Samuels, Jon D. (2012): "Semiconductors and U.S. Economic Growth"
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Semiconductors and U.S. Economic Growth∗
Jon D. Samuels
Department of Economics
IQSS
and
Johns Hopkins University
Harvard University
April 1, 2012
Abstract
Semiconductor technology is widely credited with driving the evolution of information technology, yet the device’s use as an intermediate input by many sectors of the
economy makes its economic impact difficult to quantify. I use the prototype NAICSbased industry production account data of Jorgenson et al. (2011) and the weighting
scheme of Domar (1961) to measure the direct impact of semiconductor production
on aggregate growth and productivity, and the contribution of semiconductors via industries that use these devices as intermediate input. Using total factor productivity
as a measure of innovation, I find that over the 1960-2007 period, innovation in the
Semiconductor industry grew close to 9% per year, twenty five times the innovation
growth rate for the economy as a whole, and accounted for close to 30% of aggregate
economic innovation. By sector, semiconductor deepening accounted for 37% of the
growth in labor productivity in the Communications Equipment industry, 25% of the
growth of the Other Electronic Products industry, 14% of Educational Services, and
9% of labor productivity growth in the Computer and Peripheral Equipment industry
for the period. More recent data on prices through 2009 suggests that innovation in
semiconductors remained strong in 2008, but slipped a bit in 2009 amidst the financial
crisis.
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∗
As the Robert M. Burger Fellow, I gratefully acknowledge financial support from the Semiconductor
Research Corporation, along with support from Celia Merzbacher and Ginny Wiggins at SRC and Daryl
Hatano of SIA. I thank my academic advisor at JHU, Jon Faust. I am indebted to Dale Jorgenson for
introducing me to the world of growth accounting, encouraging me to apply for the Burger Fellowship, and
supporting me during the writing of this report. I thank Mun Ho for comments and suggestions.
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Samuels, Jon D. (2012): "Semiconductors and U.S. Economic Growth"
1
Introduction
Since Robert Solow’s statement in 1987 of the productivity paradox as “You can see
the computer age everywhere but in the productivity statistics,” a substantial body
of research has emerged devoted to measuring the impact of Information Technology
on economic growth in the U.S. and the world economy. As a result of this research,
consensus has emerged on the importance of Information Technology as a driving force
of economic growth across the world, and key links have been made between IT and the
productivity statistics. The economic boom in the U.S. from 1995-2000 is now generally
accepted as being led by the production of, and investment in, Information Technology
capital goods and new research suggests the importance of information technology as
an impetus for innovation in industries that make intensive use of IT.1 Jorgenson (2001)
traces the IT-boom of 1995-2000 to a change in the product cycle of the Semiconductor industry, while Jorgenson et al. (2007) measures the contribution of IT-producing
industries to aggregate productivity growth. While these studies do identify the role of
the Semiconductor industry in measured aggregate economic growth and productivity,
they do not present estimates of the contribution of semiconductors to industries that
use these devices as inputs. In this study, using a prototype NAICS-based industry
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production account that includes estimates of how all industries in the U.S. economy
combine to produce aggregate output, I not only identify the role of semiconductors in
aggregate economic growth and productivity, but also the contribution of semiconductors to the production of all industries that make use of these devices in their production
processes.
Innovation within the Semiconductor industry has had far reaching technological
and economic implications. The semiconductor industry is a conglomerate of producers of logic and memory chips that are the backbone of modern computing, makers of
complex system on a chip (SoC) devices embedded in other electronic products such as
cell phones and digital cameras, semiconductor equipment manufactures, and manufactures of semiconductor material itself. The chain of production of many chip producers
has evolved over time; now, many semiconductor chip companies in the U.S. are fabless,
that is, the companies outsource the actual production of the semiconductor hardware
to focus on design and sales. The objective of this study is to measure the economic
impact of the industry in the U.S. as a whole. The output of the Semiconductor industry in the economic accounting described below includes all of the establishments
located in the U.S. in one industry, and the framework allows the researcher to trace
this output, and that imported from international producers, through to purchasing
1
See Jorgenson et al. (2005) and Jorgenson et al. (forthcoming).
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industries in the U.S. that use semiconductors as intermediate input.
A long history of research, conceptual, methodological, and empirical, on economic
measurement has produced a widely accepted tool kit that allows researchers to analyze
the foundations of economic growth by decomposing aggregate growth into its sources
across industries, inputs used by industries to produce output, and economic innovation
that measures the state of technology that producers use, and how it evolves over
time. This tool kit, which originated with Solow’s aggregate production function in
Solow (1957), was replaced with the new framework for analyzing the sources of growth
developed by Jorgenson and Griliches (1967) and Jorgenson et al. (1987), and shown
to be the “killer application” for analyzing the impact of information technology on
growth and productivity by Jorgenson et al. (2005).2
A primary motivation for the new framework is to measure the role of innovation in
the economy and its origins across industries. Since innovation itself is unobservable,
the framework uses economic theory to arrive at estimates of innovation and how it has
evolved over time. It turns out that by using economic theory, one need not pin down
the entire production technology used by the agents in the economy, but one needs
measure of the quantities of outputs and inputs used by industries over time, and their
respective prices. Thus, the new framework requires considerable effort to develop a
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set of economic accounts that properly captures the economic outputs of industries and
how industries use different inputs to produce that output. Furthermore, in order to
relate to officially reported economic growth of the aggregate economy, the measures
must be based on standards of national income accounting, and internally consistent
with those measures.
The importance of innovation in abstract is intuitive. In a speech by Fed Chairman
Ben Bernanke (Bernanke (2011))3 :
Innovation has not only led to new products and more-efficient production methods, but it has also induced dramatic changes in how businesses
are organized and managed, highlighting the connections between new ideas
and methods and the organizational structure needed to implement them.
For example, in the 19th century, the development of the railroad and telegraph, along with a host of other technologies, were associated with the rise
of large businesses with national reach. And, as transportation and communication technologies developed further in the 20th century, multinational
corporations became more feasible and prevalent.
This paper intends to quantify the role of innovation in growth and the Semiconductor
2
3
Approach dubbed the “Killer application” by Jorgenson and Wessner (2004).
Available http://www.federalreserve.gov/newsevents/speech/bernanke20110516a.htm
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industry’s primary role in the evolution of technology over time.
One key feature of the growth accounting framework is that aggregate economic
growth is decomposable to its sources across and within industries that make up the
aggregate economy. Industries produce output using inputs produced by other sectors
of the economy in addition to primary inputs, capital and labor, and according to the
prevailing level of technology. Aggregate growth depends on the quantity of output each
industry produces, and how industries use inputs produced by other sectors, primary
inputs, and the level of technology. In contrast to other methods that give indicators
of innovation and resource accumulation, as in World Information Technology and
Services Alliance (2010) or National Science Foundation (2010), this framework gives
internally consistent measures that aggregate to economic growth and productivity for
the whole U.S. economy. This allows for a direct comparison and analysis from a
top-down or bottom-up perspective of how different industries and their interactions
produce innovation and growth.
An important element of the new framework is that economic output and input
is measured in constant-quality units. The importance of this can be seen by simple
example; if we are measuring the quantity of goods produced over time, we need to
adjust the current vintage of product to be comparable with earlier vintages. An easy
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to grasp case for the need for quality adjustment is IT-goods whose characteristics are
changing rapidly over time, for example, a computer whose processing power, hard disk,
and memory has doubled but the components are housed in the same single unit. The
economic output of the computer producer has, essentially, doubled, hence the quantity
of output doubles in constant quality terms, and in the case where the unit price is fixed
over time, the constant quality price of computers falls by 50 percent.4 An important
feature of the new framework is when outputs are also used as inputs, both the input
and output price reflect the quality-adjusted quantity produced and used, i.e. both
sides of the account are adjusted for quality.
When economic outputs, and the corresponding inputs used to produce the outputs,
are properly adjusted for quality and composition, the change in output not accounted
for by the change in inputs yields a primary measure of economic innovation, namely
total factor productivity. In an accounting sense, total factor productivity is a residual
defined as the growth rate of output less the growth rate of input; in an economic
sense total factor productivity measures the level of technology in the economy and
how it evolves over time. Changes in innovation are captured as changes in technology
4
Typically, constant quality prices are produced with hedonic or matched model methods. Wasshausen
and Moulton (2006) describes the current implementation in the national accounts. Quality adjustment is
an ongoing area of research since outputs like services are notoriously difficult to measure in constant quality
units.
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because either more output can be produced with existing levels of input, which is
clearly innovation, or higher quality output can be produced with the current level of
input, also clearly innovation. Dredging up the computer example again, if the same
resources produced the same number of computers in consecutive years, but the latter
year’s computers were twice as fast, this technological improvement is accounted for in
the constant quality output, and since the resources employed are fixed in this example,
this innovation is measured as total factor productivity.
The total factor productivity measure of innovation has been endorsed the Advisory
Committee on Measuring Innovation in the 21st Century (Schramm et al. (2008)) made
up of a select group of members from the business and academic community. The
Committee recommends:
Developing annual industry level of total factor productivity by restructuring the NIPAs to create a more complete and consistent set of accounts
integrated with data generated by other statistical agencies to allow for the
consistent estimation of the contribution of innovation to economic growth.
This paper outlines the construction of just such a data set and uses the data to analyze
the sources of growth and innovation from 1960-2007 in the U.S.
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The goal of this paper is to measure the contribution of Semiconductors to economic growth using the growth accounting tool kit. The Semiconductor industry has
two defining characteristics that makes the new framework for analyzing productivity
salient; first, the lion share of semiconductor output is sold as intermediate input, so the
framework is able to capture how industries make use of this input in production, and
second, semiconductors and products derived from them have rapidly changing product quality. I measure the contribution of the Semiconductor industry to aggregate
growth and productivity, and its contribution to industries that use semiconductors as
an input to their production processes. A key feature of the methodology below is that
it is internally consistent, so measure of output flowing from one industry are consistent with the inputs used by other industries, and consistent with official measures of
national output and income, so that direct comparisons can be made across industries
and industry contributions aggregate to the economy as a whole.
The paper is organized as follows. Section 2 details the methodological approach of
growth accounting. Section 3 details the construction of the prototype NAICS-based
production account for 1960-2007 to match the concepts in the growth accounting
framework. Section 4 uses the framework to measure the contribution of semiconductors
to the output growth of other industries in the economy, while Section 5 details the
Semiconductor industry’s contribution to aggregate growth and productivity. Section
6 presents a back of the envelope calculation on the productivity performance of the
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Semiconductor industry during the 2007-2009 period, and Section 7 concludes.
2
Growth Accounting: A primer
This section reviews the growth accounting tool kit and its foundations. The economy as
a whole is modeled as a panoptic collection of industries. Individual industries produce
output over time by accumulating and employing more resources, and by innovating to
produce higher quality output or to employ current resources more efficiently.
The first part of this section shows how each of these industries’ growth over time can
be decomposed into accumulation of inputs used in production and innovation, labeled
as growth in total factor productivity (TFP). The second part shows how aggregate
economic growth and innovation can be traced to its sources across industries.
