BLS WORKING PAPERS 

 U.S. Department of Labor 

U.S. Bureau of Labor Statistics 

Office of Employment and Unemployment Statistics 

Business Employment Dynamics: 

Tabulations by Employer Size 

Shail J. Butani, U.S. Bureau of Labor Statistics 

Richard L. Clayton, U.S. Bureau of Labor Statistics 

Vinod Kapani, U.S. Bureau of Labor Statistics 

James R. Spletzer, U.S. Bureau of Labor Statistics 

David M. Talan, U.S. Bureau of Labor Statistics 

George S. Werking Jr., U.S. Bureau of Labor Statistics 

Working Paper 385

December 2005

All views expressed in this paper are those of the authors and do not necessarily reflect the views or policies of the 

U.S. Bureau of Labor Statistics. 
BUSINESS EMPLOYMENT DYNAMICS: 

TABULATIONS BY EMPLOYER SIZE

Shail J. Butani 

Richard L. Clayton 

Vinod Kapani 

James R. Spletzer 

David M. Talan 

George S. Werking Jr. 

Bureau of Labor Statistics 

U.S. Department of Labor 

Forthcoming, Monthly Labor Review

This version: December 8, 2005 
 1

1) Introduction 

 The gross job gains and gross job loss statistics from the BLS Business Employment 

Dynamics (BED) program measure the large gross job flows that underlie the quarterly net 

change in employment. In the fourth quarter of 2004, employment grew by 869,000 jobs. 

This growth is the sum of 8.1 million gross job gains from opening and expanding 

establishments, and 7.2 million gross job losses from contracting and closing establishments. 

The new BED data have captured the attention of economists and policymakers across the 

country, and these data are becoming a major contributor to our understanding of employment 

growth and business cycles in the U.S. economy. The data are high quality, high frequency, 

relatively timely, and historically consistent. It is also important to note that the BED data 

were created with no new data collection efforts and with no new additional respondent 

burden. 

 Following the initial release of the BED data in September 2003, the BED data series 

expanded in May 2004 with the release of industry statistics. The BLS then began work on 

tabulations by size class. The production of size-class statistics is a complex task involving 

several economic and statistical issues. Although it is trivial to classify a business into a size 

class in any given quarter, it is difficult to classify a business into a size class for a 

longitudinal analysis of employment growth. Several different classifications exist, and many 

of these possible classifications have appealing theoretical and statistical properties. 

Furthermore, these alternative classification methodologies result in sharply different portraits 

of employment growth by size class. This point was clearly documented by Cordelia Okolie 

in a July 2004 Monthly Labor Review article.1

 In this article, we discuss the alternative statistical methodologies that the BLS 

considered for creating size class tabulations from the Business Employment Dynamics data. 

Our primary focus is on four methodologies: quarterly base-sizing, annual base-sizing, meansizing, and dynamic-sizing. We discuss the evaluation criteria that BLS considered for 

choosing its official size class methodology. Although the BLS is making the seasonally 

adjusted data series from all the classification methodologies available for research purposes, 

one methodology had to be chosen as the official methodology for citation and analysis in the 

quarterly BED press release. This is analogous to the calculation of the unemployment rate 

from the Current Population Survey – the BLS produces and releases six different 

unemployment rates {U1, U2, ..., U6}, yet refers only to the official unemployment rate U3 

in the text of the monthly employment situation press release.2

 BLS chose dynamic-sizing as 

the official methodology for the BED size class statistics. 

2) The Economics of Employer Size 

 We begin this article with a brief discussion about employer size as an economic 

classification variable. Many BLS employment statistics are for the Nation as a whole, with 

additional detail provided for industry and geographical breakdowns. The BLS Quarterly 

Census of Employment and Wages (QCEW) program also produces statistics by employer 
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size. Some interesting aspects about the U.S. economy are evident in these cross-sectional 

QCEW employer size statistics. 

Empirical Findings about Employer Size 

 There are several empirical findings about the role of employer size in the U.S. 

economy. First, although most establishments are small, most people work in mid-sized and 

large establishments. This is seen in Table 1, which documents the number of establishments 

and their employment by size class.3

 The data show that 60 percent of establishments have 

less than 5 employees, and 17 percent of establishments have between 5 and 9 employees. 

Most establishments in the U.S. are small: 88 percent of establishments have less than 20 

employees, 95 percent of establishments have less than 50 employees, and 98 percent of 

establishments have less than 100 employees. 

 Looking at employment rather than establishments, the data in Table 1 show that 

employment is more evenly spread through the size class distribution. Only 7 percent of 

employment is in establishments with less than 5 employees, and 26 percent of employment is 

in establishments that have less than 20 employees. Although only 0.1 percent of 

establishments (5,487 establishments) have 1000 or more employees, 11 percent of 

employment is in these largest establishments. Similarly, 43 percent of employment is in the 

2 percent of establishments that have 100 or more employees, and 57 percent of employment 

is in the 5 percent of establishments that have 50 or more employees. The data in Table 1 

clearly show that the majority of U.S. employment is concentrated in a small percentage of all 

U.S. establishments. 

 A second empirical finding about the economics of employer size is that workers in 

large establishments earn more than workers in small establishments. This is seen in Chart 1, 

where the average weekly wages are graphed for each size class.4

 With the exception of the 

smallest size class (less than 5 employees), weekly wages are monotonically increasing with 

establishment size. Employees who work in establishments with 5 to 9 employees earn, on 

average, 585 dollars per week, and employees who work in establishments with 50 to 99 

employees earn, on average, 703 dollars per week. Workers employed in the largest 

establishments – those with 1000 or more employees, earn on average 1,156 dollars per week. 

 There is a large literature in economics that attempts to explain why the wages of 

individuals are positively associated with the size of their employer.5

 Briefly, the evidence 

from this literature suggests that theories based on compensating differentials, union 

avoidance, monitoring, and rent sharing accruing from product market power contribute little 

to explaining the employer-size wage differential. Sorting of workers into establishments is a 

more likely possibility: analysts have found that firm size coefficients are reduced by roughly 

one-half when observed labor quality variables are added to a wage regression, and 

controlling for unobserved labor quality in a longitudinal fixed effects regression further 

reduces the firm size coefficients. Even so, there remains a significant size effect after 

controlling for both observed and unobserved labor quality.6

 Recent work using linked 

employer-employee microdata allows for the evaluation of explanations that can not be 

analyzed using most analytical databases. This recent research finds that more skilled 
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workers tend to work together, and this matching reduces the employer-size wage premium 

by approximately 20 percent, yet a large and significant employer-size wage premium still 

exists and remains unexplained.7

 Although it is an accepted fact that workers in large firms 

earn more, economists have not yet conclusively answered why this is so. 

Who Creates the Most Jobs 

 One of the most discussed topics about employer size is the question of who creates 

the most jobs: small businesses or large businesses? Policy-makers often cite an important 

role for small businesses in creating jobs.8 Data analysts have known for a long time that 

estimating the number of jobs created by small businesses is extremely sensitive to the 

statistical methodology used. This is the subject of chapter 4 in the 1996 book “Job Creation 

and Destruction” written by Steven Davis, John Haltiwanger, and Scott Schuh, and was 

recently confirmed by Cordelia Okolie using BED microdata.9

 As Okolie shows in Table 2 of 

her article, a quarterly base-sizing methodology credits the smallest size class (firms with 1-4 

employees) with net employment growth of over 900,000 jobs, whereas an end-sizing 

methodology states that this smallest size class had net employment losses of almost 200,000 

jobs. These statistics highlight how alternative methodologies for assigning firms to size 

classes can result in very different conclusions regarding whether small businesses or large 

businesses are responsible for the creation of new jobs. 

3) Size Class Methodologies 

An Overview of the Issues 

 In her July 2004 Monthly Labor Review article, Cordelia Okolie mentions three 

methodology issues that influence the calculation and interpretation of business employment 

dynamic statistics by size-class. The first is how businesses should be classified into size 

classes when constructing net and gross job flow statistics. Okolie’s analysis showed that this 

is the most important methodology issue, and further discussion and analysis of this issue is 

the focus of this article. The second issue involves the appropriate measure to use in the 

denominator when calculating net and gross job flow rates. Okolie found that this had very 

small effects on the net employment growth statistics, and this issue is not discussed further in 

this article. The third issue is whether the establishment or the firm should be the unit of 

analysis. 

