Econometrics
Volume 3:
Economic Growth
in the Information Age
This page intentionally left blank
Econometrics
Volume 3:
Economic Growth
in the Information Age
Dale W. Jorgenson
The MIT Press
Cambridge, Massachusetts
London, England
© 2002 Dale W. Jorgenson
All rights reserved. No part of this book may be reproduced in any form by any electronic
or mechanical means (including photocopying, recording, and information storage and
retrieval) without permission in writing from the publisher.
This book was set in Palatino by Windfall Software using ZzTEX and was printed and
bound in the United States of America.
Library of Congress Cataloging-in-Publication Data
Jorgenson, Dale Weldeau, 1933–
Econometrics / Dale W. Jorgenson.
p. cm.
Includes bibliographical references and index.
ISBN 0-262-10094-0 (v. 3: hc: alk. paper)
1. Production (Economic theory)—Econometric models. I. Title.
HB241.J67 2000
330 .01 5195—dc21
99-046138
Contents
List of Figures
List of Tables
Preface
Dale W. Jorgenson
List of Sources
1
2
3
Information Technology and the U.S. Economy
Dale W. Jorgenson
1.1 The Information Age
1.2 The Role of Information Technology
1.3 The American Growth Resurgence
1.4 Economics on Internet Time
Notes
Computers and Growth
Dale W. Jorgenson and Kevin J. Stiroh
2.1 Introduction
2.2 Computer Investment
2.3 A Model of Computer Services
2.4 Computer Stocks and Services
2.5 Computers and Growth
2.6 Conclusion
Notes
Raising the Speed Limit: U.S. Economic Growth in the
Information Age
Dale W. Jorgenson and Kevin J. Stiroh
3.1 Introduction
3.2 The Recent U.S. Growth Experience
ix
xiii
xvii
xxix
1
3
12
22
39
40
43
43
45
49
55
61
67
68
71
71
74
vi
4
5
6
Contents
3.3 Setting the Speed Limit
3.4 Industry Productivity
3.5 Conclusions
Appendix A: Estimating Output
Appendix B: Estimating Capital Services
Appendix C: Estimating Labor Input
Appendix D: Estimating Industry-Level Productivity
Appendix E: Extrapolation for 1999
Notes
103
110
123
126
129
141
144
145
146
Why Has the Energy-Output Ratio Fallen in China?
Richard F. Garbaccio, Mun S. Ho, and Dale W. Jorgenson
4.1 Introduction
4.2 Review of Previous Work on China’s Energy-Output
Ratio
4.3 Problems with Official Chinese Data
4.4 Constructing a Consistent Data Set
4.5 A Methodology for Decomposing the Change in Energy
Intensity
4.6 Decomposition of the Change in China’s Energy
Intensity
4.7 Effects of Using Alternative Estimates of Inflation
4.8 Conclusions
Notes
151
Whatever Happened to Productivity Growth?
Dale W. Jorgenson and Eric Yip
5.1 Introduction
5.2 Investment and Productivity
5.3 Sources of Growth
5.4 Convergence
5.5 Endogenizing Growth
Appendix A: Data Sources
Notes
Tax Reform and the Cost of Capital
Dale W. Jorgenson
6.1 Introduction
6.2 International Comparisons
6.3 Alternative Approaches
151
152
155
158
164
167
173
175
176
179
179
181
187
196
201
206
209
211
211
218
237
Contents
7
8
9
vii
6.4 Summary and Conclusion
Appendix A: King-Fullerton Framework
Notes
243
248
255
Investment and Growth
Dale W. Jorgenson
7.1 Introduction
7.2 Sources and Uses of Growth
7.3 The Growth Revival
7.4 Endogenous Growth
7.5 Econometric Modeling
7.6 Conclusion
Notes
259
Policies to Stimulate Economic Growth
Mun S. Ho and Dale W. Jorgenson
8.1 Introduction
8.2 The Education Sector and Human Capital
8.3 A Dynamic Model with Human Capital
8.4 Data and Parameter Estimates
8.5 The Effect of Increased Expenditures on Education
8.6 The Effects of Increased Enrollment
8.7 Conclusion
Notes
Did We Lose the War on Poverty?
