Employment Outlook: 2022-2032

Layout and Description

Input-Output Tables:

1997 through 2022 Historical and Projected 2032

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Bureau of Labor Statistics

Office of Occupational Statistics and Employment Projections

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September 6, 2023

Nicholas Hale hale.nicholas@bls.gov (202) 691-7750
Contents

I-O Layout and Description............................................................................................................................. 1

Naming conventions for input-output tables............................................................................................. 2

Standard matrix types ................................................................................................................................ 3

How to Access Files ........................................................................................................................................ 6

Conversion of Tables to Inverse and Other Coefficient Matrices................................................................... 7

Mathematical Derivation of the Total Requirements Tables for Input-Output Analysis............................ 8
Page - 1

I-O Layout and Description

This document describes input-output, final demand, and value-added data developed by 

the Bureau of Labor Statistics in the Office of Occupational Statistics and Employment 

Projections. 

For the 2032 projections, input-output, final demand, and value-added data were 

developed for the years 1997 through 2022 and projected year 2032. Historical tables are 

provided in both nominal (current) dollars and in 2012 chain weighted real dollars. The 

projected tables are provided in 2012 chain weighted real dollars only.

In addition to the data tables, sectoring plan files “SectorPlan30.xlsx” and

“FDSectorPlan30.xlsx” are needed because the data files have no labels to signify columns 

and rows. The “SectorPlan30.xlsx” file provides our industry sectoring plan with industry 

codes and titles. The “FDSectorPlan30.xlsx” file provides our final demand column codes 

and titles. Note, the SectorPlan30.xlsx file contains summary sector codes and titles that 

DO NOT appear in the I-O tables.

The matrix tables described here are in EXCEL files. Matrices include only data and sector 

code column and row identifiers. As stated above, there are no row or column labels.

Data may not add exactly to their totals due to rounding error. In the real tables, the data 

do not add up to published totals like gross domestic product because of chain weighting.

These data are based on the 2022 North American Industrial Classification System

(NAICS); the U.S. Department of Commerce’s Bureau of Economic Analysis (BEA) 2007

and 2012 benchmark input-output tables; and the BEA Annual input-output tables for 

1997-2021.

1 The BLS industry sectoring plan is shown in the industry sectoring plan files 

discussed above.

1 Output data reflects BLS adjustments from NAICS 2017-coded BEA source data to match 2022 NAICS and 

do not fully reflect output levels for select industries.
Page - 2

Naming conventions for input-output tables

All the file names begin with either “NOMINAL_” for nominal (current) dollars, “REAL_” 

for chain weighted real dollars, or “PROJECTED_” for projections 2032. It should be noted 

that all input-output projections files only contain real dollar data. No current dollar inputoutput tables were projected.

Following “NOMINAL_”, “REAL_”, or “PROJECTED_” are either “USE”, “MAKE”, “FD”, 

“FDAGG”, “INDOUTPUT”, “COMOUTPUT”, or “OUTPUT”.

The "USE" matrix contains the sales of commodities sold to intermediate consumers and 

final demand. In addition, it contains the intermediate inputs and value-added factors of 

production to industries to produce their product.

Each column sums to its respective industry output. Each row sums to its respective 

commodity output.

The "MAKE" matrix details the production of commodities by industries. Each row sums 

to industry output, and each column sums to commodity output.

The "FD" matrix is a detailed set of 132 final demand types. Each of the 132 columns is 

distributed across the 192 input-output commodity rows identified in “SectorPlan30.xlsx” 

as mentioned in page 1. The "FDAGG" is the "FD" matrix collapsed from 132 columns to 

11 columns. The column sectors are shown in “FDSectorPlan30.xlsx” as mentioned in 

page 1. Each year is a different worksheet in the selected workbook.

The “COMOUTPUT” and “INDOUTPUT” matrices detail the respective historical 

commodity and industry outputs by each of the 192 sectors identified in the input-output 

system for the years 1997 through 2022. The sector identifier is in the first column. The 

time series starts with 1997 outputs in the second column, the next year’s outputs in the 

third column, and continues through 2022 outputs in the last column.

For the projection year, the “OUTPUT_2032” matrix contains three columns. The sector 

identifier is in the first column. The second column details industry output for each sector.

The third column details the commodity output for each sector.
Page - 3

Standard matrix types

"USE" Matrix (193x193)

This matrix contains intermediate inter-industry inputs plus value added (row 193) for the 

year specified in the worksheet name. This matrix also contains intermediate interindustry sales plus final demand (column 193) for the year specified in the matrix name.

Each column sums to its respective industry output. Each row sums to its respective 

commodity output.

"MAKE" Matrix (192x192)

This matrix contains the production of commodities by industries for the year specified in 

the matrix name. Each row sums to industry output and each column sums to commodity 

output.

