[House Hearing, 107 Congress]
[From the U.S. Government Publishing Office]





         BEA: IS THE GDP ACCURATELY MEASURING THE U.S. ECONOMY?

=======================================================================

                                HEARING

                               before the

                       SUBCOMMITTEE ON THE CENSUS

                                 of the

                              COMMITTEE ON
                           GOVERNMENT REFORM

                        HOUSE OF REPRESENTATIVES

                      ONE HUNDRED SEVENTH CONGRESS

                             FIRST SESSION

                               __________

                             APRIL 5, 2001

                               __________

                            Serial No. 107-8

                               __________

       Printed for the use of the Committee on Government Reform


  Available via the World Wide Web: http://www.gpo.gov/congress/house
                      http://www.house.gov/reform

      
            U.S. GOVERNMENT PRINTING OFFICE
75-327                     WASHINGTON : 2001

____________________________________________________________________________
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                     COMMITTEE ON GOVERNMENT REFORM

                     DAN BURTON, Indiana, Chairman
BENJAMIN A. GILMAN, New York         HENRY A. WAXMAN, California
CONSTANCE A. MORELLA, Maryland       TOM LANTOS, California
CHRISTOPHER SHAYS, Connecticut       MAJOR R. OWENS, New York
ILEANA ROS-LEHTINEN, Florida         EDOLPHUS TOWNS, New York
JOHN M. McHUGH, New York             PAUL E. KANJORSKI, Pennsylvania
STEPHEN HORN, California             PATSY T. MINK, Hawaii
JOHN L. MICA, Florida                CAROLYN B. MALONEY, New York
THOMAS M. DAVIS, Virginia            ELEANOR HOLMES NORTON, Washington, 
MARK E. SOUDER, Indiana                  DC
JOE SCARBOROUGH, Florida             ELIJAH E. CUMMINGS, Maryland
STEVEN C. LaTOURETTE, Ohio           DENNIS J. KUCINICH, Ohio
BOB BARR, Georgia                    ROD R. BLAGOJEVICH, Illinois
DAN MILLER, Florida                  DANNY K. DAVIS, Illinois
DOUG OSE, California                 JOHN F. TIERNEY, Massachusetts
RON LEWIS, Kentucky                  JIM TURNER, Texas
JO ANN DAVIS, Virginia               THOMAS H. ALLEN, Maine
TODD RUSSELL PLATTS, Pennsylvania    JANICE D. SCHAKOWSKY, Illinois
DAVE WELDON, Florida                 WM. LACY CLAY, Missouri
CHRIS CANNON, Utah                   ------ ------
ADAM H. PUTNAM, Florida              ------ ------
C.L. ``BUTCH'' OTTER, Idaho                      ------
EDWARD L. SCHROCK, Virginia          BERNARD SANDERS, Vermont 
------ ------                            (Independent)


                      Kevin Binger, Staff Director
                 Daniel R. Moll, Deputy Staff Director
                     James C. Wilson, Chief Counsel
                     Robert A. Briggs, Chief Clerk
                 Phil Schiliro, Minority Staff Director

                       Subcommittee on the Census

                     DAN MILLER, Florida, Chairman
CHRIS CANNON, Utah                   WM. LACY CLAY, Missouri
MARK E. SOUDER, Indiana              CAROLYN B. MALONEY, New York
BOB BARR, Georgia                    DANNY K. DAVIS, Illinois
------ ------

                               Ex Officio

DAN BURTON, Indiana                  HENRY A. WAXMAN, California
                       Jane Cobb, Staff Director
                Erin Yeatman, Professional Staff Member
                            Dan Wray, Clerk
           David McMillen, Minority Professional Staff Member


