NIST Technical Note 1901

Annual Manufacturing Review

Douglas S. Thomas

Anand M. Kandaswamy

This publication is available free of charge from:

http://dx.doi.org/NIST.TN.1901

NIST Technical Note 1901

Annual Manufacturing Review

Douglas S. Thomas

Anand M. Kandaswamy

Applied Economics Office

Engineering Laboratory

This publication is available free of charge from:

http://dx.doi.org/NIST.TN.1901

November 2015

U.S. Department of Commerce 

Penny Pritzker, Secretary

National Institute of Standards and Technology 

Willie E. May, Under Secretary of Commerce for Standards and Technology and Director of NIST
Certain commercial entities, equipment, or materials may be identified in this

document in order to describe an experimental procedure or concept adequately.

Such identification is not intended to imply recommendation or endorsement by the

National Institute of Standards and Technology, nor is it intended to imply that the

entities, materials, or equipment are necessarily the best available for the purpose. 

National Institute of Standards and Technology Technical Note 1901

Natl. Inst. Stand. Technol. Tech. Note 1901, 38 pages (November 2015)

CODEN: NTNOEF

This publication is available free of charge from:

http://dx.doi.org/10.6028/NIST.TN.1901 
ii

Abstract

This report provides an overview of the US manufacturing industry. There are three 

aspects of U.S. manufacturing that are considered: (1) how the US industry compares to 

other countries, (2) the trends in the domestic industry, and (3) the industry trends 

compared to other country’s trends. According to the 2013 Annual Survey of 

Manufactures (ASM), the US manufacturing sector produced $2.4 trillion in value added 

in 2013, up 4.2 % from $2.3 trillion in 2012. Value added in machinery manufacturing 

(North American Industry Classification System code (NAICS) 333), computer and 

electronic product manufacturing (NAICS 334), electrical equipment (NAICS 335), and 

transportation equipment (NAICS 336) grew 1.1 %, 10.0 %, 0.0 %, and 6.1 %,

respectively. According to data from the United Nations Statistics Division, US 

compound annual real (controlling for inflation) growth between 1988 and 2013 was 

2.2 %. This puts the US in the 47th percentile of all countries. This growth exceeded that 

of Germany, France, Canada, Japan, and Australia; however, it is slower than the global 

average and that of many emerging economies. The size of the US manufacturing 

industry, as measured in value added, remains the largest of all countries. Among the ten 

largest manufacturing countries, the US has the 4th largest manufacturing value added per 

capita.

Keywords: durable goods, economic accounts, manufacturing, value added, 

employment
iii
iv

Preface

This study was conducted by the Applied Economics Office (AEO) in the Engineering

Laboratory (EL) at the National Institute of Standards and Technology (NIST). The 

study provides aggregate manufacturing industry data and industry subsector data to 

develop a quantitative depiction of the U.S. manufacturing industry.

Disclaimer

Certain trade names and company products are mentioned in the text in order to adequately specify the 

technical procedures and equipment used. In no case does such identification imply recommendation or 

endorsement by the National Institute of Standards and Technology, nor does it imply that the products are 

necessarily the best available for the purpose.

Cover Photographs Credits

At the Paint Shop in Chrysler Group’s Sterling Heights (Mich.) Assembly Plant, a 2015 Chrysler 200 

moves through the Underbody Sealing and Underbody Coating station, flipping the vehicle body 

completely upside down to seal all appropriate seams and compartments. (2014). This image was used in 

accordance with Fiat Chrysler Automobile’s editorial use policy.
v
vi

Acknowledgements

The authors wish to thank all those who contributed so many excellent ideas and 

suggestions for this report. Special appreciation is extended to Simon Frechette, 

Katherine Morris, and Dr. Vijay Srinivasan of EL’s Systems Integration Division for 

their technical guidance, suggestions, and support. Special appreciation is also extended 

to Dr. Robert Chapman and Dr. Joshua Kneifel of EL’s AEO and to David Pitchure of 

MML’s Mechanical Performance Group for their thorough reviews and many insights. 

The author also wishes to thank Dr. Nicos Martys, of the Materials and Structural 

Systems Division for his review.
vii
viii

Table of Contents

ABSTRACT................................................................................................................................................ II

PREFACE .................................................................................................................................................IV

ACKNOWLEDGEMENTS ...........................................................................................................................VI

TABLE OF CONTENTS.....................................................................................................................VIII

LIST OF FIGURES............................................................................................................................... IX

LIST OF TABLES................................................................................................................................. IX

LIST OF ACRONYMS .......................................................................................................................... X

1 INTRODUCTION .............................................................................................................................. 1

1.1 BACKGROUND............................................................................................................................... 1

1.2 PURPOSE...................................................................................................................................................1

1.3 SCOPE AND APPROACH................................................................................................................... 1

2 VALUE ADDED................................................................................................................................. 3

2.1 INTERNATIONAL COMPARISON ......................................................................................................... 3

2.2 DOMESTIC DETAILS........................................................................................................................ 6

3 MANUFACTURING SUPPLY CHAIN ................................................................................................ 15

4 EMPLOYMENT AND COMPENSATION ........................................................................................... 17

5 DISCUSSION.................................................................................................................................. 23
ix

List of Figures

Figure 2-1: 25 Year Compound Annual Growth (1988 to 2013) ....................................... 4

Figure 2-2: 5 Year Compound Annual Growth (2008 to 2013) ......................................... 4

Figure 2-3: Manufacturing Value Added, Top 10 Manufacturing Countries (1970 to 

2013)............................................................................................................................ 5

Figure 2-4: Manufacturing Value Added Per Capita, Top 10 Manufacturing Countries 

(1970 to 2013).............................................................................................................. 6

Figure 2-5: Cumulative Percent Change in Value Added (2009 Chained Dollars).......... 11

Figure 2-6: Value Added for Durable Goods by Type, 2006-2013.................................. 12

Figure 2-7: Value Added for Nondurable Goods by Type, 2006-2013............................ 12

Figure 3-1: Manufacturing Supply Chain ......................................................................... 16

Figure 4-1: Cumulative Change in Percent in Manufacturing Employment (Seasonally 

Adjusted), 2006-2014 ................................................................................................ 19

Figure 4-2: Hours Worked per Week................................................................................ 21

Figure 4-3: Wages for Manufacturing and Private Industry............................................. 21

List of Tables

Table 2-3: Manufacturing Activity by Economic Measure by Subsector .......................... 7