 There are valid arguments for choosing either the firm or the establishment as the unit 

of analysis for producing BED size class tabulations. If employment changes are the result of 

decisions made at corporate headquarters, then the firm is the appropriate unit for analyzing 

the expansion and contraction of businesses. On the other hand, if employment changes are 

the result of individual establishment decisions based upon local labor market conditions, then 

the establishment is the appropriate unit to analyze business expansions and contractions. The 

truth obviously lies somewhere between these two extremes – employment changes at 

individual establishments are affected by both corporate decisions and by local factors. The 

BLS has decided that firm level data best satisfies user needs for net and gross job flow 
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statistics by size class. This decision was made after consultations with users and with BLS 

advisory committees, and after a review of how other international statistical agencies 

produce their longitudinal size class tabulations. The Employer Identification Number (EIN) 

is the firm-level identifier used to create the BED size class statistics. The seasonally adjusted 

time series of size-class statistics shown later in this article are all firm-level statistics.10

The Four Methodologies Under Consideration 

 The four classification methodologies discussed in this article are quarterly basesizing, annual base-sizing, mean-sizing, and dynamic-sizing. Quarterly base-sizing and 

mean-sizing were discussed by Okolie in her July 2004 Monthly Labor Review article. Based 

upon conversations with users and with BLS advisory committees, the BLS has determined 

that the end-sizing methodology discussed by Okolie is not a viable option, and thus end 

sizing is not discussed in this article. Annual base-sizing and dynamic-sizing are two 

methodologies that were introduced for evaluation following the publication of Okolie’s July 

2004 Monthly Labor Review article. 

 There are many ways that firms can be classified into size classes for a longitudinal 

analysis of employment growth. Employment growth is measured as the change in the size of 

the firm from one quarter to the next. One possible classification methodology is to use the 

firm’s size in the first of the two quarters; this is called quarterly base-sizing. Mean-sizing is 

a methodology that classifies the firm based upon the average size of the firm in the previous 

and the current quarter. A specific example may help illustrate these two methodologies – 

assume that a firm grows from 3 employees in June (the second quarter) to 13 employees in 

September (the third quarter). Using the quarterly base-sizing methodology, the firm had 3 

employees in the initial quarter and would be classified in the “1-4” size class category. 

Using the mean-sizing methodology, the mean of 3 and 13 is 8, and this firm would be 

classified in the “5-9” size class. The firm’s growth of 10 employees would be attributed to 

the “1-4” size class under quarterly base-sizing, and would be attributed to the “5-9” size class 

under mean-sizing. This example begins to hint how alternative classification methodologies 

can have a large impact on how employment growth is attributed to different size classes. 

 Annual base-sizing is a methodology that classifies a firm based upon its size class in 

the most recent March (the first quarter of the year, as measured in the BED program). In the 

example of the previous paragraph, the second to third quarter growth of 10 employees would 

be attributed to the size class of the firm as it was classified in the first quarter of the year 

(which is unknown in this simple example). As we will describe in more detail later in this 

article, annual base-sizing has some appealing statistical properties that remedy some of the 

perceived faults of the quarterly base-sizing methodology. 

 Dynamic-sizing is a straightforward measurement methodology that allocates a firm’s 

quarterly employment growth or loss to each respective size class that the growth or loss 

occurred in. Firms are initially assigned to a size class each quarter based on their 

employment in the previous quarter, but are re-assigned to a new size class during the quarter 

when their employment change indicates that a size class threshold has been crossed. In the 

example of a firm growing from 3 to 13 employees, the growth of 10 would be allocated as 
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follows: size class “1-4” would be credited with the growth of 1 employee (the growth from 3 

to 4), size class “5-9” would be credited with the growth of 5 employees (the growth from 4 to 

9), and size class “10-19” would be credited with the growth of 4 employees (the growth from 

9 to 13).11 The methodology of dynamic-sizing – also referred to as momentary sizing -- was 

initially proposed by Professor Per Davidsson in two research papers in the mid-to-late 

1990s.12

 Dynamic-sizing is based on a measurement process which assumes continuous linear 

employment growth or loss from one quarter to the next, with the growth or loss allocated into 

the appropriate size class at the moment it occurred. In the example of a firm growing from 3 

employees in June to 13 employees in September, this growth of 10 employees can be linearly 

modeled as the growth of 1 employee every 9 days (13 weeks from one quarter to the next, 7 

days per week, and 10 employee growth over these 91 days). If a firm’s employment change 

could be measured on a daily basis, and if this employment change occurred linearly within 

the quarter, then the statistics from this measurement process would be equivalent to the 

statistics from dynamic-sizing with quarterly point-in-time employment data. 

Methodology matters – a simple example 

 The example in the previous paragraphs shows that the four methodologies differ in 

how they allocate employment growth and loss to employer size classes. We now add one 

more wrinkle to this simple example by asking what happens when employment returns to its 

original level the following quarter. Specifically, assume that a firm grows from 3 employees 

in the second quarter to 13 employees in the third quarter, and then declines back to 3 

employees in the fourth quarter. The third and fourth quarter net employment growth 

statistics by size class computed under the four methodologies are given in Chart 2. 

 The upper left corner of Chart 2 shows the net employment growth statistics for this 

example computed under the quarterly base-sizing methodology. The growth of 10 

employees, from 3 to 13, is attributed to the “1-4” size class (classified on the base period 

employment of 3), and the following quarter’s decline of 10 employees, from 13 to 3, is 

attributed to the “10-19” size class (classified on the base period employment of 13). In this 

particular example with a quarterly base-sizing methodology, small firms get credit for 

creating jobs whereas larger firms get credited for losing jobs. 

 The middle left panel of Chart 2 shows the net employment growth statistics for this 

example computed under the mean-sizing methodology. The growth of 10 employees and the 

decline of 10 employees both get credited to the “5-9” size class (since the mean employment 

level for both the growth from 3 to 13 and the decline from 13 to 3 is 8). The mean-sizing 

methodology imposes symmetry in this example – the growth and the following decline back 

to the initial level of employment are allocated to the same size class. 

 The bottom left corner of Chart 2 shows the net employment growth statistics for this 

example computed under the dynamic-sizing methodology. Similar to the mean-sizing 

methodology, the dynamic sizing methodology results in statistics that are symmetrical for the 

expansion and the following contraction. However, in this example, the dynamic-sizing 
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methodology allocates the jobs gained in the expansion and the jobs lost in the contraction to 

multiple size class categories, whereas the mean-sizing methodology allocates all jobs gained 

and all jobs lost to one size class category. 

 The three right panels of Chart 2 show the net employment growth statistics for this 

example computed under the annual base-sizing methodology. Three panels are given 

because we don’t know from this simple example what the employment was in March of the 

given year. If March employment was 3, then the annual base-sizing methodology allocates 

all the growth and all the decline to the “1-4” size class category. If March employment was 

8 or 13 (two of many possibilities), then the net employment growth and following decline is 

allocated to the “5-9” or the “10-19” size class, respectively. Similar to mean-sizing and 

dynamic-sizing, the annual base-sizing statistics are symmetrical for the expansion and the 

contraction in this specific example.13

4) Transitory and Reverting Employment Changes in the BED Microdata 

Background 

 The example in the previous section shows how alternative classification 

methodologies can allocate net employment growth and decline to different size classes. 

Furthermore, and crucially important for purposes of analyzing which employers create the 

most jobs, this example also shows how some methodologies, relative to others, can 

systematically allocate employment growth into smaller size categories while simultaneously 

allocating employment decline into larger size categories. This effect is often referred to as 

regression to the mean bias.14

 We do not believe that the so-called regression to the mean effects are a bias. The 

quarterly base-sizing statistics are measuring exactly what they are designed to measure for a 

quarter, and the fact that these statistics treat growth and decline non-symmetrically is not a 

bias. Measuring bias in a statistically rigorous way implies knowing the truth and measuring 

how an estimator deviates from this truth. We view symmetry as a desirable property for an 

estimator, but we do not view symmetry as the truth. 

 In the example used in the previous section, the symmetry (or lack of) in the net 

employment change estimates calculated under the various methodologies can be traced back 

to firms that cross a size-class boundary twice within a given time interval. The firm in the 

example grew out of the “1-4” size class, through the “5-9” size class, and into the “10-19” 

size class, and then the following quarter declined out of the “10-19” size class, back through 

the “5-9” size class, and into the “1-4” size class. Thus within two quarters, the firm in this 

example crossed the size class boundary separating the “1-4” and “5-9” categories twice – 

once in each direction – and also crossed the size class boundary separating the “5-9” and 

“10-19” categories twice (again, once in each direction). 

 Seasonality is a major reason why a firm may cross a size class boundary twice within 

a given time interval. Many industries have very large and predictable seasonal swings in 
 7

employment. If we analyze quarterly changes in employment levels over the course of a year, 

seasonality will lead to transitory and reverting changes in employment. For example, an 

amusement park in a northern climate may have 75 employees in the summer, yet only have 

two or three maintenance employees on the payroll during the winter. This amusement park 

would cross multiple size class boundaries twice during the course of a year, as it moves out 

of the “1-4” and into the “50-99” size class in the spring and summer, and then falls out of the 

“50-99” size class and back into the “1-4” size class in the fall and winter. 