2.1
Sources of Industry Growth
In the analysis that follows, the fundamental economic agent is a representative industry. The first step towards decomposing aggregate economic growth to its industry
sources is to analyze the determinants of industry economic growth. The growth ac-
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counting tool kit assumes an industry-specific production function that expresses each
industry’s output as a function of inputs and its available technology at that point in
time.5
The constant-quality quantity of output produced by representative industry j depends on the industry’s use of capital, labor, intermediate materials, and the level of
technology T at time t. The non parametric production function is written:
Yj = fj (Kj , Lj , Xj , Tj )
(1)
By differentiating equation (1) with respect to time and assuming factors are paid their
marginal products, optimality conditions for producer profit maximization imply that
the growth of output can be decomposed into changes in inputs and TFP growth:
∆ ln Yj = v̄K,j ∆ ln Kj + v̄L,j ∆ ln Lj + v̄X,j ∆ ln Xj + vT,j
(2)
where v̄K,j is the average income share of capital in periods t and t − 1, and similar
for the other inputs. vT,j is TFP growth for industry j from period t − 1 to t and
measures innovation growth over the period, capturing gains in technology, increases in
output quality (holding inputs fixed), and any changes in managerial or business acumen
5
Notation throughout is borrowed from JHS.
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Samuels, Jon D. (2012): "Semiconductors and U.S. Economic Growth"
that produces more output with the same level of resource use. With data on the
production of output by the j industries in the economy and their use of capital, labor,
and intermediate materials, the unobservable contribution of innovation to growth for
the industry is the residual after subtracting the contributions of factors of production
from the growth in industry output.
Furthermore, industry output can be decomposed into contributions from value
added growth and contributions from intermediate input. The fundamental accounting
identity is that under perfect competition the value of industry output equals the value
of inputs used to produce that output:
PY,j Yj = PV,j Vj + PX,j Xj
(3)
where PY,j is the price of industry j’s output and PX,j and Xj are the prices and
quantities of intermediate purchases of industry j. PV,j and Vj are the price and quantity
of industry value added and PV,j Vj captures the direct nominal value added flow that is
the dollar value contribution of industry j that is not accounted for by the production
of goods or services by other sectors and used in the production process of industry
j.6 This avoids double counting the value of output produced by other industries in
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the contribution of industry j. By differentiating equation (3) with respect to time,
grouping terms involving quantities, and taking a discrete time approximation:
ln ∆Yj = vV,j
¯ ∆ ln Vj + vX,j
¯ ∆ ln Xj
(4)
where vV,j
¯ is the average nominal value added share in gross output in periods t and t−1,
and vX,j
¯ is the average intermediate input share. Equation (4) expresses the growth
rate in industry output as a weighted sum of the growth rates of value added and
intermediate input, where the weights are value shares in output. Equation (4) can be
used to estimate value added growth by industry when output growth and intermediate
growth are observed; this is known as the double-deflation approach because outputs
and inputs are deflated individually.
2.2
Aggregate Growth and Innovation
This section shows how contributions from individual industries aggregate to the economy as a whole. The production possibility frontier expresses growth at the aggregate
level as a weighted sum of the growth rates of individual industries. This approach ac6
It could be the case that the output of industry j is also used as an input into the production of industry
j, in which case this treated as both an output and an input. For purposes of calculating value added, this
is subtracted from the value of output just as any other intermediate input.
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Samuels, Jon D. (2012): "Semiconductors and U.S. Economic Growth"
commodates changes in relative output prices across industries, thus reflects the rapid
technological progress in information technology goods that manifests as rapidly falling
prices. Using real value added Vj from equation (4), aggregate value added growth from
the production possibility frontier is written:
∆ ln V =
X
w̄j ∆ ln Vj
(5)
j
where w̄j is industry j’s average value added share in aggregate value added over periods
t and t − 1; aggregate economic growth is the weighted sum of the growth rates of
individual industry’s growth rates, weighted by each industry’s share of aggregate value
added.
Combining equations (5),(4),(2) yields a decomposition of aggregate growth across
industry sources of growth and industry productivity growth rates:
∆ ln V =
X
j
w̄j
v̄L,j
v̄K,j
1
∆ ln Kj + w̄j
∆ ln Lj + w̄j
v̄T,j
v̄V,j
v̄V,j
v̄V,j
(6)
Aggregate value added growth can be decomposed into the weighted contributions of
capital, labor, and productivity across industries where the weights
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w¯j
v̄V,j
are referred to
Domar weights and reflect the double nature of changes in production: the direct effect
on aggregate value added and the indirect effect on final purchasers of the industry’s
output.7
3
A Prototype NAICS-based Production Account
This section describes, in brief, the data sources and methodology used to implement the
growth accounting framework described in Section 2. This coincides with the approach
used in Jorgenson et al. (forthcoming). Specifically, this section discusses the data
necessary to implement equation (2) which forms the basis for the entire system of
growth accounts. We split the aggregate economy into seventy industries which include
a wide range of manufacturing industries, including details on several producers of
IT equipment and software, along with detail on service sectors, including those that
provide information technology services.
It is important to rehash that it is not simply a matter of constructing ad hoc
data to match the concepts in the growth accounting model, but our goal is to form a
7
An equivalent view of productivity, though not explicitly discussed here, is a decrease in industry output
prices holding input prices fixed. This lends intuition to the dual effects of productivity growth, the first on
aggregate value added itself, the second as cheaper prices facing purchasers.
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Samuels, Jon D. (2012): "Semiconductors and U.S. Economic Growth"
set of internally consistent economic accounts so that concepts are comparable across
industries and in accordance with the standards of national income accounting. The
set of accounts satisfies national accounting identities in that all newly produced and
consumed values are accounted for in the formation of national income by sector. The
accounts described below represent the first effort of its kind to assemble a complete
set of accounts on a NAICS industry classification covering 1960-2007. The NAICS
classification allows for a finer classification of the role of services, including IT-Services.
The long time series permits a historical accounting of the evolution of economic growth
across the 1960-2007 horizon and a comparison between different periods within the
sample.
3.1
Output and Intermediate Input
The growth accounting approach above requires measure of output and intermediate
input for each industry in the economy in current and constant dollars. For the years
1998-2007, this data is produced by the Bureau of Economic Analysis for some 500
sectors which we aggregate to our selected industries. For the years 1972-2006, we use
the 202 sector NAICS based data from the BLS to construct output for our selected
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industries, and for 1987-1997 control these estimates to 65 sector data from the national accounts produced by the BEA. To estimate NAICS based gross output for our
industries for 1960-1972, we bridge industry output from previous studies based on SIC
to our NAICS industries.8 This gives a time series of nominal output for our selected
industries, which also serves as control totals for constructing the intermediate use estimates described below. We use a similar linking system to construct the time series
of industry output prices, but employ tornqvist aggregation to go from more detailed
data to our selected industries.
The estimates of intermediate input by industry are derived from a time series of
input output accounts that cover inter-industry transactions. We make them internally consistent with the values of industry output described above using the iterative
proportional fitting routing described in Jorgenson et al. (1987). Furthermore, the estimates of the values of labor and capital services descried below are consistent with
the value added row in the time series of input output tables we construct.
The conceptual scheme of the input output framework is represented in Figure 1.
Each column of the IO table represents an industry and each row for that column gives
it purchases of commodity i, labeled Xij . Yj is the output produced by industry j, and
industry value added is divided into payments to capital and labor services, and net
8
Specifically, we use and 88-sector SIC data set based on the methodology described in Jorgenson et al.
(2005).
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Samuels, Jon D. (2012): "Semiconductors and U.S. Economic Growth"
taxes. Each row of the table represents how each commodity is used, whether it be
sold as intermediate input to other industries or to final demand Fi . As an accounting
identity, the value of income accruing to capital and labor equals sales to final demand,
the C + I + G + X − M definition of GDP.
Figure 1: Input Output Structure
j
i
Xij
Fi
Yic
Kj
L
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j
Tj
Yj
To construct the input output data for 1993-2007, we start with the inter industry
transactions data from the Employment Projections group of the BLS that covers close
to 200 NAICS sectors. We collapse their input output matrices to our industries of
interest and use the iterative proportional fitting routing (RAS) described in Jorgenson
et al. (1987) to fit them to our control totals of industry output describe above, and
BEA data on final demand so that the resulting matrices produce an estimate of GDP
that matches the national accounts. We also construct a time series of make tables
consistent with our estimates of industry output. The make tables show the relationship between industry output and commodity output to capture that one industry can
produce more than one commodity. For example, the Chemical industry produces non
durable chemical products, but also machinery. The use table shows how industries
use commodities, and the make table tells us the relationship between industry and
commodity output. For years 1960-1992, we use the 1993 input output matrix as an
initial guess, the final demand data from the BEA and use the RAS procedure and
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Samuels, Jon D. (2012): "Semiconductors and U.S. Economic Growth"
industry output control totals described above to construct input output matrices.
To derive prices for intermediate purchases, we assume all industries pay the same
purchase price for individual commodities. We translate the industry output prices
described above to commodity prices using the make table so that:
∆ ln PY C,i,t =
X Mj,i
V Ci
j
∆ ln PY,j,t
(7)
so the commodity price is a weighted average of industry output prices where the weighs
are each industry’s share of the total commodity being produced. The final price paid
by purchasing industries also reflects the import prices available to producers. Thus,
we construct the final supply price as a composite price of the domestic supply price
and the price of imported goods, where the weights reflect the share of the commodity
being imported.9
Finally, the quantity of intermediate input for each sector reflects the changing
composition and prices of detailed commodities and is defined as:
∆ ln Xj,t =
X
v̄i,j,t ∆ ln Xi,j,t
(8)
i
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so that total intermediate growth by industry required to implement equation (2) is a
weighted average of the growth rates of the detailed commodities each industry uses
as intermediate input. It is important to note that while prices paid for individual
commodities are assumed to be the same across industries, the composite price that is
implicit in equation(2) will differ by industry because the weights in equation (8) differ
by industry.
Summarizing, with data on output and intermediate, and their respective prices we
construct ∆ ln Xj,t corresponding to the concept of real intermediate input growth in
equation(2) for each industry. The estimates of capital and labor described below are
consistent with value added in the IO accounts, forming an internally consistent set of
accounts to use for productivity analysis.
3.2
Capital Input
Analogous to aggregates of industry output and intermediate input, which are constructed to reflect changing relative prices of the components, capital and labor inputs
by industry are adjusted to reflect heterogeneity in types of capital and labor used
by producers. This section describes construction of capital input for each industry.
9
Import prices are given implicitly in the BLS use tables that give nominal and real imports by commodity.
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Capital input is the flow of capital services from the installed stock of capital into
production.
The first step is to estimate the capital stock for each employed asset for each
industry over time. The capital stock is estimated with the perpetual inventory method
with data from the fixed assets accounts from the Bureau of Economic Analysis that
gives data on the price, quantity, and value of investment goods purchased by each
industry since 1901.10 As discussed above, the prices are in constant-quality so the
estimates of capital stock reflect constant-quality measure of the stock of available
capital. Capital stock at time t is defined as:
Ak,j,t = Ak,j,t−1 (1 − δk ) + Ik,j,t
(9)
where Ik,j,t is industry j’s real purchase of investment goods of type k and δk is the depreciation rate for each type of capital good, assumed to be the same across industries.