Table 2-4: Manufacturing Capital, 2012........................................................................... 10

Table 3-1: Supply Chain Entities and Contributions........................................................ 15

Table 4-1: Employment, Annual Survey of Manufactures............................................... 17

Table 4-2: Employment by Industry for 2013 and 2014 (Thousands): Current Population 

Survey........................................................................................................................ 18

Table 4-3: Manufacturing Employment (Thousands): Current Employment Statistics... 18

Table 4-4: Fatal Occupational Injuries by Event or Exposure.......................................... 20

Table 4-5: Total Recordable Cases of Nonfatal Injuries and Illnesses, Private Industry . 20
x

List of Acronyms

ASM: Annual Survey of Manufactures

BEA: Bureau of Economic Analysis

GDP: Gross Domestic Product

IBRD: International Bank for Reconstruction and Development

IDA: International Development Association

ISIC: International Standard Industrial Classification

MAPI: Manufacturers Alliance for Productivity and Innovation

NAICS: North American Industry Classification System

NIST: National Institute of Standards and Technology

PPP: Purchasing Power Parity

SIC: Standard Industrial Classification 

UNSD: United Nations Statistics Division
xi
1

1 Introduction

1.1 Background

Manufacturing industry change agents, who are entities that invest in advancing the 

current state of the industry, have a need to understand the recent activities in 

manufacturing. Access to high quality data about manufacturing is crucial for such 

analysis. However, economic data on manufacturing is disjointed and scattered among 

various sources, and no single source can claim to capture all the relevant data. This 

makes it difficult to quickly and accurately assess the recent activities and trends in the 

industry. 

1.2 Purpose

The purpose of this report is to track domestic manufacturing activity in order to develop 

a quantitative depiction of U.S. manufacturing in the context of the domestic economy 

and global industry. This depiction provides change agents, who invest in advancing the 

current state of manufacturing, insight into the current state and recent trends in US 

manufacturing. 

1.3 Scope and Approach

There are numerous aspects one could examine in manufacturing. This report discusses a 

subset of stakeholders and focuses on US manufacturing. Among the many datasets 

available, it utilizes those that are prominent and are consistent with economic standards. 

These boundaries are further discussed below.

Stakeholders: Stakeholders are those entities that contribute resources to the industry 

and/or receive a form of benefit from industry activity. It could be the stakeholder is a 

consumer of a manufactured product, a producer, or a party that is financing the 

manufacturing itself; all that is required for a stakeholder classification is that the entity is 

materially affected by the industry. 

Each stakeholder is associated with a primary form of investment. For example, 

employees invest their labor while owners invest land, capital, labor, and/or intellectual 

property. Consumers invest their scarce resources into the purchase of manufactured 

goods. For members of the general public who do not act as consumers, the 

manufacturing process can still affect them through the existence of externalities, like air 

or water pollution from the manufacturing process. This report focuses on the employees 

and the owners/investors, as the data available facilitates examining these entities. Future 

work may move toward examining other stakeholders in manufacturing, such as the 

consumers and general public.

Geographic Scope: Many change agents are concerned with a certain group of people or 

organizations. Since NIST is concerned with "US innovation and competitiveness," this 

report focuses on activities within the national borders. In a world of globalization, this 

effort is challenging, as some of the parts and materials being used in US manufacturing 
2

activities are imported. The imported values are a relatively small percentage of the total 

activity. In terms of 2009 imported supply chain value added used by a nation’s 

manufacturing industry as a percent of all value added associated with that nation’s 

manufacturing industry, the U.S. imported 10.8 % of its supply chain.1 These imports 

have environmental impacts, require natural resources, and utilize labor; thus, they are 

important in regards to a firm’s production. NIST, however, promotes US innovation and 

industrial competitiveness; therefore, the imported goods and services are outside of the 

scope of this report.

Standard Data Categorization: US Domestic data tends to be organized using the 

NAICS, which is the standard used by Federal statistical agencies classifying business 

establishments in the U.S. NAICS was jointly developed by the U.S. Economic 

Classification Policy Committee, Statistics Canada, and Mexico’s Instituto Nacional de 

Estadística y Geografía, and was adopted in 1997. NAICS has several major categories 

each with subcategories. Historic data and some organizations continue to use the 

predecessor of NAICS, which is the Standard Industrial Classification system (SIC). 

NAICS codes are categorized at varying levels of detail. The broadest level of detail is 

the two digit NAICS code, which has 20 categories. More detailed data is reported as the 

number of digits increases; thus, three digits provide more detail than the two digit and 

the four digit provides more detail than the three digit. The maximum is six digits. 

Sometimes a two, three, four, or five digit code is followed by zeros, which do not 

represent categories. They are null or place holders. For example, the code 336000 

represents NAICS 336. International data tends to be in the International Standard 

Industrial Classification (ISIC) version 3.1, a revised United Nations system for 

classifying economic data. Manufacturing is broken into 23 major categories (ISIC 15 

through 37) with additional subcategories. This data categorization works similar to 

NAICS in that additional digits represent additional detail. 

Data Sources: Thomas (2012) explores a number of data sources for examining US 

manufacturing activity.2 This report selects from sources that are the most prominent and 

reveal the most information about the US manufacturing industry. These data include the 

United Nations Statistics Division’s National Accounts Main Aggregates Database and 

the US Census Bureau’s Annual Survey of Manufactures, among others.3 Because the 

data sources are scattered across several resources, there are differences in what yearly 

data is available for a particular category or topic. In each case, the most-up-to-date and 

available information is provided for the relevant category.

 

1 Thomas, Douglas S. The US Manufacturing Value Chain: An International Perspective. February 2014. 

NIST Technical Note 1810. <http://www.nist.gov/customcf/get_pdf.cfm?pub_id=914022>

2 Thomas, Douglas S. The Current State and Recent Trends of the US Manufacturing Industry. NIST 

Special Publication 1142. <http://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.1142.pdf>

3 See <http://unstats.un.org/unsd/snaama/dnlList.asp> and <http://www.census.gov/manufacturing/asm/>
3

2 Value Added

Value added is the primary measure of economic activity. It is the increase in the value of 

output at a given stage of production; that is, it is the value of output minus the cost of 

inputs from other firms.4 The primary elements that remain after subtracting inputs is 

taxes, compensation to employees, and gross operating surplus; thus, the sum of these 

also equal value added. Gross operating surplus is used to calculate profit, which is gross 

operating surplus less the depreciation of capital such as buildings and machinery. The 

sum of all value added for a country is that nation’s Gross Domestic Product (GDP). 