 There are several other reasons why a firm may cross a size class boundary twice 

within a given time interval. A transitory and reverting decline in employment (for example, 

from 5 to 4 and then back to 5) would occur when an employee leaves a firm and it takes time 

to fill the resulting vacancy. Similarly, a transitory and reverting increase in employment may 

occur (for example, from 4 to 5 and then back to 4) if a firm hires someone in expectation of a 

forthcoming retirement. Measurement error is another reason why firms may have transitory 

and reverting changes in employment. In the example of the previous section, where the three 

quarters of employment were {3, 13, 3}, the firm may have mistakenly reported an 

employment level of 13 in the middle quarter when it meant to report an employment level of 

3. 

 Regardless of the source of the transitory and reverting change in employment, firms 

that cross a given size-class boundary twice within a given time interval would lead to 

statistics that show small firms creating jobs and large firms losing jobs when employment 

growth is classified into size classes with a methodology that doesn’t impose symmetry on 

employment growth and decline. The question that we ask in this section is whether and to 

what extent establishments in the BED microdata exhibit such growth and decline across sizeclass boundaries, and what effect these transitory and reverting changes in employment across 

size-class boundaries have on the net employment growth statistics when tabulated under 

alternative methodologies. 

Empirical Analysis 

 We analyze the incidence and the effect of transitory and reverting changes in 

employment across size class boundaries using the universe of establishments that have 

positive employment in 1999:Q1 and 2000:Q1. Our restriction to positive employment in 

both 1999:Q1 and 2000:Q1 removes births and deaths from our sample, and gives us a 

balanced panel of establishments who are alive in all five quarters of the analysis. We remove 

births and deaths because the establishments that are born in 1999:Q2 have several quarters to 

experience transitory and reverting changes in size class, whereas establishments born in 

2000:Q1 are not able, in our sample, to experience a transitory and reverting change. We 

believe that focusing on continuous establishments with positive employment in the first 

quarter of each year is the best sample for simplicity in both the analysis and the interpretation 

of the data.15

 The incidence of transitory and reverting changes in size classes in the five quarters 

1999:Q1 to 2000:Q1 is documented in Table 2. The first column of Table 2 shows that the 

analysis sample has 5.3 million continuous establishments with an average quarterly 
 8

employment of over 100 million jobs.16 The second column shows that 80.6 percent of these 

establishments do not cross a given size class boundary twice during the year. In this data, 

19.3 percent of establishments (1.028 million establishments) make a transitory and reverting 

change in size class during the year. These establishments represent 15.9 percent of 

employment in continuous units. The bottom 3 rows of Table 2 show that the two unique 

samples have identical net employment growth rates of 0.6 percent, but the sample of 

establishments with transitory and reverting changes in size class have gross job gains and 

gross job loss rates that are more than three times higher than the sample of establishments 

without transitory and reverting changes in employment. This relatively large amount of 

gross job gains and gross job losses in the businesses with transitory and reverting changes in 

size class suggests a strong potential for the quarterly base-sizing methodology to 

systematically allocate growth and decline to different size class categories. 

 The observed transitory and reverting changes in size class can occur many ways. 

Over three-quarters of these 1.028 million establishments are in the same size class in both 

1999:Q1 and 2000:Q1, yet were in a different size class at some point during the second, 

third, and/or fourth quarters of the year. The other 22 percent of establishments with a 

transitory and reverting change in size class during the year were either annual expansions or 

annual contractions, and crossed a given size class boundary twice during the year.17 For the 

1.028 million establishments that have a transitory and reverting change in size class during 

the year, Table 3 lists the 15 most frequent temporal patterns describing which size class they 

are in during the five quarters 1999:Q1 through 2000:Q1. The most frequent pattern, 

experienced by 37,570 establishments, is starting in size class “1-4” during 1999:Q1, 

expanding into size class “5-9” during the second quarter of 1999, and then declining back 

into size class “1-4” and remaining there for the following three quarters 1999:Q3 – 2000:Q1. 

 For establishments that cross a size class boundary twice during the year, the data in 

Table 3 show that the 11 most frequent patterns are establishments that are in the same size 

class for four of five quarters, and being in an adjacent size class for only one quarter. This is 

not suggestive of seasonality, since one would expect a seasonal firm to have increased 

employment for several quarters during the year. The 14th row of Table 3 shows that 16,476 

establishments are in size class “1-4” during the first quarter of both 1999 and 2000, and are 

in size class “5-9” during the other three quarters of the year. These are likely to be seasonal 

firms, such as small landscaping companies that have more employment in the warmer 

quarters of the year than in the colder quarters of the year. One additional observation about 

Table 3 is that most frequent temporal patterns involve the smallest two size classes (1-4 and 

5-9), which suggests that the largest effects of transitory and reverting changes in size class 

should be observed for the smallest size classes. 

 The data in Chart 3a show the average 1999:Q1 – 2000:Q1 quarterly net employment 

growth rate, by size class, for the two unique samples in Table 2 computed under two 

different classification methodologies –quarterly base-sizing and mean-sizing. Several 

conclusions from Chart 3a warrant mention. The two alternative methodologies result in 

relatively similar net employment growth rates for the sample of 4.3 million establishments 

without transitory and reverting changes in employment. However, as expected, the size 

classification methodology does have a large effect on the net employment growth rates for 
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the sample of 1.028 million establishments that cross a given size class boundary twice during 

the year. The statistics computed with the quarterly base-sizing methodology show that the 

smallest establishments in size class “1-4” have a net employment growth rate of 76 percent, 

and the largest establishments in size class “1000+” have a net employment growth rate of 

negative 47 percent. This is in contrast to the statistics for the same sample computed with a 

mean-sizing methodology, which shows net employment growth rates for all size classes 

between zero and two percent. 

 In Chart 3b, we show the average quarterly net employment growth rates, by size 

class, for the entire universe of the 5.3 million continuous establishments as computed under 

the two alternative methodologies. The quarterly base-sizing methodology shows a net 

employment growth rate that is essentially monotonically declining with size class: the 

smallest establishments in size class “1-4” have a net growth rate of 19.5 percent, whereas the 

largest establishments in size class “1000+” have a net growth rate of –1.7 percent. In 

contrast, the mean-sizing methodology shows a growth rate between 0.3 and 1.5 percent for 

all size classes. These statistics in Chart 3b are similar to the statistics in Table 1 of Cordelia 

Okolie’s July 2004 Monthly Labor Review article. 

 In summary, there are three primary findings to be drawn from the empirical analysis 

in this section. First, 19 percent of continuous establishments in the BED quarterly microdata 

exhibit transitory and reverting changes across size class during a one year period. Second, 

the net employment growth rates for this sample of establishments are extremely different 

when computed under alternative methodologies. The quarterly base-sizing methodology 

results in statistics that show the smaller establishments creating jobs and the larger 

establishments losing jobs, whereas the mean-sizing methodology shows essentially no 

differences in the net employment growth rate across size classes. And third, the net 

employment growth rates for the sample of establishments without transitory and reverting 

changes in size class exhibit relatively little difference when computed under alternative 

methodologies. What is the interpretation of these findings? Many authors (see the 

references at the beginning of this section) have speculated that transitory and reverting 

changes in size class are the underlying cause of why different methodologies result in 

different net employment growth statistics. Our analysis confirms and quantifies this using 

the BED microdata. This result will play a large role in the evaluation of different 

methodologies for the official BED size classification methodology. 

5) Evaluation Criteria and Analysis 

 We now turn to a discussion of the evaluation criteria that the BLS considered for 

choosing an official methodology from the four possible size classification methodologies – 

quarterly base-sizing, annual base-sizing, mean-sizing, and dynamic-sizing. The empirical 

analysis of the effects of transitory and reverting changes in size class in the previous section 

points to symmetry as being a critical criterion for the evaluation. The other criteria used for 

the evaluation are [a] how births are treated by the alternative methodologies, [b] consistency 

with other BLS classification methods, [c] whether the statistics exhibit additivity across 
 10

quarters, and [d] whether the methodology is comprehensible to users of the Business 

Employment Dynamics data. 

Symmetry 

 For firms that cross a size class boundary twice within a given period of time, the 

quarterly base-sizing methodology will attribute the firm’s growth to the smaller size class 

below the boundary, and will attribute the firm’s job loss to the higher size class above the 

boundary. The analysis in the previous section showed substantial effects resulting from 

these transitory and reverting changes in size class. Furthermore, looking at Chart 3b, the 

statistics computed under the quarterly base-sizing methodology indicate that continuous 

establishments with 50 or more employees did not contribute any net employment growth to 

the economy during the 1999:Q1 – 2000:Q1 time period. Although there is no “truth” upon 

which to evaluate this, we find it implausible that mid-sized and large-sized employers did not 

create (on average) any net new jobs in a high-growth year when the sample of continuous 

businesses created over 2.3 million jobs. 

 The BLS has decided that the non-symmetrical effects resulting from transitory and 

reverting employment changes across size class boundaries need to be factored out of the 

Business Employment Dynamics data by employer size class. As such, quarterly base-sizing 

will not be selected as the official methodology for the Business Employment Dynamics data 

by employer size. The annual base-sizing, mean-sizing, and dynamic-sizing methodologies 

all impose symmetry on the net employment growth statistics for firms with transitory and 

reverting changes in employment across size class boundaries.18

Treatment of Births 

 The alternative methodologies differ in how they treat business births. The quarterly 

and annual base-sizing methodologies both classify firms based upon their size in some 

previous quarter, but the fact that births do not exist in previous quarters presents a challenge. 

