BLS WORKING PAPERS

U.S. DEPARTMENT OF LABOR 

Bureau of Labor Statistics 

OFFICE OF EMPLOYMENT AND UNEMPLOYMENT 

STATISTICS 

 

Gross Job Flows over the Past Two Business Cycles: Not all “Recoveries” are Created 

Equal 

R. Jason Faberman, U.S. Bureau of Labor Statistics 

 Working Paper 372

 June 2004 

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

U.S. Bureau of Labor Statistics. 
Gross Job Flows over the Past Two Business Cycles: 

Not all “Recoveries” are Created Equal 

May 2004 

R. Jason Faberman 

U.S. Bureau of Labor Statistics 

Office of Employment and Unemployment Statistics 

2 Massachusetts Ave NE, Suite 4945 

Washington, DC 20212 

Faberman.Jason@bls.gov

Abstract: 

I compare the behavior of job creation and job destruction over the past two economic downturns. 

Both periods have brief but sharp rises in job destruction followed by flat net job growth. The 

dynamics underlying these slow recoveries differ drastically. In 1991-92, job destruction is slow 

to decline. In 2001, job creation falls dramatically and remains persistently low through 2003. I 

find this trend qualitatively similar in both manufacturing and service industries. I also find that 

neither a structural shift of jobs across industries nor increased trade liberalization is a consistent 

explanation for the recent lack of growth. Instead, the evidence suggests that a large drop in 

business investment may explain the decline in job creation. 

The views expressed are solely those of the author and do not necessarily reflect the official 

positions or policies of the U.S. Bureau of Labor Statistics or the views of other staff members. 
 1

Introduction 

 Although the National Bureau of Economic Research (NBER) identified the last 

recession as ending in November 2001, the private sector has lost an additional 1.1 million jobs 

through June 2003. This job loss occurred despite increases in GDP and labor productivity. 

Weak job growth also followed the business cycle trough of March 1991. At that time, job 

growth did not pick up until the latter part of 1992, just as the longest expansion on record began. 

 In this paper, I compare the patterns of job creation and job destruction underlying the 

last two recessions and their slow employment recoveries. I define job creation as the gross 

number of jobs gained at establishments either opening up or expanding their workforce, and 

similarly define job destruction as the gross number of jobs lost at establishments either closing 

down or contracting their workforce. I use longitudinal data from the Business Employment 

Dynamics (BED) program of the Bureau of Labor Statistics (BLS). The data include all 

employees covered under state unemployment insurance programs. The BLS has these estimates 

publicly available for the private sector for mid-1992 through mid-2003. Data issues, 

unfortunately, make the release of earlier data by the BLS currently infeasible. To counter these 

issues, I manually go through the pre-1992 data and create algorithms to deal with these issues. 

Consequently, I have a time-series of gross job flows that dates back to early 1990 and forward to 

2003, allowing a previously impossible comparison of employment dynamics during the last two 

economic downturns. 

 I find that while the net employment changes over the past two recessions are similar, 

their underlying dynamics are quite different. In 1991, job destruction peaks as the recession 

reaches it height. Job creation changes little during this time. During the stagnant period that 

follows, job creation again changes little, but the pace of job destruction is slow to decline, 

leading to the small observed net gains. In 2001, job destruction again peaks as the recession 

reaches its height. This time, however, there is a dramatic drop in job creation. The pace of job 

creation continues to fall well into the recovery period. Even though job destruction returns to its 
 2

expansion-period pace relatively quickly, net losses in jobs persist because of the exceptionally 

low rate of job creation that continues well into 2003. A comparison of major industry sectors 

shows these trends to be qualitatively similar in both manufacturing and services. 

 In addition, my job flow analysis suggests that structural factors do not account for the 

drop-off in job creation that persists through the 2002-03 period. I compare the highest and 

lowest-growing industries of the expansion period. I find no major shifts in their trend patterns of 

either job creation or job destruction during or after the recent recession. If anything, there is an 

increase in trend job destruction among the expanding industries, which may be reflective of an 

employment bubble bursting. I also compare manufacturing industries of differing degrees of 

sensitivity to international trade. I find that industries who tend to gain from trade suffered just as 

much as, if not more than (from an employment perspective), those who are most sensitive to 

strong imports. 

 The next section details the data and defines the relevant job flow concepts. After that, I 

present the basic evidence on job flows between 1990 and 2003. The following section analyzes 

whether either structural changes or changes in trade patterns contributed to the recent 

employment downturn. I then discuss the recent decline in job creation in more detail. The final 

section discusses my findings and draws conclusions. 

Data and Definitions 

The data come from the Quarterly Census of Employment and Wages (QCEW), or ES202, program. The BED data are a longitudinal version of the QCEW data, used for quarterly 

estimates of gross job gains (also referred to as job creation) and gross job losses (also referred to 

as job destruction). The BED data are a virtual census of employment, which includes all 

establishments covered under state unemployment insurance programs.1

 The BED links 

establishment records over time, providing a longitudinal employment history for each. Record 

 

1

 The government, self-employed, and private households are the primary exclusions from the BED. 
 3

linkage is a detailed process, and it is summarized well in Pivetz, Searson, and Spletzer (2001) 

and Clayton et al. (2004). The longitudinal nature of the data allows the BLS to estimate the 

number of jobs gained or lost by establishments each quarter. These estimates are currently 

available from the third quarter of 1992 through the second quarter of 2003. The BED data, 

however, goes back to 1990. Major changes to the QCEW program prior to 1992 make it 

difficult for the BLS to produce estimates that meet official publication standards for this period. 

Researchers, however, can access the microdata and produce their own estimates for the 1990-92 

period. 

 My data encompass quarterly employment and job flow estimates for all private sector 

establishments between March 1990 and June 2003. I obtain job flow estimates for the earlier 

period by using my own linkage algorithm as a supplement to the current BLS methodologies. 

My technique appeals to the fact that the linkage difficulties stem from the implementation of a 

specific administrative change (the implementation of the “Multiple Worksite Report”). The 

nature of the change does not allow a straightforward linkage of some continuous records, and 

thus creates an overstatement of job creation and destruction. With several identifying 

assumptions, however, I am able to virtually eliminate this overstatement. In the appendix, I 

detail the nature of the administrative change and my methods for dealing with it. 