Again, a key feature of the framework is that Ik,j,t is in constant quality units and the
price index reflects changes in the quality of new investment goods. Depreciation rates
are taken from BEA’s fixed asset study.11 Today’s capital stock for each industry j for
type of capital k depends on the pervious period’s capital stock, adjusted for depreci-
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ation and for new investment goods purchased in the period. In this prototype we use
52 assets based on BEA’s capital stock study, in addition to the stock of inventories
and land capital.12
The capital service flow into production is proportional to the current and lagged
stock and its prices is imputed using the Jorgenson rental cost of capital. Specifically:
1
Kk,j,t = (Ak,j,t + Ak,j,t−1 )
2
(10)
so that half of periods t’s investment comes online for production purposes in year t, and
the other half in year t + 1. The rental cost of capital, i.e. the per period usage price
for the installed stock of capital, is unobserved and imputed using economic theory.
The Jorgenson cost of capital for this implicit rental price PK,k,j,t for asset type k in
industry j at time t is:
PK,k,j,t =
1 − IT Ck,t − τt Zk,t
[rk,j,t PI,j,t−1 + δj PI,k,j,t ] + τp PI,k,j,t−1
1 − τt
(11)
where ITC is the investment tax credit rate in asset k, τt is the statutory tax rate, τp
is the property tax rate, and Zk,t is the present discounted allowance of depreciation
10
11
12
See http://www.bea.gov/national/FA2004/index.asp
An exception is for autos in which case we use a best geometric fit to BEA’s depreciation schedule.
For details on the construction of the stocks of land and inventories see Jorgenson et al. (2005).
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allowances for asset k. rk,j,t is a the ex-post rate of return imposing that total capital
income in the industry is exhausted across income by asset, that is:
X
PK,k,j,t Kk,j,t = PV,j,t Vj,t − PL,j,t Lj, t
(12)
k
Finally, the industry measure of capital services is constructed as an index number
that takes into account the changing composition of capital over time:
∆ ln Kj,t =
X
v̄k,j,t ∆ ln Zk,j,t
(13)
k
where v̄k,j,t is each asset’s average share of capital income in year t and t-1. Industry
capital services growth is a weighted index of the growth rates of the service flows of the
asset stocks in the industry, each weighted by its rental capital cost share. With this
framework, assets with high rental costs, for example with those high depreciation rates,
have a higher weight in the aggregation. For some intuition on the importance of using
rental costs, information technology goods typically have relatively high depreciation
rates so that these assets receive a high weight when their rental cost is used as a
weight. In this case, the rapid accumulation of IT assets manifests in a fast growing
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measure of industry capital services. These rental shares reflect the marginal products
of different types of capital, so those with a higher marginal product receive a higher
weight in aggregation.
Summarizing, using the fixed asset data from the BEA, augmented to included land
and inventories, the price and quantity of capital services by industry is derived using
equations (9)-(13).
3.3
Labor Input
Labor input reflects the heterogeneity of each industry’s work force. Using data from the
decennial census we cross classify workers, their hours, and compensation by industry by
sex, class (employee, self-employed), age (eight age groups), and educational attainment
(six categories of educational attainment).13 For years other than the census, due to
much smaller sample sizes, we construct a smaller set of matrices that contain a subset
set of the detail based on the March supplement of the Current Population Survey. We
then use the iterative proportional fitting routine (RAS) described in Jorgenson et al.
(1987) to construct full matrices for years outside the census by using the census matrix
as an initial guess and fitting it to the marginal matrices.
13
Compensation for self employed workers is set to be the same as those employees of the same demographic
characteristics.
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These labor matrices are scaled to match data from the national accounts so that
they are consistent with the data on output, intermediate input, and capital services.
Specifically, the matrices of employment, hours, and labor compensation are scaled
to match the NIPA data, thus are estimated so that the value of labor plus capital
compensation equals value added from the input output accounts. Thus, the sum of
labor compensation, capital compensation, and net taxes is internally consistent with
the value added row of the input output tables described above.
Using the matrix of hours worked and labor compensation by worker and industry,
the industry index of labor input reflects the changing composition of the work force
and is defined as:
∆ ln Lj,t =
X
v̄l,j,t ∆ ln Hl,j,t
(14)
l
where v̄l,j,t is the average compensation share for worker type l in industry j and Hl,j,t
is that group’s corresponding hours worked. Thus, labor input for the industry required
to implement equation (2) is defined as a weighted average growth rate of hours worked
by worker, where the weights are the worker compensation shares. These compensation
shares reflect the marginal products of different workers, so those with a higher marginal
DRAFT
product receive a higher weight in aggregation.
While all of the source data required to implement the above procedure to construct
labor input is available for 2003-2007, much of the detail on NAICS is missing before
2003. Therefore, to construct matrices of employment, hours, and labor compensation
for 1960-2002, we link the SIC matrices used in Jorgenson et al. (2007) using ratios of
employment in SIC to NAICS published by the BLS Current Employment Statistics.
We do this by detailed demographic category so a share of workers gets mapped from
each SIC industry to the same demographic group of the corresponding of the NAICS
industry, or often industries. From 1987-2003 these matrices are scaled to the data from
the BEA on labor compensation by industry, so these estimates are consistent with the
national accounts, along with the measures of capital compensation and industry value
added described above.14 For years before 1987, we use a combination of NAICS based
control totals for employment from the BLS and internally constructed control totals
for labor compensation based on a mapping between SIC and NAICS industries.
14
The BEA provides detail for about 65 industries. We scale the total of the corresponding industries to
match the data from BEA.
14
Samuels, Jon D. (2012): "Semiconductors and U.S. Economic Growth"
4
How Industries Use Semiconductors
With the methodology and data described above, the role of semiconductors as an input
into the production processes of other industries can be measured. While Jorgenson
(2001) identified the Semiconductor industry as the key driver of innovation across
other producers of Information Technology, this is the first systematic study of the
contribution of semiconductors to the growth of using industries.
First, as discussed above, the rapid quality gains in semiconductor performance are
reflected in the constant quality price index of semiconductors. Figure 2 shows the price
of semiconductors relative to the GDP price on a logarithmic scale. On the log scale,
exponential price declines appear as a linear trend. The figure shows the exponential
decline in semiconductor prices relative to other prices in the economy and the turning
point in 1995 which Jorgenson (2001) argues is due to a shift in the product cycle of
new chips to two years from three. This change in product cycle manifests as change in
the slope of the price line around 1995; price declines averaged about 5% percent per
year before 1995 and about 15% per year after. These rapid price declines reflect the
quality gains in semiconductor performance because a doubling in the quality of the
chip being produced corresponds to a 50% percent decline in the corresponding price
DRAFT
index, ceteris paribus. This rapid price decline produces incentives for industries to
substitute towards making use of these cheaper, higher quality, devices.
4.1
Semiconductor Use as an Intermediate Input
To measure the contribution of semiconductors to the growth of using industries, intermediate input in equation (2) can be further decomposed to show the impact of
semiconductor use:
∆ ln Yj = v̄K,j ∆ ln Kj + v̄L,j ∆ ln Lj + v̄Xx,j ∆ ln Xxj + v̄Xs,j ∆ ln Xsj + vT,j
(15)
where Xxj is the intermediate use excluding semiconductors by industry j and Xsj is
the use of semiconductors in producing the output of industry j.
Figure 3 shows that the contribution of semiconductors, v̄Xs,j ∆ ln Xsj in equation
(15), accounted for a significant portion of output growth for many sectors of the economy. Over the period as a whole from 1960-2007, semiconductor use produced about
two percent per year of output growth for the Communications Equipment and Computer Equipment industries.15 While at first glance this two percent per year seems
15
The semiconductor industry uses semiconductors to produce semiconductors, captured via the diagonal
matrix of the use table.
15
Samuels, Jon D. (2012): "Semiconductors and U.S. Economic Growth"
Figure 2: Semiconductor Prices
100.00
10.00
1.00
0.10
Note: Domestic supply price of the semiconductor commodity relative to the GDP
price. Log scale. Source: Author’s calculation.
DRAFT
trivial, this amounts to about 37% of total output growth of the Communications industry, and 8% of the total growth of the Computer industry. In other words, based
on Figure 4, which shows the share of each industry’s output growth accounted for by
use of semiconductors, semiconductor use alone accounted for 37% of the growth in
Communications Equipment over the period, while combining all of the other factors
of production used by the industry including capital, labor, the other 69 type of intermediate input, and total factor productivity accounted for only 63% percent of output
growth. More strikingly, if factors contributed equally, the factors of productions would
each account for about 1.5% of output, but semiconductors account for about 26 times
that amount!
Figure 3 shows that semiconductor use had a broad impact on other industries in
the economy. While semiconductors had the largest impact on other producers of Information Technology goods, growth in semiconductor use also contributed significant
amounts to growth of other producers of durable goods like the Motor Vehicles and
Machinery industries, but also a wide range of producers of non durables and services.
Plastics and Metals made significant use of semiconductors as did Broadcasting, and
the Wholesale sector. It is interesting that during the 2000-2007 period, when the
16
Samuels, Jon D. (2012): "Semiconductors and U.S. Economic Growth"
Figure 3: Contribution of Semiconductors to Industry Output Growth
1960-2007
2000-2007
Communications equipment…
Semiconductor and other electronic…
Computer and peripheral equipment…
Other electronic products
Electrical equipment appliances and…
Software publishing
Motor vehicles bodies and trailers…
Machinery
Other transportation equipment
Plastics and rubber products
Miscellaneous manufacturing
Primary metals
Fabricated metal products
Nonmetallic mineral products
Broadcasting and telecommunications
Furniture and related products
Paper products
Computer systems design and related…
Printing and related support activities
Textile mills and textile product mills
Chemical products
Wholesale Trade
Information and data processing…
Federal General government
Wood products
Other services except government
Food and beverage and tobacco…
Petroleum and coal products
Retail Trade
Educational services
0.00
Other electronic products
Other transportation equipment
Software publishing
Broadcasting and telecommunications
Primary metals
Federal General government
Information and data processing…
Miscellaneous manufacturing
Plastics and rubber products
Nonmetallic mineral products
Wholesale Trade
Machinery
Paper products
Fabricated metal products
Motor vehicles bodies and trailers…
Printing and related support activities
Furniture and related products
Chemical products
Other services except government
Food and beverage and tobacco…
Computer systems design and related…
Wood products
Retail Trade
Miscellaneous professional scientific…
Petroleum and coal products
Educational services
Legal services
Administrative and support services
Hospitals Nursing and residential care…
Management of companies and…
0.01
0.01
0.02
0.02
0.00 0.00 0.00 0.00 0.00 0.01 0.01 0.01
Note: Semiconductor contribution to output growth by industry for the top thirty
industries to which they contribute. Source: Author’s calculation.