Two approaches can be used to overcome this problem: a “zero size class” category can be 

defined for births to reflect their non-existence in the previous quarter, or the employment of 

births can be measured in the current quarter when the births first appear with positive 

employment. We have found the first option to be intractable – in any given quarter, opening 

establishments create over one and one-half million new jobs, which is higher than the total 

net employment growth for any quarter. The second option (defining the size class of births 

based upon their current quarter employment) can be justified as the best measure of the 

intended size of a birth, but this results in births being treated differently than all other firms 

in both the quarterly and the annual base-sizing methodologies. 

 Unlike the quarterly and the annual base-sizing methodologies, mean-sizing treats 

births in the same manner as it treats continuous units for the purpose of assigning firms to 

size classes. Under mean-sizing, a firm is defined to a size class based upon the average 

employment in the current and the previous quarter. For births, the employment in the 

previous quarter is zero, and for deaths, the employment in the current quarter is zero. Thus 

the size class of births is based upon one-half their employment in the current quarter, and the 
 11

size class of deaths is based upon one-half of their previous quarter employment. This meansizing approach for classifying business births and deaths is not intuitively obvious. 

 The dynamic-sizing methodology appears to handle births and deaths the best. By 

definition, the movement from 0 to 1 employees and the movement from 1 to 0 employees are 

both credited to the “1-4” size class. Any birth with 4 or fewer employees in its first quarter 

of existence will have all employment growth attributed to the “1-4” size class, and any death 

with 4 or fewer employees in its last quarter will have all employment loss attributed to the 

“1-4” size class. A birth or death involving 5 or more employees would have 4 jobs gained or 

lost credited to the “1-4” size class, and the remaining jobs gained or lost would be credited to 

the “5-9” and higher size classes, as appropriate. 

Consistency with Other BLS Classification Methods 

 In the Quarterly Census of Employment and Wages (QCEW) program, which is the 

source data for the Business Employment Dynamics statistics, a distinction is made between 

economic code changes and non-economic code changes. An economic code change occurs 

when an establishment actually changes its location, industrial activities, and/or sector (e.g., 

federal, state, local government or private sector) and that change can be identified in a timely 

manner and can be reflected in the reference period of the data when it occurred. Noneconomic code changes are much more frequent than economic code changes. Non-economic 

code changes occur when the establishment’s industrial activity, location, or sector was coded 

in error, changed gradually from one primary location or activity to another, reflect a 

structural change to the codes (e.g., a change from the 2002 NAICS to the 2007 NAICS 

codes), or changed but the reference period of the change can not be determined. Economic 

code changes are introduced immediately, whereas non-economic code changes are held until 

the following first quarter, at which time all changes in classification codes collected through 

the year are implemented. This methodology is optimal for analyzing the time series of 

employment changes within industries or geographies within a year’s data. 

 The annual base-sizing methodology proposed for the BED size class statistics is 

modeled on this statistical methodology that BLS uses for industry and geography 

classifications. That is, just as changes in industry and geography codes are often held 

constant through the year, the size class of a firm should also be held constant through the 

year. However, analyzing employment changes based upon industry or geography is 

conceptually different than analyzing employment changes based upon firm size, in that the 

variable of interest (employment change) is directly related to the classification variable 

(employer size). Whether or not holding the size classification of a firm fixed throughout the 

year is desirable for a continuous quarterly measurement process for the Business 

Employment Dynamics size class data requires a subjective weighting of the strengths and 

weaknesses inherent in this approach. 

Additivity across quarters 

 One criterion that has been proposed for evaluating the various size classification 

methodologies is the additivity of size class statistics across quarters. Specifically, do the 
 12

quarterly net employment growth statistics by size class add up across quarters to the same net 

employment growth statistics by size class that would be computed from a longer 

measurement frequency such as an annual March to March change?19 If the employment 

changes occur within the year, rather than spanning a March when the firm’s size class is 

redefined, the annual base-sizing methodology satisfies the additivity criterion. For example, 

if a firm grows from 3 to 9 between March and June, grows from 9 to 13 between June and 

September, and then stays at 13 for the following several quarters, the annual base-sizing 

methodology would put the 6-job gain from 3 to 9 in the “1-4” size class, and would put the 

4-job gain from 9 to 13 in the “1-4” size class. These quarterly changes sum to the annual 

March to March change of 10 employees credited to the “1-4” size class. 

 Quarterly base-sizing and mean-sizing do not satisfy the additivity criterion between 

quarterly and annual measurements. In the example of the previous paragraph, quarterly 

base-sizing would put the 6 employee gain from 3 to 9 in the “1-4” size class, would put the 4 

employee gain from 9 to 13 in the “5-9” size class, but would put the 10 employee annual 

gain in the “1-4” size class. Mean sizing would put the 6 employee gain from 3 to 9 in the “5-

9” size class, would put the 4 employee gain from 9 to 13 in the “10-19” size class, but would 

put the 10 employee annual gain from 3 to 13 in the “5-9” size class. 

 Dynamic sizing satisfies the additivity criteria. In the specific example, the quarterly 

gain of 6 employees from 3 to 9 would be classified as 1 job gained in the “1-4” size class and 

5 jobs gained in the “5-9” size class, and the quarterly gain of 4 employees from 9 to 13 

would be classified as 4 jobs gained in the “10-19” size class. The annual gain from 3 to 13 

would result in the exact same statistics: 1 job gained in the “1-4” size class, 5 jobs gained in 

the “5-9” size class, and 4 jobs gained in the “10-19” size class. 

Comprehensibility 

 Our final and admittedly subjective evaluation criterion is that of comprehensibility. 

Users of the Business Employment Dynamics data by employer size must be able to 

understand the underlying size classification methodology in order to properly interpret the 

resulting statistics. 

 Perhaps the most intuitive classification methodology for an analysis of job growth by 

size class is quarterly base-sizing, which answers the question “where does quarterly job 

growth originate?” The quarterly base-sizing methodology falls naturally out of a transition 

matrix which relates how firms move from one size class to another, and quarterly base-sizing 

has parallels to the way most people calculate percentages. However, due to its problems 

with transitory and reverting changes across size classes, the quarterly base-sizing method 

was dismissed above when discussing symmetry. 

 The annual base-sizing methodology has some issues associated with regard to its 

comprehensibility. When measuring employment growth between the first and second 

quarters in relation to the firm’s size class in the first quarter, the annual base-sizing statistics 

answer the intuitive question of where does quarterly growth originate. However, the annual 

base-sizing methodology measures the second to third quarter employment growth by a firm’s 
 13

size class in the first quarter, which unfortunately does not provide a simple answer to the 

question of where quarterly growth originates in the second quarter. The annual base-sizing 

methodology is the correct methodology for a cohort analysis – following a well defined set 

of firms across multiple quarters, but does not provide a continuous methodology for 

measuring quarterly employment growth by size class. 

 Our discussions with users and with our advisory groups, as well as our reading of the 

literature, has resulted in a multitude of reactions regarding the comprehensibility of the 

mean-sizing methodology. The negative reaction is focused on three premises: firms with 

large employment changes may be assigned to a size class that is different from the size class 

defined by either of the quarterly cross-sectional measures of employment, classifying firms 

into a size class based upon an average is conceptually much different that classifying firms 

into industries or geographies, and similar employment changes can be treated differently (for 

example, an expansion from 1 to 7 employees would classify 6 jobs gained in the “1-4” size 

category, whereas an expansion from 1 to 8 employees would classify 7 jobs gained in the “5-

9” size category). These criticisms are said to result in the mean-sizing statistics being 

difficult to interpret. On the other hand, advocates of the mean-sizing approach recommend it 

as a statistical correction for regression to the mean effects. When pressed further, advocates 

of mean-sizing cite the economic rationale of mean-sizing being the best available measure of 

the long-run size of the firm. In any quarter, some firms are expanding and some are 

contracting, and some of these employment changes are temporary and some are movements 

along a long run path of growth or decline. In the absence of more information such as 

previous and future employment levels, the average of the employment levels from the two 

quarters is the best statistical measure of the firm’s long run employment when only two 

measures of quarterly employment are available. After extensive discussion with users and 

amongst ourselves, we have come to the conclusion that mean-sizing would be an acceptable 

but certainly not a unanimous first choice of methodologies. 

 Does dynamic sizing satisfy the comprehensibility criterion? Dynamic-sizing is a new 

size classification methodology and as yet has not been implemented by other national 

statistical agencies, nor has it been seriously discussed by either statisticians or economists.20 

The methodology of dynamic sizing is premised on an underlying model of point-in-time 

measurement of size class change from a continuously linear growth process, and has a 

straightforward measurement methodology along with desirable statistical and economic 

properties. Because it is a new methodology, the BLS will engage in user education and 

outreach activities about the dynamic sizing methodology, of which this article is a start. 