 For this study, I use the standard BLS definitions of gross job gains and losses as my 

definitions of job creation and job destruction. I measure changes in employment as those 

between the third month of employment for each quarter. I define job creation as the sum of all 

employment gains at (i) continuous establishments expanding their employment from some 

positive level, and (ii) “opening” establishments reporting either positive employment for the first 

time or after reporting zero employment in the previous quarter. I define job destruction as the 

sum of all employment losses at (i) continuous establishments contracting their employment to a 

level that is still greater than zero, and (ii) “closing” establishments either disappearing or 
 4

reporting zero employment after reporting positive employment in the previous quarter.2 The 

more familiar net change in employment is simply the difference between all jobs created and all 

jobs destroyed. Where reported, job flow and net change rates are the percentages of the thirdmonth employment average of the current and previous quarters.3

 Finally, I report estimates seasonally adjusted using the X-12 ARIMA process. I do so 

separately for the expanding, opening, contracting, and closing establishments at the 3-digit level 

of the North American Industry Classification System (NAICS). The industry detail is 

comparable to the 2-digit level of the older SIC system. Reported aggregated estimates are sums 

of these seasonally adjusted series. For the third quarter of 1992 forward, my seasonally 

unadjusted data are essentially identical to the published BED data. Due to differing adjustment 

methodologies, the seasonally adjusted series are slightly different. Overall, the data cover 5.0 

million establishments representing 89.3 million employees in March 1990 and 6.4 million 

establishments representing 107.6 employees in June 2003. On average, establishment 

expansions and contractions make up about 80 percent of quarterly job creation and destruction, 

respectively. 

Employment and Job Flows, 1990-2003 

The period from March 1990 through June 2003 contains a prolonged expansion 

sandwiched between two economic downturns. Based on the dating of the NBER, the first 

downturn begins after a business cycle peak in the third quarter of 1990, reaching its trough in the 

first quarter of 1991. Relative to previous recessions, employment losses are mild, but 

employment gains during the recovery are slow to materialize (see Figure 1). The second 

downturn begins as the economy peaks in the first quarter of 2001. Figure 1 illustrates that 

employment losses (from the business cycle peak) are sharper relative to previous recessions by 

 

2

 Given my definitions, openings and closings include re-openings and temporary closing, as well as births 

and deaths. 

3

 Rate calculation follows the methodology of both the BLS and Davis, Haltiwanger, and Schuh (1996). 
 5

the time a trough is reached in the fourth quarter of the same year. In addition, employment 

losses continue during the recovery, through the second quarter of 2003, the latest available data. 

Figure 1. 

Private Payroll Employment During the Business Cycle

96

97

98

99

100

101

102

P-1

Peak

P+1

P+2 (T ’91)P+3 (T ’01)

P+4P+5P+6P+7P+8P+9

Quarters from Peak

Index from Peak

Average of Previous 6 Recessions

1990-91 Recession

2001 Recession

Notes: Figure uses the Current Employment Statistics of the BLS. The previous six recessions span 1953 

through 1982, and count the double-dip of 1980-82 as a single event. Recent business cycle troughs are 

noted in parentheses. 

 Unlike previous downturns, the two most recent recessions have prolonged jobless spells 

during their subsequent recoveries. Based on the net employment changes over these two 

periods, one could conclude that there are many similarities in the behavior of the labor market 

over these two periods. The job flows underlying these net changes, however, show that the two 

recessions and their subsequent recoveries are quite different. Figure 2 shows the quarterly rates 

of job creation and job destruction from the second quarter of 1990 though the second quarter of 

2003. Remember that the net employment change in a given quarter is the difference between the 

job creation rate and the job destruction rate. The NBER-dated peaks and troughs are outlined. 

Both recessions have relatively high rates of job destruction, with large spikes of job loss at or 

near each trough. The spike in job destruction in the first quarter of 1991 is particularly large, 

encompassing 9.5 percent of employment. The spike in job destruction in 2001 is not as great 
 6

(8.2 percent of employment), but persists at this rate over three quarters. The job destruction rate 

declines in both recovery periods, but does so much slower in the earlier recovery. After the 

1991 trough, the pace of job loss does not reach a rate of 7.5 percent (its average rate during the 

subsequent expansion) until the end of 1992. Following the 2001 trough, the job destruction rate 

is 7.5 percent after only two quarters, and continues to fall thereafter. Job creation is markedly 

different during the two recessions and recoveries. Between 1990 and 1992, the job creation rate 

diverges little from 8.2 percent of employment, which is also its average during the subsequent 

expansion. The pace of job creation peaks at 8.4 percent by the end of 1999. By the end of 2000, 

the job creation rate is 7.8 percent. As the business cycle peaks, the job creation rate continues to 

decline, reaching a low of 7.2 percent in the third quarter of 2001. Job creation picks up 

somewhat after the trough, rising back to 7.5 percent by the first quarter of 2002, but its pace 

begins another steep decline, this time to 7.0 percent, by the first quarter of 2003. Its rate in the 

second quarter is only slightly higher. 

Figure 2. 

Private Payroll Employment

6.8

7.2

7.6

8.0

8.4

8.8

9.2

9.6

1990Q11990Q31991Q11991Q31992Q11992Q31993Q11993Q31994Q11994Q31995Q11995Q31996Q11996Q31997Q11997Q31998Q11998Q31999Q11999Q32000Q12000Q32001Q12001Q32002Q12002Q32003Q1

Percent of Employment

Job Creation Rate

Job Destruction Rate

 Notes: Estimates are based on author’s calculations from the BED data of the BLS. See text for details. 
 7

 Thus, while the past two recessions and subsequent recoveries seem quite similar on the 

surface, they are starkly different in their underlying dynamics. In particular, the pace of job 

creation between 2001 and 2003 is well below its historical norm, and accounts for the lack of job 

growth that occurs following the business cycle trough. In contrast, the flat job growth that 

follows the 1991 trough stems from a relatively slow decline in the pace of job losses, rather than 

any drop-off in job creation. Figure 3 illustrates the differences best by depicting job flows 

during the two recessions as a percentage of their level at each business cycle peak. In relative 

terms, the 1990-91 recession has a distinct episode of job loss that remains persistently higher 

long after the trough, while the 2001 recession has a substantial decline in job creation that 

continues well into the recovery period. 

Figure 3.

Gross Job Flows, 1990-1992 and 2001-2003

80

85

90

95

100

105

110

115

P-1

Peak

P+1

P+2 (T ’91)P+3 (T ’01)

P+4P+5P+6P+7P+8P+9

Quarters from Peak

Index from Peak

1990-91 Job Creation

1990-91 Job Destruction

2001 Job Creation

2001 Job Destruction

 Notes: Estimates are based on author’s calculations from the BED data of the BLS. Job flows are 

measured relative to their levels at the relevant NBER-dated business cycle peak. 
 8

Industry Comparisons 

 Job losses in the past two downturns occur disproportionately in manufacturing, as Table 

1 illustrates. In both periods, manufacturing loses a considerable amount of jobs even as the other 

industries begin a recovery. It is important to see whether manufacturing job flows behave 

differently than other industries. I present a broad comparison of the manufacturing sector to a 

grouping of service, financial and information sectors, based on the NAICS industry coding.4

 I 

replicate Figure 2 with estimates for manufacturing (Figure 4) and services, finance, and 

information (Figure 5.)