Dale W. Jorgenson
9.1 The Official Poverty Line
9.2 Measuring the Household Standard of Living
9.3 Comparing Standards of Living among Households
9.4 Measuring the Household Cost of Living
9.5 Estimates of the Poverty Rate
9.6 Poverty and Redistributional Policy
9.7 From Individual to Social Welfare
9.8 Poverty and Inequality within and between Groups
9.9 Measuring the Standard of Living
9.10 Recommendations and Conclusions
Notes
259
262
266
270
277
281
285
289
289
292
299
308
309
312
317
318
321
322
323
325
327
328
330
332
335
336
337
338
viii
Contents
10 Indexing Government Programs for Changes in the Cost of
Living
Dale W. Jorgenson and Daniel T. Slesnick
10.1 Measuring the Cost of Living
10.2 Implementing Cost-of-Living Indexes
10.3 Group Cost-of-Living Indexes
10.4 Recommendations and Conclusions
11 Controlling Carbon Emissions in China
Richard F. Garbaccio, Mun S. Ho, and Dale W. Jorgenson
11.1 Introduction
11.2 A Dynamic Economy-Energy-Environment Model for
China
11.3 Data and Exogenous Variables
11.4 Carbon Taxes and Emissions
11.5 Conclusions
Appendix A: Description of the Model
Notes
339
343
346
352
359
361
362
364
368
370
380
382
390
393
12 The Economic Impact of Fundamental Tax Reform
Dale W. Jorgenson and Peter J. Wilcoxen
12.1 Introduction
12.2 Provisions of U.S. Tax Law
12.3 Fundamental Tax Reform
12.4 Conclusion
Notes
393
401
403
419
420
References
Index
421
455
List of Figures
1.1
1.2
1.3
Relative prices of computers and semiconductors,
1959–1999
5
Relative prices of computers, communications,
software, and services 1948–1999
8
Relative prices of computers, communications, and
software, 1959–1999
10
Output shares of information technology by type,
1948–1999
17
Input shares of information technology by type,
1948–1999
21
1.6
Output contribution of information technology
30
1.7
Output contribution of information technology by type
30
1.8
Capital input contribution of information technology
31
1.9
Capital input contribution of information technology
by type
32
Contributions of information technology to total factor
productivity growth
33
1.11
Sources of gross domestic product growth
35
1.12
Sources of average labor productivity growth
37
2.1
Relative price of investment, 1958–1992
47
2.2
Share of investment quantity, 1958–1992
48
2.3
Relative price of capital stock, 1958–1992
57
2.4
Share capital stock quantity, 1958–1992
57
2.5
Relative price of capital services, 1959–1992
59
2.6
Share of capital services quantity, 1959–1992
61
1.4
1.5
1.10
x
3.1
List of Figures
Relative prices of information technology outputs,
1960–1998
79
3.2
Output shares of information technology, 1960–1998
81
3.3
Input shares of information technology, 1960–1998
82
3.4
Sources of U.S. economic growth, 1959–1998
88
3.5
Output contribution of information technology,
1959–1998
90
Output contribution of information technology assets,
1959–1998
90
Input contribution of information technology,
1959–1998
91
Input contribution of information technology assets,
1959–1998
91
3.9
Sources of U.S. labor productivity growth, 1959–1998
94
3.10
TFP decomposition for alternative deflation cases
103
3.11
Industry contributions to aggregate total factor
productivity growth, 1958–1996
122
4.1
Energy-GDP ratio, 1953–1995
153
5.1
Convergence of output and input per capita and
productivity
200
Convergence of capital input, capital stock per capita
and capital quality
201
Convergence of labor input and hours worked per
capita and labor quality
202
(a) Human capital of the United States and (b) capital
of the United States
295
(a) Student enrollment and (b) education cost as share
of GDP
296
Effects of increasing expenditures on education
(percentage change from base case)
311
(a) Educational attainment of males, age 34 and (b)
females, age 34
313
Effects of increasing college enrollment by 20 percent
(percentage change from base case)
315
Household standard and cost of living
324
3.6
3.7
3.8
5.2
5.3
8.1
8.2
8.3
8.4
8.5
9.1
List of Figures
xi
9.2
U.S. poverty ratios
329
9.3
Poverty and inequality
331
9.4
Relative poverty and remaining inequality
334
10.1
CPI-U and CPIX1 price indexes
347
10.2
Tornqvist and social cost-of-living indexes
351
10.3
Relative prices
353
10.4
White and nonwhite cost-of-living indexes
355
10.5
Male- and female-head cost-of-living indexes
356
10.6
Nonelderly and elderly cost-of-living indexes
356
11.1
Carbon emissions
373
11.2
Percentage change in GDP relative to base case
