Download A New Categorization of the US Economy

A New Categorization of the U.S. Economy:
The Role of Supply Chain Industries in Performance*
Mercedes Delgado, MIT Sloan
Karen G. Mills, Harvard Business School
This version: 05/23/2016
PRELIMINARY AND INCOMPLETE
Abstract
Supply chains have been an important part of the discussion of the American economy. However, this
discussion has lacked an empirical definition of who are the suppliers and this has limited our
understanding of their role in national performance. This paper introduces a new industry categorization
that separates Supply Chain industries (i.e., those that sell their goods and services primarily to other
businesses or governments) from Business-to-Consumer (B2C) industries (i.e., those that sell primarily to
consumers). Our analysis uses the 2002 Benchmark Input-Output Accounts from the U.S. Bureau of
Economic Analysis to identify Supply Chain and B2C industries. Using this categorization we examine the
supply chain economy during the 1998–2013 period across several metrics: the number of firms,
employment, wages, labor occupation composition, patenting, and growth dynamics. We find that supply
chain industries comprise a large segment of the economy. In particular, there are many suppliers of
traded services both in terms of employment and number of firms. Supply chain industries, especially
traded services, have higher average wages than other industry segments. This can be explained in part
by the larger relative presence of STEM (Science, Technology, Engineering and Math) occupations in
supply chain industries, and in particular in the suppliers of traded services (though non-STEM occupations
such as accounting, finance, managerial, and logistics are also important to service suppliers). While STEM
occupations are most prevalent in suppliers of traded services, patents are primarily concentrated in
manufacturing suppliers. Together, these observations suggest that much of the U.S. innovative activity
happens in the supply chain economy. We also find that the employment in the supply chain economy
has been evolving away from manufacturing and towards services for the period under examination
(1998-2013), with suppliers of traded services experiencing high growth in employment and wages.
Finally, the analysis of the growth trends during the business cycles reveals that the supply chain economy
is particularly susceptible to economic crises (2001-2002; 2007-2009). Overall, our findings call for
targeted policies that recognize that suppliers are a large segment of the U.S. economy, are a mix of
manufacturers and service providers, have a diverse and distinct set of labor occupations, drive
innovation, and are vulnerable to crises.
*
Scott Stern has contributed important insights. We also thank Alfonso Gambardella, Jorge Guzmán, Bill Kerr, and
Ramana Nanda for helpful comments. We thank Christopher Rudnicki for great assistance with the data analysis and
project stewardship. Author contact information: Mercedes Delgado (MIT Sloan, ISC; [email protected];
corresponding author) and Karen G. Mills (Harvard Business School; [email protected]).
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1. Introduction
An ongoing and long academic and policy debate has focused on the role of the
manufacturing capacity of a country on its economic and innovative performance (see e.g.,
Rosemberg, 1963; Dertouzos et al., 1989; Pisano, 1997; Pisano and Shih, 2012; Helper et al., 2012;
Fuchs and Kirchain, 2010; Berger, 2013). This question has become even more relevant as the
U.S. economy has shown a large decline in manufacturing employment in the last decades, in
part due to increased import competition (Acemoglu et al., 2015). There is a concern that by
reducing the manufacturing of goods in a country the subsequent innovation capacity may be
reduced because there are external economies from the manufacturing process that improve the
ability to innovate and the efficiency (speed, costs, and diffusion) of the innovation process.
While countries can import innovative inputs, they cannot buy the associated externalities
related to producing the inputs locally.
In particular, Rosemberg (1963) highlights the crucial role of the suppliers of capital goods
(“machine producers”) in the process of technological innovation. A country needs a large capital
goods sector (supported by a high level of demand for capital goods) in order for suppliers of
capital goods to specialize in the creation of tailored inputs for their buyers. This specialization
of suppliers creates crucial externalities: “there is an important learning process involved in
machine production, and a high degree of specialization is conducive to not only an effective
learning process but to an effective application of what is learnt.” These learning externalities
can improve the efficiency in the production of the new capital goods needed for the innovation
process.
While most prior work focuses on a narrow view of suppliers as manufacturers, an
additional perspective posits that in today’s economy there is a broader group of suppliers that
includes producers of both intermediate goods (e.g., microprocessors) and services (e.g.,
software). In other words, the production capacity of a country is broader than its manufacturing
capacity of final goods, and includes both manufacturing and service suppliers. These suppliers
are often clustered nearby their buyers, and generate externalities that contribute to the
innovation capacity of a country and its regions (Marshall 1920; Porter, 1990 1998; Audretsch
and Feldman, 1996; Delgado, Porter, and Stern, 2014; Delgado, 2016).
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The goal of this paper is to quantify who are the suppliers in today’s economy and
examine their role in national performance. While there is a large literature that focuses on
examining the supply chain that operates from business-to-business (see e.g., Pisano, 1997;
Pisano and Shih, 2012; Lessard, 2013; Gawer and Casumano, 2002), there is a lack of
quantification of the size and types of suppliers in the economy. A few of these suppliers are very
large and become the platform on which many other companies build their products (e.g., Intel
in microprocessors and Microsoft in software; Gawer and Casumano, 2002), but many of the
suppliers are unknown, small firms. To understand the role of suppliers in the U.S. economy, this
paper develops a new industry categorization that identifies “supply chain” industries (i.e., those
that provide inputs for businesses and government), and explores their role in the composition
of nonfarm private employment and in national growth dynamics.
The categorization of industries as defined by the U.S. Census Bureau’s North American
Industry Classification System (NAICS) allows for descriptive insights into the economy’s
composition and a greater understanding of the role of particular types of industries in economic
performance. Throughout the 20th century the most influential categorization of U.S. industries
was manufacturing versus services. However, manufacturing currently comprises around 10% of
U.S. employment (Figure 1), and the service industries are extremely heterogeneous, varying
from retail and restaurants to engineering and design. The economy’s evolution away from
manufacturing then calls into question the usefulness of this framework for examining today’s
dynamics of firms and employment.
The traded versus local categorization introduced by Porter (2003) is rooted in the
economies of agglomeration literature (Marshall, 1920; Porter, 1990). It separates traded
economic activity, which is geographically clustered and sold across regions and countries (e.g.,
financial services and automotive manufacturing), from local economic activity (e.g., restaurants
and retail). This framework has helped researchers shed new light on the role of the traded
economy in national and regional competitiveness, and in particular on the role of industrial
clusters in regional performance (see e.g., Delgado, Porter, and Stern, 2010, 2014).
This paper introduces a new and complementary categorization that separates supply
chain (SC) industries (i.e. those that sell their goods and services primarily to other businesses or
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governments) from business-to-consumer (B2C) industries (i.e. those that sell primarily to
personal consumers). Our analysis uses the 2002 Benchmark Input-Output (I-O) Accounts from
the U.S. Bureau of Economic Analysis to systematically identify SC and B2C industries. This
categorization allows for a better understanding of the composition of the economy and the
types of industries that drive national growth outcomes, and complements prior categorizations.
We find that supply chain industries compose a large and important segment of the
economy (Figure 1). They accounted for 43 million jobs (37% of U.S. employment) and 2.5 million
firms in 2012 (43% of all employer firms). These conservative estimates are the first
comprehensive attempt to measure the size of the supply chain economy. We also separate SC
and B2C industries into subcategories-- traded versus local and manufacturing versus services
(Figure 2). By combining these three complementary categorizations, we can define and analyze
important sub-segments of the economy. For example, there are many suppliers of traded
services both in terms of employment and number of firms – a finding at odds with most prior
work that focuses on a narrow view of suppliers as manufacturers. Suppliers of traded services
account for almost 18 million jobs (~15% of all U.S. private employment), while suppliers of
traded goods account for around 8 million jobs. There are four times as many traded supplier
firms in services than in manufacturing (756,000 versus 169,000 firms).
SC industries, especially those that are classified as traded services, have higher average
wages than B2C industries. The examination of the labor occupational composition reveals that
STEM (Science, Technology, Engineering and Math) occupations are more prevalent in SC
industries than in B2C industries. Surprisingly, they are more important for SC-Traded categories
in services than in manufacturing (17% versus 11% of employment is in STEM occupations,
respectively). We also find that labor occupations differ between SC and B2C industries in ways
besides the prevalence of STEM occupations. For example, logistics, managerial, finance, and
accounting occupations are particularly important for suppliers of traded services.
Our analysis suggests that patenting activity (a measure of innovation) is highly
concentrated in the Supply Chain economy (more than 80% of the US utility patents granted in
2013), and in particular in manufacturing suppliers (77% of the patents). While it is not surprising
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that patenting is concentrated in manufacturing, it is insightful that most patenting is taking place
in the suppliers of intermediate goods versus in the producers of consumer goods.
Note that there is a big difference between the STEM content and patenting of the
different segments of the Supply Chain economy. While STEM occupations are most prevalent
in suppliers of traded services, this sub-segment only accounts for 2% of all the patents. This
suggests that the innovativeness of the suppliers of traded services is much higher than predicted
based on patenting. We need new measures of innovation for the suppliers of services that take
into account their STEM content and their input-output links with high patenting industries.
Finally, we examine the growth trends of the supply chain economy at the national level.
We find that the employment composition of the supply chain economy has been evolving away
from manufacturing and towards services for the period under examination (1998–2013), with
suppliers of traded services experiencing high growth in both employment and wages. This
compositional change reflects the evolution that some innovative firms have experienced over
the past few decades (e.g., IBM), and is consistent with the increasing importance of some service
industries, like enterprise software and business services (Gawer and Casumano, 2002; Low,
2013).