Table 1. Net Changes in Employment (Thousands of Jobs), 1990-1992 and 2001-2003

June 1990 to March 1991 March 1991 to September 1992 

Manufacturing -834 -343 

Non-manufacturing -1,026 +446 

Total Private Sector -1,860 +103 

March 2001 to December 2001 December 2001to June 2003 

Manufacturing -1,218 -1,224 

Non-manufacturing -1,520 +121 

Total Private Sector -2,738 -1,103 

Notes: Estimates are based on author’s calculations from the BED data of the BLS. 

 The first thing to note from Figure 4 is that job reallocation in manufacturing is 

considerably lower than in the rest of the private sector. For instance, job creation averages just 

5.0 percent of manufacturing employment between 1993 and 2000, while job destruction 

averages just 4.9 percent. This compares with average private-sector rates of 8.2 and 7.5 percent, 

respectively. Manufacturing job flows have several notable differences and similarities with the 

private-sector job flows. Despite the differences in magnitude, the patterns of job destruction are 

generally similar, particularly during the two recessions, but there are some distinctions. 

Manufacturing job losses during the expansion period have a slower decline. In addition, the 

pace of job destruction following both troughs is more persistent in manufacturing. In fact, job 

destruction in manufacturing remains quite high well into 2003. Job creation trends in 

 

4

 Manufacturing corresponds to NAICS sectors 31 through 33, while my grouping of service, financial, and 

information industries correspond to NAICS sectors 51 through 81, excluding private households. 
 9

manufacturing and in the total private sector are remarkably similar. Both have similar job 

creation rates during the 1990-91 recession and subsequent expansion, and both exhibit a steep 

and persistent decline in job creation between 2001 and 2003. Note, though, that job creation 

peaks over two years earlier in manufacturing than in the total private sector. 

Figure 4. 

Manufacturing Employment

3.2

3.6

4.0

4.4

4.8

5.2

5.6

6.0

6.4

6.8

7.2

7.6

1990Q11990Q31991Q11991Q31992Q11992Q31993Q11993Q31994Q11994Q31995Q11995Q31996Q11996Q31997Q11997Q31998Q11998Q31999Q11999Q32000Q12000Q32001Q12001Q32002Q12002Q32003Q1

Percent of Employment

Job Creation Rate

Job Destruction Rate

Notes: Estimates are based on author’s calculations from the BED data of the BLS. See text for details. 

 Figure 5 shows that job flows in information, financial, and service industries (which 

average three times as many workers as manufacturing) are nearly identical to those for the total 

private sector, in both trends and magnitude. The 1991 peak in job destruction is notably lower 

for these industries. In addition, the pace of job creation during the expansion period, particularly 

from 1997 through 2000, is considerably higher. Other notable trends, however, such as the 

steep, persistent drop in job creation between 2000 and 2003, occur in these industries just as they 

do in the total private sector. 
 10

Figure 5. 

Information, Finance, & Service Industries

6.8

7.2

7.6

8.0

8.4

8.8

9.2

9.6

1990Q11990Q31991Q11991Q31992Q11992Q31993Q11993Q31994Q11994Q31995Q11995Q31996Q11996Q31997Q11997Q31998Q11998Q31999Q11999Q32000Q12000Q32001Q12001Q32002Q12002Q32003Q1

Percent of Employment

Job Creation Rate

Job Destruction Rate

Notes: Estimates are based on author’s calculations from the BED data of the BLS. See text for details. 

Some Structural Factors and Job Flows 

Some argue that structural change may account for the recent lack of growth in the labor 

market. For example, Groshen and Potter (2003) argue that an acceleration of these structural 

changes may account for the current lack of growth. They study the employment growth rates of 

all major industries during the recession and recovery periods of the past several economic 

downturns. They group industries by whether they went through a cyclical or structural change in 

each downturn. Cyclically changing industries are those with employment changes that generally 

follow the business cycle, while structurally changing industries are those with more permanent 

changes (i.e., relative gains or losses that persist through both the recession and recovery). They 

find that 79 percent of employment falls into the “structural” category during the 2001-03 period, 

compared to 57 percent in the 1990-92 period and 51percent in the two preceding downturns, 

implying that structural employment reallocation across industries plays an important role in the 

recent downturn. Indeed, in replicating the analysis of Groshen and Potter with three-digit 
 11

NAICS industries, I find that 74 percent of employment falls into the “structural” category during 

2001-03, compared with 68 percent during the 1990-92 period. 

 There has also been popular speculation that the current lack of job growth is the result of 

the permanent reallocation of jobs overseas. The reallocation may stem from either the 

contraction or closing of firms unable to compete with their foreign counterparts.5

 Hampering the debate over these hypotheses is a lack of appropriate data with which to 

test them. The U.S. labor market is dynamic, reallocating about 15 percent of jobs each quarter—

analyses of the net changes in industry employment fail to capture these dynamics. In addition, 

even with data such as the BED it is difficult to identify the portion of reallocation attributable to 

permanent changes in the economy, whether they are across industries or across borders. While 

data on job flows cannot provide definitive answers on these topics, they can illustrate whether 

the underlying dynamics, both within and across industries, are consistent with these arguments. 

 Below, I analyze whether the growth and job flows of particular industries have 

differential responses to the recent business cycle. I first compare industries with the greatest 

growth over the 1990’s to those with the least growth. Using the same analysis, I then compare 

the job flows of manufacturing industries with differing levels of trade exposure. For each 

analysis, I present the net employment growth rates and job flows independent of business cycle 

trends, using a linear de-trending.6

 Trend net growth estimates are thus the growth rate of 

industry i at time t, Nit, less the private-sector growth rate at time t, Nt. For job flows, it is slightly 

more complex, since a) there are large persistent differences in industry-level job flows,7

 and b) 

job flow trends contain information about the long-run growth of an industry. The former point 

implies that a simple differencing of estimates will provide a poor measure of trend job flow 

 

5

 Klein, Schuh, and Triest (2003) discuss the effects of international competition on manufacturing as well, 

though their most recent data is only through 1994. 

6

 I use a linear de-trending since most cyclical movements occur at the endpoints of my sample period. 