2.1 International Comparison

There are a number of sources of international estimates of value added for 

manufacturing. The United Nations Statistics Division National Accounts Main 

Aggregates Database has a very complete dataset that covers a large number of countries 

over a significant period of time. According to this data, in 2013, there was $9.5 trillion

in value added (i.e. GDP) by global manufacturing, which is 18 % ($53.7 trillion) of the 

value added by all industries, according to the United Nations Statistics Division. The top 

5 manufacturing countries accounted for $5.5 trillion or 57.6 % of manufacturing value 

added: United States (18.8 %), China (18.5 %), Japan (10.5 %), Germany (7.0 %), and 

France (2.8 %) (UNSD 2015).

5

As seen in Figure 2-1, US compound real (controlling for inflation) annual growth 

between 1988 and 2013 was 2.2 %, which places the US in the 47

th percentile of all 

countries. This growth exceeded that of Germany, France, Canada, Japan, and Australia; 

however, it is slower than the global average (3 %) and that of many emerging 

economies. It is important to note that emerging economies can employ idle or 

underutilized resources and adopt technologies that are already proven in other nations to 

achieve high growth rates. Developed countries are already utilizing resources and are 

employing advanced technologies; thus, comparing U.S. growth to the high growth rates

in China or India has limited meaning. As seen in Figure 2-2, the compound annual 

growth for the US between 2008 and 2013 was -0.1 %. This puts the US at the 29th

percentile below France and Germany but still above that of Japan and Australia.

As seen in Figure 2-3, the size of the US manufacturing industry, as measured in value 

added, remains the largest of all countries, slightly above China and well above all other 

countries. Among the ten largest manufacturing countries, the US is the 4th largest 

manufacturing value added per capita, as seen in Figure 2-4. It is important to note, 

however, that there are varying means for adjusting data. Some methods show China as 

being the largest while others show the US being the largest. The UNSD data uses market 

exchange rates while others might use purchasing power parity (PPP) exchange rates.

 

4 Dornbusch, Rudiger, Stanley Fischer, adn Richard Startz. 2000. Macroeconomics. 8th ed. London, UK: 

McGraw-Hill.

5 United Nations Statistics Division. “National Accounts Main Aggregates Database.” 

<http://unstats.un.org/unsd/snaama/Introduction.asp>
4

Figure 2-1: National 25 Year Compound Annual Growth, by Country (1988 to 2013)

Figure 2-2: National 5 Year Compound Annual Growth, by Country (2008 to 2013)

Australia, 0.7%

Canada, 1.0%

Germany, 1.4%

France, 1.7%

Japan, 1.7%

United States, 2.2%

Finland, 2.6%

Mexico, 2.9%

World, 3.0%

Ireland, 5.5%

-10.0%

-5.0%

0.0%

5.0%

10.0%

15.0%

25th 

Percentile

50th 

Percentile

75th 

Percentile

100th 

Percentile

Finland, -6.5%

Australia, -0.6%

Japan, -0.2%

United States, -0.1%

France, 0.0%

Ireland, 0.5%

Germany, 0.8%

Mexico, 1.8%

World, 2.1%

China, People's 

Republic of, 9.9%

-20.0%

-15.0%

-10.0%

-5.0%

0.0%

5.0%

10.0%

15.0%

20.0%

25th 

Percentile

50th 

Percentile

75th 

Percentile

100th 

Percentile
5

Poland

Switzerland

Mexico

India

Italy

France

Germany

Japan

China

United States

0

200

400

600

800

1000

1200

1400

1600

1800

2000

1970

1973

1976

1979

1982

1985

1988

1991

1994

1997

2000

2003

2006

2009

2012

Manufacturing Value Added ($Billions 2005)

PPP is the rate that a currency in one country would have to be converted to purchase the 

same goods and services in another country. The drawback of PPP is that it is difficult to 

measure and methodological questions have been raised about some surveys that collect 

data for these calculations.6 Market based rates tend to be relevant for internationally 

traded goods7; therefore, this report utilizes these rates. 

Additional data collected by the International Bank for Reconstruction and Development 

(IBRD) and the International Development Association (IDA) at the World Bank, shows 

manufacturing (defined for World Bank purposes as belonging to ISIC divisions 15-37) 

added 12% value to U.S. GDP in 2013, the most recent year for which the statistic is 

available. This is only slightly less than its 13% contribution to American GDP for each 

of the previous 3 years. Going back to 2000 in the World Bank statistics, 

manufacturing’s contribution to GDP has varied within a fairly narrow band between 

12% and 16%. Thus manufacturing’s contribution to GDP has remained fairly stable in 

this millennium, even as the United States emerges from a serious recession. For 

comparison’s sake, Thailand was the category leader in 2013 with 33% value added to 

GDP from manufacturing. The United States falls roughly in the middle of the country 

rankings, which is not surprising for an advanced economy.8 

Figure 2-3: Manufacturing Value Added, Top 10 Manufacturing Countries (1970 to 2013)

 

6 Callen, Tim. March 2007. PPP Versus the Market: Which Weight Matters? Finance and Development. 

Vol 44 number 1. <http://www.imf.org/external/pubs/ft/fandd/2007/03/basics.htm>

7

Ibid.

8 See World Bank Data at <http://data.worldbank.org/indicator/NV.IND.MANF.ZS>
6

India

China

Mexico

Poland

France

Italy United States

Japan Germany Switzerland

0

2000

4000

6000

8000

10000

12000

1970

1974

1978

1982

1986

1990

1994

1998

2002

2006

2010

Manufacturing Value Added (dollars 2005)

Figure 2-4: Manufacturing Value Added Per Capita, Top 10 Manufacturing Countries (1970 to 2013)

2.2 Domestic Details

Annual Survey of Manufactures: According to the 2013 Annual Survey of Manufactures 

(ASM) data shown in Table 2-1, the manufacturing sector produced $2 398 billion in 

value added in 2013, up 4.2 % from $2 301 billion in 2012.