373
11.3
Carbon taxes required to attain a given reduction in
emissions
374
11.4
Reduction in other taxes to offset carbon tax revenues
374
11.5
Percentage change in consumption relative to base case
375
11.6
Percentage change in investment relative to base case
376
12.1
Organization of the Use table
396
12.2
Organization of the Make table
396
12.3
Base Case GDP
408
12.4
Consumption tax rates
408
12.5
GDP
409
12.6
Investment
410
12.7
Consumption
411
12.8
Exports
411
12.9
Imports
412
12.10 Price of investment
413
12.11
413
Price of consumption
12.12 Labor supply
414
12.13 Industry prices, 1996
415
12.14 Industry prices, 2020
416
12.15 Industry outputs, 1996
417
12.16 Industry outputs, 2020
418
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List of Tables
1.1
Information technology output and Gross Domestic
Product
14
1.2
Growth rates of outputs and inputs
16
1.3
Information technology capital stock and domestic
tangible assets
18
Information technology capital services and gross
domestic income
20
1.5
Labor Services
24
1.6
Sources of Gross Domestic Product growth
28
1.7
Sources of total factor productivity growth
34
1.8
Sources of average labor productivity growth
37
2.1
Investment quantity in 1987 dollars
46
2.2
Capital stock quantity in 1987 dollars
56
2.3
Capital services quantity in 1987 dollars
58
2.4
Growth rates of aggregate output, inputs, and
productivity, 1947–1992
63
3.1
Average growth rates of selected outputs and inputs
80
3.2
Growth in U.S. private domestic output and the sources
of growth, 1959–1999
86
3.3
The sources of ALP growth, 1959–1998
93
3.4
Impact of alternative deflation of software and
communications equipment on the sources of U.S.
economic growth, 1959–1998
98
1.4
3.5
Information technology decomposition of TFP growth
for alternative deflation cases, 1990–1998
102
xiv
3.6
List of Tables
Growth rates of output, inputs, and total factor
productivity comparison of BLS, CBO, and
Jorgenson-Stiroh
106
3.7
1996 value added and gross output by industry
114
3.8
Sources of U.S. economic growth by industry, 1958–1996
116
A.1
Private domestic output and high-tech assets
127
B.1
Investment and capital stock by asset type and class
136
B.2
Total capital stock and high-tech assets
138
B.3
Total capital services and high-tech assets
139
C.1
Labor input
143
4.1
GVO-GDP ratios, 1980–1995
155
4.2
Energy-output ratios, 1980–1995
157
4.3
Comparison of value and physical quantity growth
rates, 1987–1992
157
Summary figures for adjusted input-output tables (bil.
yuan)
162
4.5
Domestic output of energy sectors
163
4.6
Decomposition of change in energy use per unit of GDP
169
4.7
Sectoral energy intensity, 1987 and 1992
171
4.8
Changes in composition of final demand, 1987–1992
172
4.9
Decomposition of change in energy use with alternative
estimates of inflation
174
5.1
Disaggregation of capital by asset characteristics
186
5.2
Disaggregation of labor by demographic characteristics
187
5.3
Levels of output and input per capita and productivity
(U.S. = 100.0 in 1985)
188
5.4
Growth rate and level in output
188
5.5
Growth rate and level in population
189
5.6
Growth in output and input per capita and productivity
(percentage)
190
5.7
Levels of capital input and capital stock per capita and
capital quality (U.S. = 100.0 in 1985)
192
Growth in capital input and capital stock per capita
and capital quality (percentage)
193
4.4
5.8
List of Tables
5.9
xv
Levels of labor input and hours worked per capita and
labor quality (U.S. = 100.0 in 1985)
194
Growth in labor input and hours worked per capita
and labor quality (percentage)
196
Marginal effective corporate tax rates, nine countries,
1980, 1985, 1990
220
Marginal effective personal tax rates, nine countries,
1980, 1985, 1990
224
Marginal effective tax rates on corporate source income,
nine countries, 1980, 1985, 1990
226
Marginal effective noncorporate tax rates, nine
countries, 1980, 1985, 1990
228
Marginal effective housing tax rates, nine countries,
1980, 1985, 1990
231
8.1
Input-output structure of model
299
8.2
(top) Estimates of the parameters of model; (bottom)
estimates of coefficients of production and consumption
functions
303
8.3
Effects of higher expenditures on education
310
8.4
Effects of higher enrollment
314
9.1
Jorgenson-Slesnick household equivalence scales
(Reference: Size 4, age 35–44, northeast, urban, white)
327
Census equivalence scales (Reference: Size 4, nonfarm,