                            C O N T E N T S

                              ----------                              
                                                                   Page
Hearing held on April 5, 2001....................................     1
Statement of:
    Dennis, Bob, Congressional Budget Office, Assistant Director, 
      Macroeconomic Analysis; Richard Berner, president, NABE; 
      Diane Swonk, chief economist, Bank One, Inc.; Gordon 
      Richards, economist, National Association of Manufacturers; 
      and Dr. Ernst R. Berndt, MIT, chair of the Federal Economic 
      Statistics Advisory Committee..............................    34
    Landefeld, J. Steven, Director, Bureau of Economic Analysis; 
      and Frederick Knickerbocker, Associate Director for 
      Economic Programs, Bureau of the Census....................     5
Letters, statements, etc., submitted for the record by:
    Berndt, Dr. Ernst R., MIT, chair of the Federal Economic 
      Statistics Advisory Committee, prepared statement of.......    81
    Berner, Richard, president, NABE, prepared statement of......    54
    Clay, Hon. Wm. Lacy, a Representative in Congress from the 
      State of Missouri, prepared statement of...................    98
    Dennis, Bob, Congressional Budget Office, Assistant Director, 
      Macroeconomic Analysis, prepared statement of..............    37
    Knickerbocker, Frederick, Associate Director for Economic 
      Programs, Bureau of the Census, prepared statement of......    21
    Landefeld, J. Steven, Director, Bureau of Economic Analysis, 
      prepared statement of......................................     9
    Miller, Hon. Dan, a Representative in Congress from the State 
      of Florida, prepared statement of..........................     3
    Richards, Gordon, economist, National Association of 
      Manufacturers, prepared statement of.......................    68
    Swonk, Diane, chief economist, Bank One, Inc., prepared 
      statement of...............................................    62

 
         BEA: IS THE GDP ACCURATELY MEASURING THE U.S. ECONOMY?

                              ----------                              


                        THURSDAY, APRIL 5, 2001

                  House of Representatives,
                        Subcommittee on the Census,
                            Committee on Government Reform,
                                                    Washington, DC.
    The subcommittee met, pursuant to notice, at 2:02 p.m., in 
room 2247, Rayburn House Office Building, Hon. Dan Miller 
(chairman of the subcommittee) presiding.
    Present: Representative Miller.
    Staff present: Jane Cobb, staff director; Chip Walker, 
deputy staff director; Michael Miguel, senior data analyst; 
Erin Yeatman and Andrew Kavaliunas, professional staff members; 
Daniel Wray, clerk; David McMillen, minority professional staff 
member; and Teresa Coufal, minority staff assistant.
    Mr. Miller. Good afternoon. The subcommittee will come to 
order. We will proceed. I will have a brief opening statement 
and then we will go with our first panel. I called this hearing 
to examine the function and needs of a relatively small but 
significant Federal player in providing the policymaker and the 
public a timely and accurate picture of national and 
international economic activity. The Bureau of Economic 
Analysis [BEA], is a statistical agency within the Commerce 
Department's economic and statistics administration. It has a 
budget of close to $50 million and employs approximately 445 
people. It produces, among other things, one of our Nation's 
primary economic indicators, the Gross Domestic Product [GDP], 
something we will be looking at closely today.
    BEA also produces estimate of analyses of personal income 
population and employment for regions, States, metropolitan 
areas and countries. BEA helps define the international 
economic picture by producing the U.S. balance of payments. 
Additionally, it measures U.S. direct investment abroad and 
foreign direct investment in the United States. In information 
provided to the subcommittee by BEA, it is clear that BEA's 
statistics are heavily relied on by government and industry.
    For example, the Congressional Budget Office and Office of 
Management and Budget rely on BEA estimate of economic growth 
to make Federal budget projections. BEA's regional income and 
product estimates are used to allocated more than $100 billion 
annually in Medicaid and other Federal grants to States. 
Virtually, all States use BEA data in their tax projections 
infrastructure planning and allocations of State funds to 
counties. BEA's national, international and regional estimates 
are essential inputs to private sector business forecasts and 
production and investment plan. Business associations use BEA's 
national and regional data by industry to gauge the economic 
health of association members. Financial planners use BEA's 
income and saving data, as well as the growth of GDP and its 
components, to develop and assess investment and retirement 
planning strategies.
    Today we will examine DEA to give Congress and the public a 
better understanding of this agency's important functions, with 
a particular focus on the accuracy of the Gross Domestic 
Product. We also hope to learn of some of the issues BEA faces 
in its challenge to produce vivid, accurate and timely 
snapshots of our rapidly changing economy.
    [The prepared statement of Hon. Dan Miller follows:]