The growth analysis during the 1998-2013 business cycles also reveals that the Supply
Chain economy is very cyclical. It experiences larger contractions in employment and wage
growth than the B2C economy in both crises periods (2001-2002 and 2007-2009). The
vulnerability of suppliers calls for targeted policies during crises.
Our new categorization also helps better understand the performance of the local
economy, the largest part of the economy in terms of employment (more than 60% of all jobs).
We break out the local economy into Healthcare and “Main Street.”
We then use our
categorization to divide Main Street into two segments: B2C-Main Street represents the
traditional consumer facing shops and services (e.g., restaurants, dry cleaners, and car repair),
while SC-Main Street represents the business-to-business local firms (e.g., commercial real estate
and landscaping services). The B2C-Main Street segment has the lowest average wages of any
industry segment. It grew faster in terms of employment than the total economy during 19982013, but this category was the only one that experienced a decline in real wages. In contrast,
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SC-Main Street experienced low employment growth, but a positive wage growth during the
period. Healthcare registered high employment and wage growth, and has been a significant
growth factor in the economy.
Overall, our findings suggests that well paid jobs have been created in the supply chain
economy, especially in traded services. SC traded services is the segment of the traded economy
experiencing the highest growth in employment and wages. Our findings call for targeted policies
that recognize that suppliers are a large part of the economy, are not just manufacturers,
encompass both STEM and other set of labor occupations, drive innovation, and are cyclical.
The remainder of the paper is organized as follows: Section 2 describes the prior literature
on the role of suppliers in firm, regional, and country competitiveness. Section 3 presents our
empirical method to define SC and B2C industries. Section 4 explains the composition of the
supply chain economy in terms of employment, number of firms, wages, and labor occupations.
The employment, wage, and patenting growth trends of the SC and B2C industry categories is
examined in Section 5. A final section concludes and offers policy implications and remarks
regarding the applicability of our categorization for future research.
2. Is Prior Work Underestimating the Importance of Suppliers?
Suppliers provide inputs for businesses and governments and have played a central role
in the economic and strategy literature. In the economic growth literature, the production of
intermediate goods (capital goods) has been linked to the innovation capacity of a country (see
e.g., Rosemberg, 1963; Dertouzos et al., 1989). There are learning externalities from producing
specialized intermediate goods that improve the efficiency of the innovation process.
In economic geography, the co-location of suppliers and buyers has been identified as a
driver of agglomeration economies (Marshall, 1920; Chinitz, 1961; Porter 1990, 1998; Audretsch
and Feldman, 1996; Feldman and Audretsch, 1999; Glaeser and Kerr, 2009; Delgado, Porter, and
Stern, 2014, 2016; Feldman et al., 2014). When suppliers are clustered together and located near
their buyers, they can create agglomeration benefits through shared pools of skills, technologies,
knowledge, and specialized inputs. Prior work highlights the importance of nearby suppliers
(often measured by the presence of upstream industries) for fostering innovation and
entrepreneurship in manufacturing industries (Glaeser and Kerr, 2009). The collaboration
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between nearby buyers and suppliers in manufacturing has been associated with greater
innovation (Helper, MacDuffie, and Sabel, 2000). A recent study finds that firm innovativeness
(i.e., the development of products new to the market) is facilitated especially by the collaboration
with suppliers and to a much lesser extent by the collaboration with end-users (Arora, Cohen,
and Walsh, 2014). This suggests that, to the extent that this collaboration is facilitated with
geographical proximity, the presence of suppliers can play a crucial role on the innovation
capacity of a region.
Suppliers also provide important inputs to the government. The U.S. government has a
long tradition of contracting with businesses in many sectors (e.g., defense, energy, utilities,
healthcare, and research labs).1 Significant policy initiatives have focused on helping small
suppliers, including efforts led by the Small Business Administration to meet the small businesses
contracting goals of 23 percent; and the Obama Administration’s QuickPay initiative in 2011
aimed to reduce the working capital costs of small suppliers to the government (Helper,
Nicholson, and Noonan, 2015).
In the strategy literature, decisions regarding value-chain design and internal versus
external sourcing of inputs are the cornerstone of firm strategy and performance (Porter, 1996;
Pisano, 1997; Cohen and Levinthal, 1990; Helper, MacDuffie, and Sabel, 2000; Alcacer and
Delgado, 2016). These choices will depend on the availability of nearby suppliers. International
business studies have paid close attention to the organization of global supply chains, and
managerial practices to reduce the coordination costs and risk inherent in outsourcing inputs
from multiple locations (Lessard, 2013).
Furthermore, the organization of a firm’s value chain will also depend on whether the
firm is business-to-business (i.e., a supplier) or business-to-consumer (B2C). For example, prior
studies find that the adoption of some operational practices, like electronic selling (McElheran,
2015), can vary for B2B and B2C firms.
Overall, the prior literature suggests that suppliers are important for the competitiveness
of firms, regions, and countries, but who are the suppliers? Most prior work has focused on
manufacturing suppliers. This does not capture the increasingly important role of service inputs
1
Government contracts in 2014 totaled over $450 billion with approximately $90 billion going to smaller suppliers.
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(e.g., business services, accounting services, financial services, engineering, software publishers,
and design) in the value of final products (Ali-Yrkkö et al., 2011). Some of these service suppliers,
like Microsoft in software, become the platform on which many other companies build their
products (Gawer and Casumano, 2002).
To identify and characterize the suppliers in the U.S. economy, this paper distinguishes
between supply chain (SC) industries that primarily sell goods and services to businesses or to
the government and business-to-consumer (B2C) industries that focus on selling to consumers.
In the next Section we explain how we identify SC and B2C industries. Using this new
categorization, we then examine the importance of the supply chain economy across several
metrics: the number of firms, employment, wages, labor occupation composition, patenting, and
their growth dynamics.
Prior studies focus on the capacity to manufacture final goods as a key driver of the
innovativeness and economic performance of a country (e.g., Dertouzos et al., 1989; Pisano,
1997; Berger, 2013). Our characterization of the supply chain economy suggests that we should
focus on a broader definition of the production capacity of a country that includes both
manufacturing and service suppliers. As we explain below, the majority of traded suppliers are in
services industries. This segment of the supply chain economy has the highest wages, a very large
presence of STEM occupations, and has experienced a high growth.
3. The Supply Chain Categorization of the U.S. Economy
In this section we first explain prior categorizations: Manufacturing versus Services, and
Traded versus Local. We then describe the method to define SC industries and B2C industries. A
detailed explanation of the methodology is offered in the Appendix.
3.1 Prior Categorizations of the U.S. Economy
The manufacturing versus services categorization of industries has been broadly used in
economics and policy since the creation of the Standard Industrial Classification (SIC) by the U.S.
Government in 1937. The current NAICS code industry classification (as well as the prior SIC code)
separates out manufacturing and services industries based on what is produced. The 2-digit
NAICS codes 31-to-33 correspond to manufacturing industries, and the rest correspond to
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services industries. There are 1,088 6-digit NAICS (2007 definition) industries (excluding farming
and some government activity) in the US Census Bureau’s County Business Pattern data (CBP).
These industries are classified into 472 manufacturing and 616 service industries. In 2012,
manufacturing industries accounted for less than 10% of total U.S. employment (Figure 1).
A related categorization used in the I-O accounts separates goods-producing industries
from service-producing industries. Goods-producing industries includes both manufacturing
goods and other goods in the following sectors: Agriculture, Forestry, Fishing, and Hunting (NAICS
code 11); Mining (NAICS code 21); and Construction (NAICs code 23). Goods-producing industries
represented 15% of the total employment in 2012. While the “Services” category that we use
includes all industries not classified as manufacturing, our sensitivity analysis considers an
alternative definition for the Service category that excludes all durable goods (what we refer to
as the “Services (no goods)” category).
The traded versus local categorization developed by Porter (2003) represents a more
recent classification of industries based on their patterns of spatial competition (selling across
regions versus within regions). Specifically, traded industries are geographically concentrated
and sell their goods and services across regions and countries. Local industries sell primarily in
the local market, and they are geographically dispersed (i.e., their employment in a region is
proportional to the size of the population). We use the most recent traded categorization defined
in Delgado, et al. (2016b). Building on Porter (2003), they identify traded industries using the
employment specialization and concentration patterns of each industry across U.S .regions. Using
the 1,088 6-digit NAICS-2007 industries in the CBP data, they identify 778 traded industries and
310 local industries. In 2012, traded industries account for 36% of total U.S. employment (Figure
1).
Throughout our analysis, we separate the local economy into industries related to
Healthcare and those industries related to the ‘Main Street’ economy. This distinction allows us
to shed some light on the dynamics of the local economy. Healthcare includes 35 industries.2 The
other 275 local industries are defined as Main Street industries.
