000, well before the recession began.The rate of job gains fell during 

the recession and continued its decline until well after it 

ended. In fact, even though net job gains rebounded starting in mid-2003, gross job gains remained relatively low 

through the middle of 2006. Finally, flows into employment showed little change over the business cycle, other 

than to rise modestly during each recession. At first glance, 

this might appear inconsistent with the other data measures, but these are the individuals who find work after 

having been unemployed or out of the labor force in the 

prior month. The flows from these labor force states will 

tend to be higher when their stocks are larger.

Employment inflows do not include workers who are 

hired while employed at another job (“job-to-job” transitions). To make the employment inflows comparable to the 

JOLTS hiring rate, one would have to add these job-to-job 

transitions to the employment inflow estimate.11 For this 

estimate to match the observed movement of the JOLTS

hiring rate, the rate of job-to-job transitions would have 

to drop precipitously during 2001. Most people who leave 

one job and take another job separate from their previous 

employer by quitting; the JOLTS data exhibit a large fall in 

quits, suggesting there were fewer of these job-to-job transitions in 2001. 

In chart 7, the JOLTS data show a large decline in the rate 

CES nonfarm employment growth and the CPS unemployment rate, quarterly and

seasonally adjusted

Chart 5.

Unemployment rate (left axis)

Nonfarm employment growth (right axis)

9.0

8.0

7.0

6.0

5.0

4.0

3.0

Percent

1990	 1992	 1994	 1996	 1998	 2000	 2002	 2004	 2006

1.2

0.8

0.4

0.0

–0.4

–0.8

–1.2

Percent
BLS Labor Dynamics Data

14 Monthly Labor Review • Februar  20

Worker and job flows out of employment, quarterly, seasonally adjusted, percent of average 

employment

Chart 7.

14.0

12.0

10.0

8.0

6.0

4.0

2.0

0.0

Percent

1990	 1992	 1994	 1996	 1998	 2000	 2002	 2004	 2006

Percent

14.0

12.0

10.0

8.0

6.0

4.0

2.0

0.0

Worker and job flows into employment, quarterly, seasonally adjusted, percent of average 

employment

Chart 6.

14.0

12.0

10.0

8.0

6.0

4.0

2.0

0.0

Percent

1990	 1992	 1994	 1996	 1998	 2000	 2002	 2004	 2006

Flows into employment (CPS)

Hire (JOLTS)

Gross job gains (BED)

Job openings (BED)

14.0

12.0

10.0

8.0

6.0

4.0

2.0

0.0

Percent

Flows out of employment (CPS)

Quits (JOLTS)

All other separations (JOLTS)

Gross job losses (BED)
Monthly Labor Review • February 2008 1

of quits during the recession, comparable to the decline in 

hires shown in chart 6. Moreover, quits start to rise and 

reach their prerecession levels about the same times that 

hires do. Layoffs and other separations, on the other hand, 

rise modestly during the 2001 recession and then decline. 

They remain higher between 2002 and 2004 and decline 

again in 2005. Gross job losses also rise and then decline 

during the 2001 recession. Like the gross job gains, they 

continue to decline during the first half of 2006. Finally, 

employment outflows exhibit a pattern quite similar to 

layoffs and other separations, with a rise during the recession that declines somewhat after it ends, but doesn’t completely fall to prerecession levels until 2005. Employment 

outflows exhibit a similar pattern during and after the 

1990–91 recession. Unlike employment inflows, there is 

little disconnect between employment outflows and what 

is shown by the JOLTS data on layoffs and other separations 

and the BED gross job loss data show. This occurs for two 

reasons: first, unlike inflows, the outflow rate has employment as its initial stock, making it more comparable to the 

other estimates; and second, outflows from employment 

are more closely related to layoffs and job losses than they 

are to total separations, which include quits.