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    Mr. Miller. We have invited a number of witnesses to help 
us look at BEA today. On panel one we will hear from the 
Director of BEA, Mr. Steven Landefeld and Mr. Frederick 
Knickerbocker of the Census Bureau, a key survey taker and data 
provider to the BEA. On panel two we will hear from economists 
and officials in business government and academia who have been 
asked to speak to BEA's role the accuracy of GDP and the issues 
they see are important to this agency. I welcome and thank you 
for joining us today and look forward to your testimony, so we 
will proceed immediately with the first panel.
    We are delighted that both of you have joined us here 
today. We will start with Dr. Landefeld. He is the Director of 
the Bureau of Economic Analysis. Dr. Landefeld has been the 
Director of BEA since 1995. Prior to becoming Director, he 
served as Deputy Director and Associate Director of economics 
at BEA. Joining Dr. Landefeld on panel one is Frederick 
Knickerbocker, the Associate Director for economic programs at 
the Census Bureau. Mr. Knickerbocker became the Associate 
Director for economic programs in 1995. As such, Mr. 
Knickerbocker is responsible for approximately 100 economic and 
business surveys as well as preparation of many of the Nation's 
principal economic indicators.
    Mr. Landefeld.

STATEMENTS OF J. STEVEN LANDEFELD, DIRECTOR, BUREAU OF ECONOMIC 
 ANALYSIS; AND FREDERICK KNICKERBOCKER, ASSOCIATE DIRECTOR FOR 
            ECONOMIC PROGRAMS, BUREAU OF THE CENSUS