9 Value added in machinery 

manufacturing (NAICS 333), computer and electronic product manufacturing (NAICS 

334), electrical equipment (NAICS 335), and transportation equipment (NAICS 336) 

grew 1.1 %, 10.0 %, 0.0 %, and 6.1 % respectively. Shipments increased 2.6 % over the 

same period to a total of $5 847 billion. The ASM calculation of value added is equal to 

the value of shipments less the cost of materials, supplies, containers, fuel, purchased 

electricity, and contract work. It is adjusted by the addition of value added by 

merchandising operations plus the net change in finished goods and work-in-process 

goods:

ASM Value Added = shipments − net inventories shipped −

suppliers of materials + merchandising operations

 

9 Census Bureau. “Annual Survey of Manufactures.” February 2015. Accessed from the American 

FactFinder. <http://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml> and Census Bureau. “Economic 

Census.” March 2015. Accessed from the American FactFinder. 

<http://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml>
7

Value added avoids the duplication caused from the use of products of some 

establishments as materials. It is important to note that the Bureau of Economic Analysis 

(BEA) and the ASM calculate value added differently. The BEA, which follows the more 

Table 2-1: Manufacturing Activity by Economic Measure by Subsector

2012 2013 Percent

($Billions 2012) ($Billions 2013) Change

Manufacturing Shipments and Value Added

a. TOTAL MANUFACTURING

i. Net Inventories Shipped -11.64 -8.47 27.2%

ii. Depreciation of Capital 181.90 a -

iii. Net Income 780.68 a -

iv. Expenditures 4 745.78 4 826.39 1.7%

a. Suppliers of Materials 3 407.06 3 456.98 1.5%

v. Shipments (i + ii + iii + iv) 5 696.73 5 846.77 2.6%

vi. ASM Value Added = v - i - iv.a + adjustment[1] 2 300.72 2 398.39 4.2%

vii. Value Added = v - i - iv + Compensation [2] 1 736.20 1 817.90 4.7%

viii. BEA Value Added 1 829.50 1 922.90 5.1%

b. NAICS 324: Petroleum & coal products mfg

i. Net Inventories Shipped 0.03 -0.60 -2302.5%

ii. Depreciation of Capital 10.92 a -

iii. Net Income 71.40 a -

iv. Expenditures 768.79 788.26 2.5%

a. Suppliers of Materials 719.58 733.09 1.9%

v. Shipments (i + ii + iii + iv) 851.14 865.69 1.7%

vi. ASM Value Added = v - i - iv.a + adjustment 131.53 133.25 1.3%

vii. Value Added = v - i - iv + Compensation 95.14 91.23 -4.1%

c. NAICS 325: Chemical mfg

i. Net Inventories Shipped 1.44 -1.15 -179.9%

ii. Depreciation of Capital 30.21 a -

iii. Net Income 188.84 a -

iv. Expenditures 564.80 568.05 0.6%

a. Suppliers of Materials 419.07 423.46 1.0%

v. Shipments (i + ii + iii + iv) 785.30 797.83 1.6%

vi. ASM Value Added = v - i - iv.a + adjustment 364.78 375.91 3.1%

vii. Value Added = v - i - iv + Compensation 289.01 300.07 3.8%

d. NAICS 326: Plastics & rubber products mfg

i. Net Inventories Shipped -0.87 -0.75 14.5%

ii. Depreciation of Capital 9.47 a -

iii. Net Income 24.53 a -

iv. Expenditures 185.45 192.99 4.1%

a. Suppliers of Materials 119.25 123.14 3.3%

v. Shipments (i + ii + iii + iv) 218.57 227.10 3.9%

vi. ASM Value Added = v - i - iv.a + adjustment 100.19 104.70 4.5%

vii. Value Added = v - i - iv + Compensation 74.31 76.42 2.8%
8

2012 2013 Percent

($Billions 2012) ($Billions 2013) Change

e. NAICS 327: Nonmetallic mineral product mfg

i. Net Inventories Shipped -0.17 -0.39 -123.6%

ii. Depreciation of Capital 7.61 a -

iii. Net Income 8.97 a -

iv. Expenditures 82.64 86.19 4.3%

a. Suppliers of Materials 44.91 47.12 4.9%

v. Shipments (i + ii + iii + iv) 99.04 105.50 6.5%

vi. ASM Value Added = v - i - iv.a + adjustment 54.31 58.76 8.2%

vii. Value Added = v - i - iv + Compensation 38.00 41.93 10.4%

f. NAICS 331: Primary metal mfg

i. Net Inventories Shipped 0.15 -0.13 -190.5%

ii. Depreciation of Capital 9.00 a -

iii. Net Income 18.96 a -

iv. Expenditures 241.44 231.46 -4.1%

a. Suppliers of Materials 182.76 173.56 -5.0%

v. Shipments (i + ii + iii + iv) 269.54 262.19 -2.7%

vi. ASM Value Added = v - i - iv.a + adjustment 86.63 88.66 2.3%

vii. Value Added = v - i - iv + Compensation 59.64 62.60 5.0%

g. NAICS 332: Fabricated metal product mfg

i. Net Inventories Shipped -1.44 -0.97 32.4%

ii. Depreciation of Capital 13.49 a -

iii. Net Income 35.22 a -

iv. Expenditures 292.66 296.74 1.4%

a. Suppliers of Materials 161.58 162.29 0.4%

v. Shipments (i + ii + iii + iv) 339.93 345.09 1.5%

vi. ASM Value Added = v - i - iv.a + adjustment 179.79 183.91 2.3%

vii. Value Added = v - i - iv + Compensation 134.20 136.93 2.0%

h. NAICS 333: Machinery mfg

i. Net Inventories Shipped -1.55 -0.56 63.6%

ii. Depreciation of Capital 10.96 a -

iii. Net Income 54.98 a -

iv. Expenditures 337.78 327.13 -3.2%

a. Suppliers of Materials 214.00 203.08 -5.1%

v. Shipments (i + ii + iii + iv) 402.18 394.07 -2.0%

vi. ASM Value Added = v - i - iv.a + adjustment 189.72 191.75 1.1%

vii. Value Added = v - i - iv + Compensation 143.49 146.80 2.3%

i. NAICS 334: Computer & electronic product mfg

i. Net Inventories Shipped 1.10 1.19 8.0%

ii. Depreciation of Capital 14.93 a -

iii. Net Income 28.21 a -

iv. Expenditures 269.34 258.87 -3.9%

a. Suppliers of Materials 132.43 126.58 -4.4%

v. Shipments (i + ii + iii + iv) 313.59 325.81 3.9%

vi. ASM Value Added = v - i - iv.a + adjustment 180.05 197.97 10.0%

vii. Value Added = v - i - iv + Compensation 125.16 145.41 16.2%
9

2012 2013 Percent

($Billions 2012) ($Billions 2013) Change

j. NAICS 335: Electrical equipment, appliance, & component mfg

i. Net Inventories Shipped -0.34 -0.23 32.9%

ii. Depreciation of Capital 3.47 a -

iii. Net Income 20.59 a -

iv. Expenditures 99.90 99.81 -0.1%