DRAFT
growth of IT fell relative to the 1995-2000 boom, non-IT industries that rely on semiconductors continued to employ these devices to grow their output. For example, while
IT-producers purchases of semiconductors fell in the 2000-2007 period relative to the
boom, Other Transportation Equipment, Broadcasting and Telecom, Primary Metals,
used semiconductors to grow their output over that period.
Figure 4 shows the share of using industries output growth accounted for by the
use of semiconductors. Output growth, from equation (2) can be decomposed into the
contribution from intermediate input, including semiconductors, capital, labor services,
and total factor productivity. This figure gives the contribution of semiconductor use
relative to total output growth. Strikingly, for the 1960-2007 period over forty percent
of the output of the Primary Metal industry can be accounted for by its purchases of
semiconductor input. That means that all of the other remaining factors of production
and TFP account for less than 60% of its output growth. Textile Mills, Nonmetallic
Mineral, Motor vehicles, among others had a significant portion of their output accounted for by their use of semiconductors. In the 2000-2007 period, Food and Tobacco
made wide use of semiconductors, as did the Chemical, Wholesale, and Construction
industries.
Summarizing, these figures show the widespread impact of semiconductor use on
other industries in the economy. Responding to the rapid constant quality price de-
17
Samuels, Jon D. (2012): "Semiconductors and U.S. Economic Growth"
Figure 4: Share of Output Accounted for by Semiconductor Use
1960-2007
2000-2007
Primary metals
Communications equipment…
Other electronic products
Electrical equipment appliances and…
Semiconductor and other electronic…
Other transportation equipment
Textile mills and textile product mills
Computer and peripheral equipment…
Nonmetallic mineral products
Motor vehicles bodies and trailers…
Machinery
Fabricated metal products
Paper products
Miscellaneous manufacturing
Furniture and related products
Printing and related support activities
Plastics and rubber products
Federal General government
Chemical products
Wood products
Other services except government
Food and beverage and tobacco…
Broadcasting and telecommunications
Wholesale Trade
Software publishing
Computer systems design and related…
Petroleum and coal products
Information and data processing…
Transit and ground passenger…
Educational services
Other electronic products
Motor vehicles bodies and trailers…
Communications equipment…
Other transportation equipment
Food and beverage and tobacco…
Miscellaneous manufacturing
Chemical products
Electrical equipment appliances and…
Federal General government
Wholesale Trade
Construction
Software publishing
Broadcasting and telecommunications
Other services except government
Petroleum and coal products
Information and data processing…
Textile mills and textile product mills
Legal services
Computer systems design and related…
Educational services
Retail Trade
Utilities
Management of companies and…
Administrative and support services
Miscellaneous professional scientific…
Apparel and leather and allied products
Hospitals Nursing and residential care…
Food services and drinking places
S&L General Government
S&L Government enterprises
0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45
0.00
0.05
0.10
0.15
0.20
0.25
Note: Share of industry output accounted for by semiconductor input for the top
thirty industries to which the contribute. Source: Author’s calculation.
DRAFT
clines in semiconductors, industries responded by employing semiconductors in their
production in new and innovative ways, to produce cheaper and higher quality output.
Table 5 gives the complete accounting of semiconductors as an intermediate input
across industries.
4.2
Semiconductor Contribution to Labor Productivity
Semiconductors contribute to the measured efficiency of labor in using industries. That
is, the growth of output per hour, or labor productivity, by industry depends directly on
the use of semiconductors. Subtracting the growth rate of hours worked from the both
sides of equation (15) yields and expression for the growth rate of labor productivity
(ALP):
∆ ln ALPj = v̄K,j ∆ ln
Lj
Xxj
Xsj
Kj
+ v̄L,j ∆ ln
+ v̄Xx,j ∆ ln
+ v̄Xs,j ∆ ln
+ vT,j
Hj
Hj
Hj
Hj
(16)
where Hj is hours worked and the share weighted growth rate of an input less hours
worked is referred to is input deepening. The intuition is that labor hours can be more
productive because the industry employs more inputs, like capital, per hour worked,
18
Samuels, Jon D. (2012): "Semiconductors and U.S. Economic Growth"
Figure 5: Share of ALP Accounted for by Semiconductor Deepening
1960-2007
2000-2007
Communications equipment…
Other electronic products
Educational services
Semiconductor and other electronic…
Electrical equipment appliances and…
Computer and peripheral equipment…
Other transportation equipment
Motor vehicles bodies and trailers…
Primary metals
Fabricated metal products
Nonmetallic mineral products
Machinery
Plastics and rubber products
Printing and related support activities
Miscellaneous manufacturing
Paper products
Furniture and related products
Textile mills and textile product mills
Chemical products
Federal General government
Other services except government
Wood products
Transit and ground passenger…
Broadcasting and telecommunications
Wholesale Trade
Software publishing
Food and beverage and tobacco…
Information and data processing…
Hospitals Nursing and residential care…
Petroleum and coal products
Communications equipment…
Other electronic products
Other transportation and support…
Semiconductor and other electronic…
Computer and peripheral equipment…
Other transportation equipment
Nonmetallic mineral products
Fabricated metal products
Primary metals
Electrical equipment appliances and…
Machinery
Plastics and rubber products
Paper products
Printing and related support activities
Motor vehicles bodies and trailers…
Textile mills and textile product mills
Furniture and related products
Miscellaneous manufacturing
Federal General government
Food and beverage and tobacco…
Other services except government
Wholesale Trade
Software publishing
Chemical products
Broadcasting and telecommunications
Wood products
Information and data processing…
Petroleum and coal products
Computer systems design and related…
Legal services
0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40
0.00
0.05
0.10
0.15
0.20
0.25
0.30
Note: Share of industry ALP accounted for by semiconductor input deepening for
the top thirty industries to which the contribute. Source: Author’s calculation.
DRAFT
or by using more intermediate inputs, like semiconductors, per hour worked, or by
innovating via TFP.
Figure 5 shows the importance of semiconductor use for labor productivity for the
top thirty industries ranked as a share of ALP growth. Over the 1960-2007, semiconductor deepening (growth of semiconductors per hour worked) accounted for over 35%
of the growth of labor productivity in the Communications Equipment industry. Over
that period, semiconductor use accounted for a significant portion of labor productivity growth for manufacturing industries like Other Electronic Products, Electrical
Equipment, Other Transportation Equipment, and Motor Vehicles. Also, Educational
Services, Primary Metal, Federal General Government, Wholesale all saw labor productivity gains due to increased use of semiconductors. The 2000-2007 contribution
of semiconductors to labor productivity growth to using industries was very similar to
that for the period as whole.
5
The Aggregate Impact of Semiconductors
This section measures the contribution of the Semiconductor industry to aggregate
U.S. economic growth and productivity. Using equation (6), aggregate value added in
the economy can be decomposed into contributions from individual industries. Each
19
Samuels, Jon D. (2012): "Semiconductors and U.S. Economic Growth"
industry contributes to aggregate value added by employing capital and labor services,
and innovating, to produce gross output that gets sold either to other industries as
intermediate input or to final demand.
Figures 6 shows productivity (TFP) growth for each of the industries for the 19602007 based on equation (2). As discussed above, total factor productivity is a primary
measure of economic innovation, endorsed by Schramm et al. (2008), because it captures how industries can produce more output holding inputs fixed, and encompasses
improvements in product quality. TFP captures product innovation because increased
quality is reflected in the constant quality output growth of industry output. For the
period as a whole, producers of IT dominated economic innovation. In the Computer industry, productivity grew by almost 11% per year, remarkable compared to the economy
wide productivity growth rate of 0.41% per year reported by Jorgenson et al. (forthcoming). The Semiconductor industry exhibited the third highest innovation rate from
1960-2007, following Software Publishing. Over 1960-2007, Semiconductor TFP grew
by close to 9% per year, almost 22 times higher than the rate of aggregate productivity
growth in the economy! Other high productivity industries include the Securities, Commodities, and Investment industry, Trade, Transportation, and Farms. Jorgenson et al.
(forthcoming) argue that industries that make intensive use of information technology
DRAFT
have higher productivity growth rates than those do not.
During the IT boom years of 1995-2000, the Semiconductor industry had the fastest
innovation rate in the economy. Figure 7 shows that productivity grew on average of
20% per year in the Semiconductor industry over the period, followed by about 17% per
year in the Computer industry. Jorgenson (2001) traces the rapid growth of productivity
in the Semiconductor industry after 1995 to a change in the product cycle to two from
three years; during this period, higher quality semiconductors were produced at an
even faster rates than in previous periods. These gains in technology manifest in the
TFP growth rate of the industry. Just as for the period as a whole, innovation rates in
industries that made intensive use of IT outpaced that of non-IT industries.
For the 2000-2007 period, productivity growth in Semiconductors fell compared to
the blistering 1995-2000 pace, but still had the second highest productivity growth rate
in the economy and grew ten times more rapidly than aggregate economy productivity
growth rate. Furthermore, Jorgenson et al. (forthcoming) show that industries that
made intensive use of IT dominated the productivity growth of industries that did not
rely as much on IT. Because semiconductor technology had a major role in the advancement of IT production and services, the productivity growth of IT-Users is ultimately
tied to innovation in the Semiconductor industry. As the quality adjusted price of
semiconductor fell and quality increased, there is strong evidence that industries that
20
Samuels, Jon D. (2012): "Semiconductors and U.S. Economic Growth"
are able to organize their production processes to take into account this higher quality
and cheaper technology are outperforming sectors that are unable to realize the gains
from the new technology. The Retail and Wholesale industries, which have relatively
intensive use in IT in the post 1995 period are high productivity producers indicating
they are able to economize on gains from this semiconductor related technology. These
results are not surprising; we observe that most restaurants have computerized and can
easily imagine how wholesalers use computers to manage their trades.
To analyze the impact of the Semiconductor industry on aggregate growth and
productivity, equation (6) can be decomposed to show the impact individual industries
and groups of industries. First, using equation (5) for the production possibility frontier:
X
∆ ln V =
X
w̄j ∆ ln Vj +
j∈IT-Prod
w̄j ∆ ln Vj +
j∈IT-Use
X
w̄j ∆ ln Vj
(17)
j∈Non-IT
where IT-Prod refers to industries classified as producers of information technology
equipment and services, and IT-Use are industries that rely intensively on purchases of
Information Technology services.16 Since the contribution of an individual industry is
its growth rate times its value share, groups of industries can be formulated as simple
weighted sums.
DRAFT
Similarly, equation (6) can be decomposed to show the contributions of industries to
the aggregate innovation rate. Contributions for the IT-Producer, IT-User, and Non-IT
groups are defined as:
X
j
w̄j
1
v̄V,j
v̄T,j =
X
j∈IT-Prod
w̄j
1
v̄V,j
v̄T,j +
X
j∈IT-Use
w̄j
1
v̄V,j
v̄T,j +
X
j∈Non-IT
w̄j
1
v̄V,j
v̄T,j
(18)
so that aggregate Domar weighted productivity growth can be decomposed into that
due to individual industries and sectors of the economy.