NEW DATA ON LABOR DYNAMICS recently released by the 

BLS complement the standard measures of the labor market, such as the employment and unemployment statistics 

provided in the monthly BLS employment report. The Job 

Openings and Labor Turnover Survey measures the number of workers who move into and out of jobs each month, 

distinguishes between those who quit or are laid off, and 

tracks the number of job openings businesses have open at 

a given point in time. The Business Employment Dynamics 

data decompose employment growth into the jobs gained at 

opening and expanding establishments and the jobs lost at 

contracting and closing establishments. Finally, labor force 

status flows data from the Current Population Survey measure the movement of individuals as their status changes 

between being employed, unemployed, or out of the labor 

force entirely. These new data track the rich dynamics that 

underlie movements in employment and unemployment and 

provide a better understanding of labor market changes. 

Notes

1

 For more about the JOLTS data see Kelly A. Clark and Rosemary 

Hyson, “New tools for labor market analysis: JOLTS,” Monthly Labor 

Review, December 2001, pp. 32–37 and Kelly Clark, “The Job Openings and Labor Turnover Survey: what initial data show,” Monthly Labor Review, November 2004, pp. 14–23. The JOLTS data are publicly 

available on the Internet at http://www.bls.gov/jlt.

2

 For more information on the Business Employment Dynamics 

(BED) data, see Timothy R. Pivetz, Michael A. Searson, and James R. 

Spletzer, “Measuring job and establishment flows with BLS longitudinal microdata,” Monthly Labor Review, April 2001, pp. 13–20; and 

James R. Spletzer, R. Jason Faberman, Akbar Sadeghi, David M. Talan, 

and Richard L. Clayton, “Business employment dynamics: new data 

on gross job gains and losses,” Monthly Labor Review, April 2004, pp. 

29–42. The BED data are publicly available on the Internet at http://

www.bls.gov/bdm.

3

 Using average employment in the denominator provides a symmetric growth rate and allows a symmetric treatment of changes at 

opening and closing establishments. This is the official BLS methodology, which is consistent with that of Steven J. Davis, John C. Haltiwanger, and Scott Schuh, Job Creation and Job Destruction (MIT Press, 

1996).

4

 For an explanation of the Current Population Survey’s coverage and concepts, see “Explanatory Notes and Estimates of Error,” 

Employment and Earnings (Bureau of Labor Statistics, January 2007). 

For more on the concepts and estimation of labor force status flows 

data, see Harley J. Frazis, Edwin L. Robinson, Thomas D. Evans, and 

Martha A. Duff, “Estimating gross flows consistent with stocks in the 

CPS,” Monthly Labor Review, September 2005, pp. 3–9 and Randy E. 

Ilg, “Analyzing CPS data using gross flows,” Monthly Labor Review, 

September 2005, pp. 10–18. The CPS data are publicly available on the 

Internet at http://www.bls.gov/cps.

5

 The CPS has a specific definition of discouraged workers. They 

are individuals who wish to work and have looked for work sometime 

in the prior 12 months, but who are not currently looking for work 

specifically because they believe that no jobs are available for them.

6

 To make the CPS labor force status flows consistent with the reported stock estimates, the BLS developed a method that forces their 

reconciliation. In addition to the nine flows shown in the text table, 

there are adjustments that correct for all sources of discrepancies, so 

that implied changes in stocks derived from the flows match changes 

in CPS stock estimates. These adjustments account for changes in the 

working-age population and include net immigration, persons who 

just turned 16, and average death rates. For more information, see 

Frazis and others, “Estimating gross flows consistent with stocks in 

the CPS.” 

7

 Note that with the 1994 redesign of the CPS, it became possible 

to measure the job-to-job transitions that are contained within the EE

estimate. Respondents are now asked whether their current employer 

is the same as their employer from the previous month. The publicly 

available data do not report these estimates separately, although research studying their behavior exists (for example, Bruce Fallick and 

Charles A. Fleischmann, “Employer-to-Employer Flows in the U.S. 

Labor Market: The Complete Picture of Gross Worker Flows,” Federal Reserve FEDS Working Paper 2004–34). For more information 

on their measurement, see “Effects of Job Changing on Payroll Survey 

Employment Trends,” available on the Internet at http://www.bls.

gov/ces/cesjobch.pdf.