Summary of the Evaluation 

 As discussed in the analysis above, annual base sizing measures where growth 

originates in a fixed cohort type analysis, whereas dynamic sizing provides a more current 

evolving picture of size class growth on a continuous basis. The BLS has concluded that 

dynamic-sizing is an economically and statistically preferred methodology for continuous 

quarterly measures of employment growth by employer size. 
 14

6) Net Employment Change Statistics by Size Class 

 Dynamic-sizing emerged from our evaluation as the preferred methodology for the 

Business Employment Dynamics tabulations by firm size. We now turn to the size class 

statistics from this methodology. We also present, for comparison purposes, the seasonally 

adjusted time series of size class statistics from the other three methodologies discussed and 

evaluated in this article. 

The Business Employment Dynamics Data 

 The quarterly BLS Business Employment Dynamics data series is constructed from 

microdata originating from the Quarterly Census of Employment and Wages (QCEW), also 

known as the ES-202 program. All employers subject to state Unemployment Insurance (UI) 

laws are required to submit quarterly contribution reports detailing their monthly employment 

and quarterly wages to the State Employment Security Agencies. The BLS also directs the 

States to conduct two supplemental surveys that are necessary to yield accurate industry and 

geographical data. The first is the Annual Refiling Survey (ARS), where nearly two million 

businesses each year are contacted to obtain or update business name, addresses, industry 

codes, and related contact information. The second is the Multiple Worksite Report (MWR), 

which collects employment and wages for each establishment in multi-unit firms within the 

State. 

 After the microdata are augmented and thoroughly edited by the State Labor Market 

Information staff, the States submit these data and other business identification information to 

the Bureau of Labor Statistics as part of the federal-state cooperative QCEW program. The 

data gathered in the QCEW program are a comprehensive and accurate source of employment 

and wages, and provide a virtual census (98%) of employees on nonfarm payrolls. In the 

fourth quarter of 2004, the QCEW statistics show an employment level of 131.6 million, with 

8.5 million establishments in the U.S. economy. 

 The Business Employment Dynamics statistics are tabulated by linking establishments 

across quarters. The accuracy of the Business Employment Dynamics statistics depends on 

two primary factors: the quality of the establishment level microdata being reported by 

businesses to the States, and the record linkage methodology used by the BLS to link 

establishments and firms across quarters. The basic products from the BLS Business 

Employment Dynamics program are statistics measuring quarterly net employment change, 

gross job gains, and gross job losses. The time series of historical statistics starts in the third 

quarter of 1992. The April 2004 issue of the Monthly Labor Review contains a thorough 

description of the BED program.21

Net Employment Growth 

 Tables 4a-4d present the 1993:Q2 through 2003:Q4 seasonally adjusted time series of 

net employment growth statistics by firm size, calculated under the four possible size 

classification methodologies: quarterly base-sizing, annual base-sizing, mean-sizing, and 

dynamic-sizing. Before discussing the tables, several points need to be mentioned. First, 
 15

within each table, each separate size class series was seasonally adjusted, and the seasonally 

adjusted size class series were then added to create the seasonally adjusted total series. This 

standard seasonal adjustment procedure will lead to the total net employment change series 

varying across the four tables. Second, these data are calculated on a firm-level basis. With 

the exception of Cordelia Okolie’s July 2004 Monthly Labor Review article, these are the first 

firm-level tabulations to be published from the Business Employment Dynamics program. 

And third, the data in these tables were produced on a research basis, and these data may 

differ from the published size class data from the BED program for several reasons – the main 

reason being that the published data include more quarters and thus the seasonal adjustment 

factors will be different for the research and the published series.

22

 One striking conclusion evident in Tables 4a-4d is how the contributions of the 

various size classes to net employment growth varies across the methodologies. This is most 

evident in the smallest and largest size classes (which is not surprising given the analysis 

reported earlier in this paper). The quarterly base-sizing methodology shows that firms in the 

“1-4” size class grew by 499 thousand jobs in the average quarter between 1993:Q2 and 

2003:Q4 (see the penultimate row in Table 4a). The annual base-sizing methodology shows 

that firms in the “1-4” size class grew by 263 thousand jobs in the average quarter, whereas 

the corresponding statistic for the dynamic-sizing methodology is a substantially smaller 38 

thousand jobs in the average quarter. Thus methodology matters. The BED data indicate that 

the firms in size class “1-4” account for 10 percent, 67 percent, or 127 percent of average 

quarterly net employment growth, depending upon methodology. Similarly, firms in the 

largest size class of “1000+” account for between negative 20 percent and positive 30 percent 

of average quarterly net employment growth, depending upon the methodology used to 

classify firms into size classes. 

 The major differences in the data resulting from the alternative methodologies are seen 

in the “1-4” size class and the “1000+” size class. To visually see this, we graph these data 

series in Charts 4a-4d (putting all nine size classes in the charts would result in too much 

clutter). These charts show the substantial variation in the average level of net employment 

growth in the “1-4” size class (499 thousand in Chart 4a, 38 thousand in Chart 4d). 

6) Conclusions 

 This article has described the size class statistics in the BLS Business Employment 

Dynamics program. Four alternative size classification methodologies were evaluated on 

multiple criteria, and dynamic-sizing was chosen as the best methodology for continuous 

quarterly measurement of employment growth by employer size. The size class statistics 

presented in this article greatly expand the value of the BED program, and we expect the BED 

size class statistics to receive a lot of attention from the user community. We conclude by 

noting that the analysis and the statistics presented in this article are the first step of a longer 

research agenda into documenting and understanding the employment dynamics of U.S. 

businesses. There is discussion in both the academic and the policy communities that size 

class statistics may be proxying for age: young businesses are often small businesses, and 

large businesses are often older mature businesses. The BLS is creating a measure of age for 
 16

all firms in the BED program (not a trivial task), and we hope to present research in the near 

future that not only documents the relationship of firm size and firm age, but also analyzes 

their contributions to employment growth. 
 17

Endnotes 

 

1

 Cordelia Okolie, “Why size class methodology matters in analyses of net and gross job flows,” Monthly Labor 

Review, July 2004, pp. 3-12. 

2

 Table A12 of the monthly Employment Situation press release is titled “Alternative measures of labor 

underutilization” and lists the six unemployment rates. For more information, see John E. Bregger and Steven E. 

Haugen, “BLS introduces new range of alternative unemployment measures,” Monthly Labor Review, October 

1995, pp, 19-26. 

3

 These data refer to the first quarter of 2004, and were downloaded from the BLS Quarterly Census of 

Employment and Wages (QCEW) website https://www.bls.gov/cew/ (accessed June 2005). 

4

 These data refer to the first quarter of 2004, and were downloaded from the BLS Quarterly Census of 

Employment and Wages (QCEW) website https://www.bls.gov/cew/ (accessed June 2005). 

5

 A comprehensive survey article is Walter Oi and Todd Idson, “Firm Size and Wages,” Handbook of Labor 

Economics, 1999, edited by Orley Ashenfelter and David Card, North-Holland Press, pp. 2165-2214. 

6

 See Charles Brown and James Medoff, “The Employer Size-Wage Effect,” Journal of Political Economy, 

1989, pp. 1027-1059. 

7

 See Kenneth R. Troske, “Evidence on the Employer Size-Wage Premium from Worker-Establishment 

Matched Data,” Review of Economics and Statistics, 1999, pp. 15-26. 

8

 For example, in the October 2004 Vice-Presidential debate, Mr. Cheney said “ ... seven out of 10 new jobs in 

America are created by small businesses.” The Small Business Administration’s website “Small Business by the 

Numbers, Answers to Frequently Asked Questions” (http://www.sba.gov/advo/stats/sbfaq.html) states “In 1999-

2000 (according to the most recent data), small businesses created three-quarters of U.S. net new jobs (2.5 

million of the 3.4 million total). The small business share varies from year to year and reflects economic trends. 

Over the decade of the 1990s, small business net job creation fluctuated between 60 and 80 percent.” 

9

 Steven J. Davis, John C. Haltiwanger, and Scott Schuh “Job Creation and Destruction,” MIT Press, 1996. 

Cordelia Okolie, “Why size class methodology matters in analyses of net and gross job flows,” Monthly Labor 

Review, July 2004, pp. 3-12. 

10 At some point in the near future, the BLS hopes to produce BED size-class statistics at the establishment level 

and release these for research purposes. 

11 Defining a size class for the employment change that crosses a size class threshold requires some discussion. 

For example, should the growth of 1 employee from 4 to 5 that moves the firm from the “1-4” size class to the 

“5-9” size class be credited to the “1-4” or the “5-9” size class? The dynamic sizing methodology classifies a 

firm that moves from 4 to 5 employees in the “5-9” size class. This is done for two reasons. First, we want 

employment change to be symmetrical – the loss of 1 job from 5 to 4 should be credited to the same size class as 

the gain of 1 job from 4 to 5. Second, because there is no “zero” size class, the first job credited to a birth needs 

to be attributed to the “1-4” size class, which would be symmetrical to the last job lost credited to a death being 

attributed to the “1-4” size class. Thus when a firm moves from one size class to another by either expanding or 

contracting, dynamic sizing credits the single job that moves the firm across the threshold to the higher of the 

two size classes. 