Nonlinear filters, such as an HP filter, tend to be less efficient at time-series endpoints. 

7

 For examples with other data sources, see Anderson and Meyer (1994), Foote (1998), and Burgess, Lane, 

and Stevens (2000). 
 12

movements. The latter point implies that correcting for these differences in too simple a manner 

(e.g., a difference-in-difference approach) will distort the underlying industry growth trend. To 

account for both issues, I use the excess reallocation rate measure, which Davis, Haltiwanger, 

and Schuh (1996) define as the sum of the job creation and job destruction rates, less the absolute 

value of the net growth rate. Excess reallocation measures the amount of turnover independent of 

growth in a particular period. As such, it simultaneously captures the persistent differences in 

industry job reallocation while retaining industry differences in growth trends. I take the excess 

reallocation rate for the private sector, XRt, averaged across all quarters in the sample, and divide 

it by the excess reallocation rate for the industry, XRit, also averaged across all quarters. I use this 

ratio to normalize the industry job flow rates to the private-sector rates, which makes a linear 

differencing possible. Formally, my trend estimates for net growth, job creation (Cit), and job 

destruction (Dit) are 

nit = Nit − Nt ~ , it t

i

it C C

XR

XR

c − ⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ = ~ , it t

i

it D D

XR

XR d − ⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ = ~ , 

where = ∑( ) + − t i Cit Dit Nit T

XR 1, and similarly for XR . 

Expanding versus Declining Industries 

 If, as Groshen and Potter (2003) suggest, the lack of job growth during the recent 

recovery stems from an accelerated pace of structural change, it should be evident in the industrylevel rates of job creation and job destruction. My replication of Groshen and Potter’s analysis 

with the BED data is generally consistent with their suggestion, but this approach only appeals to 

industry net employment changes. The industry gross job flows would provide stronger evidence 

either for or against their argument. The structural reallocation of jobs from declining industries 

to expanding industries is a phenomenon that dates back several decades. If this reallocation 

accelerated in the recent downturn then, all else equal, one should observe a relatively higher 
 13

pace of job destruction among historically declining industries and a relatively higher pace of job 

creation among historically expanding industries during this period. 

 To explore this hypothesis, I separate 3-digit NAICS industries based on their 

employment growth between December 1993 and December 2000. I define “Expanding” 

industries as those with growth at least one standard deviation greater than the private sector rate 

over this period (about 18 percent), and “Declining” industries as those with growth less than one 

standard deviation below the private sector rate. By this definition, there are 11 expanding 3-digit 

industries, which notably include, internet publishing and services, telecommunications, and 

professional and administrative services. There are also 16 declining industries, which primarily 

include manufacturing plants in the food, textile, apparel, paper, printing, chemicals, and primary 

metal industries.8

 I list all industries in Table A.2 of the appendix. Table 2 shows the 

employment trends of each group. There are stark differences in growth between the two groups 

during the expansion, but both groups lost jobs (albeit at different rates) through the business 

cycle trough and through the end of the sample period. 

Table 2. Growth in Expanding and Declining Industries 

Employment (in thousands) 

Group Dec. 1993 Dec. 2000 Dec. 2001 June 2003 

16,461 24,253 23,098 22,604 Expanding Industries

Change: 7,792 -1,155 -498 

7,662 6,904 6,485 6,171 Declining Industries

Change: -758 -419 -314 

Notes: Estimates are based on author’s calculations from the BED data of the BLS. See appendix for 

details of industry groupings. 

 The trend growth and job flow patterns for expanding industries are in Figure 6a and the 

patterns for declining industries are in Figure 6b. Expanding industries (by definition) gain a 

disproportionate share of jobs during the expansion, though they also lose a disproportionate 

 

8

 There are also six resource and mining industries that meet the criteria for a declining industry, but are 

excluded. They make up a very small share of employment, but their trend job flows are large and volatile 

enough to make an analysis with them included difficult to interpret. 
 14

share of jobs during the two recessions. Declining industries (by definition) lose a 

disproportionate share of jobs during the expansion, but their recession-period losses are much 

closer to the national trend, producing a somewhat countercyclical trend growth pattern. 

 Job creation in expanding industries is above average (as represented by the “0” line), 

relative to the business cycle. This is true almost throughout the entire period, with an exception 

during the 1990-91 recession, when it is roughly similar to the national trend. Job destruction 

follows the national trend very closely from 1990 through the end of 2000. Job losses then rise 

well above the national trend and persist at this level through mid-2003. Within declining 

industries, both job creation and destruction are well above the national trend throughout the early 

1990’s. Their trends, however, decline through 2000. By 1995, job creation falls below the 

national trend. The pace continues to decline and does not stabilize until early 2000. Afterward, 

the trend is constant but still well below the national trend. The pace of job destruction declines 

but remains high through 2000, at which time it stabilizes at a rate comparable with the national 

trend. There is a slight dip in trend job destruction in 2002, but overall, job losses in these 

industries follow the national trend from 2001 through 2003. 

 Taken together, the evidence does not support the argument that job losses in the recent 

downturn are the result of an accelerated pace of between-industry reallocation. While there does 

seem to be some structural adjustment within the declining industries, their reallocation trends 

actually decline over time. In addition, the period in question is the time of the least turbulence 

(relative to the national trend) for these industries. If there exist any structural shifts between 

2001 and 2003, they occur among the industries that grew the most over the 1990’s. These 

industries have a sharp increase in trend job destruction that persists through these years. 

Regardless, trend job creation remains above the national rate at a proportion similar to that of the 

preceding expansion period. Thus, my job flow findings are consistent with the work of Groshen 

and Potter on two of three counts. Most importantly, the evidence from this and previous sections 

suggests that the latest prolonged downturn in the labor market is unique, and quite different from 
 15

the 1990-92 downturn. The evidence also suggests that patterns of between-industry structural 

change are prevalent throughout the sample period. The evidence does not suggest, however, that 

an accelerated pace of this structural change substantially contributed to the recent lack of job 

growth. 

Manufacturing Job Flows and Trade Exposure 

 There is some speculation that industries that face strong international competition were 

more susceptible to permanent job losses during the recent downturn. As these industries recover 

from an adverse aggregate shock, increased competition may reallocate lost jobs to countries with 

lower labor costs. If this hypothesis were true, all else equal, one should observe high rates of job 

destruction and low rates of job creation among the industries most sensitive to trade during the 

recent downturn. Industries that either gain from trade (through exports) or are independent of 

trade should be relatively unaffected. 

Figure 6a. 