2
Healthcare industries are those within the local Health Services cluster identified in the US Cluster Mapping Project
(USCMP). It includes local health care establishments and services such as hospitals, medical laboratories, home and
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3.2 New Categorization: Supply Chain and Business-to-Consumer Industries
To identify and characterize the suppliers in the U.S. economy, we distinguish between
SC and B2C industries. Conceptually, SC industries primarily sell goods and services to businesses
and the government. Thus, most of the firms operating in these industries will be suppliers (i.e.,
they sell mainly to other businesses or to the government). In contrast, B2C industries primarily
sell final goods and services for personal consumption. Note that the concept of SC industry is
different from upstream industry. The latter is a relative term that refers to an industry that
provides inputs to another industry.3
To measure the extent to which industries sell to personal consumption, we use the 2002
U.S. Benchmark Input-Output (I-O) Accounts of the Bureau of Economic Analysis (BEA). The I-O
Accounts allow researchers to capture input and output flows between industries and output
flows from each industry into final use for personal consumption (see e.g., Feser, 2005; Feldman
et al., 2014; McElheran, 2015; Delgado et al., 2016a). To our knowledge, we offer the most
systematic and comprehensive classification of industries into SC and B2C. Building on prior work,
we classify all 6-digit NAICS industries into SC or B2C based on the output sold to Personal
Consumption Expenditure (PCE). PCE is a final use item in the I-O Accounts that captures the
value of the goods and services that are directly purchased by households, such as food, cars,
and college education (see detailed explanation in the Appendix). We identify industries as SC if
they sell less than one-third of their output to PCE, and the rest are classified as B2C. Thus in our
definition those industries that sell most of their goods and services to other businesses or the
government (i.e., more than two-thirds sold outside PCE) will be classified as SC. We explored
additional cut-offs to define SC industries (PCE scores <25% to PCE < 50%) to test the validity of
our definition and the sensitivity of the estimates of the size of the supply chain economy to
alternative definitions (see Table A4 in the Appendix).
Table 1 shows some representative examples of SC and B2C industries. For example,
Engineering Services (NAICS code 541330) is a SC industry in services that sells 0% of its value to
residential care, and funeral services and crematories; and pharmacies and optical goods retail stores. The list of
industries can be accessed at the USCMP (http://www.clustermapping.us/content/cluster-mapping-methodology).
3
Any industry can be upstream to some other industry. The only exceptions are industries that sell all their
products for personal consumption (e.g., Child Day Care services).
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PCE. In contrast, Computer Training (NAICS code 611420) is a B2C service industry that sells more
than 91% of its value to PCE. In manufacturing, Biological Product Mfg (NAICS code 325414) is a
SC industry that sells 0% of its value to PCE; and Pharmaceutical Preparation Mfg (NAICS code
325412) is a B2C industry that sells more than 91% of its value to PCE. In the local economy, there
are also both SC industries (e.g., Temporary Help Services – establishments engaged in supplying
temporary workers to businesses) and B2C industries (e.g., Full-Service Restaurants).
Note that in many industries their products are clearly intermediate inputs (e.g., biological
products and engineering services). However, in other industries, the same product can be SC or
B2C depending on the go-to-market channel used by the firm. For example, the Automobile
Manufacturing industry sells 47% of its output to final consumers and the rest is sold to
businesses. By choosing a conservative cut-off to define SC industries (PCE<33%), we are able to
identify industries that contain primarily suppliers.
3.3 Data
In our analysis, we examine the six main industry categories described above:
Manufacturing, Services, Traded, Local, SC and B2C. We also separate SC and B2C industries into
traded/local and manufacturing/services creating a total of eight subcategories (see Figure 2).
We use the County Business Patterns (CBP) dataset produced by the U.S. Census Bureau to
measure the employment and wages of the industry categories (and their sub-categories) over
the 1998-2013 period. The CBP is a publicly available database that provides annual county-level
measures of private-sector non-agricultural employment (excluding self-employed) and payroll
at the level of 6-digit NAICS codes (which we refer to as industries). 4 Data on the number of firms
by 6-digit NAICS is sourced from the US Census Bureau’s 2012 Economic Census. 5 We use the
Occupational Employment Statistics (OES) Survey administered by the Bureau of Labor Statistics
(BLS; 2009 data) to determine the labor occupation composition of each industry. The
employment, number of firms, payroll data, and labor occupational data is aggregated from
individual industries into our categories and sub-categories.
4
5
There are 6 industries in SC-Traded Services for which wage data is missing in the CBP data.
More detail about the 2012 Economic Census here: https://bhs.econ.census.gov/ec12/pages/about.html.
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Patent data is drawn from the U.S. Patent and Trademark Office (USPTO). This dataset
includes detailed information about all utility patents. Constructing patenting measures for each
of our industry categories is complicated and involves some art because USPTO patents are
assigned to patent classes but are not directly matched to industry codes. We created a bridge
between the SIC code industries and our industry subcategories, and then utilized the patent-SIC
code concordance algorithm developed by Silverman (1999), in which USPTO patents are
assigned, on a fractional basis, to four-digit SIC codes in a consistent (but somewhat noisy)
manner.
4. Findings: The Supply Chain Economy Matters
Our new categorization allows for a better understanding of the supply chain economy
(and its sub-categories) across several metrics: the size in terms of employment and number of
firms (Section 4.1), wages (Section 4.2), labor occupation composition (Section 4.3), and the
impact on national growth (Section 5). In addition to the SC category, the SC Traded Services
segment proved surprisingly meaningful in terms of size, wages, and STEM content. Additional
important findings come from the comparison of the SC-Main Street and B2C-Main Street
industries. The latter has a meaningful size, but the lowest wages in the economy. We explain
this and other findings next.
4.1 Size of the Supply Chain Economy: Employment and Firms
We find that suppliers are a large part of the economy in terms of both employment and
number of firms (Figure 2). Suppliers accounted for 42.8 million jobs (37% of U.S. employment)
and roughly 2.5 million firms in 2012. We also separate SC and B2C industries into traded and
local, creating a total of eight sub-categories. Traded suppliers account for 25.7 million jobs (22%
of U.S. employment) and nearly one million firms. Local suppliers are also important with more
than 17 million jobs and 1.6 million firms.
As mentioned earlier, prior work on the role of suppliers in the economy tend to focus on
manufacturing. However, Figure 2 shows that traded suppliers are not just manufacturers.
Suppliers of traded services account for 17.8 million jobs (more than 15% of U.S. employment),
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while suppliers of traded manufacturing goods account for around 8 million jobs (~7% of U.S.
employment).6 Furthermore, there are four times as many traded supplier firms in services than
in manufacturing (756,000 versus 169,000).
4.2 Wages in the Supply Chain Economy
Figure 3 shows that the jobs in the supply chain economy are well paid. SC industries have
higher average wages than B2C industries (both in the traded and local economy). SC Traded
Services is the sub-category with the highest average wages (i.e., $81,134 compared to $47,664
for the total economy in 2013).
The average wages are weighted by industry employment size. For example, the average
wage in the total economy is computed by dividing total payroll by the total employment. Thus,
to understand whether the higher wages in SC Traded Services is driven by a few large industries
or by many industries, we study the wage distribution across the 155 SC Traded Service Industries
(Figure 4). Finance Services is an important part of this sub-category (representing 21 industries
and 9% of the employment in SC Traded Services). The wages of these finance service industries
are high ($133,000 on average), and they include the top-3 industries by wages within the SC
Traded Services subcategory (Investment Banking and Securities Dealing with the highest wage
across all industries at +$300,000 followed by Portfolio Management, and Securities and
Commodity Exchanges).
While Finance Services is a meaningful component of the SC Traded Services industries, it
is not driving the high wages observed in this subcategory.7 There are many other industries (e.g.,
business, marketing, design, transportation, energy, and R&D services) with high-paying jobs.
Figure 4 shows that 30% of the industries have wages above $82,000, and the majority are not in
finance (e.g., the wage of the software publishers industry is +$137,000). Furthermore, 70% of
industries have wages greater than the total average wage in the economy.8 Finally, if we exclude
6
If we exclude from the SC Traded Services category the non-manufacturing goods, the employment only declines
slightly to 16.4 million (14% of total employment).
7
The average wage of the SC traded services excluding finance services is $75,700 in 2013.
8
Figure 4 shows that the 30th percentile value of wages across the industries is $51,000 versus the total economy
average wage of $47,664.
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non-manufacturing goods from SC Traded Services (i.e., exclude Agriculture, Mining, and
Construction), the average wages change minimally ($81,692 versus $81,134).
While SC Traded Services have the highest wages, B2C Main Street industries have the
lowest (39% lower than the average wage for the entire economy as of 2013). The latter
subcategory includes many low-skill jobs (e.g., retail occupations).
Importantly, the same findings hold when we use alternative definitions of SC industries
(Table A4) and when we compute the wages per category for the sub-groups of small firms (1500 jobs) and large firms (+500 jobs). As expected, the average wages are greater for large firms
across all the sub-categories. But for both sub-groups of firms, the SC Traded Services categories
have the highest wages and B2C Main Street categories have the lowest wages (not reported).
4.3 Labor Occupations in the Supply Chain Economy
We examine the labor occupations of SC and B2C industries to assess whether they have
different labor pools. Understanding the labor occupation composition across industry categories
can inform labor policy initiatives to support suppliers. This analysis can also help explain some
of the observed differences in wages in the SC and B2C categories.
4.3.1 Measuring the Labor Composition across Industry Categories
Prior work has examined the labor composition of industries (see e.g., Glaeser and Kerr,
2009; Delgado, Porter, and Stern, 2016). Similarly, we use the Occupational Employment
Statistics (OES) Survey administered by the Bureau of Labor Statistics (BLS; 2009 data) to
determine the labor occupation composition of each of the industries in our dataset. The OES
data provides 792 non-governmental occupations and information on the prevalence of these
occupations for each industry. For example, consider the Computer Software Engineers,
Applications occupation o. The OES data provides the percentage of that occupation in the total
occupational employment of each NAICS industry i (Occupationoi =empoi/empi).9 We aggregate
9
We are using 7-digit Standard Occupational Classification (SOC) and 4-digit NAICS data because of better coverage.