12 See Per Davidsson, “Methodological Concerns in the Estimation of Job Creation in Different Firm Size 

Classes” 1996 Working Paper, Jönköping International Business School; accessed June 2005 from 

http://www.ihh.hj.se/eng/research/publications/wp/1996-1%20Davidsson.pdf. Also see Per Davidsson, Leif 
 18

 

Lindmark, and Christer Olofsson, “The Extent of Overestimation of Small Firm Job Creation – An Empirical 

Examination of the Regression Bias,” Small Business Economics, 1998, pp. 87-100. 

13 It is possible to construct an example where annual base-sizing would result in non-symmetrical statistics. If 

employment in March 2003 is 3, and the December 2003 to March 2004 employment growth is from 3 to 13, 

followed by a March 2004 to June 2004 employment decline from 13 to 3, the annual base-sizing estimator 

would put the employment growth of 10 into the “1-4” size class but would put the following employment 

decline of 10 into the “10-19” size class. 

14 References to regression to the mean bias include Davis, Haltiwanger, and Schuh’s 1996 book, Per 

Davidsson’s two research articles, and Milton Friedman (1992), “Do Old Fallacies Ever Die?” Journal of 

Economic Literature, Vol. 30, Issue 4, pp. 2129-2132. 

15 We have also removed a very small number of businesses involved in breakouts or consolidations at any point 

during the year. This is done because it is difficult to follow the employment patterns of businesses with 

changes in reporting configurations across five consecutive quarters. Also note that this is the only section of 

this article where we present new results using establishments rather than firms; we do not believe the results 

will change if firms rather than establishments were the unit of analysis. 

16 The full sample of BED microdata for the 1999:Q1 to 2000:Q1 period, with births, deaths, and businesses 

involved in breakouts or consolidations, has an average quarterly employment of 107,578,247 jobs. Thus our 

sample has 93.5 percent of all employment. 

17 The most frequent example of this is the 8,096 establishments that start in size class “1-4” in 1999:Q1, are in 

size class “5-9” in 1999:Q2, are back in size class “1-4” in 1999:Q3, and then expand into size class “5-9” in 

1999:Q4 and 2000:Q1. 

18 To be precise, annual base-sizing imposes symmetry only on changes within the year, but does not impose 

symmetry on transitory and reverting changes that happen before and after March. 

19 The BED net and gross job flow statistics are unique in that they measure quarterly employment change, 

whereas almost all other similar statistics in the U.S. (and elsewhere in the world) measure employment change 

on an annual March to March frequency. For a further discussion of the difference between quarterly and annual 

net and gross job flow statistics, see Joshua C. Pinkston and James R. Spletzer, “Annual measures of gross job 

gains and gross job losses,” Monthly Labor Review, November 2004, pp. 3-13. 

20 Our review of the literature, and our email conversations with Per Davidsson, have not found any references 

beyond the two articles by Professor Davidsson cited earlier. 

21 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. 

22 One other point warrants mention. The BLS is not planning on publishing firm counts for the dynamic sizing 

statistics. Firm counts are trivial to calculate for tables of employment change by industry and by geography. 

Firm counts are also trivial to calculate for tables of employment change by size class, when size class is defined 

by the mean-sizing or either of the base-sizing methodologies. However, it is difficult to calculate firm counts 

when using the dynamic-sizing methodology. Recall the example of a firm expanding from 3 to 13 employees, 

where size class “1-4” is credited with the growth of 1 employee, size class “5-9” is credited with the growth of 

5 employees, and size class “10-19” is credited with the growth of 4 employees. In this example, which size 

class would this expanding firm get placed? This is a question being researched. 
Table 1: Number of Establishments and Employment, by Size Class 

 2004 1st Quarter QCEW data 

Size Class 

Number of 

Estabs Employment 

Number of 

Estabs Employment 

Cumulative 

Number of 

Estabs 

Cumulative 

Employment 

<5 4,768,812 7,095,128 60.1% 6.7% 60.1% 6.7% 

5-9 1,331,834 8,810,097 16.8% 8.3% 76.9% 15.1% 

10-19 872,241 11,763,253 11.0% 11.1% 87.9% 26.2% 

20-49 597,662 18,025,655 7.5% 17.1% 95.4% 43.3% 

50-99 203,030 13,970,194 2.6% 13.2% 98.0% 56.5% 

100-249 115,598 17,299,058 1.5% 16.4% 99.4% 72.9% 

250-499 28,856 9,864,934 0.4% 9.3% 99.8% 82.2% 

500-999 10,454 7,090,739 0.1% 6.7% 99.9% 89.0% 

>=1000 5,487 11,664,490 0.1% 11.0% 100.0% 100.0% 

Total 7,933,974 105,583,548 

Chart 1: Average Weekly Wage by Establishment Size 

 2004 1st Quarter QCEW data 

0

300

600

900

1,200

<5

5-9

10-1920-4950-99

100-249250-499500-999

>=1000
 

Chart 2: Example of Net Employment Growth by Size Class 

 Four Different Classification Methodologies 

Quarterly Base-Sizing

-12

-6

0

6

12

1-4 5-9 10-19

Expansion 3 to 13 Contraction 13 to 3

Annual Base-Sizing (March Emp=3)

-12

-6

0

6

12

1-4 5-9 10-19

Expansion 3 to 13 Contraction 13 to 3

Mean-Sizing

-12

-6

0

6

12

1-4 5-9 10-19

Expansion 3 to 13 Contraction 13 to 3

Annual Base-Sizing (March Emp=8)

-12

-6

0

6

12

1-4 5-9 10-19

Expansion 3 to 13 Contraction 13 to 3

Dynamic-Sizing

-12

-6

0

6

12

1-4 5-9 10-19

Expansion 3 to 13 Contraction 13 to 3

Annual Base-Sizing (March Emp=13)

-12

-6

0

6

12

1-4 5-9 10-19

Expansion 3 to 13 Contraction 13 to 3
 

Table 2: Transitory and Reverting Changes in Size Class 

 1999:Q1 – 2000:Q1 Quarterly BED Microdata, Continuous Establishments 

 

All Establishments 

Establishments 

without a transitory 

and reverting 

change in size class 

Establishments 

with a transitory 

and reverting 

change in size class 

Number of 

Establishments 

5,324,506 4,296,241 

(80.6%) 

1,028,265 

(19.3%) 

Average Quarterly 

Employment 

100,633,651 84,582,061 

(84.0%) 

16,051,590 

(15.9%) 

Average Quarterly 

Emp. Change 

577,869 489,992 

(84.7%) 

87,877 

(15.2%) 

Average Quarterly 

Gross Job Gains 

6,612,451 4,095,154 

(61.9%) 

2,517,297 

(38.0%) 

Average Quarterly 

Gross Job Losses 

6,034,582 3,605,162 

(59.7%) 

2,429,420 

(40.2%) 

Average Quarterly 

Emp. Change 

0.6% 0.6% 0.6% 

Average Quarterly 

Gross Job Gains 

6.6% 4.8% 15.6% 

Average Quarterly 

Gross Job Losses 

6.0% 4.3% 15.0% 
 

Table 3: Establishments with a Transitory and Reverting Change in Size Class 

 1999:Q1 – 2000:Q1 Quarterly BED Microdata, Continuous Establishments 

Size Class in: 

1999 Q1 1999 Q2 1999 Q3 1999 Q4 2000 Q1 Frequency Percent 

1-4 5-9 1-4 1-4 1-4 37,570 3.7% 

1-4 1-4 0 1-4 1-4 36,666 3.6% 

1-4 1-4 1-4 0 1-4 36,145 3.5% 

1-4 0 1-4 1-4 1-4 35,307 3.4% 

1-4 1-4 1-4 5-9 1-4 34,698 3.4% 

1-4 1-4 5-9 1-4 1-4 28,049 2.7% 

5-9 5-9 5-9 10-19 5-9 25,970 2.5% 

5-9 10-19 5-9 5-9 5-9 23,210 2.3% 

5-9 5-9 1-4 5-9 5-9 20,536 2.0% 

5-9 5-9 5-9 1-4 5-9 20,508 2.0% 

5-9 1-4 5-9 5-9 5-9 20,387 2.0% 

1-4 5-9 5-9 1-4 1-4 19,589 1.9% 

5-9 5-9 10-19 5-9 5-9 17,651 1.7% 

1-4 5-9 5-9 5-9 1-4 16,476 1.6% 

1-4 1-4 5-9 5-9 1-4 14,469 1.4% 

Other 641,034 62.3% 

Total 1,028,265 100.0% 
 

Chart 3a: The Effects of Transitory and Reverting Changes in Size Class 

 1999:Q1 – 2000:Q1 Quarterly BED Microdata, Continuous Establishments 

-50.0%

-25.0%

0.0%

25.0%

50.0%

75.0%

 1- 4 5- 9 10- 19 20- 49 50- 99 100-249 250-499 500-999 1000+ 

Quarterly Base-Sizing, Establishments with Transitory and Reverting Employment Change