A starting point for analyzing the contribution of individual industries to economic
growth is each industry’s share of nominal aggregate value added, given in Table 3.
If industries grew equally over time, each industry’s contribution would equal this
share. Over the period as a whole, IT-Producing industries averaged 1.8% of nominal
aggregate value added and the Semiconductors industry averaged 0.4%. Relative to
the rest of the economy, IT-Production had a much smaller share compared to the
IT-Using (50.9%) and Non-IT industries (47.%). Again if industries grew at the same
rate this would imply that IT production would account for less than 2% of economic
growth, but we will see below that the contribution of IT-Producers greatly outweighed
its share in value added. The increased importance of semiconductors during the IT16
See Jorgenson et al. (forthcoming) for a discussion of how industries are classified.
21
Samuels, Jon D. (2012): "Semiconductors and U.S. Economic Growth"
Figure 6: Industry Productivity Growth 1960-2007
Computer and peripheral equipment manufacturing
Software publishing
Semiconductor and other electronic component…
Securities commodity contracts and investments
Wholesale Trade
Warehousing and storage
Air transportation
Rail transportation
Farms
Retail Trade
Textile mills and textile product mills
Broadcasting and telecommunications
Other transportation and support activities
Miscellaneous manufacturing
Other electronic products
Accommodation
Truck transportation
Communications equipment manufacturing
Water transportation
Pipeline transportation
Plastics and rubber products
Furniture and related products
Waste management and remediation services
Social assistance
Mining except oil and gas
Motor vehicles bodies and trailers and parts
Machinery
Apparel and leather and allied products
Fabricated metal products
Performing arts spectator sports museums and related…
Electrical equipment appliances and components
Petroleum and coal products
Other transportation equipment
Federal General government
Nonmetallic mineral products
Motion picture and sound recording industries
Miscellaneous professional scientific and technical services
Wood products
Amusements gambling and recreation industries
Printing and related support activities
Chemical products
Food services and drinking places
Paper products
Food and beverage and tobacco products
Information and data processing services
Household
Administrative and support services
S&L General Government
Primary metals
Federal Government enterprises
Insurance carriers and related activities
Management of companies and enterprises
Other services except government
Support activities for mining
Utilities
Educational services
Forestry fishing and related activities
Construction
Real estate
S&L Government enterprises
Hospitals Nursing and residential care facilities
Transit and ground passenger transportation
Ambulatory health care services
Federal Reserve banks credit intermediation and related…
Computer systems design and related services
Legal services
Newspaper; periodical; book publishers
Funds trusts and other financial vehicles
Rental and leasing services and lessors of intangible assets
Oil and gas extraction
DRAFT
-4
-2
0
2
4
6
8
Percent per Year
Note: Industry Productivity Growth by industry. Source: Author’s calculation.
22
10
12
Samuels, Jon D. (2012): "Semiconductors and U.S. Economic Growth"
Figure 7: Industry Productivity Growth 1995-2000
Semiconductor and other electronic component…
Computer and peripheral equipment manufacturing
Securities commodity contracts and investments
Software publishing
Mining except oil and gas
Wholesale Trade
Warehousing and storage
Farms
Retail Trade
Federal Government enterprises
Forestry fishing and related activities
Petroleum and coal products
Miscellaneous manufacturing
Rail transportation
Waste management and remediation services
Plastics and rubber products
Textile mills and textile product mills
Primary metals
Pipeline transportation
Real estate
Utilities
Other transportation and support activities
Truck transportation
Apparel and leather and allied products
Accommodation
Air transportation
Motion picture and sound recording industries
Other transportation equipment
Paper products
Electrical equipment appliances and components
Newspaper; periodical; book publishers
S&L Government enterprises
Nonmetallic mineral products
Communications equipment manufacturing
Insurance carriers and related activities
Food services and drinking places
Household
Miscellaneous professional scientific and technical…
Social assistance
Transit and ground passenger transportation
Administrative and support services
Furniture and related products
Wood products
S&L General Government
Fabricated metal products
Printing and related support activities
Federal General government
Motor vehicles bodies and trailers and parts
Hospitals Nursing and residential care facilities
Ambulatory health care services
Performing arts spectator sports museums and related…
Computer systems design and related services
Chemical products
Water transportation
Construction
Management of companies and enterprises
Other services except government
Food and beverage and tobacco products
Broadcasting and telecommunications
Legal services
Machinery
Educational services
Amusements gambling and recreation industries
Support activities for mining
Information and data processing services
Other electronic products
Federal Reserve banks credit intermediation and related…
Oil and gas extraction
Funds trusts and other financial vehicles
Rental and leasing services and lessors of intangible assets
DRAFT
-10
-5
0
5
10
15
Percent per Year
Note: Industry Productivity Growth by industry. Source: Author’s calculation.
23
20
25
Samuels, Jon D. (2012): "Semiconductors and U.S. Economic Growth"
Figure 8: Industry Productivity Growth 2000-2007
Computer and peripheral equipment manufacturing
Semiconductor and other electronic component…
Information and data processing services
Software publishing
Securities commodity contracts and investments
Air transportation
Retail Trade
Broadcasting and telecommunications
Computer systems design and related services
Communications equipment manufacturing
Farms
Miscellaneous professional scientific and technical…
Miscellaneous manufacturing
Other electronic products
Social assistance
Real estate
Textile mills and textile product mills
Other transportation and support activities
Motor vehicles bodies and trailers and parts
Rail transportation
Administrative and support services
Other transportation equipment
Electrical equipment appliances and components
Pipeline transportation
Apparel and leather and allied products
Machinery
Chemical products
Truck transportation
Printing and related support activities
Furniture and related products
Wood products
Warehousing and storage
Federal Reserve banks credit intermediation and related…
Wholesale Trade
Amusements gambling and recreation industries
Utilities
Fabricated metal products
Accommodation
Water transportation
Ambulatory health care services
Paper products
Food services and drinking places
Federal General government
Insurance carriers and related activities
Food and beverage and tobacco products
Household
Nonmetallic mineral products
Plastics and rubber products
Motion picture and sound recording industries
Other services except government
Performing arts spectator sports museums and related…
Forestry fishing and related activities
Hospitals Nursing and residential care facilities
Newspaper; periodical; book publishers
Transit and ground passenger transportation
S&L General Government
Waste management and remediation services
Legal services
S&L Government enterprises
Funds trusts and other financial vehicles
Primary metals
Federal Government enterprises
Educational services
Petroleum and coal products
Mining except oil and gas
Construction
Management of companies and enterprises
Support activities for mining
Rental and leasing services and lessors of intangible assets
Oil and gas extraction
DRAFT
-10
-5
0
5
10
Percent per Year
Note: Industry Productivity Growth by industry. Source: Author’s calculation.
24
15
20
Samuels, Jon D. (2012): "Semiconductors and U.S. Economic Growth"
Table 1: IT-Related Industries
IT-Producing Industries
IT share 2005
Computer and peripheral equipment mfg
Communications equipment mfg
Semiconductor and other electronic component mfg
Software publishing
Information and data processing services
Computer systems design and related services
0.3571
0.3868
0.4105
0.4421
0.7929
0.9497
IT-intensive Using Industries
Construction
Machinery
Motor vehicles bodies and trailers and parts
Other transportation equipment
Miscellaneous mfg
Printing and related support activities
Wholesale Trade
Retail Trade
Air transportation
Water transportation
Transit and ground passenger transportation
Pipeline transportation
Other transportation and support activities
Broadcasting and telecommunications
Fed. Res. banks, credit intermediation
Securities commodity contracts and investments
Insurance carriers and related activities
Rental & leasing, and lessors of intangible assets
Legal services
Misc. professional scientific and technical services
Management of companies and enterprises
Administrative and support services
Waste management and remediation services
Educational services
Hospitals Nursing and residential care facilities
Social assistance
Performing arts, spectator sports & related activities
Federal General government
S&L General Government
Other electronic products
Newspaper; periodical; book publishers
DRAFT
0.2271
0.3387
0.2428
0.3053
0.1631
0.2018
0.2186
0.1572
0.6796
0.4788
0.3182
0.4168
0.1789
0.5695
0.2226
0.8461
0.3161
0.3217
0.3382
0.6331
0.5426
0.5017
0.1759
0.5468
0.3715
0.2125
0.2291
0.3046
0.1672
0.4445
0.5459
Notes: IT-Using industries are those with more than the median
share of 15.4 percent for III in 2005.
Note: For discussion of industry classification see Jorgenson et al. (forthcoming).
25
Samuels, Jon D. (2012): "Semiconductors and U.S. Economic Growth"
Boom of 1995-2000 is evident in its value share which increased to 0.7% of value added;
the Computer industry showed a similar increase. Following 2000, the share of ITProduction in aggregate value added fell relative to the 1995-2000 level, but the results
below show that the contribution of IT-Producers, including Semiconductors still far
outweighed their shares in value added.
Table 3: Value Added Shares
Value Added Shares
IT-Producing Industries
Information and data processing services
Computer systems design and related services
Computer and peripheral equipment manufacturing
Communications equipment manufacturing
Semiconductor manufacturing
Software publishing
IT-Using Industries
Non-IT Industries
1960-2007
1960-1995
1995-2000
2000-2007
100.0
1.8
0.2
0.5
0.3
0.2
0.4
0.2
50.9
47.3
100.0
1.5
0.2
0.3
0.3
0.3
0.4
0.1
50.1
48.4
100.0
3.0
0.3
0.9
0.3
0.3
0.7
0.5
52.7
44.4
100.0
2.8
0.4
1.1
0.2
0.2
0.4
0.5
53.2
44.0
Note: Each industry’s share in aggregate value added. IT-Producing, IT-Using, and
Non-IT are defined in Jorgenson et al. (forthcoming). Source: Author’s calculations.
Table 4, based on equations (17) and (18), shows that the contribution of the Semi-
DRAFT
conductor industry, and other IT-Producers that make heavy use of semiconductors,
greatly outweighs their value shares and were key drivers of growth and productivity
over the whole sample period, and each of the sub-samples. The top line of the table
gives aggregate economic growth from the production possibility frontier of equation
(5) which can be decomposed into the contributions of IT-Producing, IT-Using, and
Non-IT industries using equation (17). Of the 3.45% average growth over the 1960-2007
period, 0.31% resulted from the direct production of Information Technology goods and
services. Compared to its value added share of 1.8%, this implies that IT-Producers
contributed about five times their share. Alternatively, had all industries grown equally,
IT-Production would have accounted for 1.8% of growth, but this sector accounted for
five times that amount. Over the period, the Semiconductor industry contributed 0.10%
to aggregate value added growth, or 3% of aggregate growth, but over seven times its
nominal share! This can be compared to the IT-Using and Non-IT industries that
accounted for 51% and 40% of aggregate value added, respectively, actually less than
their shares of nominal value added.