Trend Job Flows, Expanding Industries

-0.020

-0.015

-0.010

-0.005

0.000

0.005

0.010

0.015

0.020

0.025

1990Q11990Q31991Q11991Q31992Q11992Q31993Q11993Q31994Q11994Q31995Q11995Q31996Q11996Q31997Q11997Q31998Q11998Q31999Q11999Q32000Q12000Q32001Q12001Q32002Q12002Q32003Q1

Job Creation

Job Destruction

Net Growth
 16

Figure 6b. 

Trend Job Flows, Declining Industries

-0.025

-0.020

-0.015

-0.010

-0.005

0.000

0.005

0.010

0.015

0.020

0.025

1990Q11990Q31991Q11991Q31992Q11992Q31993Q11993Q31994Q11994Q31995Q11995Q31996Q11996Q31997Q11997Q31998Q11998Q31999Q11999Q32000Q12000Q32001Q12001Q32002Q12002Q32003Q1

Job Creation

Job Destruction

Net Growth

Notes: Estimates are based on author’s calculations from the BED data of the BLS. See text for details. 

 To test the trade hypothesis, I group manufacturing industries by their level of trade 

exposure. I use data on imports (I), exports (X), and the value of shipments (Q) compiled by the 

U.S. International Trade Administration. These data primarily use the Annual Survey of 

Manufactures of the U.S. Census Bureau and are readily available for 3-digit NAICS sector 

annually for 1997 through 2001. I group the industries into four categories. “Trade Sensitive” 

industries are industries that have relatively high imports and low exports. These industries 

include textile product and apparel makers, wood and furniture makers, and primary metals 

industries. “Trade Gaining” industries are those with high exports and relatively low imports, and 

include chemicals, plastics, and machinery. “High-Volume Trade” industries are those that are 

very open to trade and have high exports and imports. They include computers, electrical 

equipment, and transportation equipment. Finally, “Trade-Independent” industries are those that 

have low imports and exports. They include food and beverage manufacturing, paper and 

printing, and fabricated metals manufacturing. In Table 3, I report the 1997 estimates of each 
 17

group’s import penetration ratio, export share, and index of trade-openness.9 The import 

penetration ratio ( ) I ( ) Q + I − X is the ratio of imports to domestic consumption, where 

consumption is defined as shipments plus imports less exports. The export share is the ratio of 

exports to shipments ( ) X / Q . Finally, the measure of trade-openness is the sum of exports and 

imports as a share of the sum of shipments and imports ( ) ( )( ) I + X Q + I . The trade sensitive 

industries are the smallest of the three groups, in terms of value of shipments. These industries, 

along with high-volume trading industries, have the highest import penetration ratios. Highvolume trading industries have the highest export shares (followed by trade-gaining industries), 

and consequently have the greatest openness to trade. Trade-independent industries have 

considerably lower trade measures relative to the other three groups. 

Table 3. Trade Patterns in Manufacturing 

1997 Values 

Group 

Value of 

Shipments 

(Q, $ billion) 

Import 

Penetration 

[I /(Q + I - X)]

Export 

Share 

[X /Q] 

Trade Openness 

Index 

[(I + X)/(Q + I)] 

Trade Sensitive 530.6 0.266 0.107 0.325 

High-Volume Trade 1,126.8 0.289 0.237 0.417 

Trade Gainers 904.2 0.156 0.184 0.291 

Trade Independent 1,273.2 0.072 0.066 0.129 

All Manufacturing 3,834.7 0.187 0.149 0.289 

Notes: Estimates based on author’s calculations from industry data by the U.S. International Trade 

Administration. See appendix for details of industry groupings. 

 Figures 7a through 7d present the trend growth and job flow rates for each group. Figure 

7a presents the evidence for trade-sensitive industries. As one might expect, job growth in these 

industries have been well below the national trend. This is especially true during the two 

recessions and in the years immediately preceding and following the 2001 recession. These 

losses occur primarily through high rates of trend job destruction that persist through 2003. Job 

creation is somewhat above the national trend early in the sample period and somewhat below the 

 

9

 There is an increasing level of trade between 1997 and 2001, but the ordinal rankings of industries’ trade 

measures are essentially constant across the years. Thus, I only report the 1997 estimates. 
 18

trend later on, but the differences are small in comparison to the behavior of job destruction. By 

itself, this evidence suggests that trade liberalization indeed adversely affects the most sensitive 

industries: they destroy jobs at a rate well above the national trend, and it is exacerbated during 

the recent recession and subsequent stagnant recovery. 

 The evidence in Figures 7b and 7c, however, casts serious doubt on this claim. In these 

figures, which present the evidence for trade-gaining and high-volume trading industries, 

respectively, trend job losses (both net and gross) are much greater between 2001 and 2003 

relative to the losses in trade sensitive industries. The major differences occur during the 

expansion period where, between 1994 and 1998, trade-gaining and high-volume trading 

industries destroyed jobs near the national rate, while trade-sensitive industries destroyed jobs 

above that rate. The only divergent trends are among industries with low imports and exports 

(Figure 7d). These industries have relatively high trend rates of both job creation and destruction 

at the beginning of the period, but they exhibit a steady decline that eventually stabilizes. If 

anything, the patterns mimic those of the declining industries in Figure 6b. This is no surprise, 

however, since four of the seven trade-independent industries are also in the earlier-defined 

declining group. 
 19

Figure 7a. 

Trend Job Flows, Trade-Senstive Industries

-0.030

-0.020

-0.010

0.000

0.010

0.020

0.030

0.040

1990Q11990Q31991Q11991Q31992Q11992Q31993Q11993Q31994Q11994Q31995Q11995Q31996Q11996Q31997Q11997Q31998Q11998Q31999Q11999Q32000Q12000Q32001Q12001Q32002Q12002Q32003Q1

Job Creation

Job Destruction

Net Growth

Figure 7b. 

Trend Job Flows, Trade-Gaining Industries

-0.030

-0.020

-0.010

0.000

0.010

0.020

0.030

0.040

1990Q11990Q31991Q11991Q31992Q11992Q31993Q11993Q31994Q11994Q31995Q11995Q31996Q11996Q31997Q11997Q31998Q11998Q31999Q11999Q32000Q12000Q32001Q12001Q32002Q12002Q32003Q1

Job Creation

Job Destruction

Net Growth
 20

Figure 7c. 

Trend Job Flows, High-Volume Trade Industries

-0.040

-0.030

-0.020

-0.010

0.000

0.010

0.020

0.030

0.040

0.050

1990Q11990Q31991Q11991Q31992Q11992Q31993Q11993Q31994Q11994Q31995Q11995Q31996Q11996Q31997Q11997Q31998Q11998Q31999Q11999Q32000Q12000Q32001Q12001Q32002Q12002Q32003Q1

Job Creation

Job Destruction

Net Growth

Figure 7d. 