    Mr. Landefeld. Thank you, Mr. Chairman. Also thank you for 
doing a good part of my testimony today. I was just able to cut 
out a whole bunch of things I was going to say. But I did want 
to thank you for the opportunity to appear before you to 
discuss the Bureau of Economic Analysis. As you and the Census 
Subcommittee know, and as you indicated, Mr. Chairman, we are 
the other statistical bureau in the Commerce Department. 
Although we are small in size relative to our sister agency 
Census--our staff is about 400 people now, not 450-something--
we are, as you noted, one of the Nation's most important 
statistical agencies. Our signature products are the GDP and 
the national income and product accounts, which were developed 
in the late 1930's by the Nobel Laureate, Simon Kuznets, and 
which are regarded as the mainstay for analyzing the U.S. 
economy.
    Although you reviewed a number of functions, I thought it 
would be useful to describe how we do what we do, which is, in 
essence, we are the Nation's economic accountant. That is, we 
obtain and interpret large volumes of diverse data from both 
government and private sources, such as the Census Bureau and 
then organize, combine and transform these data into a 
consistent and comprehensive set of economic accounts for the 
Nation as a whole. BEA's accounts provide a full detailed 
picture of economic activity and include such widely watched 
statistics as GDP, corporate profits and some of the other 
series you have noted. These data have a large impact on 
interest rates, stock prices and exchange rates and are vital 
ingredients for public policy and business planning and 
investment decisions. As a result, they affect every American 
who runs a business, saves for retirement or takes out a 
mortgage.
    In your wonderful summary, there was one area I noted that 
was not mentioned--and it certainly does deserve mention, 
especially as people worry about the new economy,--which is our 
industry accounts. In addition to our national, regional and 
international accounts you described, we have industry 
accounts, which include gross product by industry, which 
measures the contribution of private industry and government to 
GDP, and the input-output tables, which show the linkages 
between industries. These data are important because they 
provide policymakers and business planners with critical 
information to assess such issues as the impact of taxes in a 
particular industry on other industries or the indirect impact 
of growth in one industry on other industries.
    I will now turn to one of the major topics you asked us to 
discuss today, which is the accuracy of BEA's estimates. 
Although our estimates of GDP and related measures are regarded 
among the most accurate and timely in the world, they are not 
without error. In order to provide timely estimates within 1 
month of the end of the quarter, BEA must use partial data and 
estimate missing source data in inventories, merchandise trade, 
things of that sort. As more complete and accurate source data 
become available in the following months, BEA revises the 
estimates. In general, one finds that BEA's early GDP estimates 
do a relatively good job of providing a general picture of 
economic activity. In particular, the estimates can generally 
tell you if the economy is expanding or contracting, something 
of relevance right now; if growth is accelerating or 
decelerating; if growth is high, average or low relative to 
trend; what components of the U.S. economy are the main sources 
of growth--consumer spending, investment spending, 
inventories--or what is going on; what the general trend and 
patterns are for key variables such as investment, saving 
rates, or government share of GDP; and the timing of components 
contributing to recessions and economic expansions. Where the 
estimates have been subject to greater uncertainty is in the 
measurement of longer-term growth rates.
    Unfortunately in recent years, there has been a persistent 
difference between growth as measured by production, or GDP, 
and growth as measured by the incomes earned in production, or 
gross domestic income. In concept, the two measures should be 
equal, but in recent years the income measure has been growing 
at a 4.9 percent annual rate while growth as measured by the 
product side has grown at a 4\1/2\ percent annual rate, a 0.4 
percentage point difference.
    While there has always been uncertainty about trend growth 
in the economy, the difference between the two measures is not 
only larger than in the past, but the impact of such a 
discrepancy seems to have a larger pocketbook effect. The 
larger effect is due to the importance of BEA's estimates for 
long-term budget projections and the reliance on BEA data for 
the allocation of Federal funds to State and local governments.
    The discrepancy also has had a larger effect on the economy 
because of the increasing impact of BEA's data on financial and 
foreign exchange markets. The impact of BEA's data on these 
markets is more widely felt than in the past because almost 
half of U.S. households now hold stock in one form or another, 
an increasing share of loans are indexed, and with the 
globalization of the U.S. economy, an increasing share of 
businesses and households are affected by exchange rates.
    In my written testimony, I focus on three examples of 
challenges that BEA confronts in keeping up with the rapidly 
changing economy. The first example deals with measuring GDP as 
we move from an industrial economy to the new economy. The 
second example deals with measuring the balance payments, which 
as highlighted by the Trade Deficit Review Commission has 
become increasingly difficult because of rapid changes in size 
and complexity of international trade and financial 