a. Suppliers of Materials 63.68 63.22 -0.7%

v. Shipments (i + ii + iii + iv) 123.62 123.29 -0.3%

vi. ASM Value Added = v - i - iv.a + adjustment 60.27 60.25 0.0%

vii. Value Added = v - i - iv + Compensation 47.00 47.09 0.2%

k. NAICS 336: Transportation equipment mfg

i. Net Inventories Shipped -5.82 -3.21 44.8%

ii. Depreciation of Capital 22.05 a -

iii. Net Income 75.82 a -

iv. Expenditures 693.64 735.07 6.0%

a. Suppliers of Materials 506.65 538.01 6.2%

v. Shipments (i + ii + iii + iv) 785.69 836.97 6.5%

vi. ASM Value Added = v - i - iv.a + adjustment 284.64 302.14 6.1%

vii. Value Added = v - i - iv + Compensation 213.70 226.36 5.9%

l. NAICS 339: Miscellaneous mfg

i. Net Inventories Shipped -0.25 -0.31 -21.2%

ii. Depreciation of Capital 4.90 a -

iii. Net Income 30.75 a -

iv. Expenditures 113.76 117.64 3.4%

a. Suppliers of Materials 54.61 56.43 3.3%

v. Shipments (i + ii + iii + iv) 149.16 156.26 4.8%

vi. ASM Value Added = v - i - iv.a + adjustment 94.80 100.00 5.5%

vii. Value Added = v - i - iv + Compensation 70.70 75.54 6.8%

m. Other: Food, apparel, wood product, and printing mfg

i. Net Inventories Shipped -3.91 -1.35 65.5%

ii. Depreciation of Capital 44.88 a -

iii. Net Income 222.41 a -

iv. Expenditures 1 095.60 1 124.19 2.6%

a. Suppliers of Materials 788.53 806.99 2.3%

v. Shipments (i + ii + iii + iv) 1 358.99 1 406.97 3.5%

vi. ASM Value Added = v - i - iv.a + adjustment 574.00 601.09 4.7%

vii. Value Added = v - i - iv + Compensation 445.85 467.50 4.9%

a: values are unavailable

[1] It is adjusted by the addition of value added by merchandising operations plus the net change in finished 

goods and work-in-process goods. 

[2] Compensation includes payroll and fringe benefits (not shown)

traditional method, calculates value added as “gross output (sales or receipts and other 

operating income, plus inventory change) less intermediate inputs (consumption of goods 

and services purchased from other industries or imported).” Moreover, the difference is 

that ASM’s calculation of value added includes purchases from other industries such as 

mining and construction while BEA’s does not include it. Table 2-1 has both the ASM’s 

calculation and a calculation that follows the more traditional approach.
10

Net income, which could also be referred to as profit, for all manufacturing in 2013 could 

not be calculated, as the depreciation of capital was not available. The 2012 value was 

$781 billion. Expenditures amounted to $4 746 billion, resulting in a return on investment 

of approximately 16.5 %. The return on investment in machinery manufacturing (NAICS 

333), computer and electronic product manufacturing (NAICS 334), electrical equipment 

(NAICS 335), and transportation equipment (NAICS 336) was 16.3 %, 10.5 %, 20.6 %, 

and 10.9 %.

In terms of acquisition costs, manufacturing capital (i.e., buildings and machinery) 

increased $116 billion for all of manufacturing, as seen in Table 2-2. In terms of the total 

value of capital, however, it decreased by $17 billion. Net capital acquisitions for 

machinery, computer and electronics, electrical equipment, and transportation equipment 

manufacturing increased $7 billion, $14 billion, $2 billion, and $17 billion, respectively. 

The value of capital for machinery and electrical equipment decreased while it increased 

for computer and electronics and transportation equipment.

Table 2-2: Manufacturing Capital, 2012

2012 

NAICS 

code NAICS Description

Total capital 

expenditures 

($Billions)

Total 

retirements 

(acquisition 

costs) 

($Billions)

Gross value 

of 

depreciable 

assets 

(acquisition 

costs), end 

of year 

($Billions)

Total 

depreciation 

charges 

during year 

($Billions)

Net Capital 

Acquisitions 

($Billions)*

Change in 

value of 

capital 

($Billions)**

31-33 Manufacturing 164.8 49.2 2 830.4 181.9 115.5 -17.1

311 Food 15.4 6.0 265.8 16.4 9.3 -1.0

312 Beverage and tobacco 3.6 1.0 73.1 4.4 2.7 -0.8

313 Textile mills 0.9 0.2 22.3 1.7 0.7 -0.8

314 Textile product mills 0.4 0.1 11.0 0.8 0.3 -0.3

315 Apparel 0.2 0.1 4.6 0.5 0.2 -0.2

316 Leather and allied product 0.1 0.0 1.9 0.1 0.1 0.0

321 Wood product 2.1 1.0 54.0 3.6 1.1 -1.5

322 Paper 8.0 2.0 173.2 10.7 6.0 -2.6

323

Printing and support 

activities 2.5 1.3 71.0 4.9 1.2 -2.4

324 Petroleum and coal products 16.4 1.7 233.3 10.9 14.7 5.5

325 Chemical 23.1 7.2 506.0 30.2 15.9 -7.1

326 Plastics and rubber products 6.5 2.4 134.5 9.5 4.1 -3.0

327 Nonmetallic mineral product 4.2 1.5 114.7 7.6 2.7 -3.4

331 Primary metal 8.2 3.6 156.3 9.0 4.6 -0.8

332 Fabricated metal product 11.5 3.0 187.2 13.5 8.5 -2.0

333 Machinery 10.5 3.2 155.8 11.0 7.4 -0.4

334 Computer and electronics 19.7 5.5 204.2 14.9 14.3 4.8

335 Electrical equipment 2.8 1.1 52.2 3.5 1.7 -0.7

336 Transportation equipment 23.2 5.8 315.0 22.1 17.4 1.1

337 Furniture and related 1.1 0.4 29.4 1.9 0.7 -0.8

339 Miscellaneous 4.4 2.1 65.0 4.9 2.2 -0.6

*calculated as capital expenditures less retirements

**Calculated as capital expenditures less depreciation
11

Bureau of Economic Analysis: The most recent Industry Economic Accounts data (July 

2015) from the BEA shows that manufacturing declined by 0.3 % in the first quarter of 

2015 to $1.9 trillion10 and contributed 10.6 % of GDP growth or 0.3 percentage points of 

GDP growth since the first quarter of 2014.11 Approximately 67.6 % of manufacturing 

growth could be attributed to durable goods manufacturing and 32.4 % could be 

attributed to nondurable goods manufacturing. As illustrated in Figure 2-5, manufacturing 

declined significantly in 2008 and has nearly returned to its peak level occurring in 2007. 