8

 By this notion, one could use the JOLTS microdata to estimate 

both job flows and worker flows.

9

 Although the official Business Employment Dynamics (BED) 

data begin in 1992, there exists firm-level BED data that begin in 
BLS Labor Dynamics Data

16 Monthly Labor Review • Februar  20

1990. See Jessica Helfland, Akbar Sadeghi and David Talan, “Employment dynamics: small and large firms over the business cycle,” 

Monthly Labor Review, March 2007, pp. 39–50; and R. Jason Faberman, “Job Flows over the Recent Business Cycle: Not all ‘Recoveries’ 

are Created Equal,” BLS Working paper No. 391 (Bureau of Labor 

Statistics, 2005). 

10 As a result of the authors imposing this consistency on the data, 

the employment flow rates in charts 7 and 8 use a different denominator than the employment flow rates in chart 3.

11 Note that this addition would also be necessary if one wanted to 

compare employment outflows with the JOLTS total separations rate. 

In addition, note that adding job-to-job transitions would make the 

CPS employment inflows considerably larger in magnitude than the 

JOLTS hiring rate. (See note 7 for more information about job-to-job 

transitions.) Understanding why such a difference in magnitudes exists is a topic of ongoing research. 

Nominations Sought for 2008 Julius Shiskin Award 

Nominations are invited for the annual Julius Shiskin Memorial Award for Economic Statistics. The 

award is given in recognition of unusually original and important contributions in the development 

of economic statistics or in the use of statistics in interpreting the economy. Contributions are recognized for statistical research, development of statistical tools, application of information technology 

techniques, use of economic statistical programs, management of statistical programs, or developing 

public understanding of measurement issues. The award was established in 1980 by the Washington 

Statistical Society (WSS) and is now cosponsored by the WSS, the National Association for Business 

Economics, and the Business and Economics Statistics Section of the American Statistical Association (ASA). The 2007 award recipient was Arthur Kennickell, Senior Economist and Head of the 

Microeconomic Surveys Unit at the Federal Reserve Board, for his leadership of the Federal Reserve’s 

Survey of Consumer Finances and his achievements as an international expert on the design and 

implementation of household economic surveys. 

Because the program was initiated many years ago, it is little wonder that statisticians and economists 

often ask, “Who was Julius Shiskin?” At the time of his death in 1978, “Julie” was the Commissioner 

of the Bureau of Labor Statistics (BLS) and earlier served as the Chief Statistician at the Office of 

Management and Budget (OMB), and the Chief Economic Statistician and Assistant Director of the 

Census Bureau. Throughout his career, he was known as an innovator. At Census he was instrumental 

in developing an electronic computer method for seasonal adjustment. In 1961, he published Signals 

of Recession and Recovery, which laid the groundwork for the calculation of monthly economic indicators, and he developed the monthly Census report Business Conditions Digest to disseminate them to 

the public. In 1969, he was appointed Chief Statistician at OMB where he developed the policies and 

procedures that govern the release of key economic indicators (Statistical Policy Directive Number 3), 

and originated a Social Indicators report. In 1973, he was selected to head BLS where he was instrumental in preserving the integrity and independence of the BLS labor force data and directed the most 

comprehensive revision in the history of the Consumer Price Index (CPI), which included a new CPI

for all urban consumers. 

Nominations for the 2008 award are now being accepted. Individuals or groups in the public or private 

sector from any country can be nominated. The award will be presented with an honorarium of $750 

plus additional recognition from the sponsors. A nomination form and a list of all previous recipients 

are available on the ASA Web site at www.amstat.org/sections/bus_econ/shiskin.html or by writing 

to the Julius Shiskin Award Committee, Attn: Monica Clark, American Statistical Association, 732 

North Washington Street, Alexandria, VA 22314–1943. 

Completed nominations must be received by April 1, 2008. For further information contact Steven 

Paben, Julius Shiskin Award Committee Secretary, at paben.steven@bls.gov.