male)
328
10.1
Group cost-of-living indexes
348
10.2
Unit-root tests; null hypothesis: unit root
349
10.3
Cointegration tests; null hypothesis: no cointegration
350
10.4
Relative prices
354
10.5
Group cost-of-living indexes
357
10.6
Tornqvist cost-of-living indexes
358
11.1
Summary social accounting matrix for China, 1992
(billion yuan)
366
11.2
Sectoral characteristics for China, 1992
367
11.3
Effects of a carbon tax on selected variables (percentage
change from base case)
377
5.10
6.1
6.2
6.3
6.4
6.5
9.2
xvi
11.4
List of Tables
Effects of a carbon tax on first year sectoral prices
(percentage change from base case)
378
Effects of a carbon tax on first year sectoral output
(percentage change from base case).
379
Selected parameters and variables in the China model
parameters
383
12.1
The definitions of industries
394
12.2
Make and Use table variables
395
11.5
A.1
Preface
Dale W. Jorgenson
The stagflation of the 1970s greatly undermined the Keynesian Revolution of the 1930s, leading to the New Classical Counterrevolution that
has transformed the economics of the business cycle. The unanticipated
American growth revival of the 1990s has similar potential for revolutionizing economists’ perspectives on economic growth. It is not surprising that the combination of more rapid growth and lower inflation
has touched off a strenuous debate about whether the improvements in
America’s economic performance can be sustained.
This volume presents my econometric studies of economic growth in
the information age. The point of departure is my presidential address
to the American Economic Association, “Information Technology and
the U.S. Economy,” delivered in New Orleans, Louisiana, on January 6,
2001. In chapter 1 I show that the remarkable behavior of information
technology (IT) prices is the key to understanding the growth resurgence
of the American economy. This can be traced to developments in semiconductor technology that are widely understood by technologists and
economists.
The economics of information technology begins with the observation
that semiconductors have become cheaper at a truly astonishing rate.
Modeling the behavior of semiconductor prices is a severe test for the
econometric methods used in the official price statistics. A hedonic
model gives the price of semiconductor products as a function of the
characteristics that determine performance, such as speed of processing
and storage capacity. A constant quality price index isolates the price
change by holding these characteristics constant.
Mainframe and personal computers have come to rely heavily on
semiconductor storage devices, or “memory chips,” for main memory.
Similarly, computers rely on microprocessors, or “logic chips,” for central processing. However, semiconductors account for less than half of
xviii
Preface
computer costs, and computer prices have fallen much less rapidly than
semiconductor prices. In 1985 the Bureau of Economic Analysis (BEA)
introduced constant quality price indexes for computers and peripheral
equipment into the U.S. National Income and Product Accounts (NIPA).
Rosanne Cole et al. (1986) of IBM constructed the computer price indexes
employed by BEA.
In 1985 the Program on Technology and Economic Policy that I direct
at Harvard University organized a conference to discuss the BEA-IBM
constant quality price indexes for computers. Ralph Landau and I edited
the conference proceedings, Technology and Capital Formation (1989). This
volume established the foundation for my research with Kevin Stiroh
(1995) on the impact of computers on economic growth. In chapter 2 we
show that the concept of the cost of capital, presented in my volume
Capital Theory and Investment Behavior (1996), is the key to modeling the
economic impact of information technology.
Swiftly falling IT prices provide a powerful economic incentive for
substituting capital for labor, as well as substituting IT equipment for
other forms of capital. The rate of the IT price decline is also a key
component of the cost of capital, required for assessing the impacts of
rapidly growing stocks of computers. Constant quality price indexes
are used as deflators for investments in computers. These investments
are cumulated into stocks of computer capital. Finally, constant quality
service prices, incorporating the cost of capital, are employed to convert
the stocks into flows of computer services.