“INDOUTPUT” Matrix (192x26)

This matrix contains the industry output time series for the 192 industry sectors for the 

years starting from 1997 and continuing through 2022.

“COMOUTPUT” Matrix (192x26)

This matrix contains the commodity output time series for the 192 commodity sectors for 

the years starting from 1997 continuing through 2022.

“OUTPUT_2032” Matrix (192x2)

This table contains the total outputs for the projected year 2032. The first column of data 

is the total industry output and the second is the total commodity output for the sector 

designated by the sector number column.
Page - 4

"FD" Matrix (192x132)

This is the final demand matrix for the year specified in the worksheet name. Each “FD” 

matrix has 192 rows and 132 columns. Rowsrepresent commodity final demand. Columns 

represent final demand by detailed category, margin reallocations, or import valuation 

adjustments. The column types are described below.

Each “FD” matrix has 116 columns containing final demand data by detailed category.

Their column sums are obtained from BEA’s National Income Product Accounts (NIPA) 

and are sub-aggregates of GDP2. Using distributional data from BEA’s benchmark InputOutput (IO) tables, the data in each column are allocated to the 192 commodity rows.

Summing these data by row yields commodity final demand on a purchaser value basis.

Commodity output in the input-output system is on producers’ value rather than 

purchaser value. Margin costs, i.e., transportation, wholesale, retail, and insurance, are 

removed and reallocated to the sectors providing the margin services. In the intermediate 

portion of the Use table, for a given industry, the input cells reflect the producer cost of 

the input commodity. Margin costs for commodity inputs are reallocated to the margin 

sectors.

In the “FD” matrix the columns containing the detailed category data are purchaser value. 

For imports of goods, the column data is foreign port value. Producer value excludes 

margin costs and import valuation adjustments, which are removed in the margin 

reallocation and import valuation adjustment columns, respectively. There are 14 margin 

reallocation columns and two import valuation adjustment columns3 in each “FD” matrix. 

These columns and their functions are described below.

Three margin columns are associated with 2 of the 10 non-import aggregate final demand 

categories4. The three margin columns are used to reallocate margin costs for four retail, 

one wholesale trade, and five transportation commodities. Wholesale has one 

reallocation column and the reallocation of the four retail types and five transportation 

modes are combined into one column each. 8 of the 10 other non-import aggregate final 

demand categories have one margin column for all of the four retail, one wholesale, and 

5 transportation commodities. 

Commodity margin rates5 are calculated for the margins for each final demand category.

Each rate is multiplied by the purchaser value of the commodities within the associated 

final demand category. The resulting margins appear as negative entries in the margin 

columns for that final demand category. Within each margin column, the sum of these 

entries is exactly offset by positive values inserted in the row cells corresponding to the 

appropriate margin sectors, so that the column sum is zero.

2 Chain weighted aggregation methods must be used for tables containing values in chain weighted 

dollars.

3 Import valuation adjustments reconcile differences in the valuation of import goods: NIPA accounting 

uses foreign port value, whereas input-output accounting uses domestic port value as the producer value.

Because imports are negative values in the NIPAs, and because the import valuation adjustments increase 

the absolute value of imports, the import adjustment values are negative and the reallocation offsets are 

positive.

4 The existence of the PCE_Bridge and PEQ_Bridge files from BEA allow us to have 3 margin columns for 

the Personal Consumption Expenditures and Private Investment in Equipment aggregate final demand 

categories.

5 Margin rates are based on data from BEA’s benchmark IO tables.
Page - 5

There are two import valuation adjustment columns in the Imports of Goods and Services

category. The columns are used to reallocate the import valuation adjustment on 

imported goods and services for transportation and insurance in one column, and 

wholesale trade in the other. 

Import valuation adjustment rates6 are calculated on a commodity basis for each of the 

two import valuation adjustment columns. Each rate is multiplied by the foreign port (or 

purchaser) value of the commodity row for the Imports of Goods and Services category. 

The resulting import valuation (margin) adjustments appear as negative entries in the 

adjustment columns. Within each adjustment column, the sum of these entries is exactly 

offset by positive values inserted in the row cells corresponding to the appropriate margin 

sectors, so that the column sum is zero.

"FDAGG" Matrix (192x11)

This matrix is an aggregated version of the "FD" matrix above for the year specified in the 

matrix name. The 132 detailed final demand categories along the columns of the “FD” 

matrix are aggregated to 11 categories as shown in the file, “FDSectorPlan30.xlsx”. The 

11 columns corresponding to the 11 aggregate categories are on a producer value basis. 