The data can be accessed at http://www.bls.gov/oes/oes_dl.htm. A limitation of this measure is that occupation
data is aggregated at the 4-digit NAICS level (i.e., industries with the same 4-digit NAICS will have the same
occupational composition).
14
the occupation-industry data into our occupation-categories using weighted averages (i.e.,
weighting by the employment size of each industry). For example, the percentage of occupation
o in the employment of the SC category is computed as follows:
empoi
empi
*Occupationoi  
iSC empSC
iSC empSC
SC Occupationo,2009 =
(1)
where empi and empSC are the employment in industry i and in the SC category; and Occupationoi
is the percentage of occupation o in industry i employment. For example, Computer Software
Engineers, Applications occupation accounts for 1% of the occupational employment in SC. This
analysis allows us to identify the top occupations for each category (and sub-category) as
reported in Table 3.
Furthermore, we identify the sub-set of STEM and engineer occupations in each industry
category using Hecker’s (2005) STEM definition. He identifies 81 STEM occupations, and 28 of
them we categorize as engineering occupations (i.e., those with the word "engineer" in the title
-- e.g., Computer Software Engineers, Applications).10 These definitions allow us to examine the
importance of STEM occupations (a proxy for technology intensity) in the supply chain and B2C
economy. For example, the percentage of STEM occupations in the employment of the SC
category is computed as follows:
SC STEM2009 =
empoi
  emp
oSTEM iSC
(2).
SC
4.3.2 STEM Occupations
Table 2 shows the importance of STEM occupations in different segments of the economy
(i.e., the percentage of occupational employment accounted by total STEM occupations and by
the sub-set of engineers). We find that SC industries have a much larger relative presence of
10
Based on Hecker (2005; p. 58), the following Standard Occupational Classification codes (SOC) are classified as
“high-technology occupations” (i.e., STEM): Computer and mathematical scientists (SOC 15-0000); engineers (SOC
17–2000); drafters, engineering, and mapping technicians (SOC 17–3000); life scientists (SOC 19–1000); physical
scientists (SOC 19–2000); life, physical, and social science technicians (SOC 19–4000); computer and information
systems managers (SOC 11–3020); engineering managers (SOC 11–9040); and natural sciences managers (SOC 11–
9120).
15
STEM and engineering occupations than B2C industries. The gap is larger for STEM (11.2% versus
1.5%) than engineers (5.6% versus 0.3%). STEM and engineering occupations are also more
prevalent in SC-Traded industries than in B2C-Traded industries (15% versus 4.7% in STEM and
7.6% versus 1.1% in engineers).
We find that STEM and engineering occupations are very prevalent in suppliers of traded
services (17% and 7.3%). Surprisingly, STEM occupations are more important for SC Traded
industries in services than in manufacturing (17% versus 11%); and engineering occupations are
very meaningful in both types of traded suppliers (7.3% versus 8.3%). This suggests that suppliers
of traded services have high technology intensity.
4.3.3 Top Occupations in SC vs. B2C Industries
While STEM occupations matter for SC Traded industries, other types of occupations also
matter within this category. Table 3a reports the top-10 occupations for the manufacturing and
services subcategories of the SC Traded segment; and Table 3b reports the top-10 occupations
for B2C Traded subcategories. Together, Tables 3a and 3b suggest that the labor occupations
differ between SC and B2C industries in ways besides the prevalence of STEM occupations.
Comparing subcategory pairs where the only definitional difference is the SC/B2C designation
(e.g. SC Traded Manufacturing vs. B2C Traded Manufacturing) reveals that supplier industries are
composed of different labor occupations than B2C industries. For industries coded as both traded
and manufacturing, those that are also SC have top-occupations in more traditional durable
goods-producing jobs: machinists, welders, and maintenance/repair workers. However, B2C
Traded Manufacturing jobs are weighted more towards final-good packaging activities and food
processing activities: packaging machine operators, food packagers, and meat packers.
What are the top-occupations in SC Traded Services (the part of the supply chain economy
with the highest wages)? As mentioned earlier, STEM is a very meaningful part of the labor
composition of SC Traded Services (e.g., Computer Software Engineers accounts for 2% of all
occupational employment). But not all the occupations in this segment are STEM. Logistics (e.g.,
Truck Drivers (3.1%) and warehouse related occupations (3.4%)); accounting (Accountants and
Auditors (2.4%), Bookkeeping Clerks (2.2%)), and managerial occupations (e.g., General and
16
Operations Managers (2.2%)) are also important to the category’s labor composition. While
differences persist between the top-occupation lists for SC Traded Services and B2C Traded
Services, interestingly, certain lower-skill occupations (i.e., those that require a high school
degree or less) feature prominently in both categories: Customer Service Representatives, Office
Clerks, and general Laborers and movers.11
Finally, there are relevant differences in the labor occupation composition of the three
subcategories of the local economy: Healthcare, SC Main Street and B2C Main Street (Table 3c).
Healthcare is the part of the local economy that registered the highest wages. Unsurprisingly, the
top occupations in this segment include nurses (e.g., Registered Nurses (14.3%)), medical aides,
and orderlies. SC Main Street industries show top-occupations that cover an array of low-skill
jobs such as Janitors and Cleaners (4.7%), Security Guards (3.7%), Truck Drivers (3.7%), and
Construction Laborers (3.6%). In contrast, B2C Main Street industries (the sub-category with the
lowest wages) show top occupations primarily related to low-skill retail and food-service (e.g.
Retail Salespersons (6.9%), Cashiers (5.8%), Food Preparation & Serving Workers (4.5%), and
Waiters (3.8%)) and healthcare (e.g., Registered Nurses (4.1%)).
5. The Role of the Supply Chain Economy in National Growth
In this section we examine the growth in employment, real wages, and patenting of the
SC and B2C categories and subcategories to understand the evolution of the US economy from
1998 to 2013. There has been a shift in the traded economy out of manufacturing into supply
chain services during 1998–2013. The SC Traded Service category is the part of the traded
economy that has registered high growth in employment and in wages. While there has been a
large decline in employment in SC Traded Manufacturing, patenting activity remains highly
concentrated in this subcategory. In the local economy, the Healthcare category shows high
growth in employment and wages. Whereas the SC Main Street category registers low growth in
11
The data do not allow us to determine whether these shared occupations within traded services vary in their skill
level and/or wages depending on a given industry’s status as SC or B2C.
17
employment and wages; and the B2C Main Street category shows high growth in employment
but negative growth in wages.12
5.1 Employment Growth, 1998–2013
The employment size in 1998 and 2013 and the growth over that time period for each
industry category is reported in Table 4. Across the six broad categories, Manufacturing shows
the highest decline in the share of total employment during the 1998–2013 period (from 16% to
10%). The share of total employment in SC industries has declined by 2% (from 39% to 37%).
The SC Traded category experienced a decline of 1% in its share of total employment and
low employment growth (4% versus 10% in the total economy during the 1998–2013 period).
Employment within the SC Traded category has evolved away from manufacturing and towards
services during this period. This evolution is illustrated in Figure 5c. SC Traded Manufacturing
registered a large negative growth of -44%. In contrast, SC Traded Services registered the largest
growth across all the categories (34%) and had the highest increase in the share of total
employment (from 12% in 1998 to 16% in 2013). Within the B2C Traded category, manufacturing
also registered a large negative growth (-37%) accompanied by a more moderate increase in B2C
Traded Services (10%).
In the local economy, the Healthcare category experienced high growth in employment
from 1998-2013 (25%). This is the only segment displaying a positive growth every year, including
the recession years (see Figure 5b). The B2C Main Street category showed moderate growth
(14%), but the suppliers in Main Street registered low growth (6%).
Overall, the analysis suggests that the employment composition of the SC Traded
economy has changed in recent years. Industries related to consulting, design, software
development, and other services are creating many jobs. While many manufacturing jobs were
lost in our period (and in the decades prior), the supply chain economy is not decimated. It has
evolved towards high value services that leverage a highly-skilled labor force.
12
The analysis presented in this section uses our core SC industry definition (PCE<33%), but the same findings hold
when we use alternative definition of the SC industries (see the Appendix).
18
5.2 Wage Growth, 1998–2013
The growth in real wages (2013 USD) for each industry category is reported in Table 5.
Across the six broad categories, the Traded category registered the highest growth during the
1998-2013 period (15% compared to 9% for the total economy), followed by the Supply Chain
category (13%).
When we compare the employment and wage trends (Table 4 versus Table 5), our
descriptive analysis shows that the overall SC Traded Services subcategory is the part of the
economy experiencing both high growth in employment and in real wages. It is also the part of
the economy with the largest average wages. Overall, these findings suggest that in aggregate
the SC Traded Services category is the part of the economy that is disproportionately creating
high-paying jobs. Identifying the underlying causes of this superior performance in the suppliers
of traded services is an area for future research.
In the local economy, Healthcare registered high employment and wage growth over the
period. The Healthcare category has been rapidly creating new jobs with average wages. In
contrast, B2C Main Street employment grew faster than the total economy during 1998-2013
(with a growth rate of 14%), but this was the only category that experienced a decline in real
wages (with a growth rate of -1%). In both 1998 and 2013, this subcategory has the lowest wages.
This suggests that the B2C Main Street segment is creating many jobs, but those jobs have the
lowest wages. This result sheds light on recent studies that find an increase in low-skill service
jobs in the economy (Autor and Dorn, 2013).