The production possibility frontier was the principal innovation in
“The Embodiment Hypothesis,” chapter 2 in my volume, Postwar U.S.
Economic Growth (1995). The most compelling advantage of this model
is the explicit role that it provides for constant quality price indexes. The
frontier captures substitution between capital and labor inputs, as well
as substitution between investment and consumption outputs. Using
this concept, Stiroh and I have generated evidence of massive substitutions of computers for outputs of consumption goods and other investment goods, as well as similar substitutions of services of computers for
labor inputs and other capital inputs.
The eleventh set of comprehensive revisions of the U.S. national accounts, released by BEA in 1999, reclassified the output of software as an
investment good. These revisions also incorporated a constant quality
price index for prepackaged software developed by Steven Oliner and
Daniel Sichel (1994). In chapter 3 Stiroh and I extend the production possibility frontier to include telecommunications equipment and software
Preface
xix
as well as computers. We employ a hedonic model of the prices of digital
telephone switching equipment from the U.S. national accounts.
The rapid progress of econometric research on prices of information
technology has left some significant gaps. While hedonic models of
prices for computers and peripheral equipment now cover all forms of
investment in these IT products, constant quality prices for telecommunications equipment and software cover only part of the investment. In
chapter 3 Stiroh and I show that the impact of the resulting biases in IT
price indexes is to underestimate the growth of output and overestimate
the growth of total factor productivity.
In chapter 1 I include investments by the government sector, as well
as investments by business and household sectors, in the measure of
IT outputs. My output measure also includes the imputed value of IT
services in the household and government sectors. (The value of these
services employed in the business sector is included in business income
and does not require a separate imputation.) This measure of output
is similar to the concept of gross domestic product employed by BEA.
However, my measure of IT services incorporates all the components of
the cost of IT capital, while the BEA measure includes only depreciation.
A key innovation in the model of production employed in chapter 1 is
the allocation of total factor productivity growth between information
and non-information technology. I show that the contribution of information technology roughly doubled between the periods 1990–1995
and 1995–1999, but that the contribution of non-information technology
increased even more. However, the rise in the growth of total factor productivity accounted for less than a third of the two percent jump in U.S.
economic growth after 1995. Almost half the jump was due to a surge in
the growth of capital input, while the rising contribution of labor input
accounted for the rest.
As a consequence of the advance of information technology, many of
the most familiar concepts in growth economics have been superseded.
The aggregate production function employed by Robert M. Solow (1957,
1960) heads the list. The production function gives a single output as a
function of capital and labor inputs. There is no role for separate prices
of investment and consumption goods and, hence, no place for constant
quality prices of information technology in measuring the output of
investment goods.
Similarly, capital stock is no longer adequate to capture the rising importance of IT. This measure of capital input completely obscures the
restructuring that is the wellspring of the American growth resurgence.
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Preface
Accurate modeling of substitution among different types of capital input, especially information technology and other forms of capital, is
essential in assessing the impact of investment. Finally, hours worked
omits the rapid shifts in the evaluation of skills as a consequence of
advances in information technology. This has been superseded by a
measure of labor input that reflects substitution among workers with
different skills.
The second major theme of this volume is international comparisons
of patterns of economic growth in the information age. This is also
the primary focus of my volume, International Comparisons of Economic
Growth (1995). In chapter 5 Eric Yip and I present empirical support for
a neo-classical growth model characterized by persistent differences in
productivity, capital quality, labor quality, and hours worked per capita
among countries. This can be contrasted with the econometric version
of Solow’s (1956) neo-classical model employed in the seminal paper
by Gregory Mankiw, David Romer, and David Weil (1991) where these
critical differences among countries are suppressed.
Yip and I assemble the empirical evidence for our neo-classical growth
model by constructing consistent data on the sources of economic
growth for the G7 countries, covering the period 1960–1995. Our methodology is based on the same innovations as those employed in modeling the U.S. economy in chapter 1. The cost of capital plays a central role
in capturing the impact of investment in tangible assets. We employ a
production possibility frontier for each country in order to incorporate
the available data on investment in information technology.
Yip and I find that the United States has retained its lead in output
per capita among the G7 countries throughout the period 1960-1995.