transactions. And the third is the need to better explain the 
sources of the precipitous decline in the U.S. personal saving 
rate through an integrated statistical treatment that focuses 
on the impact of changes in the stock market and household 
finances on personal savings. However, in the interest of time, 
I will discuss just the first of these examples, the challenges 
in measuring GDP.
    One of the most difficult issues confronting public and 
private decisionmakers is the uncertainty over the rates of 
inflation and growth in the U.S. economy over the last 5 years 
and their likely rates of change over the next 5 to 10 years. 
BEA has had difficulty in keeping up with the changing economy, 
and as I noted, errors have been creeping into BEA's measures 
of trend growth in real GDP, incomes and inflation. Upward 
visions in estimated tax receipts, or the ``tax surprises'' 
seen in recent years, have been, in part, the result of a 
pattern of upward revisions in BEA estimates. BEA estimates are 
an important factor in policy decisions that have a lasting 
impact on the economy. Not only do BEA's estimates form the 
baseline for the projections, but most long-term projections 
assume that future growth will resemble the recent trends 
published by BEA.
    As Federal Reserve Board Chairman Alan Greenspan noted in a 
recent speech, the biggest payoffs in efforts to improve 
economic forecasts are likely to come from raising the quality 
of data collected rather than improving forecasting techniques. 
Small errors in real GDP can have such a large impact on long-
term budget projections that they can swamp differences in 
proposed policy initiatives. Understatement of the growth rate 
of real GDP associated with a given rate of inflation may lead 
monetary policy officials to understate the rate of growth that 
can be sustained without sparking higher inflation. Business 
planners are also affected as they try to determine whether the 
performance of the economy over the last 5 years is real and 
permanent, the so-called ``new economy.''
    BEA has worked hard in recent years to keep up to date with 
the rapidly changing economy. Using resources made available at 
BEA by eliminating programs, such as the leading indicators, 
and utilizing improved data developed by BEA and its source 
data agencies, the Bureau has been able to make a number of 
advances. These include new price and output indexes that 
better measure things such as banking services, cell phones, 
computer software and the Internet. These accomplishments 
notwithstanding, scarce resources and gaps in the source data 
have prevented us from fully keeping up with changes in the 
economy. The remaining gaps have a direct impact in the quality 
of estimates. They include, first, for over 20 percent of real 
GDP, mainly in services, there are no price indexes to produce 
inflation-adjusted estimates, and the estimates are based on 
measures of physical inputs and outputs or cost-based deflators 
resulting in an understatement of GDP and productivity growth 
and an overestimate of inflation for these components.
    Second, for 20 percent of nominal GDP, also in services, 
BEA has developed estimates using a broad range of source data 
that differ significantly in coverage, concept, level of 
detail, classification and timing. These inconsistencies 
contribute to our persistent inability to keep up with changes 
in this rapidly growing sector.
    Third, the source data used in BEA's quarterly estimates 
focus on the old industrial economy and cover only the wages 
and salaries of production and nonsupervisory workers, thereby 
missing over 40 percent of compensation in the U.S. BEA must 
estimate the wages and salaries of these missing supervisory 
and professional workers and estimate the impact of stock 
options, in-kind benefits and other new forms of compensation 
using a patchwork of partial data.
    And finally, BEA lacks quality-adjusted price indexes for a 
number of key products in telecommunications and other IT 
areas, resulting in an understatement of real GDP and an 
overstatement of inflation.
    In summary, while BEA is doing a good job of measuring 
today's economy, significant challenges remain. Discussing the 
problems that new technologies and changes in the structure of 
output pose for the measurement of GDP, Chairman Greenspan 
recently noted, ``Certainly statistical systems in the United 
States, both public and private are world class, and indeed, in 
many respects, set the world standard. But given the rapidly 
changing economic structure, one could readily argue that more 
statistical resources need to be applied to understanding the 
complexities of the newer technologies that confront 
analysts.''
    In the current fiscal year, BEA received its first real 
increase in funding in nearly 8 years. The President's budget 
blueprint for fiscal year 2002 proposes a $9 million, or 18 
percent, increase in BEA's budget to extend the work begun in 
fiscal year 2001. These funds would enable BEA to begin to fill 
the gaps in BEA's estimates outlined above by developing new 
price and output indexes for services and high-tech products, 
new measures of compensation that measure the stock options and 
rapidly growing forms of compensation that I mentioned, updated 
measures of international trade and finance and integrated 
measures of change in the real and financial economy.
    Second and equally important, it would help us to upgrade 
BEA's IT infrastructure so as to raise the efficiency and 
accuracy of BEA's estimates, upgrade BEA's ability to 
disseminate its data to its customers, and introduce electronic 
reporting to reduce the respondent burden on the 40,000 
companies reporting on BEA's surveys.
    Thank you, Mr. Chairman, for this opportunity.
    [The prepared statement of Mr. Landefeld follows:]