During the IT-Boom, the contribution of the Semiconductor industry to value added
growth was even more pronounced. Value added growth in the Semiconductor industry
alone accounted for over 7.5% of aggregate economic growth, almost 12 times its value
added share! IT-Producers as a whole accounted for almost 18% of growth even though
26
Samuels, Jon D. (2012): "Semiconductors and U.S. Economic Growth"
their share was only 3% of value added. Following the IT-Boom, aggregate value added
growth fell relative to the boom and contributions from the IT-Producing, IT-Using,
and Non-IT sectors all fell. During this period, Semiconductors accounted for 1.7% of
the 2.78% average annual growth over the period. While this contribution fell relative
to the boom, this still outweighed the nominal value added share by a factor of four.
For IT-Producers as a whole, their contribution was about 3.5 times their nominal value
added share, so the contribution of Semiconductor production outpaced the group as
a whole. Like earlier periods, IT-Using and Non-IT industries produced gains in close
proportion to their shares in aggregate value added.
Table 4 also shows how IT-Producers dominated innovation over the period. While
innovation accounted for less than 10% of growth over the period, this was led by
productivity due to IT-related production. First, one should not interpret the small
innovation rate for the economy as a whole, on average of 0.33% per year, as indicating
that innovation is not important for economic growth. Jorgenson et al. (forthcoming)
show that these economy wide innovation rates induce large investments in human and
physical capital that drive economic growth over time. Of the 0.33% per year of aggregate productivity, the Semiconductor industry contributed 0.10% per year, i.e. the
Semiconductor industry alone accounted for 30% of aggregate productivity growth, or
DRAFT
about 160 times its value added share. IT-Producers as a group contributed 0.22% per
year to aggregate productivity growth, or about thirty six times the group’s share in
aggregate value added. During the IT-Boom of 1995-2000, the Semiconductor industry
alone accounted for 48% of aggregate productivity growth, and the IT-Producer group
for almost 80% of the aggregate total. In the 2000-2007 period, innovation rates fell
relative to the boom in the aggregate and for the IT-Producer group, but the Semiconductor industry alone still accounted for 10% of aggregate productivity and the
IT-Producer group for over 43%. While aggregate growth and innovation slowed during that period, the Semiconductor industry innovated at higher rates than all other
industries in the economy, except the Computer industry.
6
Semiconductor Productivity: 2008 & 2009
Even though the complete source data to analyze the sources of growth and productivity is available through 2007 only, it is possible to get an estimate of more recent
developments using a back of the envelope approach. Instead of using primary data
on both prices and quantities, using only prices, and holding quantities fixed, gives
an updated picture of productivity in the Semiconductor industry through 2009. This
approach is based on the price-dual estimate of industry total factor productivity. The
27
Samuels, Jon D. (2012): "Semiconductors and U.S. Economic Growth"
Table 4: Decomposition of Aggregate Growth
Value-Added (ΔlnV=(V1)+(V2)+(V3)=(KT)+(LT)+(DT))
1960-2007
1960-1995
1995-2000
2000-2007
3.45
3.42
4.52
2.78
Contributions
(V1) IT-Producing Industries
Information and data processing services
Computer systems design and related services
Computer and peripheral equipment manufacturing
Communications equipment manufacturing
Semiconductor manufacturing
Software publishing
(V2) IT-Producing Industries
(V3) Non-IT Industries
0.31
0.02
0.04
0.09
0.01
0.10
0.05
1.75
1.39
0.24
0.01
0.02
0.08
0.01
0.08
0.04
1.77
1.41
0.81
0.03
0.13
0.20
0.02
0.34
0.09
2.31
1.40
0.28
0.06
0.05
0.07
-0.01
0.05
0.05
1.27
1.24
(KT) Domar Weighted Capital Input
(LT) Domar Weighted Labor Input
(DT) Domar Weighted TFP
(D1) IT-Producing Industries
Information and data processing services
Computer systems design and related services
Computer and peripheral equipment manufacturing
Communications equipment manufacturing
Semiconductor manufacturing
Software publishing
(D2) IT-Using Industries
(D3) Non-IT Industries
2.16
0.95
0.33
0.22
0.01
0.00
0.09
0.00
0.10
0.03
0.18
-0.07
2.19
1.02
0.22
0.16
0.00
-0.01
0.07
0.00
0.07
0.03
0.15
-0.10
2.53
1.33
0.67
0.53
-0.02
-0.01
0.19
0.00
0.32
0.05
0.10
0.04
1.76
0.35
0.67
0.29
0.06
0.03
0.08
0.00
0.07
0.04
0.35
0.03
DRAFT
Note: V1-V3 sum to aggregate value added growth, as does KT+LT+DT. D1-D3
sum to DT. Source:Author’s calculations.
price dual estimate of total factor productivity is equivalent to that from the primal
quantity side in equation (2). Differentiating the accounting identity equation (3) with
respect to time and using the definition of vT,j from equation (2) yields the price dual
estimate of industry total factor productivity, which produces an equivalent estimate
to the primal, but uses weighted growth rates of prices in replace of quantities.
vT,j = v̄K,j ∆ ln PK,j + v̄L,j ∆ ln PL,j + v̄X,j ∆ ln PX,j − ∆ ln PY j
(19)
so that the price dual estimate is the share-weighted growth in inputs prices less the
growth in the output price. The intuition for this formulation is that if an industry is able to lower the price it charges for fixed input prices, this is due to gains in
productivity.
I use the price dual approach to derive estimates for productivity in the Semiconductor industry in 2008 and 2009. The price of Semiconductor output PY j is available
through 2009 from the Bureau of Economic Analysis. To estimate the price of intermediate input, I assume that intermediate input prices that have a share of five percent or
less in the total value of industry output grew at the same rate in 2008 and 2009 as the
28
Samuels, Jon D. (2012): "Semiconductors and U.S. Economic Growth"
GDP price. For intermediate inputs with a share of greater than 5 percent (Wholesale,
Semiconductor, and Management of Companies), I assume that these prices grew like
the output prices for these sectors. Finally, I assume that the price of capital and labor
grew like the aggregate economy capital and labor price.17 This approach yields estimates that productivity in Semiconductor industry grew by 12.5% and 5.6% in 2008
and 2009, respectively. These growth rates are a decline from the blistering pace of
productivity growth for semiconductor production in the late 1990’s of around 20% per
year, but are well above typical productivity growth rates observed between 1960 and
2007 for the other industries in the U.S. economy.
7
Conclusions
This paper develops a framework and data set to analyze the economic impact of semiconductor production in the U.S. from 1960-2007. Over that period, innovation in the
Semiconductor industry grew close to 9% per year, twenty five times the innovation
growth rate for the economy as a whole. Over the 1995-2000 period, the innovation
rate was around 21% per year, thirty one times that of the economy as a whole. Because
a defining feature of semiconductor production is that the devices are used as an inter-
DRAFT
mediate input for many other industries, I quantify the contribution of semiconductors
to growth in using industries. From 1960-2007, semiconductors accounted for 41% of
the growth of the Primary Metals industry, 37% of the Communications Equipment
industry, and 8% of the Computer industry. From 2000-2007, the period following the
IT-Boom, semiconductors had a widespread impact on many sectors of the economy
including accounting for 24% of the growth of the Other Electronic Components industry, 16% of the Motor Vehicles industry, 15% of the Communications Equipment
industry, 7% of the Other Transportation equipment industry, and 5% of the growth in
Food and Beverages. The results show the broad impact of semiconductors, from their
contribution to the remarkable productivity gains in the production of IT-equipment
itself, to the more widespread gains post-2000 in industries that use semiconductors as
an intermediate input.
17
I verified that this approach produces reasonable results by comparing it to the estimates using the
actual prices for all inputs and outputs for 1960-2007. The results are comparable.
29
Samuels, Jon D. (2012): "Semiconductors and U.S. Economic Growth"
A
Appendix
References
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and US Economic Growth,” .
Jorgenson, D. and Z. Griliches (1967): “The explanation of productivity change,”
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Jorgenson, D., M. Ho, J. Samuels, and K. Stiroh (2007): “Industry origins of
the American productivity resurgence,” Economic Systems Research, 19, 229–252.
Jorgenson, D., M. Ho, and K. Stiroh (2005): Information technology and the
DRAFT
American growth resurgence, MIT Press, Cambridge, Mass.
Jorgenson, D. and C. Wessner (2004): Productivity and Cyclicality in Semiconductors: Trends, Implications, and Questions: report of a symposium, Natl Academy
Pr.
Jorgenson, D. W., M. S. Ho, and J. D. Samuels (forthcoming): “Information
Technology and U.S. Productivity Growth: Evidence from a Prototype Industry
Production Account,” Journal of Productivity Analysis.
National Science Foundation (2010): Science and Engineering Indicators 2010,
NSF, Washington, DC.
Schramm, C. et al. (2008): “Innovation Measurement–Tracking the State of Innovation in the American Economy,” A report to the Secretary of Commerce by The
Advisory Committee on Measuring Innovation in the 21st Century Economy.
Solow, R. (1957): “Technical change and the aggregate production function,” The
Review of Economics and Statistics, 39, 312–320.
Wasshausen, D. and B. Moulton (2006): “The role of hedonic methods in measuring real GDP in the United States,” Are We Measuring Productivity Correctly.
30
Samuels, Jon D. (2012): "Semiconductors and U.S. Economic Growth"
World Information Technology and Services Alliance (2010): Digital Planet
2010, WITSA, Washington, DC.
DRAFT
31
Samuels, Jon D. (2012): "Semiconductors and U.S. Economic Growth"
Table 5: Contributions of Semiconductors to Industry Output Growth.