Trend Job Flows, Trade-Independent Industries

-0.030

-0.020

-0.010

0.000

0.010

0.020

0.030

0.040

1990Q11990Q31991Q11991Q31992Q11992Q31993Q11993Q31994Q11994Q31995Q11995Q31996Q11996Q31997Q11997Q31998Q11998Q31999Q11999Q32000Q12000Q32001Q12001Q32002Q12002Q32003Q1

Job Creation

Job Destruction

Net Growth

Notes: Estimates are based on author’s calculations from the BED data of the BLS. See text for details. 
 21

The Recent Decrease in Job Creation 

 The above evidence on job flows shows that the last two recessions and their subsequent 

recovery periods are quite different. Job destruction spikes and then declines during the 1990-92 

downturn, while job creation is relatively unchanged. Job destruction spikes and then declines 

during the 2001-03 downturn, but job creation decreases and persists at a dramatically low rate 

through the end of the sample period. Which of these two outcomes is closer to the historical 

norm? Evidence from previous research suggests that the 2001-03 downturn is unlike other 

recessions. Job flow data for the entire private sector is not available pre-1990, but Davis, 

Haltiwanger, and Schuh (1996) have job flow estimates for manufacturing for 1972 through 1993 

based on the Census Bureau’s Census of Manufactures and Annual Survey of Manufactures.

10 I 

overlay these estimates with my manufacturing estimates in Figure 8. The data are relatively 

comparable, with two caveats. First, most of the Census estimates are based on smaller samples, 

and thus estimates are somewhat more volatile. Second, the sample nature of the Census data 

makes it easier to track continuing plants, which reduces the potential for overstatement of job 

flows, so their average estimates may be somewhat lower. One can see the effects of these 

differences where the two series overlap between 1990 and 1993. With these caveats in mind, it 

is evident how starkly different the behavior of job creation is from 2000 through 2003 when 

compared to earlier years. There are other periods where a decrease in job creation is at least as 

dramatic, but no other time when it is as persistent. Conversely, the behavior of job destruction is 

comparable to earlier years. In fact, the large spikes in job destruction in 1991 and 2001 are small 

compared to the sharp losses in 1975, 1980, and 1982. Foote (1998) argues that manufacturing is 

different than other industries, but his argument is directed towards its patterns of job destruction. 

Both job destruction and job creation patterns in manufacturing, though, are strikingly similar in 

behavior to the information, finance, and service industries (see Figures 4 and 5). While the 

 

10 I thank John Haltiwanger for providing these estimates. They are publicly available at 

http://www.bsos.umd.edu/econ/haltiwanger/download.htm. 
 22

evidence is not definitive, it strongly suggests that the large, persistent decrease in job creation 

makes the most recent economic downturn unlike any other in the past 30 years. 

 What caused such a drastic and unique downturn? This remains an open question, but the 

behavior of business investment and its relation to gross job creation provides some clues. Real 

investment in equipment and software falls 8.4 percent during the 2001 recession and remains 5.0 

percent below its peak value through the third quarter of 1992.11 Similarly, the pace of job 

creation falls 7.4 percent during the recession and is 12.1 percent below its peak value by the 

second quarter of 2003. Between 1990 and 1992, investment falls only 3.4 percent during the 

recession and is 6.0 percent higher than its peak value by the third quarter of 1992. Job creation 

changes little in either the recession or recovery periods, indicating that both investment and job 

creation have similar trends in both downturns. 

Figure 8. 

Manufacturing Job Flows,1972 - 2003

3.0

4.0

5.0

6.0

7.0

8.0

9.0

10.0

1972Q11973Q11974Q11975Q11976Q11977Q11978Q11979Q11980Q11981Q11982Q11983Q11984Q11985Q11986Q11987Q11988Q11989Q11990Q11991Q11992Q11993Q11994Q11995Q11996Q11997Q11998Q11999Q12000Q12001Q12002Q12003Q1

Percent of Employment

Job Creation BLS

Job Destruction BLS

Job Creation LRD

Job Destruction LRD

Notes: Estimates are based on author’s calculations from the BED data of the BLS and Longitudinal 

Research Database of the Census Bureau. See text for details. 

 

11 Percentages are based on National Income Product Account estimates from the Bureau of Economic 

Analysis. 
 23

Figure 9 illustrates the movement of job creation and business investment between 1990 

and 2003. It shows the quarterly levels of job creation and job destruction (both in thousands of 

employees) compared to investment in equipment and software (in billions of chained 2000 

dollars).12 The patterns of job creation and investment are very similar throughout the period. 

Evident in the figure are the relatively flat patterns of job creation and investment between 1990 

and 1992 and the substantial declines in both series between 2001 and 2003. Job creation and 

investment also track each other well during the expansion period, with both series increasing 

considerably. Consequently, the Pearson correlation between the two series is a robust 0.78 over. 

Job destruction and investment also track each other closely, but do so primarily during the 

expansion. Job destruction and investment generally move in opposite directions during the two 

recessions. 

Figure 9. 

Gross Job Flows and Investment in Equipment & Software

6,500

7,000

7,500

8,000

8,500

9,000

9,500

1990Q11991Q11992Q11993Q11994Q11995Q11996Q11997Q11998Q11999Q12000Q12001Q12002Q12003Q1

300

400

500

600

700

800

900

1,000

Gross Jobs Created (Left axis)

Gross Jobs Destroyed (Left axis)

Investment (Right axis)

Notes: Estimates are based on author’s calculations from the BED data of the BLS and the National 

Income Product Accounts of the Bureau of Economic Analysis. See text for details. 

 This evidence suggests an important relation between gross job creation and business 

investment. As with job creation, evidence from previous business cycles suggests that the recent 

 

12 I show estimates in levels rather than rates since comparable data on the appropriate denominator for 

investment (the total stock of capital) is not readily available. 
 24

decline in business investment runs counter to its historical trends. Eighteen months into the 

recoveries of the previous seven recessions, real gross private investment is an average of 10.0 

percent higher than its peak level. Eighteen months into the current recovery, real gross private 

investment is 4.9 percent lower than its peak level.13 An economic relation between investment 

and job creation is easy to perceive, since the former is a gross flow of capital inputs and the latter 

a gross flow of labor inputs. It is also conceivable that the relation between job destruction and 

investment would be weaker, since labor is less costly to adjust (and hence more responsive to 

aggregate shocks) than capital. Whether a labor market downturn stems from high job 

destruction or low job creation may depend on whether a macroeconomic shock propagates 

through aggregate demand or investment. Further research can identify whether the nature of a 

shock or other factors determine these relations. 