Manufacturing value added declined more than total US GDP, creating a persistent gap. 

The result is that first quarter GDP is 8.6 % above its peak level while manufacturing is at 

0.6 % below its peak level. This is largely driven by nondurable goods manufacturing, 

which is 7.7 % below its peak occurring in 2007.12

Figure 2-6 and Figure 2-7 provide data on durable and nondurable goods. As seen in 

Figure 2-6, value added for a number of durable goods is higher in 2013 than it was in 

2006, including computer and electronic products, machinery, and motor vehicles. As 

seen in Figure 2-7, in 2013 every category of nondurable goods was below its 2006 

value, including chemical manufacturing, petroleum and coal products, and plastics and 

rubber.

Figure 2-5: Cumulative Percent Change in Value Added (2009 Chained Dollars)

 

10 Billions of chained dollars seasonally adjusted at annual rates

11 Growth estimates were made using billions of chained 2009 dollars seasonally adjusted at annual rates.

12 Bureau of Economic Analysis. “Industry Economic Accounts Data.” 

<http://www.bea.gov/iTable/index_industry_gdpIndy.cfm>

-15%

-10%

-5%

0%

5%

10%

15%

2006200720082009201020112012201320142015

 Gross domestic product

 Manufacturing

 Durable goods

 Nondurable goods
12

Figure 2-6: Value Added for Durable Goods by Type, 2006-2013

Figure 2-7: Value Added for Nondurable Goods by Type, 2006-2013

2006 2008 2009 2010 2011 2012 2013

 Miscellaneous manufacturing 73 78 80 82 79 78 80

 Furniture and related products 40 32 23 23 24 24 25

 Other transportation equipment 103 118 112 112 114 113 117

 Motor vehicles and parts 143 107 48 100 127 139 150

 Electrical equipment/appliances 60 60 50 51 49 48 49

 Computer and electronic products 180 228 229 256 265 272 273

 Machinery 139 145 116 128 145 145 141

 Fabricated metal products 158 154 118 129 137 141 140

 Primary metals 41 41 40 38 40 50 57

 Nonmetallic mineral products 51 47 37 37 39 40 39

 Wood products 26 25 21 21 23 24 22

0

200

400

600

800

1000

1200

Billions of Chained 2009 Dollars

2006 2007 2008 2009 2010 2011 2012 2013

 Plastics and rubber products 70 71 62 62 65 64 67 68

 Chemical products 315 334 305 310 330 311 299 297

 Petroleum and coal products 109 111 119 115 99 85 84 90

 Printing and related activities 45 47 46 39 40 41 40 40

 Paper products 69 64 56 59 53 51 50 48

 Apparel, leather, and allied products 13 12 12 10 11 11 10 10

 Textile mills and products 21 20 19 15 16 13 15 16

 Food, beverage, and tobacco 236 236 225 243 233 225 218 220

0

100

200

300

400

500

600

700

800

900

1000

Billions of Chained 2009 Dollars
13

Survey of Plant Capacity Utilization: The Survey of Plant Capacity Utilization reveals 

the industry’s ability to increase value added without increasing the amount of 

infrastructure needed for production. Even small changes in plant utilization capacity can 

have large effects on output. Looking at plant capacity utilization statistics for the first 

quarter of 2015, the time period for which the most recent statistics were available, and 

focusing on the manufacturing sector defined by NAICS codes 31 through 33, a 69.9% 

utilization rate of plant capacity was reported, only slightly changed from the 71.3% 

utilization rate reported in the final quarter of 2014.

Digging down deeper into the statistics, we see that the manufacturing of complex 

durable goods tends to outpace the industry-wide utilization rate for manufacturing. For 

example, the semiconductor and related device manufacturing has a high utilization rate 

of 88.7%, automobile manufacturing is at 81.4%, and light truck and utility vehicle 

management is at 93.7%. Aerospace products and parts manufacturing was at 86.5%. A 

complex good is defined here as one containing components that are themselves the 

finished products of other manufacturing processes. 

Utilization rates for plants depend on a variety of factors. For example, there might be 

some change specific to the industry that changes how a plant is utilized. The automobile 

manufacturing industry has seen many such changes over the last few years due to greater 

efficiencies in manufacturing sequencing, development of parallel processing, use of 

quality control processes (e.g. Taguchi methods), and greater use of computer 

simulations to permit simultaneous multiple part manufacturing under one roof.

Plant capacity utilization rates can also be driven by economic conditions at both the 

micro and macro level. When the economy is steadily growing, there is greater demand 

for manufactured products, particularly more complex ones that tend to require more 

disposable income to purchase. Also, all things being equal, one would expect to see 

greater plant utilization in industries for which the United States has a relative 

comparative advantage. However, one should not venture any guesses about why a 

particular industry has a particular capacity utilization rate without conducting an 

underlying analysis of both the industry-specific plant characteristics and conditions

governing the larger macroeconomic environment.
14
15

3 Manufacturing Supply Chain

There are many suppliers of goods and services that have a stake in manufacturing; these 

include resellers, providers of transportation and warehousing, raw material suppliers, 

suppliers of intermediate goods, and suppliers of professional services with values from the 

ASM.

13 Table 3-1 presents and Figure 3-1 maps, the purchases that the manufacturing 

industry made for production, which is disaggregated into five categories: suppliers of 

services, computer hardware, software, and other costs (blue), refuse removal, intermediate 

goods, and recycling (gold), machinery, structures, and compensation (orange), repair of the 

machinery and structures (red), and suppliers of materials (green). These items all feed into 

the design and production of manufactured goods which are inventoried and/or shipped

(gray). The depreciation of capital and net income are also included in Figure 3-1, which 

affects the market value of shipments. In addition to the stakeholders, there are also public 

vested interests, the end users, and financial service providers.