5.3 Growth in Employment and Wages during the Business Cycles
In this section we examine the annual growth during the 1998–2013 business cycles for
each industry category (see Table 6 and Figure 6). During this time period there are two economic
crisis (2001-2002 and 2007–2009) allowing us to better assess how the supply chain economy
responds to shocks.13
13
The NBER’s Business Cycle Dating Committee determined that the 2001 recession took place between March and
November; and the Great Recession years were December 2007 through June 2009 (see www.nber.org/cycles.html).
It is important to note that the CBP annual employment data corresponds to mid-March. The recession period using
this data corresponds to the years 2000, 2001 and the years 2008 and 2009.
19
Figure 6 illustrates the annual growth in employment (Figure 6a) and in wages (Figure 6b)
for the SC and B2C categories. This analysis reveals that the Supply Chain economy is very cyclical.
It has experienced a higher contraction in (employment and wage) growth than the B2C
industries in both crises. In other words, during a crisis the annual growth of the SC category is
lower than that of the B2C category, but in the pre- and post-recession periods the SC category
tends to grow faster than the B2C category. For example, Table 6 shows that during the last
business cycle, the average annual employment growth in the pre-crisis period (2002–2007) was
2% in the SC category versus 1.3% in the B2C category. Then during the Great Recession (2007–
2009), the average annual employment growth was -5.4% in the SC category versus -0.9% in the
B2C category. In the post-recession period (2009–2013) both have the same average growth
(0.8%), and after 2009 the growth is higher for the SC category (Figure 6a).
The SC Traded category is also more vulnerable than the B2C Traded category, both in
terms of employment and wage growth (Table 6). In the local economy, SC Main Street is more
vulnerable than B2C Main Street in terms of employment growth. However, in terms of real
wages, B2C Main Street is more vulnerable. It shows a large wage contraction in both crises, and
especially during the Great Recession.
The vulnerability of suppliers implied by these findings calls for targeted policies. For
example, the Obama Administration’s QuickPay initiative in 2011 aimed to reduce the working
capital costs of small suppliers to the government, and was later broadened as SupplierPay, an
initiative for any type of small supplier (Helper, Nicholson, and Noonan, 2015).
5.4 Patenting Growth, 1998–2013
Where is patenting in the U.S .economy happening? To answer this question, the utility
patents granted in 1998 and 2013 for each industry category is reported in Table 7.14 We find
that patenting is primarily concentrated in the SC industries, with 81% of all granted patents in
2013 (78% in 1998). Within the supply chain economy, patenting is concentrated in SC Traded
Manufacturing industries (77% of US patents in 2013). While there has been a large decline in
14
The number of patents in each category is somewhat noisy given the complexity in matching the patents’
technology classes to industry codes (see Section 3). However, this analysis offers a good insight on the relative
patenting size of each category.
20
employment in SC Traded Manufacturing during 1998–2013, patenting remains highly and
increasingly concentrated in this sub-category (from 73% to 77%).
Overall the number of patents granted in the U.S. economy has increased significantly
during 1998–2013 (45% growth rate). The Supply Chain economy experienced a large growth
(49%) and the B2C economy a slow growth (29%). SC Traded Manufacturing industries registered
the largest growth in the flow of patenting (50%).
While it is not surprising that patenting is concentrated in manufacturing, it is insightful
that most patenting is taking place in the suppliers of manufacturing goods. This finding supports
the view that manufacturing capacity is important for innovation. However, there is a big
difference between the STEM content and the patenting of the different segments of the supply
chain economy. While STEM occupations are most prevalent in suppliers of traded services, this
sub-segment only accounts for 2% of all the patents. This suggests that the knowledge and
technology intensity of the suppliers of traded services is much higher than suggested by
patenting measures. These findings support the need for new measures of innovation for service
industries that take into account their STEM content and their input-output links with high
patenting industries.
Overall, our findings support the idea that the production capacity of a country is broader
than its manufacturing capacity of final goods, and includes both manufacturing and service
suppliers. The majority of traded suppliers are in services industries. This segment of the supply
chain economy has the highest wages, has a very large presence of STEM occupations, and has
experienced a high growth.
6. Conclusion
This paper identifies the boundaries of the supply chain economy in the U.S. and sheds
some light on the role of suppliers in national performance. To do so, we establish a new
categorization that separates SC industries from B2C industries based on observable measures
of industry-level sales to personal consumption provided in the Input-Output Accounts. We find
that the supply chain economy is large, contains relatively high-paying jobs, has a larger presence
of STEM occupations, and generates the majority of patents. Furthermore, we find that the
21
subcategory of supply chain traded services is very large and an important contributor to the
employment and wage growth of the U.S. economy. A diverse set of labor occupations are
important for the suppliers of traded services. They have the largest relative presence of STEM
occupations, but other occupations (e.g., managerial, accounting, finance, and logistics
occupations) are also important for suppliers of traded services.
Our industry categorization helps to better diagnose and understand the production
capacity of the economy. It complements the Manufacturing versus Services categorization that
has heavily influenced economists and policymakers since the 19 th century. One of the legacies
of the latter classification is that the study of the supply chain economy has often been limited
to manufacturing suppliers. Instead, our categorization establishes a definition of supplier
industries that is inclusive of both manufacturing and services. Thus, we are able to provide a
more accurate representation of the production capacity of the U.S. We find that a significant
portion of this part of the economy resides in the service sector.
Our categorization also complements the Traded versus Local distinction that is crucial in
explaining regional and national competitiveness. By identifying suppliers within the local and
traded economies we are able to focus on those industries that provide the intermediate inputs
to grow the economy and pay higher wages. We also find that the employment in the traded
economy has evolved from manufacturing into supply chain services, which have registered high
growth in employment and wages.
Finally, the growth analysis during the 1998-2013 business cycles reveals that the supply
chain economy has experienced larger contraction in growth than the B2C economy in both crises
periods (2001-2002 and 2007-2009). While the supply chain economy is a driver of innovative
activity in the economy (i.e., accounts for the majority of patents and contains a large presence
of STEM occupations), it is particularly susceptible to economic crises, and as such deserves
policies that recognize its importance and vulnerability.
The new categorization of the US economy described in this paper has important
implications for policy. The supply chain has long been a focus of the federal government
manifested primarily through its procurement activities. Suppliers are recognized as important
sources of innovation, as past investments in major research projects by the federal government
22
that were buttressed by private-sector suppliers often resulted in important commercial
applications down the road (e.g., GPS). The ability to define and measure the total category of
suppliers and to evaluate the dynamics of its segments— in particular the suppliers of traded
services—improves the ability of policymakers to define and assess new programs. Policies need
to recognize the evolution of the supply chain economy from manufacturing into services. For
example, skills training initiatives should take into account the broader range of labor
occupations in the growing supply chain traded services segment, in addition to traditional STEM
occupations. Trade agreements could potentially be analyzed in terms of their impact on the
supply chain economy. In the private sector, policies that encourage larger companies to create
partnerships with and invest in their domestic supply chains also have potential to bolster growth
and resilience in this critical part of the economy. The SupplierPay initiative that encourages
private firms to reduce the working capital costs of their small suppliers is one example of this
type of policy (Helper, Nicholson, and Noonan, 2015).
Our analysis offers many directions for future research aimed at informing policies
focused on fostering the innovation and production capacity of a country and its regions. First,
future research could characterize the SC and B2C industries based on other relevant input and
outcomes, like capital intensity, exports-imports, and entrepreneurship.
Second, building on our analysis of the labor occupations that support the supply chain
economy, a related line of inquiry relates to the evolution of the labor occupation composition
within the supply chain economy. For example, we could examine whether the importance of
STEM and other occupations in suppliers of traded services has changed over time. Such research
would have implications for labor and education policies (Autor, 2015).
Third, future research might assess the attributes of a location that foster the growth of
the supply chain economy. For example, suppliers are more likely to develop linkages with nearby
buyers and these inter-firm linkages are fostered in clusters. Hence, they could especially benefit
from proximity to other related businesses within regional clusters (Delgado, Porter, and Stern,
2016).
Another important question in need of exploration is the role of the supply chain
economy in regional performance. We expect that the presence of suppliers could increase the
23
subsequent growth of a region. Suppliers that are agglomerated with their buyers (i.e., they
participate in strong regional clusters) can provide specialized inputs to regional businesses and
improve regional performance. A particular mechanism to test is the role of suppliers of different
types (small versus large, single-location versus multi-location, young versus old, etc.) in the
innovation and entrepreneurial activity of a region. Supplier-buyer linkages in a location have
been associated with entrepreneurship in manufacturing industries (Glaeser and Kerr, 2009); and
a recent study finds that firms often collaborate with their suppliers in order to develop new-tothe-market products (Arora, Cohen, and Walsh, 2014). Future work should examine the role of
suppliers in the innovation ecosystem of regions.
Finally, understanding the broad implications for firm strategy and performance of being
a supplier versus a B2C firm is a fruitful area for future research. The organization and operation
of a firm’s value chain can depend on whether the firm is B2B versus B2C (McElheran, 2015).
Location choices can also depend on the type of firm. Suppliers can benefit especially from being
co-located with their buyers (Delgado, Porter, and Stern, 2016). Relatedly, while firms in many
industries are clearly suppliers (e.g., semiconductors and engineer services), in other industries,
a firm’s product can be B2B or B2C depending on the go-to-market channel used by the firm. For
example, some medical devices (e.g., a non-contact thermometer) can be sold through hospitals
(B2B) or retailers (B2C). Thus, being a B2B or B2C firm can be an important strategic choice.