The United States has also maintained its lead in input per capita, while
relinquishing the lead in productivity to France. Investments in tangible
assets and human capital account for the overwhelming proportion of
economic growth in the G7 countries and also explain the predominant
share of international differences in output per capita.
The third major theme of this book is the econometric modeling of
economic growth in the information age. An econometric model of the
production possibility frontier was the central contribution of “Transcendental Logarithmic Production Frontiers,” chapter 4 in volume 1 of
this set, Econometric Modeling of Producer Behavior (2000). This econometric model represents the technology of the U.S. economy in my book
with Kun-Young Yun, Lifting the Burden: Tax Reform, the Cost of Capi-
Preface
xxi
tal, and U.S. Economic Growth (2001). We estimate the parameters of this
model from a data set that includes the BEA-IBM constant quality price
for computers.
In “Inflation-Proof Depreciation of Assets,” chapter 8 in Tax Policy and
the Cost of Capital (1996), Alan Auerbach and I augment the cost of capital framework by introducing the marginal effective tax rate. The cost
of capital summarizes information about the future consequences of investment in tangible assets essential for current decisions. The marginal
effective tax rate characterizes the consequence of investment decisions
that is particularly suitable for comparisons among alternative tax policies. Efficient capital allocation requires the equalization of marginal
effective tax rates on all assets.
Yun and I summarize the tax burden on capital income by means
of marginal effective tax rates for all assets and all sectors of the U.S.
economy. We show that the Tax Reform Act of 1986 significantly reduced differences in the tax burdens among corporate, non-corporate,
and household sectors. Differences between short-lived and long-lived
depreciable assets were almost eliminated by this legislation. However,
substantial differences in marginal effective tax rates between household and corporate sectors still remain. These gaps reveal important
opportunities for gains in efficiency through reallocation of capital by
means of tax reform.
In chapter 6 I employ marginal effective tax rates to compare the effects of reforms of capital income taxation in the G7 countries, Australia,
and Sweden during the 1980s and 1990s. In most countries these reforms
reversed decades of erosion of the income tax base to provide incentives
for saving and investment. Efforts were made to equalize tax rates on assets within the business sector. However, equalization of tax burdens on
housing and business capital has proved to be extraordinarily difficult
within the framework of the income tax. Although reforms have substantially reduced barriers to efficient allocation of capital, important
opportunities for further gains in efficiency remain in all nine countries.
Yun and I focus on the determinants of investment in tangible assets, including investments in information technology. Our econometric
model combines the production possibility frontier with an econometric
representation of preferences. This representation was first presented in
“Transcendental Logarithmic Utility Functions,” chapter 1 of Aggregate
Consumer Behavior (1997). Yun and I employ our econometric model of
economic growth to simulate the impact of alternative tax reforms. We
xxii
Preface
compare the level of social welfare for each tax reform with welfare in the
absence of reform, translating these welfare comparisons into monetary
terms.
In chapter 8 Mun S. Ho and I extend the econometric modeling of
economic growth in the information age by incorporating a model of
investment in human capital. We treat this investment as the output
of the educational sector. Inputs of the sector include purchases of intermediate goods such as school supplies and energy by educational
institutions, the services of tangible assets like buildings and equipment
employed in these institutions, the services of human capital from teachers, and—most important of all—the services of human capital from
students.
A detailed set of growth accounts for the educational sector is contained in my paper with Barbara Fraumeni, “The Output of the Educational Sector,” chapter 7 of Postwar U.S. Economic Growth (1995). Our
point of departure is that education is a service industry, but its output
is investment in human capital. This is measured as increments to the
lifetime incomes of all students enrolled in the educational system. The
value of investment in education, measured in this way, is roughly equal
to the value of the working time of the entire U.S. labor force.
Ho and I have evaluated alternative educational policies by transforming changes in welfare associated with policy changes into changes
in wealth. We consider policies that would increase educational “quality” by increasing expenditures and taxes that finance them, while holding educational participation rates constant. We also consider policies
that would hold expenditures and taxes constant, while increasing participation rates. We conclude that enhancing educational quality would
reduce social welfare, while increasing participation rates would increase welfare.