Table 3-1: Supply Chain Entities and Contributions

2012 2013 Percent

($Billions 2012) ($Billions 2013) Change

I. Services, Computer Hardware, Software, and Other Expenditures

a. Communication Services 4.52 4.78 5.7%

b. Computer Hardware, Software, and Other Equipment 12.38 11.92 -3.7%

c. Professional, Technical, and Data Services 36.83 35.99 -2.3%

d. Other Expenditures 260.94 264.62 1.4%

e. TOTAL 314.68 317.31 0.8%

II. Refuse Removal Expenditures 13.56 13.74 1.3%

III. Machinery, Structures, and Compensation Expenditures

a. Payroll, Benefits, and Employment 773.61 789.06 2.0%

b. Capital Expenditures: Structures (including rental) 55.60 57.38 3.2%

c. Capital Expenditures: Machinery/Equipment (including rental) 136.94 145.71 6.4%

d. TOTAL 966.16 992.15 2.7%

IV. Suppliers of Materials Expenditures

a. Materials, Parts, Containers, Packaging, etc... Used 3 098.56 3 135.56 1.2%

b. Contract Work and Resales 223.31 232.71 4.2%

c. Purchased Fuels and Electricity 85.19 88.71 4.1%

d. TOTAL 3 407.06 3 456.98 1.5%

V. Maintenance and Repair Expenditures 44.33 46.22 4.3%

VI. Shipments

a. Expenditures 4 745.78 4 826.39 1.7%

b. Net Inventories Shipped -11.64 -8.47 27.2%

c. Depreciation 181.90 a -

d. Net Income 780.68 a -

E. TOTAL 5 696.73 5 846.77 2.6%

a: estimates were unavailable

 

13 Census Bureau. “Annual Survey of Manufactures.” February 2015. Accessed from the American 

FactFinder. <http://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml> 
16

Figure 3-1: Manufacturing Supply Chain
17

4 Employment and Compensation

The Annual Survey of Manufactures estimates that there were 11.1 million employees in 

manufacturing in 2013, which is the most recent data available (see Table 4-1). The 

Current Population Survey and Current Employment Statistics have more recent data that 

estimate that there were 15.1 million and 12.2 million employees in 2013, respectively

(see Table 4-2 and Table 4-3). Each of these estimates has its own method for how the 

data was acquired and its own definition of employment. The Current Population Survey 

considers an employed person to be any individual who did any work for pay or profit 

during the survey reference week or were absent from their job because they were ill, on 

vacation, or taking leave for some other reason. It also includes individuals who 

completed at least 15 hours of unpaid work in a family-owned enterprise operated by 

someone in their household. In contrast, the Current Employment Statistics specifically 

exclude proprietors, self-employed, and unpaid family or volunteer workers; thus, the 

estimates from the Current Employment Statistics are lower than the Current Population 

Survey estimates. Additionally, the Current Employment Statistics include temporary and 

intermittent employees. The Annual Survey of Manufactures considers an employee to 

include all full-time and part-time employees on the payrolls of operating establishments 

during any part of the pay period being surveyed excluding temporary staffing obtained 

through a staffing service. It also excludes proprietors along with partners of 

unincorporated businesses.

Between 2013 and 2014, manufacturing employment increased 1.6 % according to the 

Current Population Survey (see Table 4-2) and 1.4 % according to the Current 

Employment Statistics (see Table 4-3). Meanwhile, total employment increased 1.7 % 

according to the Current Population Survey (see Table 4-3). 

Table 4-1: Employment, Annual Survey of Manufactures

2012 2013 Percent

(employees) (employees) Change

a. NAICS 324: Petroleum & coal products mfg 101 209 101 473 0.3%

b. NAICS 325: Chemical mfg 735 553 718 181 -2.4%

c. NAICS 326: Plastics & rubber products mfg 699 924 703 688 0.5%

d. NAICS 327: Nonmetallic mineral product mfg 352 424 348 434 -1.1%

e. NAICS 331: Primary metal mfg 392 495 386 251 -1.6%

f. NAICS 332: Fabricated metal product mfg 1 388 550 1 379 859 -0.6%

g. NAICS 333: Machinery mfg 1 055 375 1 057 684 0.2%

h. NAICS 334: Computer & electronic product mfg 856 725 811 598 -5.3%

i. NAICS 335: Electrical equipment & component mfg 337 672 332 176 -1.6%

j. NAICS 336: Transportation equipment mfg 1 357 124 1 383 528 1.9%

k. NAICS 339: Miscellaneous mfg 546 814 537 021 -1.8%

l. Other: Food, apparel, wood product, and printing mfg 3 390 303 3 322 343 -2.0%

J. TOTAL MANUFACTURING 11 214 165 11 082 237 -1.2%
18

Table 4-2: Employment by Industry for 2013 and 2014 (Thousands): Current Population Survey

Industry Total Employed 

2013

Total Employed 

2014

Employment 

Change

Percent 

Change

Mining 1 065 1 088 23 2.2%

Construction 9 271 9 813 542 5.8%

Manufacturing 14 869 15 100 231 1.6%

Wholesale and Retail Trade 19 653 20 251 598 3.0%

Transportation and Utilities 7 415 7 581 166 2.2%

Information 2 960 3 115 155 5.2%

Financial Activities 9 849 9 871 22 0.2%

Professional and Business Services 16 793 17 004 211 1.3%

Education and Health Services 32 535 32 830 295 0.9%

Leisure and Hospitality 13 554 13 489 -65 -0.5%

Other Services 7 127 7 169 42 0.6%

Public Administration 6 708 6 757 49 0.7%

Agriculture 2 130 2 237 107 5.0%

TOTAL* 143 929 146 305 2 376 1.7%

* The sum may not match the total due to rounding of annual averages

Source: Current Population Survey, Bureau of Labor Statistics. "Table 17: Employed Persons by 

Industry, Sex, Race, and Occupation." <http://www.bls.gov/cps>

Table 4-3: Manufacturing Employment (Thousands): Current Employment Statistics

2013 2014 Percent Change

Manufacturing 12 020 12 188 1.4%

Durable Goods 7 548 7 685 1.8%

Nondurable Goods 4 472 4 503 0.7%

Source: Bureau of Labor Statistics. Current Employment Statistics.