Conclusions 

 Between 1990 and 1992, the U.S. private sector has a dramatic spike in job destruction 

with job losses slow to decline until the latter half of 1992. Throughout this period, creation 

changes little. This leads to a net loss of 1.9 million jobs during the recession and a gain of only 

103,000 jobs over the following 18 months. There are also large job losses between 2001 and 

2003. The private sector loses 2.7 million jobs during the recession and an additional 1.1 million 

over the following 18 months. This time, however, after a spike during the recession, the pace of 

job destruction quickly returns to its pre-recession pace. The large, persistent job losses instead 

stem from a dramatic decline in job creation. This decline begins a year before the business cycle 

peak and continues (with a brief revival in early 2002) through mid-2003. 

 Groshen and Potter (2003) suggest that an accelerated pace of structural change may have 

led to the most recent period of prolonged job loss. My findings suggest that patterns of 

 

13 Note that these statistics are for gross private investment, of which investment in equipment and software 

is a component. The latter statistic is not available in real dollars prior to 1990. 
 25

structural change are indeed prevalent dating back to 1990. Declining industries lose jobs 

throughout the period, and do so with a job destruction rate well above the national trend. 

Expanding industries gain jobs throughout, though their net gains are more responsive to the 

business cycle. Expanding industries have an above-average rate of job creation beginning in 

1991 and continuing through 2003. Trend job destruction generally follows national patterns, 

though it increases in 2000. Nevertheless, the evidence does not support the hypothesis that these 

trends accelerated during the recent downturn. Between 2000 and 2003, job destruction in 

declining industries generally follows the national trend. Trend job creation begins low and 

remains so throughout. Neither job flow deviates from its pattern during this time, however. In 

other words, within traditionally declining industries, neither trend job creation nor trend job 

destruction change during the recent slowdown, implying that an accelerated pace of structural 

change is likely not the cause of the observed jobless spell. The same is true of trend job creation 

in the expanding industries. Trend job destruction does increase for expanding industries during 

this time. This is inconsistent with a structural change hypothesis, but it does create an empirical 

puzzle. It may be reflective of an employment bubble bursting, though there is no comparable 

increase in trend job creation that precedes it. Given their large losses, manufacturing has 

received most of the attention during the recent downturn. This evidence suggests that further 

research on traditionally expanding industries is warranted as well. 

 Another hypothesis suggests that changing trade patterns have made certain industries 

more susceptible to international competition during slowdowns and increases the reallocation of 

jobs overseas. The massive losses in manufacturing (i.e., the sector most affected by international 

trade) lend credence to this reasoning. Between 2000 and 2003, however, I find that 

manufacturing industries most sensitive to international competition fare no worse than the 

manufacturing industries that gain from trade. The losses in manufacturing may be more 

reflective of a slowdown in global aggregate demand. According to estimates from the Bureau of 

Economic Analysis, the real value of exports falls 10.4 percent between the first and fourth 
 26

quarters of 2001, and exports are still 8.4 percent lower than their first quarter, 2001 levels by 

mid-2003. These decreases are well below the historical business cycle norms, suggesting that 

the flagging levels of exports may directly contribute to the sharp job losses in manufacturing. 

 Finally, job flow evidence from other data sources suggest that the recent decline in the 

pace job creation has no precedent in at least 30 years. The drop in job creation parallels a 

similarly unusual drop in business investment, and the patterns of both gross job creation and 

investment in equipment and software track each other closely between 1990 and 2003. 

Conversely, gross job destruction and investment only move together during the expansion 

period, and generally move in opposite directions during each recession. Whether low job 

creation or high job destruction dominates during a recession may depend on the relative impacts 

of shocks to investment versus shocks to aggregate demand. One must also consider other factors 

outside the labor market. Between 2000 and 2003, the U.S. experienced a rapid decline in stock 

market values, the September 11 terrorist attacks, corporate accounting scandals, and geopolitical 

uncertainties resulting from the war in Iraq. These events may have had a direct effect on job 

creation via increased uncertainty that reduced the incentive to hire, or an indirect effect via 

reductions in the incentive to invest in new capital. Further research will enhance our 

understanding of the job losses over the last two downturns, and the evidence I present in this 

paper will no doubt aid in guiding this research. 

References 

Anderson, Patricia and Bruce R. Meyer, “The Extent and Consequences of Job Turnover,” 

Brookings Papers on Economic Activity, Microeconomics, Washington, DC (1994). 

Burgess, Simon, Julia I. Lane, and David Stevens, “Job Flows, Worker Flows, and Churning,” 

Journal of Labor Economics 18:3 (2000), 473-502. 

Clayton, Richard L., R. Jason Faberman, Akbar Sadeghi, James R. Spletzer, and David M. Talan, 

“Business Employment Dynamics: New Data on Gross Job Gains and Losses,” Monthly Labor 

Review 127:4 (2004), 29-42. 
 27

Davis, Steven, John C. Haltiwanger, and Scott Schuh, Job Creation and Destruction (Cambridge, 

MA: MIT Press, 1996). 

Foote, Christopher, “Trend Employment Growth and the Bunching of Job Creation and 

Destruction,” Quarterly Journal of Economics 113:3 (1998), 809-834. 

Groshen, Erica L., and Simon Potter, “Has Structural Change Contributed to a Jobless 

Recovery?” Current Issues in Economics and Finance 9:8 (2003). 

Klein, Michael W., Scott Schuh, and Robert K. Triest, Job Creation, Job Destruction, and 

International Competition (Kalamazoo, MI: W.E. Upjohn Institute for Employment Research, 

2003). 

Pivetz, Timothy R., Michael A. Searson, and James R. Spletzer, “Measuring Job Flows and the 

Life Cycle of Establishments with BLS Longitudinal Establishment Microdata,” Monthly Labor 

Review 124:4 (2001), 13-20 . 
 28

Appendix

 Implementation of the “Multiple Worksite Report” (MWR) in the early 1990’s caused 

serious complications to the LDB linkage process. The MWR was implemented so that multiestablishment firms could easily report the employment and payroll of their separate 

establishments. Prior to the MWR, many firms reported their multiple establishments as a single 

UI record. Consequently, the MWR implementation caused a widespread restructuring of the UI 

establishment records of many large firms. This restructuring generally involved the breaking out 

of a single UI record into multiple establishment records. The UI account number remained the 

same during these changes, but the reporting unit numbers (by which the BED links 

establishment records) did not. In addition, predecessor and successor unit information (which 

the BED linkage process uses to identify routine administrative changes) was often not reported 

for the MWR implementation. As a result, the linkage process failed to identify these changes 

and instead counted the MWR implementations as employment changes due to closing and 

opening establishments. This created large job flow overstatements in 1991/1 and 1992/2, and a 

minor overstatement in 1993/1. 