In chapter 7 I describe the barriers to extending econometric models of
economic growth to encompass intellectual capital. The standard model
for investment in intellectual capital, formulated by Zvi Griliches (1973),
treats this investment as an output of research and development. The
services of intellectual capital are a factor of production, like the services
of tangible assets and human capital in my model with Ho. While the
output of the educational sector can be defined in terms of increments
to lifetime incomes of students, there is no comparable measure for
the output of research and development. Pricing this output remains
a major barrier to incorporating intellectual capital into econometric
models of economic growth.
Preface
xxiii
The fourth major theme of this book is the econometric approach for
measuring social welfare in the information age, also the focus of Measuring Social Welfare (1997). The essential idea is to recover measures of
individual welfare from an econometric model of aggregate consumer
behavior. These are combined into an indicator of welfare that reflects
horizontal and vertical equity, as well as economic efficiency. The econometric approach is summarized in chapter 1 of the volume, “Aggregate
Consumer Behavior and the Measurement of Social Welfare,” my presidential address to the Econometric Society. Daniel Slesnick provides a
much more detailed account in his book, Consumption and Social Welfare
(2001).
Multi-million dollar budgets are involved in statistical reporting of
measures of the cost of living, while millions more are spent on measures of poverty, inequality, and the standard of living. Unfortunately,
these well-established programs give highly misleading results and require a complete overhaul. The key to revision of these programs is the
effective exploitation of existing surveys of household consumption. In
chapter 9 (“Did We Lose the War on Poverty?”) I give a detailed example of econometric measures of the incidence of poverty based on
consumption. I show that the War on Poverty was a success, while official estimates based on income rather than consumption purport to
show the reverse.
In chapter 10, Slesnick and I present a new measure of the cost of
living based on the econometric approach to measuring social welfare.
This incorporates all the information employed in the Consumer Price
Index (CPI) but preserves important features of the data ignored in
constructing these price index numbers. For example, the econometric
approach captures changes in household spending patterns in response
to changes in prices and total expenditure. In addition, it includes the
effects of changes in the demographic structure of the population on
aggregate spending patterns.
Slesnick and I show that inflation rates over the period 1947–1995 are
virtually identical for the econometric measure of the cost of living and
the CPI. Over the first half of the period, the econometric approach generates slightly higher inflation rates, while the reverse is true for the
second half. We find that group cost of living indexes are similar for
white and nonwhite households, for female-headed and male-headed
households, and for non-elderly households. The elderly have experienced slightly higher inflation rates since 1973. We recommend indexing
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Preface
government programs, such as Social Security, by group cost of living
indexes rather than the CPI.
The fifth theme of this volume is econometric general equilibrium
modeling in the information age. This is also the subject of Energy, the
Environment, and Economic Growth (1998). In chapter 12 Peter J. Wilcoxen
and I present an intertemporal general equilibrium model for analyzing
the impact of tax policies in the United States. This preserves the key
features of more highly aggregated models, like the one presented in
chapter 8. However, Wilcoxen and I have disaggregated the representations of technology and preferences in order to provide a more detailed
perspective on the impact of changes in tax policy.
One important dimension for disaggregation is to introduce a distinction between commodities and industries in order to model business responses to tax-induced price changes. We also distinguish among
households by level of wealth and demographic characteristics so that
we can model the responses of households to tax policies as well. Finally, we model demands for different types of capital services in each
of thirty-five industrial sectors, as well as the household sector. These
demands depend on tax policies through measures of the cost of capital
that incorporate the characteristic features of U.S. tax law described in
my book with Yun.
We consider the economic impact of substituting a tax on consumption for the existing system of income taxes in the United States. We first
consider the Armey-Shelby Flat Tax. This proposal levies taxes on the
difference between business receipts and the sum of business purchases
from other firms and payrolls. Labor income is taxed at the individual
level. An important feature of this proposal is a system of personal exemptions that have the effect of setting the marginal rates of taxation
equal to zero up to the exempt amount of income. The purpose of the
exemptions is to introduce progressivity into the rate structure, since average tax rates rise gradually from zero to the flat tax rate as household
income increases.
The second tax reform proposal we consider is the National Retail
Sales Tax. The tax base is the same as in our simulations of the Flat Tax.
However, the method of collection is different. The Flat Tax preserves
the existing structures of the corporate and individual income taxes but
alters the tax base. The National Retail Sales Tax eliminates corporate
and individual income taxes and relies on retail establishments to collect
the taxes. This definition of retail establishments would include real
estate developers and providers of professional services, such as legal