24
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26
Figure 1: Industry Categorizations of the U.S. Economy, 2012
Manufacturing
Average wage
Employment
No. of Firms
All industries
Average wage
Employment
No. of Firms
$46,802
115,930,680
5,845,229
$53,466
11,192,043
266,915
Services
Average wage
Employment
No. of Firms
$46,087
104,738,640
5,578,314
Traded
Average wage
Employment
No. of Firms
All industries
Average wage
Employment
No. of Firms
$46,802
115,930,680
5,845,229
$65,926
41,550,344
1,483,728
Local
Average wage
Employment
No. of Firms
All industries
Average wage
Employment
No. of Firms
$36,033
74,380,336
4,361,501
Supply Chain
Average wage
Employment
No. of Firms
$60,762
42,762,268
2,495,875
$46,802
115,930,680
5,845,229
B2C (Business-to-Consumer)
Average wage
$38,568
Employment
73,168,408
No. of Firms
3,349,354
New categorization framework
of U.S. industries
Notes: Private Employment, excluding self-employed. Employment and wages are sourced from CBP data, and the number of firms is sourced from the 2012
Economic Census. The Services category includes non-manufacturing goods (Agriculture, Forestry, Fishing and Hunting; Mining; and Construction).If we compute
services excluding all goods the employment decline slightly to 98.6 millions and average wages to $45,486.
Figure 2: The Supply Chain versus B2C Categorization, 2012
All industries
Average wage
Employment
No. of Firms
Supply Chain Traded Service
industries are a large part of the
U.S. Economy
Supply Chain Traded Services
Average wage
$80,210
Employment
17,756,554
No. of Firms
755,618
Supply Chain
Average wage
Employment
No. of Firms
Supply Chain Traded
Average wage
$72,865
Employment
25,663,542
No. of Firms
924,186
$60,762
42,762,268
2,495,875
Supply Chain Local
Average wage
$42,624
Employment
17,098,728
No. of Firms
1,571,689
Supply Chain Traded Mfg
Average wage
$56,361
Employment
7,906,988
No. of Firms
168,568
$46,802
115,930,680
5,845,229
``
B2C (Business-to-Consumer)
Average wage
$38,568
Employment
73,168,408
No. of Firms
3,349,354
B2C Local
Average wage
Employment
No. of Firms
$34,042
57,281,608
2,789,812
B2C Traded
Average wage
Employment
No. of Firms
$54,715
15,886,802
559,542
B2C Traded Services
Average wage
$56,006
Employment
13,390,282
No. of Firms
510,509
27
B2C Traded Mfg
Average wage
Employment
No. of Firms
$47,741
2,496,520
49,033
Table 1. Examples of SC and B2C Industries.
Traded Mfg
Traded Services
Local (Main Street)
SC
B2C
SC
B2C
Biological
Products
Pharmaceutical
Preparation
Engineering
Services
Computer
Training
NAICS (2012)
325414
325412
541330
611420
561320
722511
% sold to PCE
0%
71%
0%
91%
0.5%
81%
Industry
Name
SC
B2C
Temporary Help Full-Service
Services
Restaurants
Notes: PCE is Personal Consumption Expenditure.
Figure 3. Where are the Good Jobs?: Average Wages, 2013
Note: Nominal Wages. %s in parentheses represent percent of total private employment in 2013.
Figure 4. Wage Distribution Across SC Traded Service Industries
28
Table 2. The Importance of STEM Occupations across Categories in 2009
Total
Manufacturing (Mfg)
Services (Svc)
Traded
Local
Supply Chain (SC)
B2C
SC Traded
B2C Traded
SC Traded Mfg
SC Traded Svc
B2C Traded Mfg
B2C Traded Svc
SC Local
B2C Local
SC Main Street
B2C Main Street
Healthcare
% of Employment in STEM
4.9
9.0
4.4
11.8
1.2
11.2
1.5
15.0
4.7
11.0
17.2
4.6
4.7
3.3
0.8
3.3
0.8
0.9
% of Employment in Engineers
2.2
6.4
1.6
5.6
0.4
5.6
0.3
7.6
1.1
8.3
7.3
1.8
0.9
1.3
0.2
1.3
0.2
0.1
Notes: Data sourced from BLS (2009). We use Hecker’s (2005) definition of STEM occupations.
Table 3a. Top-10 Labor Occupations in Supply Chain Traded Sub-categories
SC Traded Mfg, % Employment
Team assemblers
First-line supervisors/managers of production
workers
Machinists
Inspectors, testers, sorters, samplers, and weighers
Welders, cutters, solderers, and brazers
Helpers--production workers
Laborers & freight, stock, and material movers, hand
Maintenance and repair workers, general
Cutting, punching, and press machine setters,
operators, and tenders, metal and plastic
Sales representatives, Wholesale & mfg *
Top-10 Occupations
6.4
3.7
2.6
2.5
2.2
2.2
2.1
1.8
1.8
1.7
27.1
SC Traded Svc, % Employment
Customer service representatives
Laborers and freight, stock, and material movers,
hand
Office clerks, general
Truck drivers, heavy and tractor-trailer
Accountants and auditors
Bookkeeping, accounting, and auditing clerks
General and operations managers
Executive secretaries and administrative assistants
Computer software engineers, applications
Computer systems analysts
3.6
3.4
3.1
3.1
2.4
2.2
2.2
2.1
2.0
1.7
25.9
*
except technical & scientific products. Data sourced from BLS (2009).
Table 3b. Top-10 Labor Occupations in Business-to-Consumer Traded Sub-categories
B2C Traded Mfg, % Employment
Team assemblers
Packaging & filling machine operators and tenders
Meat, poultry, and fish cutters and trimmers
Slaughterers and meat packers
First-line supervisors/managers of production
workers
5.7
5.1
5.0
3.5
Laborers & freight, stock, & material movers, hand
Helpers--production workers
Packers and packagers, hand
Food batchmakers
3.0
2.6
2.6
2.3
Industrial truck and tractor operators
Top-10 Occupations
*
3.3
2.2
35.2
B2C Traded Svc, % Employment
Sales representatives, Wholesale & mfg,*
Customer service representatives
Maids and housekeeping cleaners
Office clerks, general
Laborers & freight, stock, & material movers, hand
Sales representatives, wholesale and mfg,
technical & scientific products
Bookkeeping, accounting, and auditing clerks
General and operations managers
Hotel, motel, and resort desk clerks
First-line supervisors/managers of office and
administrative support workers
except technical & scientific products. Data sourced from BLS (2009).
29
4.8
3.9
3.4
2.7
2.3
1.9
1.7
1.7
1.7
1.6
25.6
Table 3c. Top-10 Labor Occupations in Local Economy
Healthcare, % Employment
Registered nurses
Nursing aides, orderlies, &
attendants
Home health aides
Licensed practical & vocational
nurses
Medical assistants
Medical secretaries
Receptionists & information
clerks
14.3
8.4
SC Main St., % Employment
Janitors and cleaners*
4.7
Security guards
3.7
drivers**
5.3
Truck
4.0
3.0
2.9
Construction laborers
Office clerks, general
Carpenters
Laborers & freight, stock, and
material movers, hand
Landscaping & groundskeeping
workers
Electricians
Accountants and auditors
2.6
3.7
Office clerks, general
2.1
Dental assistants
1.8
Personal and home care aides
1.8
Top-10 Occupations
46.0
*Except maids and housekeeping cleaners. **heavy & tractor-trailer.
3.6
3.3
3.3
3.2
2.7
2.5
2.3
33.0
B2C Main St., % Employment
Retail salespersons
6.9
Cashiers
Food preparation and serving
workers, including fast food
5.8
Registered nurses
Waiters and waitresses
Stock clerks and order fillers
Nursing aides, orderlies, &
attendants
First-line supervisors/
managers of retail workers
Home health aides
Office clerks, general
4.1
3.8
2.4
4.5
2.4
1.8
1.8
1.7
35.1
Table 4. Employment Trends across Categories, 1998-2013
Total
Manufacturing (Mfg)
Services (Svc)
Traded
Local
SC
B2C
SC Traded
B2C Traded
SC Traded Mfg
SC Traded Svc
SC Traded Svc*
B2C Traded Mfg
B2C Traded Svc
SC Local
B2C Local
SC Main Street
B2C Main Street
Healthcare
1998
Emp (mill) % Total
107.1
100%
16.9
16%
90.2
84%
41.4
39%
65.7
61%
41.8
39%
65.3
61%
25.5
24%
16.0
15%
12.3
12%
13.1
12%
11.9
11%
3.7
3%
12.3
11%
16.4
15%
49.3
46%
16.3
15%
36.4
34%
12.9
12%
2013
Emp (000s) % Total
118.3
100%
11.3
10%
107.0
90%
42.6
36%
75.7
64%
43.9
37%
74.4
63%
26.5
22%
16.1
14%
8.0
7%
18.5
16%
17.1
14%
2.5
2%
13.6
11%
17.4
15%
58.3
49%
17.4
15%
41.8
35%
16.6
14%
1998-2013
Change % Growth
Total
0%
10%
-6%
-41%
6%
17%
-3%
3%
3%
14%
-2%
5%
2%
13%
-1%
4%
-1%
1%
-5%
-44%
3%
34%
3%
36%
-1%
-37%
0%
10%
-1%
6%
3%
17%
-1%
6%
1%
14%
2%
25%
Notes: Svc* excludes all non-mfg goods (Agriculture, Forestry, Fishing and Hunting; Mining; and Construction).