1960-2007
Contribution
Share
Farms
0.000
0.00
Forestry fishing and related activities
0.000
0.01
Oil and gas extraction
0.000
0.00
Mining except oil and gas
0.000
0.01
Support activities for mining
0.001
0.02
Utilities
0.001
0.06
Construction
0.001
0.07
Wood products
0.041
2.26
Nonmetallic mineral products
0.101
7.50
Primary metals
0.123
41.35
Fabricated metal products
0.102
5.74
Machinery
0.166
5.93
Electrical equipment appliances and components 0.244
14.30
Motor vehicles bodies and trailers and parts
0.186
6.97
Other transportation equipment
0.140
8.82
Furniture and related products
0.094
3.94
Miscellaneous manufacturing
0.128
4.15
Food and beverage and tobacco products
0.026
1.63
Textile mills and textile product mills
0.078
8.62
Apparel and leather and allied products
0.008
-0.49
Paper products
0.090
5.16
Printing and related support activities
0.082
3.68
Petroleum and coal products
0.019
1.13
Chemical products
0.072
2.71
Plastics and rubber products
0.133
3.53
Wholesale Trade
0.071
1.38
Retail Trade
0.014
0.35
Air transportation
0.001
0.02
Rail transportation
0.000
0.06
Water transportation
0.001
0.03
Truck transportation
0.001
0.02
Transit and ground passenger transportation
0.003
0.42
Pipeline transportation
0.001
0.07
Other transportation and support activities
0.001
0.02
Warehousing and storage
0.000
0.00
Motion picture and sound recording industries 0.001
0.03
Broadcasting and telecommunications
0.098
1.52
Information and data processing services
0.059
0.76
Federal Reserve banks credit intermediation and related
0.001 activities0.02
Securities commodity contracts and investments0.001
0.01
Insurance carriers and related activities
0.000
0.00
Funds trusts and other financial vehicles
0.000
0.00
Rental and leasing services and lessors of intangible
0.001
assets
0.01
Legal services
0.007
0.27
Computer systems design and related services 0.089
1.19
Miscellaneous professional scientific and technical
0.010
services
0.20
Management of companies and enterprises
0.004
0.13
Administrative and support services
0.006
0.14
Waste management and remediation services
0.000
0.01
Educational services
0.011
0.37
Ambulatory health care services
0.000
0.00
Hospitals Nursing and residential care facilities 0.005
0.13
Social assistance
0.000
0.00
Performing arts spectator sports museums and related
0.000activities 0.01
Amusements gambling and recreation industries 0.000
0.01
Accommodation
0.000
0.00
Food services and drinking places
0.003
0.11
Other services except government
0.041
1.77
Federal General government
0.058
3.50
Federal Government enterprises
0.000
0.01
S&L General Government
0.001
0.04
S&L Government enterprises
0.002
0.06
Computer and peripheral equipment manufacturing
1.471
8.11
Communications equipment manufacturing
1.856
36.60
Semiconductor and other electronic component manufacturing
1.581
12.67
Other electronic products
1.024
24.40
Newspaper; periodical; book publishers
0.002
0.11
Software publishing
0.214
1.20
Real estate
0.000
0.00
Household
0.000
0.00
1995-2000
2000-2007
Contribution
Share
Contribution
Share
0.000
0.001
0.000
0.000
0.003
0.002
0.004
0.145
0.341
0.363
0.338
0.543
0.938
0.649
0.434
0.331
0.367
0.091
0.308
0.039
0.275
0.255
0.051
0.216
0.400
0.179
0.045
0.003
0.001
0.002
0.004
0.007
0.004
0.004
0.000
0.004
0.353
0.186
0.002
0.003
0.000
0.000
0.003
0.018
0.376
0.032
0.011
0.023
0.001
0.036
0.000
0.010
0.000
0.002
0.003
0.000
0.009
0.119
0.131
0.000
0.004
0.004
3.638
6.364
4.423
2.234
0.006
0.555
0.000
0.000
0.00
0.36
0.00
0.04
0.04
0.14
0.08
4.87
10.47
46.62
10.76
23.30
28.52
15.72
13.67
7.12
8.84
7.86
-107.02
-1.20
551.64
27.57
3.30
12.53
11.10
2.89
0.78
0.07
1.84
0.07
0.09
4.25
3.26
0.13
0.00
0.13
3.29
1.43
0.05
0.01
0.00
0.00
0.03
0.66
2.27
0.36
0.30
0.27
0.03
1.09
0.01
-2.14
0.00
0.08
0.08
0.00
0.29
4.21
526.10
0.01
0.13
0.16
12.53
42.92
15.50
145.96
0.13
3.13
0.00
0.00
0.000
0.000
0.000
0.000
0.001
0.000
0.001
0.013
0.054
0.091
0.040
0.044
-0.063
0.040
0.145
0.030
0.077
0.020
-0.023
-0.017
0.042
0.034
0.009
0.027
0.067
0.048
0.010
0.001
0.000
0.000
-0.001
0.001
0.000
-0.001
0.000
0.000
0.097
0.085
0.000
0.000
0.000
0.000
0.001
0.007
0.014
0.009
0.002
0.004
0.000
0.007
0.000
0.004
0.000
0.000
0.000
0.000
0.002
0.025
0.088
0.000
0.001
0.001
-0.062
-0.669
-0.518
0.587
0.001
0.133
0.000
0.000
0.00
-0.02
0.00
0.00
0.02
0.21
1.69
-2.63
-19.59
-13.61
-9.96
-22.17
2.48
15.82
6.86
-3.26
3.43
4.69
0.46
0.15
-2.44
-2.54
0.68
2.66
-24.50
1.72
0.25
0.02
0.02
-0.29
-0.11
-0.35
-0.03
-1.03
0.00
0.03
1.65
0.68
0.01
0.01
0.00
0.00
0.02
0.41
0.40
0.16
0.19
0.17
0.01
0.40
0.00
0.13
0.00
-0.01
-0.03
0.00
0.09
1.51
2.19
-0.02
0.07
0.07
-0.57
15.48
-25.98
23.54
-0.17
1.67
0.00
0.00
DRAFT
Note: The contribution is the contribution (in percent) of the use of semiconductor
intermediate input to output growth; a contribution is the value share times the
growth rate. Share is the share (in percent) of industry output growth accounted for
by semiconductor input. Source:Author’s calculations.
32
Samuels, Jon D. (2012): "Semiconductors and U.S. Economic Growth"
Table 6: Contributions to Aggregate Value Added Growth.
1960-2007
Share
Growth
Farms
0.018
2.589
Forestry fishing and related activities
0.003
2.005
Oil and gas extraction
0.009
-1.661
Mining except oil and gas
0.005
1.917
Support activities for mining
0.002
1.661
Utilities
0.020
1.520
Construction
0.043
0.881
Wood products
0.004
1.416
Nonmetallic mineral products
0.006
1.448
Primary metals
0.011
-1.218
Fabricated metal products
0.015
1.768
Machinery
0.016
2.993
Electrical equipment appliances and components 0.007
2.016
Motor vehicles bodies and trailers and parts
0.014
2.407
Other transportation equipment
0.010
1.206
Furniture and related products
0.004
2.244
Miscellaneous manufacturing
0.005
3.601
Food and beverage and tobacco products
0.017
1.297
Textile mills and textile product mills
0.005
2.677
Apparel and leather and allied products
0.007
-0.353
Paper products
0.007
1.281
Printing and related support activities
0.006
1.847
Petroleum and coal products
0.004
3.649
Chemical products
0.017
2.834
Plastics and rubber products
0.007
3.813
Wholesale Trade
0.048
6.392
Retail Trade
0.060
3.865
Air transportation
0.004
8.338
Rail transportation
0.007
0.573
Water transportation
0.001
5.046
Truck transportation
0.009
3.867
Transit and ground passenger transportation
0.002
0.601
Pipeline transportation
0.001
3.944
Other transportation and support activities
0.006
3.817
Warehousing and storage
0.002
4.948
Motion picture and sound recording industries 0.003
3.231
Broadcasting and telecommunications
0.021
6.522
Information and data processing services
0.002
6.612
Federal Reserve banks credit intermediation and related
0.025 activities3.824
Securities commodity contracts and investments0.007
9.173
Insurance carriers and related activities
0.017
3.217
Funds trusts and other financial vehicles
0.001
-4.649
Rental and leasing services and lessors of intangible
0.008
assets
4.836
Legal services
0.010
2.465
Computer systems design and related services 0.005
7.454
Miscellaneous professional scientific and technical
0.027
services
5.122
Management of companies and enterprises
0.016
2.767
Administrative and support services
0.015
5.206
Waste management and remediation services
0.002
3.734
Educational services
0.007
2.771
Ambulatory health care services
0.024
3.329
Hospitals Nursing and residential care facilities 0.018
2.782
Social assistance
0.003
5.330
Performing arts spectator sports museums and related
0.003activities 3.509
Amusements gambling and recreation industries 0.004
4.062
Accommodation
0.007
4.081
Food services and drinking places
0.014
2.209
Other services except government
0.023
1.553
Federal General government
0.036
0.598
Federal Government enterprises
0.007
1.017
S&L General Government
0.066
2.533
S&L Government enterprises
0.007
1.904
Computer and peripheral equipment manufacturing
0.003
35.348
Communications equipment manufacturing
0.002
4.120
Semiconductor and other electronic component manufacturing
0.004
22.139
Other electronic products
0.005
3.798
Newspaper; periodical; book publishers
0.006
0.044
Software publishing
0.002
21.349
Real estate
0.050
3.342
Household
0.149
4.562
Total
1.000
1995-2000
2000-2007
Contribution
Share
Growth
Contribution
Share
Growth
Contribution
0.04
0.01
-0.02
0.01
0.00
0.03
0.03
0.01
0.01
-0.01
0.03
0.06
0.02
0.04
0.01
0.01
0.02
0.03
0.02
0.01
0.01
0.01
0.01
0.05
0.03
0.31
0.23
0.03
0.00
0.01
0.04
0.00
0.00
0.02
0.01
0.01
0.13
0.02
0.09
0.09
0.05
-0.01
0.04
0.02
0.04
0.14
0.04
0.07
0.01
0.02
0.08
0.04
0.02
0.01
0.01
0.03
0.03
0.04
0.02
0.01
0.16
0.01
0.09
0.01
0.10
0.02
0.00
0.05
0.17
0.68
0.010
0.003
0.005
0.003
0.001
0.019
0.039
0.003
0.005
0.005
0.012
0.011
0.005
0.012
0.006
0.003
0.005
0.014
0.003
0.003
0.006
0.005
0.003
0.017
0.007
0.046
0.053
0.005
0.003
0.001
0.009
0.001
0.001
0.006
0.002
0.003
0.023
0.003
0.029
0.014
0.022
0.001
0.010
0.013
0.009
0.037
0.017
0.024
0.002
0.007
0.031
0.024
0.005
0.004
0.004
0.008
0.014
0.022
0.026
0.007
0.067
0.007
0.003
0.003
0.007
0.005
0.006
0.005
0.050
0.157
6.490
3.966
-7.762
7.514
-3.331
1.524
3.217
1.843
2.968
3.712
2.026
0.150
0.913
1.434
3.896
3.429
5.236
-3.047
1.798
-3.488
0.775
0.447
11.068
0.701
5.351
8.870
6.550
9.359
0.552
1.378
3.346
4.239
2.298
4.466
6.838
2.011
6.011
7.464
1.025
28.566
3.107
-24.640
4.735
1.578
14.686
6.275
2.623
5.248
2.503
2.149
1.567
1.374
4.391
2.502
4.095
4.286
3.441
0.163
-1.183
3.415
1.643
2.221
59.457
4.736
52.787
-3.220
3.895
21.462
2.880
5.458
0.06
0.01
-0.05
0.02
-0.01
0.03
0.12
0.01
0.01
0.02
0.02
0.00
0.00
0.02
0.02
0.01
0.03
-0.05
0.00
-0.01
0.01
0.00
0.04
0.01
0.04
0.42
0.35
0.05
0.00
0.00
0.03
0.01
0.00
0.03
0.01
0.01
0.14
0.03
0.03
0.39
0.07
-0.03
0.05
0.02
0.13
0.24
0.04
0.12
0.01
0.02
0.05
0.03
0.02
0.01
0.02
0.03
0.05
0.00
-0.03
0.02
0.11
0.02
0.20
0.02
0.34
-0.02
0.02
0.09
0.14
0.86
0.008
0.002
0.009
0.003
0.002
0.017
0.044
0.003
0.004
0.004
0.010
0.009
0.004
0.009
0.006
0.003
0.005
0.012
0.002
0.002
0.004
0.004
0.004
0.016
0.005
0.044
0.051
0.004
0.003
0.001
0.009
0.001
0.001
0.006
0.003
0.003
0.022
0.004
0.036
0.014
0.021
0.002
0.009
0.013
0.011
0.040
0.017
0.025
0.002
0.009
0.033
0.026
0.006
0.004
0.004
0.007
0.016
0.021
0.026
0.005
0.068
0.006
0.002
0.002
0.004
0.004
0.006
0.005
0.052
0.162
2.892
1.087
-4.291
-1.674
0.739
2.208
-2.509
0.659
-0.656
-8.741
-0.275
1.156
-0.185
3.359
2.693
-0.467
2.629
0.309
-1.720
-5.554
-2.250
-0.380
-7.790
2.089
-1.679
2.678
5.010
6.645
1.919
4.544
2.689
1.065
4.686
1.596
4.603
1.517
6.033
13.154
3.815
8.403
1.154
-3.540
1.711
0.130
5.116
5.747
-0.379
3.069
-0.651
1.554
4.669
1.664
5.372
2.085
3.308
0.801
2.896
0.302
1.646
-1.930
0.662
0.406
39.297
1.704
12.930
2.054
-2.081
9.825
3.761
5.301
0.03
0.00
-0.04
0.00
0.01
0.04
-0.11
0.00
0.00
-0.04
-0.01
0.01
0.00
0.02
0.02
0.00
0.01
0.00
0.00
-0.01
-0.01
0.00
-0.06
0.03
-0.01
0.12
0.25
0.03
0.01
0.00
0.02
0.00
0.00
0.01
0.01
0.00
0.13
0.06
0.13
0.12
0.02
0.00
0.01
0.00
0.05
0.24
-0.01
0.08
0.00
0.01
0.15
0.04
0.03
0.01
0.01
0.01
0.05
0.01
0.04
-0.01
0.04
0.00
0.07
-0.01
0.05
0.01
-0.01
0.05
0.20
0.86
3.446
1.000
4.519
1.000
DRAFT
Note: The share is the industry nominal
33share in aggregate value added. Growth
rate is industry value added growth rate and contributiuon is defined as in text as
value share times value added growth rate. Source:Author’s calculations.