http://www.bls.gov/ces/home.htm

Between January of 2006 and January of 2010, manufacturing employment declined by 

19.4 %, as seen in Figure 4-1. As of August 2015, employment is still 13.2 % below its 

2006 level. In times of financial difficulty, large purchases are often delayed or

determined to be unnecessary. Thus, it would be expected that during the recent recession 

durable goods would decline more than nondurable goods. As can be seen in the Figure

4-1, durable goods declined more than manufacturing as a whole while nondurable goods 

did not decline as much. By January of 2010, durable goods had declined 22.2 % while 

nondurables declined 14.5 %. As of August of 2013, durables was 13.3 % below its 2006 

levels while nondurables was at 13.2 %.
19

Figure 4-1: Cumulative Change in Percent in Manufacturing Employment (Seasonally Adjusted), 

2006-2014

The employees that work in manufacturing sacrifice their time and, in some cases, their 

safety in return for compensation. In terms of safety, the number of fatal injuries

decreased between 2012 and 2013 (see Table 4-4). Nonfatal injuries and the injury rate 

has decreased as well (see Table 4-5). However, the incident rate for nonfatal injuries in 

manufacturing remains higher than that for all private industry. During the recession, the 

number of hours worked per week declined, as seen in Figure 4-2. Unlike employment, 

however, the number of hours worked per week returned to its pre-recession levels or 

slightly higher. Average wages increased significantly during the recession and decreased 

during the following recovery, as can be seen in Figure 4-3. This is likely because low 

wage earners are disproportionately impacted by employment reductions, which suggests 

that high wage earners not only receive more pay, they also have more job security.

-25.0%

-20.0%

-15.0%

-10.0%

-5.0%

0.0%

5.0%

2006200720082009201020112012201320142015

Cumulative Change % (2006 Base)

Nondurable Goods

Durable Goods

Manufacturing
20

Table 4-4: Fatal Occupational Injuries by Event or Exposure

Total

Violence and 

other injuries 

by persons or 

animals

Transportation 

Incidents

fires and 

explosions

Falls, 

slips, 

trips

exposure to 

harmful substances or 

environments 

Contact 

with 

objects and 

equipment 

2012

Total 4628 803 1923 122 704 340 723

Manufacturing 327 45 87 25 39 28 102

2013

Total 4585 773 1865 149 724 335 721

Manufacturing 312 36 91 12 42 18 110

Percent 

Change

Total Private Industry -0.9% -3.7% -3.0% 22.1% 2.8% -1.5% -0.3%

Manufacturing -4.6% -20.0% 4.6% -52.0% 7.7% -35.7% 7.8%

Source: Bureau of Labor Statistics. Census of Fatal Occupational Injuries. "Industry by Event or Exposure." 

<http://stats.bls.gov/iif/oshcfoi1.htm>

Table 4-5: Total Recordable Cases of Nonfatal Injuries and Illnesses, Private Industry

2012 2013 Percent Change

Manu- facturing

Incident Rate per 100 full time 

workers 4.2 4.0 -4.8%

Total Recordable Cases 

(thousands) 503.8 476.7 -5.4%

Private 

Industry

Incident Rate per 100 full time 

workers 3.4 3.3 -2.9%

Total Recordable Cases 

(thousands) 3027.6 3007.3 -0.7%

Source: Bureau of Labor Statistics. Injuries, Illness, and Fatalities Program. 2010-

2011. http://www.bls.gov/iif/
21

Figure 4-2: Hours Worked per Week

Source: Bureau of Labor Statistics. Current Employment Statistics. <http://www.bls.gov/ces/home.htm>

Figure 4-3: Wages for Manufacturing and Private Industry

Source: Bureau of Labor Statistics. Current Employment Statistics. <http://www.bls.gov/ces/home.htm>

32.0

34.0

36.0

38.0

40.0

42.0

2006200720082009201020112012201320142015

Hours per Week

Private

Manufacturing

Durable Goods

Nondurable Goods

17.00

17.50

18.00

18.50

19.00

19.50

20.00

20.50

21.00

21.50

22.00

2006200720082009201020112012201320142015

$ per Hour

Private

Manufacturing

Durable Goods

Nondurable Goods
22
23

5 Discussion

This report provides an overview of the US manufacturing industry. There are three 

aspects of U.S. manufacturing that are considered: (1) how the US industry compares to 

other countries, (2) the trends in the domestic industry, and (3) the industry trends 

compared to other country’s trends. According to the 2013 Annual Survey of 

Manufactures (ASM), the US manufacturing sector produced $2.4 trillion in value added 

in 2013, up 4.2 % from $2.3 trillion in 2012. Value added in machinery manufacturing 

(North American Industry Classification System code (NAICS) 333), computer and 

electronic product manufacturing (NAICS 334), electrical equipment (NAICS 335), and 

transportation equipment (NAICS 336) grew 1.1 %, 10.0 %, 0.0 %, and 6.1 %, 

respectively. According to data from the United Nations Statistics Division, US 

compound annual real (controlling for inflation) growth between 1988 and 2013 was 

2.2 %. This puts the US in the 47

th percentile of all countries. This growth exceeded that 

of Germany, France, Canada, Japan, and Australia; however, it is slower than the global 

average and that of many emerging economies. The size of the US manufacturing 

industry, as measured in value added, remains the largest of all countries. Among the ten 

largest manufacturing countries, the US has the 4th largest manufacturing value added per 

capita.

In addition to the data on past activities in manufacturing, some entities work toward 

forecasting future activities. The Manufacturers Alliance for Productivity and Innovation 

(MAPI), a large alliance of various manufacturing concerns, makes widely followed 

predictions on the growth or contraction of the manufacturing industry. For 2015, it 

forecasts a 2.5% growth rate in the manufacturing industry as compared to a 3.5% growth 

rate in 2014. MAPI believes there will be a slowdown from last year’s manufacturing 

growth rate because of the drawn-out economic recovery (which they attribute in part to 

weather fluctuations), which has seen smaller growth in consumer demand. MAPI also 

believes that the consumers are using any extra income they are earning (or receiving 

from wider economic trends like the collapse in oil prices) to pay down current debt 

instead of consuming manufactured goods. This creates a ripple effect in the wider U.S. 

manufacturing industry that leads to less-than-robust demand in the near future.
24

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