30
Table 5. Average Wage Trends across Categories, 1998-2013 (in 2013 USD)
Total
Manufacturing (Mfg)
Services
Traded
Local
SC
B2C
SC Traded
B2C Traded
SC Traded Mfg
SC Traded Svc
SC Traded Svc*
B2C Traded Mfg
B2C Traded Svc
SC Local
B2C Local
SC Main Street
B2C Main Street
Healthcare
Wage
43,578
51,222
42,141
57,698
34,675
54,404
36,643
63,212
48,910
53,734
72,147
73,912
44,594
50,189
40,712
32,670
40,721
29,100
42,758
1998
% Total
100%
118%
97%
132%
80%
125%
84%
145%
112%
123%
166%
170%
102%
115%
93%
75%
93%
67%
98%
Wage
47,664
54,241
46,967
67,244
36,550
61,716
39,287
73,858
56,392
56,962
81,134
81,692
49,010
57,752
43,322
34,495
43,332
28,871
48,400
2013
% Total
100%
114%
99%
141%
77%
129%
82%
155%
118%
120%
170%
171%
103%
121%
91%
72%
91%
61%
102%
1998–2013
Growth
9%
6%
11%
15%
5%
13%
7%
16%
14%
6%
12%
10%
9%
14%
6%
5%
6%
-1%
12%
Notes: Real wages in 2013 US Dollars. Wages adjusted using CPI-U (All Urban Consumers; BLS).
Table 6. Annual Growth during the Business Cycle (Pre-crisis, Crisis, Post-crisis)
Total
SC
B2C
SC Traded
B2C Traded
SC Main Street
B2C Main Street
Healthcare
Average Annual Employment Growth
1998– 2000– 2002– 2007– 2009–
2000
2002
2007
2009
2013
2.6%
-0.7%
1.6%
-2.6%
0.8%
3.7%
-2.7%
2.0%
-5.4%
0.8%
1.9%
0.6%
1.3%
-0.9%
0.8%
2.6%
-3.0%
1.8%
-4.3%
1.0%
1.6%
-2.0%
0.4%
-1.2%
0.5%
5.4%
-2.3%
2.4%
-7.0%
0.5%
2.5%
1.0%
1.4%
-1.6%
0.7%
0.5%
2.5%
2.1%
1.5%
1.3%
Average Annual Wage Growth
1998– 2000– 2002– 2007– 2009–
2000
2002
2007
2009
2013
2.5%
-0.6%
0.8%
-0.9%
0.7%
2.6%
-0.8%
1.0%
-0.8%
1.5%
1.9%
0.3%
0.5%
-0.1%
0.1%
3.8%
-2.1%
1.4%
-1.3%
1.9%
2.6%
-0.2%
1.1%
-0.3%
1.2%
0.8%
2.2%
0.2%
-0.7%
0.2%
2.3%
-0.1%
-0.3%
-1.2% -0.3%
0.9%
2.4%
0.9%
1.3% -0.3%
Table 7. Utility Patents Granted by Category (USPTO, 1998, 2013)
Total
SC
B2C
SC Traded
B2C Traded
SC Traded Mfg
SC Traded Svc
B2C Traded Mfg
B2C Traded Svc
SC Main Street
B2C Main Street
Healthcare
Patent
79,066
61,329
17,738
58,990
10,700
57,544
1,446
9,823
877
2,305
1,703
5,369
1998
% Total
100%
78%
22%
75%
14%
73%
2%
12%
1%
3%
2%
7%
Patent
123,621
100,021
23,601
97,098
13,390
94,926
2,172
12,212
1,178
2,881
1,989
8,263
31
2013
% Total
100%
81%
19%
79%
11%
77%
2%
10%
1%
2%
2%
7%
1998–2013
Change
Growth
0%
45%
3%
49%
-3%
29%
4%
50%
-3%
22%
4%
50%
0%
41%
-2%
22%
0%
30%
-1%
22%
0%
16%
0%
43%
Figure 5. Annual Employment by Industry Category (indexed to 1998 level), 1998–2013
Fig. 5a. Employment Growth: Six Categories
Fig. 5b. Employment Growth: SC/B2C and Traded/Local Subcategories
Fig. 5c. Employment Growth: SC/B2C and Traded-Mfg/Traded-Svc Subcategories
32
Figure 6. Annual Growth in the SC versus B2C Economy 1998–2013
Figure 6a. Annual Employment Growth in SC vs. B2C, 1998–2013
Figure 6b. Annual Wage Growth in SC vs. B2C, 1998–2013
33
Appendix: Defining Supply Chain vs. Business-to-Consumer Industries
A1.
Classification of industries as Supply Chain versus B2C
Our analysis is based on the 2002 Benchmark Input-Output Accounts of the United States
of the BEA. 15 The Input-Output Accounts have been widely used to capture supplier and buyer
flows between pair of industries (see e.g., Feser, 2005; Glaeser and Kerr, 2009; Delgado et al.,
2016). To our knowledge, we offer the most systematic and comprehensive classification of
industries into Supply Chain (business-to-business and business-to-government) and Businessto-Consumers (B2C).
Building on prior work, we classify all the Input-Output (IO) commodity codes (and their
corresponding NAICS industries) into Supply Chain or B2C based on the value sold to Personal
Consumption Expenditure (PCE).16 The PCE is a final use item in the Input-Output Account that
captures household expenditures. It is the value of the products and services that are directly
purchased by households, such as food, cars, and college education (see Stewart, Stone, and
Streitwieser, 2007). Products and services sold to businesses as intermediate inputs are excluded
from PCE. For example, for the automotive manufacturing industry, cars bought by businesses
are excluded from PCE, while cars bought by households are part of PCE.
For each IO code j we compute the percentage of its total value sold to PCE, which takes
a minimum value of zero if j does not sell to PCE, and a maximum of 100 if it sells exclusively to
PCE. For sensitivity, we also compute for each IO code the percentage sold to other comodities
(Industry) and to other final use items: Government (Federal Government Defense Investment;
Federal Government Other Investment; and State/Local Government Investment); Private Fixed
Investments (PFI); Change in Private Investment (CPI); and Exports. 17 The IO codes are then
matched into industries (6-digit NAICS codes, 2007 definition) using the bridge provided by the
15
As an extension we plan to implement the analysis using the recently released 2007 I-O Accounts.
There has been some prior efforts to clasify industries as B2B and B2C based on PCE. For manufacturing industries,
McElheran (2015) defines B2C industries as those with PCE>75%.
17
A detailed definition of these items is available at the I-O manual. PFI consists of investment by private business
and nonprofit institutions. It includes purchases of new and used equipment and software by businesses. CPI
represents the flow of goods into and out of inventory.
16
34
Input-Output Tables.18 Then, we know for each industry the percent of its output sold across the
I-O Account items. For example, the Full-Service Restaurants industry sells 81% to PCE and 19%
to Industries (Table A1).
Choice of the PCE cut-off to define SC industries.
We identify as SC industries those with less than one-third of their output sold to PCE.
Thus, in our definition those IO industries that sell most of their goods and services to other
businesses or the government (i.e., more than two-thirds sold outside PCE) will be classified as
SC, and the rest are classified as B2C. Because we are interested in estimating the size of the
supply chain economy and understand its performance, we use this conservative PCE cut-off to
define SC industries and implement a series of validation tests that we explain below.
Our SC industry definition results in 581 SC and 507 B2C (6-digit) industries based on
NAICS-2007 definitions. To build a timeseries 1998-2013, some industries need to be
consolidated because the NAICS code definition changed during the period.19
Using our core cut-off (PCE<33%), the SC economy accounts for 37% of employment in
2012. We examined the definition of the industries with PCE less than 33%, and corroborated
that their goods and services are primarily oriented to business customers. To illustrate and
validate our core categorization, Table A2 shows the largest SC Industries (Top-20 by
employment). Based on the industry definitions as well as their low PCE scores (<33%) all these
industries seem to be properly categorized as primarily SC. Business-to-Government (B2G)
industries are part of the SC categorization. There are only 3 SC industries that sell the majority
of their value to the government (+50%), and they account for less than 0.4% of the total
employment in the SC economy.20
Some industries are purely supply chain (e.g., Engineering Services has a PCE of 0%) or
B2C (e.g., Religious Organizations have a PCE of 100%). Specifically, 211 industries are purely SC,
and they account for 16% of employment in 2012; and 53 industries are purely B2C and they
18
The input-output data is aggregated above the 6-digit NAICS for some industries (e.g., the NAICS-488000 is
aggregated at the 3-digit level). In those cases, the 6-digit industry codes receive the same PCE score than their
aggregated industry.
19
The 1,088 industries in NAICS-2007 are aggregated into 972 industries.
20
Guided Missile and Space Vehicle manufacturing (NAICS 336414); Military Armored Vehicle, Tank, and Tank
Component manufacturing (NAICS 336992); and Ship Building and Repairing (NAICS 336611).
35
account for 18% of employment. Many industries contain a mix of SC and B2C activities, and we
categorize them as one type based on their main focus. Because our measure of SC is
conservative (less than 1/3 sold to PCE), our estimates of the supply chain economy are likely
downward biased (i.e., it is a lower bound for the actual size). For example, the Hotels and Motels
industry (Table A3) is clasified as a B2C industry (sells 56% to PCE), but a meaningful percent of
its value is sold to businesses. This means that our measurement of the size of the supply chain
economy has some noise.
Sensitivity Analysis: Alternative SC Industry Definitions.