Mean-Sizing, Establishments with Transitory and Reverting Employment Change

Quarterly Base-Sizing, Establishments without Transitory and Reverting Employment Change

Mean-Sizing, Establishments without Transitory and Reverting Employment Change

Chart 3b: The Effects of Transitory and Reverting Changes in Size Class 

 1999:Q1 – 2000:Q1 Quarterly BED Microdata, Continuous Establishments 

-5.0%

0.0%

5.0%

10.0%

15.0%

20.0%

 1- 4 5- 9 10- 19 20- 49 50- 99 100-249 250-499 500-999 1000+ 

Quarterly Base-Sizing, All Establishments Mean-Sizing, All Establishments
 

Table 4a: Quarterly Net Employment Growth by Firm Size, 1993:Q2 – 2003:Q4 

 Quarterly base-sizing Methodology, Seasonally Adjusted (in Thousands) 

total 1-4 5-9 10-19 20-49 50-99 

100-

249 

250-

499 

500-

999 1000+ 

1993 Q2 786 516 124 52 31 7 -18 -19 18 75 

1993 Q3 896 538 156 93 74 27 17 2 -10 -1 

1993 Q4 665 501 128 65 43 6 0 -14 -12 -52 

1994 Q1 409 439 92 35 9 -12 -9 -3 -7 -135 

1994 Q2 1034 527 131 54 41 21 19 9 5 227 

1994 Q3 1207 546 180 116 114 66 49 2 2 132 

1994 Q4 531 461 92 51 2 -14 -6 -19 6 -42 

1995 Q1 648 481 120 69 31 32 5 -24 -30 -36 

1995 Q2 426 486 104 28 -28 -27 -40 -65 -1 -31 

1995 Q3 820 495 121 56 32 8 6 -17 0 119 

1995 Q4 407 494 114 33 7 -17 -44 -34 -15 -131 

1996 Q1 445 515 112 42 17 -15 -47 -41 -33 -105 

1996 Q2 674 507 116 39 -26 -36 -51 6 -8 127 

1996 Q3 634 517 129 52 20 -19 11 -16 -15 -45 

1996 Q4 858 504 123 57 21 17 15 -4 33 92 

1997 Q1 785 502 142 80 52 2 -4 -18 -35 64 

1997 Q2 643 489 104 36 -19 -25 -3 -1 -21 83 

1997 Q3 873 515 114 63 30 13 25 -12 7 118 

1997 Q4 644 506 105 42 7 -14 -30 -11 -11 50 

1998 Q1 837 532 111 62 2 -25 -21 -10 26 160 

1998 Q2 670 550 133 90 33 -17 -32 -12 -71 -4 

1998 Q3 684 488 84 25 -26 -15 -26 -10 -12 176 

1998 Q4 694 495 107 58 28 23 -3 -10 -13 9 

1999 Q1 466 540 117 49 -17 -25 -64 -53 -44 -37 

1999 Q2 564 486 85 35 5 -20 5 -23 -26 17 

1999 Q3 562 533 110 49 -6 -25 -36 -30 -23 -10 

1999 Q4 1042 575 165 101 76 33 35 5 -6 58 

2000 Q1 802 519 134 71 26 13 22 -6 -1 24 

2000 Q2 524 506 84 21 -8 -35 -22 -42 -34 54 

2000 Q3 143 512 68 -2 -33 -57 -59 -55 -49 -182 

2000 Q4 313 510 76 6 -43 -61 -69 -41 -68 3 

2001 Q1 -32 494 87 18 -49 -86 -124 -117 -109 -146 

2001 Q2 -803 464 73 -19 -112 -128 -196 -161 -161 -563 

2001 Q3 -1450 405 26 -72 -187 -190 -243 -195 -176 -818 

2001 Q4 -907 490 61 -32 -148 -161 -201 -176 -162 -578 

2002 Q1 5 468 105 3 -54 -81 -101 -81 -76 -178 

2002 Q2 -102 471 87 10 -44 -43 -84 -95 -59 -345 

2002 Q3 -211 469 80 -10 -95 -72 -130 -66 -84 -303 

2002 Q4 -172 487 66 -17 -91 -100 -119 -83 -74 -241 

2003 Q1 -423 492 48 -45 -123 -91 -108 -93 -74 -429 

2003 Q2 -169 481 99 5 -39 -46 -104 -74 -93 -398 

2003 Q3 74 456 80 3 -46 -72 -87 -53 -70 -137 

2003 Q4 366 486 86 6 -32 -57 -82 -44 -62 65 

Average 392 499 104 34 -12 -31 -45 -42 -38 -77 

% Total 100% 127% 27% 9% -3% -8% -12% -11% -10% -20% 
 

Table 4b: Quarterly Net Employment Growth by Firm Size, 1993:Q2 – 2003:Q4 

 Annual base-sizing Methodology, Seasonally Adjusted (in Thousands) 

total 1-4 5-9 10-19 20-49 50-99 

100-

249 

250-

499 

500-

999 1000+ 

1993 Q2 704 282 78 73 94 66 44 15 34 18 

1993 Q3 682 293 92 69 82 54 53 32 15 -9 

1993 Q4 720 290 92 80 78 68 63 50 27 -27 

1994 Q1 597 220 50 27 53 32 66 48 44 58 

1994 Q2 1002 299 93 79 119 78 96 51 23 164 

1994 Q3 964 285 108 88 127 93 78 55 39 92 

1994 Q4 602 245 54 57 40 51 69 35 19 31 

1995 Q1 801 252 78 63 71 68 78 42 17 132 

1995 Q2 415 246 64 46 36 35 28 -23 24 -40 

1995 Q3 641 242 63 42 60 36 39 30 29 99 

1995 Q4 449 277 67 38 43 25 40 30 5 -76 

1996 Q1 467 274 61 36 45 36 36 8 22 -51 

1996 Q2 708 278 78 55 46 25 22 56 23 125 

1996 Q3 531 276 71 44 48 29 59 29 9 -35 

1996 Q4 838 278 84 61 83 68 56 20 31 157 

1997 Q1 807 268 86 65 77 56 45 45 8 157 

1997 Q2 636 259 64 44 33 27 64 39 21 85 

1997 Q3 812 276 68 49 65 61 62 41 32 158 

1997 Q4 675 269 56 37 39 22 41 42 34 134 

1998 Q1 695 262 44 25 65 19 53 27 71 131 

1998 Q2 791 323 105 108 102 47 52 29 -20 45 

1998 Q3 690 266 56 30 27 30 31 36 25 188 

1998 Q4 654 263 70 58 82 61 41 31 16 30 

1999 Q1 312 278 73 27 29 6 -8 -19 5 -78 

1999 Q2 689 269 72 51 63 36 83 33 11 72 

1999 Q3 665 287 80 82 57 40 34 17 18 50 

1999 Q4 933 303 94 70 112 83 88 28 25 128 

2000 Q1 767 274 75 66 73 55 42 52 -5 135 

2000 Q2 601 282 59 35 45 17 52 10 1 100 

2000 Q3 315 247 47 14 27 27 34 -14 6 -73 

2000 Q4 221 242 43 23 -6 -9 -13 -26 -34 0 

2001 Q1 -258 238 33 10 -19 -33 -98 -83 -64 -242 

2001 Q2 -660 231 31 -19 -69 -80 -125 -114 -107 -406 

2001 Q3 -1084 193 0 -50 -110 -119 -160 -134 -126 -578 

2001 Q4 -959 247 14 -26 -83 -105 -158 -137 -137 -573 

2002 Q1 -103 238 51 5 -21 -35 -55 -42 -19 -226 

2002 Q2 -59 236 39 9 -8 -14 -26 -46 -35 -214 

2002 Q3 4 260 50 8 -4 -28 -40 -18 -40 -185 

2002 Q4 -237 255 33 -11 -36 -45 -44 -67 -44 -277 

2003 Q1 -449 236 26 -35 -69 -71 -66 -66 -58 -346 

2003 Q2 -173 252 47 -5 -12 -25 -66 -34 -55 -275 

2003 Q3 234 255 51 34 20 -3 -9 -18 -27 -69 

2003 Q4 311 258 56 17 25 4 4 4 -8 -50 

Average 394 263 62 37 36 18 16 2 -3 -36 

% Total 100% 67% 16% 9% 9% 5% 4% 1% -1% -9% 
 

Table 4c: Quarterly Net Employment Growth by Firm Size, 1993:Q2 – 2003:Q4 

 Mean-Sizing Methodology, Seasonally Adjusted (in Thousands) 