 To correct for these overstatements, I appeal to the characteristics of the MWR 

implementation to create a linkage strategy. First, I note that MWR implementation occurs at the 

state level. Most states introduced the MWR in the first quarter of 1991, while Ohio did so in two 

stages, in the second quarter of 1992 and the third quarter of 1993.14 Some states already had a 

similar report in place, and so did not have to restructure their accounts. Other states also 

included predecessor and successor record information, allowing a successful linkage with the 

LDB algorithm. Thus, I only have to focus on a subset of states, minimizing my chances of 

making a false match. Second, UI account numbers should not change in a MWR 

implementation. This is not necessarily true of other administrative changes. Third, since these 

 

14 Further analysis showed that a single, very large multi-state firm had a similar account restructuring in 

the first quarter of 1992. I deal with its restructuring in a similar manner to the MWR changes, but do not 

report the results of this match for confidentiality reasons. 
 29

changes are theoretically only changes in paperwork, there should be no movement of 

employment across industries or locations, which sometimes occurs in the data during corporate 

mergers and other account restructurings. Finally, the UI data have a fine level of geographic and 

industry detail (county level, and either 4-digit SIC or 6-digit NAICS, respectively). Large 

employment fluctuations at these levels of detail are relatively rare and thus easily identifiable in 

the data. 

 Given these characteristics, I use a three-step process. The first step calculates job flows 

using the standard BED methodology. From this, I take the subset of establishments classified as 

openings or closings. By only looking at this subset, I tacitly assume that MWR restructurings 

cannot be part of other administrative changes, which I find to be entirely plausible. The second 

step identifies within-state linkages by UI account number, county, and detailed industry. When 

doing so, I make every effort to ensure that records are correctly linked to each other within these 

match cells. The final step recognizes that, in practice, some new records will have different 

industry codes than their predecessor. To account for this, the final pass takes the remaining 

unlinked records and attempts to match by UI account number and county. In general, this step 

produces less than 10 percent of the total matches I identify. 

 My approach is not without risks. First, there exists the possibility of producing false 

matches of truly opening and closing establishments. I am not too concerned with this possibility 

since the false match would have to occur among opening and closing establishments within both 

the same firm and the same county, an occurrence that is generally rare, especially among larger 

establishments (which are disproportionately represented among the potentially affected UI 

records). Second, there exists the possibility that I miss links that occur either within UI accounts 

and across counties or across entirely different UI accounts. Since I have no predecessor or 

successor record information, I cannot identify these matches without increasing the chances of a 

false match among other records. Thus, missed linkages potentially remain after my 

identification. While this may seem troublesome, administrative changes of this nature are 
 30

inconsistent with the implementation procedures of the MWR, so I am confident in my final 

estimates. 

 Table A.1 lists the number of matches made by and the effects of my identification 

strategy in the three quarters of interest. Note that the matches should significantly reduce 

employment changes at opening and closing establishments. Matches will also slightly increase 

employment changes at continuing establishments, since newly-matched records often have 

legitimate changes in employment during these quarters. Note that matches in the first quarter of 

1991 occur across most of the U.S., while matches in the second quarter of 1992 and first quarter 

of 1993 are only in Ohio. Overall, my final job flow estimates in the problem quarters are 

comparable to those in other quarters. 

Table A.1. Results of Match Identification for Potential MWR Issues 

 Initial Estimate Corrected Estimate 

Thousands of 

Employees 

Percent of 

Employment 

Thousands of 

Employees 

Percent of 

Employment 

First Quarter, 1991 

 Changes at Openings 5,321 6.0 2,270 2.5 

 Changes at Closings 5,462 6.1 2,103 2.4 

 Changes at Expansions 4,402 4.9 4,685 5.3 

 Changes at Contractions 7,784 8.7 8,376 9.4 

Second Quarter, 1992 

 Changes at Openings 3,156 3.6 1,887 2.1 

 Changes at Closings 2,481 2.8 1,226 1.4 

 Changes at Expansions 6,642 7.5 6,747 7.6 

 Changes at Contractions 4,310 4.9 4,401 5.0 

First Quarter, 1993 

 Changes at Openings 2,111 2.4 1,835 2.1 

 Changes at Closings 2,171 2.4 1,871 2.1 

 Changes at Expansions 4,706 5.3 4,752 5.3 

 Changes at Contractions 6,319 7.1 6,388 7.1 

Note: Listed employment changes are prior to seasonal adjustment. 
 31

Table A.2. NAICS Industries In Each Category 

Expanding Industries (NAICS) Declining Industries (NAICS) 

Specialty Trade Contractors (238) 

Electronics & Appliance Stores (443) 

Rail Transportation (482)* 

Support for Transportation (488) 

Internet Publishing (516) 

Telecommunications (517) 

Internet Services & Data Processing (518) 

Financial Investment Services (523) 

Professional, Scientific, & Technical Services (541) 

Administrative & Support Services (561) 

Amusement & Recreation (713) 

Foods (311) 

Textile Mills (313) 

Textile Product Mills (314) 

Apparel (315) 

Leather & Allied Products (316) 

Paper (322) 

Printing (323) 

Petroleum & Gas Products (324) 

Chemicals (325) 

Primary Metals (331) 

Wholesale Electronic Markets (425) 

Water Transportation (483) 

Pipeline Transportation (486) 

Postal Service [private employment] (491)* 

Central Bank Monetary Authorities (521)* 

Performing Arts, Sports, & Related Industries (711) 

Trade Gaining Industries (NAICS) High-Volume Trade (NAICS) 

Textile Mills (313) 

Chemicals (325) 

Plastics & Rubber Products (326) 

Machinery (333) 

Computers & Electronics (334) 

Electrical Equipment (335) 

Transportation Equipment (336) 

Trade Sensitive Industries (NAICS) Trade-Independent Industries (NAICS) 

Textile Product Mills (314) 

Apparel (315) 

Leather & Allied Products (316) 

Wood Products (321) 

Primary Metals (331) 

Furniture (337) 

Misc. Manufacturing (339) 

Foods (311) 

Beverages & Tobacco (312) 

Paper (322) 

Printing (323) 

Petroleum & Gas Products (324) 

Nonmetallic Minerals (327) 

Fabricated Metals (332) 

* Private employment in these industries is very small, averaging less than 25,000.