We examined the sensitivity of the size of the supply chain economy to PCE values around
33%. Figure A1 shows the percentage of total employment in industries with PCE scores below
different cut-off values; and Figure A2 shows the number of industries with PCE scores below
different cut-off values. For PCE values between 30% and 35% the accumulated employment
changes minimally from 35% to 37%, and the number of industries from 549-to-584. In the
sensitivity analysis, we consider alternative lower and larger cut-offs to define SC industries. This
analysis is reported in Table A4, which compares the size of the supply chain economy (by
employment and number of firms) and its average wages changes for four alternative definitions
of SC industries.21 Importantly, our main conclussions regarding occupations, average wages,
patenting, and growth trends are robust to using different cut-offs to identify industries that are
primarily SC versus B2C (See Tables A5 and A6).
A2.
Background on I-O Account Methodology
A detailed explanation on how the accounts are built is provided in the I-O manual
(Horowitz and Planting, 2009) and it is beyond the scope of this paper. In this section, we address
some common questions that can help interpret our SC versus B2C industry categorization. It is
important to note that the I-O accounts are built up with establishment level data. Their
methodology assigns establishments to their primary industries.22 Then, industries are broken
21
In the sensitivity analysis, we drop ‘marginal’ industries with a PCE score between 33% and 40% (i.e., they could
be SC or B2C). For example, in the IO data all the wholesaler industries have the same PCE value of 36%.
22
For an establishment that produces multiple commodities, the commodities are divided up into the “primary
product” and the “secondary products.” In the standard I-O Tables that we use, an establishment’s “primary
product” determines its commodity designation. Thus, the total output of a single establishment in a given year only
counts as output in the Use Tables for a single commodity. In the supplementary I-O Tables, an establishment’s
36
down to commodities. This is how they compute the various components of the Use Tables. For
example, consider Amazon. This firm has multiple establishments. Based on Hoovers database,
most of Amazon’s establishments belong to retail and store industries that are primarily B2C; but
it also has some establishments that focus on business-to-business activities, like advertising.
The databases used to build the I-O tables depend on the type of transaction
(intermediate, final use, and value added). The main data sources for intermediate transactions
(i.e., transactions between commodities) are the Census Bureau’s Economic Census and Class of
Customer data. Intermediate transactions are based on establishment-level data where possible.
They include any transformation of the original product, which are registered as intermediate
inputs.23 The final-use fixed-percentage allocations are arrived at through complex analysis and
some art by the I-O analysts who consider a variety of data sources in the process. The allocations
are done at a commodity-level rather than at the establishment-level. For example, when a
commodity is sold to PCE regardless of who produced it, that PCE figure is underpinned by I-O
analysis that uses the Census Bureau’s Class of Customer data and the Consumer Expenditure
Survey from BLS. Calculating other final-use fixed percentages, such as PFI and Government
consumption, have the same general process, but the data that underpins those is different.
Table A1. Selected Examples: Distribution of Value Sold Across the I-O Account Items
NAICS
611420
722110
325412
561320
541330
325414
336414
Name
Computer Training
Full-Service Restaurants
Pharmaceutical Preparation Mfg
Temporary Help Services
Engineering Services
Biological Product Mfg
Guided Missile/Space Vehicle
Type
Traded Svc
Main Street
Traded Mfg
Main Street
Traded Svc
Traded Mfg
Traded Mfg
B2C
B2C
B2C
SC
SC
SC
SC
PCE
91%
81%
71%
1%
0%
0%
0%
Government
0%
0%
0%
0%
0%
0%
75%
PFI
0%
0%
0%
0%
21%
0%
1%
CPI
0%
0%
0%
0%
0%
5%
5%
Exports
0%
0%
8%
0%
4%
13%
8%
Industries
9%
19%
21%
99%
75%
82%
11%
Notes: Percent of industry value supplied to: Personal Consumption Expenditure (PCE); Government; Private fixed
investment (PFI); Change in private inventories (CPI); Exports; and to Industries (NAICS).
output is distributed across multiple commodities using a somewhat noisy reallocation process. (See Chapter 9 in
Horowitz and Planting (2009) for a description of this process).
23
For example, to the extent that the private labels by an establishment do some transformation of the orginal
product they are recorded as an intermediate input (i.e., they are excluded from PCE).
37
Table A2. Largest Supply Chain Industries: Top-20 by Employment in 2013
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
NAICS-2012 Name
Traded
551114 Corporate, Subsidiary, and Regional Managing Offices
1
561320 Temporary Help Services
0
561330 Professional Employer Organizations
1
541330 Engineering Services
1
561720 Janitorial Services
0
238220 Plumbing, Heating, and Air-Conditioning Contractors
0
238210 Electrical Contractors
0
541511 Custom Computer Programming Services
1
561612 Security Guards and Patrol Services
0
524210 Insurance Agencies and Brokerages
0
541512 Computer Systems Design Services
1
493110 General Warehousing and Storage
1
561730 Landscaping Services
0
492110 Couriers
0
518210 Data Processing, Hosting, and Related Services
1
236220 Commercial and Institutional Building Construction
0
541712 R&D in the Physical, Engineering, and Life Sciences (except Biotechnology)
1
541611 Administrative Management and General Management Consulting Services
1
484121 General Freight Trucking, Long-Distance, Truckload
1
541211 Offices of Certified Public Accountants
0
Emp, 2013
2,997,059
2,957,497
2,001,857
1,028,083
965,304
840,511
709,731
707,004
674,604
656,079
618,917
613,677
547,533
488,990
488,879
484,647
482,819
475,071
469,369
446,782
SC=1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
% sold to PCE
0.0%
0.5%
0.5%
0.0%
10.0%
0.0%
0.0%
0.0%
23.0%
0.0%
0.0%
0.7%
10.0%
2.2%
0.0%
0.0%
16.8%
0.0%
27.1%
13.7%
Emp, 2013
5,300,436
4,896,174
3,771,189
2,482,664
2,224,264
1,827,587
1,687,013
1,685,205
1,615,866
1,488,512
1,420,442
1,275,229
1,068,937
1,010,052
937,944
932,486
880,733
862,043
746,433
739,694
SC=1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
% sold to PCE
99.9%
81.1%
81.1%
87.7%
100.0%
96.2%
100.0%
100.0%
43.8%
56.1%
87.7%
100.0%
41.2%
87.7%
100.0%
100.0%
100.0%
100.0%
49.3%
87.7%
Table A3. Largest B2C Industries: Top-20 by employment in 2013
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
NAICS-2012 Name
622110 General Medical and Surgical Hospitals
722511 Full-Service Restaurants
722513 Limited-Service Restaurants
445110 Supermarkets and Other Grocery (except Convenience) Stores
621111 Offices of Physicians (except Mental Health Specialists)
611310 Colleges, Universities, and Professional Schools
623110 Nursing Care Facilities
813110 Religious Organizations
522110 Commercial Banking
721110 Hotels (except Casino Hotels) and Motels
452910 Warehouse Clubs and Supercenters
621610 Home Health Care Services
541110 Offices of Lawyers
441110 New Car Dealers
611110 Elementary and Secondary Schools
624120 Services for the Elderly and Persons with Disabilities
621210 Offices of Dentists
624410 Child Day Care Services
517110 Wired Telecommunications Carriers
447110 Gasoline Stations with Convenience Stores
Traded
0
0
0
0
0
1
0
0
0
1
0
0
0
0
0
0
0
0
0
0
Table A4. Supply Chain Economy Size for Alternative SC Definitions (2012)
SC Industry Def.
SC Employ (Mill) % Total
SC No. Firms (000s)
PCE=0%
18.7
16%
1,355
PCE<25%
38.8
33%
2,082
PCE<33% (Core)
42.8
37%
2,494
PCE<40%
49.2
42%
2,851
PCE<50%
54.6
47%
3,070
Notes: No. of industries based on 2003-2012 bridge of 6-digit NAICS codes.
38
% Total
23%
32%
43%
49%
52%
SC No. Industries
211
466
511
599
635
Table A5. Employment Trends across Categories: Alternative SC Definitions
SC
B2C
SC Traded Mfg
SC Traded Svc
B2C Traded Mfg
B2C Traded Svc
SC Main Street
B2C Main Street
Employment 2013 (% Total)
SCPCE<33
SCPCE<40
SCPCE<50
37%
43%
47%
63%
57%
53%
7%
7%
7%
16%
20%
20%
2%
2%
2%
11%
8%
7%
15%
16%
20%
35%
34%
30%
Employ Growth 2003–2013
SCPCE<33
SCPCE<40
SCPCE<50
1%
1%
0%
6%
7%
8%
-22%
-23%
-22%
14%
11%
11%
-25%
-25%
-26%
5%
8%
8%
0%
0%
-2%
5%
6%
8%
Table A6. Average Wage Trends across Categories (in 2013 USD): Alternative SC Definitions
Wage 2013
Growth 2003–2013
SC
B2C
SC Traded Mfg
SC Traded Svc
B2C Traded Mfg
B2C Traded Svc
SC Main Street
B2C Main Street
SCPCE<33
61,716
39,287
56,962
81,134
49,010
57,752
43,332
28,871
SCPCE<40
62,053
36,808
57,293
78,848
47,232
51,586
43,951
27,889
SCPCE<50
63,449
33,339
57,240
79,473
46,287
46,883
49,386
22,247
SCPCE<33
9%
3%
6%
11%
2%
9%
1%
-4%
SCPCE<40
9%
3%
6%
12%
1%
7%
1%
-4%
SCPCE<50
10%
1%
6%
13%
0%
3%
2%
-5%
Figure A1. Distribution of Employment by PCE values: % of Total Employment in SC Industries
Notes: 37% of total employment are in industries selling < than 33% to PCE.
39
Figure A2. Distribution of Number of Industries across PCE Values: Number of SC Industries
Note: 573 industries selling < than 33% to PCE.
40