1 Personal consumption expenditures

2 Private investment in equipment

3 Private investment in intellectual property products

4 Private investment in nonresidential structures

5 Private investment in residential structures

6 Change in private inventories

7 Exports of goods and services

8 Imports of goods and services

9 Federal Government defense consumption and investment

10 Federal Government non-defense consumption and investment

11 State and local government consumption and investment

6 Import valuation adjustment rates are calculated from detailed trade data.
Page - 6

How to Access Files

Data files:

The folder “IONom” contains nominal (current) dollar historical I-O/FD data. The folder

“IOReal” contains chain weighted real 2012 dollar historical I-O/FD data. The folder

“IO2032” contains chain weighted real 2012 dollar I-O/FD projections. No current dollar 

I-O table projections were made.

The data files contained in these folders are described in Part I. The data are EXCEL 

workbooks with each year a worksheet in the workbook. These matrices contain only data

and row and column sector code identifiers.

The sectoring plan files are needed to understand the data files because the data files 

have no labels to signify columns and rows.

Sectoring plan files:

The BLS industry sectoring plan is provided by the EXCEL file called “SectorPlan30.xlsx”.

In addition, “FDSectorPlan30.xlsx” provides the final demand sectoring plan.
Page - 7

Conversion of Tables to Inverse and Other Coefficient Matrices

From the make and use tables, the following are defined:

^: A symbol that, when placed over a vector, indicates a square matrix in which the 

elements of the vector appear on the main diagonal and zeros elsewhere.

q: Total commodity output. A column vector in which each entry shows the total 

amount of commodity output. It is a commodity-by-one vector.

g: Total industry output. A column vector in which each entry shows the total 

amount of each industry's output, including its production of scrap. It is an 

industry-by-one vector.

U: Intermediate portion of the use matrix in which the column shows for a given 

industry the amount of each commodity it uses, including noncomparable 

imports and rest of the world adjustment and scrap, used and secondhand 

goods. This is a commodity-by-industry matrix.

V: Make matrix, in which the column shows for a given commodity the amount 

produced in each industry. It is an industry-by-commodity matrix.

B: Direct input coefficients matrix (also known as the direct requirements matrix) in 

which entries in each column show the amount of a commodity used by an 

industry per dollar of output of that industry. It is a commodity-by-industry 

matrix.

1

ˆ

−

B = Ug

( 1 )

D: A matrix in which entries in each column show, for a given commodity (excluding 

scrap), the proportion of the total output of that commodity produced in each 

industry. It is assumed that each commodity (other than scrap) is produced by 

the various industries in fixed proportions (industry technology assumption). D is 

an industry-by-commodity matrix. D also is referred to as the market share 

matrix or transformation matrix.

1

ˆ

− D = Vq

( 2 )

i: Unit (summation) vector containing only l's.

I: Identity matrix, where I = 

i

ˆ. Each of the diagonal elements of the matrix contain 

the value 1, and zeros elsewhere.

e: A column vector in which each entry shows the total final demand purchases for 

each commodity from the use table.
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Mathematical Derivation of the Total Requirements Tables for Input-Output Analysisi

From the above definitions, the following identities are derived:

q = Ui + e ( 3 )

g = Vi ( 4 )

The model expressed in equations (1) through (4) thus involves two constants (B, D) and 

five variables (U, V, e, q, g). The model solution is derived as follows:

From (1) and (3), we derive:

q = Bg + e ( 5 )

From (2) and (4), we derive:

g = Dq ( 6 )

Substituting (6) into (5) and solving for g:

q = B(Dq) + e

(I – BD)q = e

q = (I-BD)-1e ( 7 )

The matrix (I-BD)-1is known as the commodity-by-commodity total requirements matrix 

and it shows, on a per-dollar basis, the commodity output the economy generates to

provide commodities to final users.

Substituting (5) into (6) and solving for g gives:

g = D(Bg + e)

(I - DB)g = De

g = (I - DB)-1De( 8 )

The matrix (I - DB)-1is known as the industry-by-industry total requirements matrix and 

it shows, on a per-dollar basis, the industry output the economy generates to provide an 

industry’s commodities to final users. The vector De is a final demand vector where each 

entry shows the final demand for an industry’s output.

Substituting (7) into (6) and solving for q gives:

g = D(I – BD)-1e ( 9 )

The matrix D(I – BD)-1is known as the industry-by-commodity total requirements matrix 

and it shows, on a per-dollar basis, the industry output the economy generates to

provide commodities to final users.

i The notation and derivation of the tables presented follow the System of National Accounts 

recommended by the United Nations. See: A System of National Accounts Studies in Methods, Series F 

No. 2 Rev. 3, United Nations, New York, 1968; also, Stone, R., Bacharach, M. & Bates, J., "Input-Output 

Relationships, 1951-1966," Programme for Growth, Volume 3, London, Chapman, and Hall, 1963.