total 1-4 5-9 10-19 20-49 50-99 

100-

249 

250-

499 

500-

999 1000+ 

1993 Q2 716 63 57 67 97 64 82 66 66 154 

1993 Q3 880 125 79 85 121 104 106 76 21 163 

1993 Q4 524 46 59 58 105 84 82 43 58 -11 

1994 Q1 624 24 25 45 63 66 79 61 43 218 

1994 Q2 952 66 45 57 117 80 118 94 66 309 

1994 Q3 1164 125 104 121 172 124 120 91 73 234 

1994 Q4 435 6 21 30 64 67 89 54 46 58 

1995 Q1 827 67 48 58 109 87 88 44 62 264 

1995 Q2 385 41 23 31 38 37 54 38 19 104 

1995 Q3 779 38 41 54 103 77 82 67 68 249 

1995 Q4 348 29 27 29 70 49 74 57 9 4 

1996 Q1 526 46 33 44 87 52 60 19 8 177 

1996 Q2 634 57 38 34 37 33 44 68 61 262 

1996 Q3 640 81 49 52 78 60 84 34 61 141 

1996 Q4 800 40 43 59 98 89 106 59 60 246 

1997 Q1 847 84 62 73 123 80 77 56 33 259 

1997 Q2 606 41 26 31 45 45 85 58 40 235 

1997 Q3 852 34 44 45 111 79 115 55 71 298 

1997 Q4 723 17 23 36 63 51 67 74 43 349 

1998 Q1 738 52 24 31 46 50 80 72 102 281 

1998 Q2 687 104 75 66 77 36 68 6 9 246 

1998 Q3 643 26 10 13 41 32 64 44 49 364 

1998 Q4 764 18 36 44 116 70 84 72 26 298 

1999 Q1 332 57 38 30 36 20 21 -5 17 118 

1999 Q2 590 1 19 33 73 47 77 40 36 264 

1999 Q3 558 17 29 35 66 53 61 36 43 218 

1999 Q4 1153 90 83 102 144 91 123 82 53 385 

2000 Q1 774 53 64 67 105 75 114 85 88 123 

2000 Q2 514 31 6 12 37 48 51 37 47 245 

2000 Q3 183 2 9 5 21 22 41 9 37 37 

2000 Q4 427 41 1 6 22 5 34 0 -8 326 

2001 Q1 -236 16 19 17 9 -23 -61 -50 -21 -142 

2001 Q2 -694 10 -11 -31 -65 -64 -90 -98 -90 -255 

2001 Q3 -1283 -63 -55 -64 -127 -116 -163 -104 -148 -443 

2001 Q4 -819 41 -7 -36 -82 -98 -132 -113 -71 -321 

2002 Q1 -74 18 22 12 5 -23 -26 -8 -24 -50 

2002 Q2 -53 35 15 2 21 16 -4 -4 -23 -111 

2002 Q3 -156 39 16 -8 -33 -32 -44 -28 -18 -48 

2002 Q4 -179 46 6 -13 -24 -44 -50 -28 -14 -58 

2003 Q1 -409 -13 -22 -33 -55 -25 -21 -21 -40 -179 

2003 Q2 -136 33 29 20 39 -4 -10 -16 -39 -188 

2003 Q3 92 30 22 18 10 -9 0 -1 2 20 

2003 Q4 314 53 23 31 27 7 -3 1 15 160 

Average 395 41 30 32 51 34 42 26 22 116 

% Total 100% 10% 8% 8% 13% 9% 11% 7% 6% 29% 
 

Table 4d: Quarterly Net Employment Growth by Firm Size, 1993:Q2 – 2003:Q4 

 Dynamic-Sizing Methodology, Seasonally Adjusted (in Thousands) 

total 1-4 5-9 10-19 20-49 50-99 

100-

249 

250-

499 

500-

999 1000+ 

1993 Q2 761 62 56 65 90 64 86 67 68 203 

1993 Q3 942 125 78 91 127 100 115 75 43 188 

1993 Q4 640 44 54 62 101 80 89 56 55 99 

1994 Q1 439 23 20 42 66 58 76 57 47 50 

1994 Q2 1010 61 48 61 106 82 119 96 67 370 

1994 Q3 1249 137 101 122 175 122 135 83 74 300 

1994 Q4 508 -1 16 35 66 71 93 56 53 119 

1995 Q1 677 64 44 62 102 82 87 51 51 134 

1995 Q2 404 43 23 27 36 30 55 33 31 126 

1995 Q3 867 38 40 59 108 81 91 61 77 312 

1995 Q4 383 23 25 30 63 59 77 50 23 33 

1996 Q1 482 41 31 48 77 51 52 22 11 149 

1996 Q2 648 55 35 35 37 30 45 64 50 297 

1996 Q3 685 87 45 55 82 60 88 51 48 169 

1996 Q4 821 34 41 59 96 88 113 64 63 263 

1997 Q1 805 77 60 77 116 77 73 54 24 247 

1997 Q2 616 37 27 31 39 44 83 62 37 256 

1997 Q3 933 35 38 59 109 89 120 60 68 355 

1997 Q4 619 4 20 35 64 59 77 67 54 239 

1998 Q1 864 45 24 36 51 52 78 70 85 423 

1998 Q2 644 114 65 66 72 38 57 20 4 208 

1998 Q3 747 24 11 26 46 47 69 56 51 417 

1998 Q4 672 6 33 53 106 87 93 61 39 194 

1999 Q1 499 48 37 31 31 23 13 1 19 296 

1999 Q2 531 -1 18 37 66 46 76 45 34 210 

1999 Q3 624 14 24 44 71 58 67 48 47 251 

1999 Q4 1017 88 80 102 139 104 124 76 68 236 

2000 Q1 839 52 56 68 97 81 108 87 69 221 

2000 Q2 491 29 5 12 36 37 59 39 44 230 

2000 Q3 207 -1 6 11 23 32 45 22 33 36 

2000 Q4 293 28 0 6 19 14 32 9 1 184 

2001 Q1 -1 7 12 15 -2 -29 -56 -47 -21 120 

2001 Q2 -832 4 -12 -32 -64 -69 -96 -92 -93 -378 

2001 Q3 -1383 -69 -54 -68 -119 -112 -151 -111 -123 -576 

2001 Q4 -957 35 -14 -34 -85 -92 -126 -102 -90 -449 

2002 Q1 39 17 20 12 -5 -22 -29 -14 -19 79 

2002 Q2 -125 38 13 5 9 12 3 -13 -24 -168 

2002 Q3 -159 43 11 -4 -33 -30 -38 -19 -12 -77 

2002 Q4 -215 42 3 -13 -29 -34 -41 -28 -15 -100 

2003 Q1 -384 -16 -24 -33 -59 -30 -30 -25 -25 -142 

2003 Q2 -186 32 28 22 28 -1 -10 -13 -37 -235 

2003 Q3 123 34 22 18 16 3 2 3 3 22 

2003 Q4 340 50 21 28 22 10 7 14 0 188 

Average 399 38 28 34 49 36 45 28 23 119 

% Total 100% 10% 7% 9% 12% 9% 11% 7% 6% 30% 
 

Chart 4a: Quarterly Net Employment Growth by Firm Size, 1993:Q2 – 2003:Q4 

 Quarterly base-sizing Methodology, Seasonally Adjusted (in Thousands) 

-1500

-1000

-500

0

500

1000

1500

1993 Q21994 Q11994 Q41995 Q31996 Q21997 Q11997 Q41998 Q31999 Q22000 Q12000 Q42001 Q32002 Q22003 Q12003 Q4

total 1-4 1000+

Chart 4b: Quarterly Net Employment Growth by Firm Size, 1993:Q2 – 2003:Q4 

 Annual base-sizing Methodology, Seasonally Adjusted (in Thousands) 

-1500

-1000

-500

0

500

1000

1500

1993 Q21994 Q11994 Q41995 Q31996 Q21997 Q11997 Q41998 Q31999 Q22000 Q12000 Q42001 Q32002 Q22003 Q12003 Q4

total 1-4 1000+
 

Chart 4c: Quarterly Net Employment Growth by Firm Size, 1993:Q2 – 2003:Q4 

 Mean-Sizing Methodology, Seasonally Adjusted (in Thousands) 

-1500

-1000

-500

0

500

1000

1500

1993 Q21994 Q11994 Q41995 Q31996 Q21997 Q11997 Q41998 Q31999 Q22000 Q12000 Q42001 Q32002 Q22003 Q12003 Q4

total 1-4 1000+

Chart 4d: Quarterly Net Employment Growth by Firm Size, 1993:Q2 – 2003:Q4 

 Dynamic-Sizing Methodology, Seasonally Adjusted (in Thousands) 

-1500

-1000

-500

0

500

1000

1500

1993 Q21994 Q11994 Q41995 Q31996 Q21997 Q11997 Q41998 Q31999 Q22000 Q12000 Q42001 Q32002 Q22003 Q12003 Q4

total 1-4 1000+