2.784
Samuels, Jon D. (2012): "Semiconductors and U.S. Economic Growth"
Table 7: Contributions to Aggregate Productivity Growth.
1960-2007
Domar
Weight
Growth
Farms
0.042
1.401
Forestry fishing and related activities
0.006
-0.766
Oil and gas extraction
0.017
-2.249
Mining except oil and gas
0.009
0.386
Support activities for mining
0.004
-0.435
Utilities
0.037
-0.519
Construction
0.093
-0.789
Wood products
0.011
0.100
Nonmetallic mineral products
0.013
0.159
Primary metals
0.033
-0.229
Fabricated metal products
0.034
0.306
Machinery
0.037
0.327
Electrical equipment appliances and components 0.017
0.229
Motor vehicles bodies and trailers and parts
0.051
0.362
Other transportation equipment
0.024
0.177
Furniture and related products
0.008
0.458
Miscellaneous manufacturing
0.013
0.959
Food and beverage and tobacco products
0.078
0.036
Textile mills and textile product mills
0.016
1.175
Apparel and leather and allied products
0.018
0.308
Paper products
0.020
0.049
Printing and related support activities
0.011
0.063
Petroleum and coal products
0.029
0.185
Chemical products
0.051
0.056
Plastics and rubber products
0.017
0.470
Wholesale Trade
0.076
1.937
Retail Trade
0.083
1.378
Air transportation
0.010
1.599
Rail transportation
0.010
1.592
Water transportation
0.004
0.675
Truck transportation
0.020
0.762
Transit and ground passenger transportation
0.004
-1.015
Pipeline transportation
0.004
0.525
Other transportation and support activities
0.009
1.068
Warehousing and storage
0.003
1.686
Motion picture and sound recording industries 0.006
0.140
Broadcasting and telecommunications
0.038
1.154
Information and data processing services
0.004
0.004
Federal Reserve banks credit intermediation and related
0.036 activities-1.569
Securities commodity contracts and investments0.012
2.035
Insurance carriers and related activities
0.037
-0.342
Funds trusts and other financial vehicles
0.006
-1.915
Rental and leasing services and lessors of intangible
0.013
assets
-2.088
Legal services
0.015
-1.608
Computer systems design and related services 0.006
-1.597
Miscellaneous professional scientific and technical
0.043
services
0.124
Management of companies and enterprises
0.025
-0.354
Administrative and support services
0.024
-0.082
Waste management and remediation services
0.005
0.438
Educational services
0.012
-0.563
Ambulatory health care services
0.032
-1.016
Hospitals Nursing and residential care facilities 0.036
-0.877
Social assistance
0.006
0.389
Performing arts spectator sports museums and related
0.005activities 0.233
Amusements gambling and recreation industries 0.005
0.084
Accommodation
0.010
0.815
Food services and drinking places
0.032
0.050
Other services except government
0.042
-0.403
Federal General government
0.063
0.162
Federal Government enterprises
0.009
-0.239
S&L General Government
0.096
-0.172
S&L Government enterprises
0.015
-0.828
Computer and peripheral equipment manufacturing
0.008
10.774
Communications equipment manufacturing
0.007
0.741
Semiconductor and other electronic component manufacturing
0.010
8.856
Other electronic products
0.014
0.824
Newspaper; periodical; book publishers
0.013
-1.731
Software publishing
0.004
9.006
Real estate
0.066
-0.815
Household
0.149
0.000
Total
1.814
1995-2000
2000-2007
Contribution
Domar
Weight
Growth
Contribution
Domar Weight
Growth
Contribution
0.05
0.00
-0.05
0.00
0.00
-0.03
-0.07
0.00
0.00
-0.01
0.01
0.01
0.00
0.02
0.00
0.00
0.01
0.01
0.02
0.00
0.00
0.00
0.00
0.00
0.01
0.15
0.11
0.02
0.02
0.00
0.01
0.00
0.00
0.01
0.00
0.00
0.04
0.01
-0.06
0.06
-0.01
-0.01
-0.03
-0.02
0.00
0.01
-0.01
0.00
0.00
-0.01
-0.03
-0.04
0.00
0.00
0.00
0.01
0.00
-0.02
0.01
0.00
-0.02
-0.01
0.09
0.00
0.10
0.01
-0.02
0.03
-0.05
0.00
0.024
0.006
0.009
0.006
0.003
0.031
0.078
0.010
0.010
0.018
0.027
0.029
0.012
0.048
0.017
0.007
0.012
0.056
0.010
0.008
0.017
0.011
0.018
0.044
0.018
0.072
0.084
0.011
0.005
0.003
0.020
0.003
0.003
0.009
0.003
0.007
0.044
0.006
0.048
0.024
0.040
0.007
0.017
0.017
0.012
0.057
0.027
0.036
0.005
0.013
0.044
0.045
0.008
0.006
0.007
0.012
0.032
0.040
0.045
0.008
0.103
0.015
0.011
0.009
0.015
0.012
0.013
0.008
0.068
0.157
2.605
2.287
-4.451
4.510
-2.514
0.630
-0.926
-0.178
0.114
0.854
-0.356
-1.184
0.246
-0.501
0.305
-0.171
1.344
-1.018
0.865
0.412
0.279
-0.376
1.895
-0.749
0.963
3.354
2.500
0.394
1.199
-0.845
0.426
-0.127
0.803
0.535
2.635
0.350
-1.083
-3.045
-3.842
12.432
0.039
-6.007
-8.065
-1.085
-0.677
-0.054
-0.999
-0.146
1.179
-1.605
-0.544
-0.526
-0.098
-0.640
-1.701
0.404
0.018
-1.011
-0.481
2.338
-0.294
0.117
16.894
0.045
20.874
-3.264
0.153
7.296
0.730
0.000
0.06
0.01
-0.04
0.02
-0.01
0.02
-0.07
0.00
0.00
0.02
-0.01
-0.03
0.00
-0.02
0.01
0.00
0.02
-0.06
0.01
0.00
0.01
0.00
0.04
-0.03
0.02
0.25
0.21
0.00
0.01
0.00
0.01
0.00
0.00
0.00
0.01
0.00
-0.04
-0.02
-0.18
0.30
0.00
-0.04
-0.14
-0.02
-0.01
0.00
-0.03
-0.01
0.01
-0.02
-0.02
-0.02
0.00
0.00
-0.01
0.00
0.00
-0.04
-0.02
0.02
-0.03
0.00
0.19
0.00
0.32
-0.04
0.00
0.05
0.05
0.00
0.020
0.004
0.015
0.005
0.005
0.029
0.084
0.008
0.008
0.014
0.022
0.022
0.009
0.039
0.014
0.006
0.011
0.049
0.006
0.004
0.013
0.008
0.027
0.042
0.015
0.067
0.083
0.010
0.004
0.003
0.018
0.002
0.003
0.009
0.003
0.007
0.050
0.010
0.051
0.025
0.042
0.007
0.019
0.018
0.014
0.069
0.027
0.039
0.005
0.015
0.047
0.045
0.009
0.006
0.007
0.012
0.033
0.040
0.050
0.007
0.107
0.015
0.006
0.006
0.010
0.010
0.012
0.009
0.071
0.162
1.851
-0.557
-4.938
-2.004
-2.722
0.444
-2.394
0.705
-0.101
-1.392
0.427
0.950
0.990
1.383
1.125
0.720
1.586
0.002
1.441
0.979
0.197
0.731
-1.511
0.902
-0.127
0.574
2.594
3.023
1.308
0.323
0.803
-0.704
0.982
1.396
0.628
-0.200
2.396
6.160
0.574
3.442
0.019
-1.267
-2.826
-1.032
2.367
1.597
-2.525
1.225
-0.843
-1.461
0.293
-0.630
1.502
-0.234
0.516
0.423
0.194
-0.220
0.137
-1.433
-0.709
-1.232
14.586
2.117
7.262
1.528
-0.703
5.145
1.470
0.000
0.04
0.00
-0.08
-0.01
-0.01
0.01
-0.21
0.01
0.00
-0.02
0.01
0.02
0.01
0.05
0.02
0.00
0.02
0.00
0.01
0.00
0.00
0.01
-0.08
0.04
0.00
0.04
0.21
0.03
0.01
0.00
0.01
0.00
0.00
0.01
0.00
0.00
0.12
0.06
0.03
0.09
0.00
-0.01
-0.05
-0.02
0.03
0.11
-0.07
0.05
0.00
-0.02
0.01
-0.03
0.01
0.00
0.00
0.00
0.01
-0.01
0.00
-0.01
-0.08
-0.02
0.08
0.00
0.07
0.01
-0.01
0.04
0.11
0.00
0.332
1.757
0.666
1.739
DRAFT
Note: Domar weight is value of industry 34
output over aggregate value added. Growth
rate is industry TFP growth rate and contributiuon is defined as in text as domar
weight times TFP growth rate. Source:Author’s calculations.
0.675