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    Mr. Miller. Thank you. We will proceed with Mr. 
Knickerbocker. And everybody's written statement will be 
included in the record. You may proceed.
    Mr. Knickerbocker. Mr. Chairman, thank you for the 
opportunity to participate in today's hearing on the activities 
of the Bureau of Economic Analysis and the challenges BEA 
faces. We in the economic programs part of the Census Bureau 
collaborate with BEA in many different ways and very 
frequently. While the data we collect are used by practically 
all Federal agencies and are closely monitored by the Federal 
Reserve Board, we regard BEA as our most important government 
customer. A high proportion of all the data we collect serves 
as source data for BEA. We are the principal source of the data 
BEA uses to develop its product side estimates of the gross 
domestic product.
    Close collaboration between BEA and the Census Bureau means 
that the two agencies share a common view of the most promising 
opportunities for the improvement of economic statistics.
    Two examples of how basic data are organized illustrate 
this point. First, until a few years ago, the Federal 
statistical system operated with an antiquated industry 
classification system, the 60-year-old Standard Industrial 
Classification system. In the last decade, a team established 
by the Office of Management and Budget of Federal statistical 
agencies designed a new, up-to-date and flexible industry 
classification system. The result, it is called the North 
American Industry Classification System, provides statistics, 
profiling the American economy as it enters the 21st century, 
not as it was at the time of World War II. The Census Bureau, 
in cooperation with BEA and Bureau of Labor Statistics has led 
the effort to introduce the new classification industry system 
into Federal economic statistics.
    Second, while the updating of the industrial classification 
system represents a significant step forward, more needs to be 
done. Firms and manufacturing industries make quite specific 
products. Firms in service industries deliver quite specific 
services. To generate the statistics that will support analyses 
of many economic policy issues, for example, the sources of 
productivity growth in the economy--data at the detailed 
product level are required. This is especially true for 
services where measuring the output of service providers is 
particularly difficult. The Census Bureau, again, in 
collaboration of BEA and the Bureau of Labor Statistics, is 
developing a product classification system that will provide 
the framework for the collection of substantially more product 
level data then has been available in the past. The collection 
task will fall to the Census Bureau. The task of putting the 
more abundant data to work will fall to BEA.
    Of late, officials at BEA has devoted much time to 
measuring, describing and putting into perspective the new 
economy. The one feature of the new economy that has attracted 
much attention is E-business. The Census Bureau has pioneered 
the collection of official statistics on E-business starting in 
late 1999 with a collection of quarterly data on retail sales 
over the Internet. This was followed by collecting annual data 
on E-commerce activity in the manufacturing, retail, wholesale 
and services sector. Detailed data on the E-businesses 
processes used in manufacturing plants were collected at the 
same time. The results of these collections have been released 
in recent weeks with more results scheduled for release in May.
    Our efforts at collecting data on E-business are in their 
early stages. Still, our early efforts will give BEA some 
baseline statistics from which it can develop its own measures 
on the role of E-business in the economy. Looking forward, the 
Census Bureau believes it can contribute to further 
understanding of E-business by enhancing its collection of data 
on business purchases of information, technology hardware and 
software, the infrastructure of E-business.
    Currently, the Census Bureau captures much of its data on 
business expenditures for plant equipment through the Annual 
Capital Expenditures Survey. Without too much change, we 
believe this survey can be modified to pick up more specific 
data on E-business infrastructure, an advance that should help 
BEA perfect in its own investment statistics, a key element in 
GDP, and these improvements in investment statistics would 
certainly be welcomed by private industry.
    Another feature of the new economy where BEA and the Census 
Bureau have a common interest is in the increasing reliance by 
business on leasing. Once upon a time, companies bought their 
plants and bought the equipment they put in the plants. Once 
upon a time, companies hired the workers that worked in the 
plants. The company, its assets and its work force were all 
under the same control. That simple world made it relatively 
easy to collect data for a company and its operations. Now more 
and more companies are leasing their assets and leasing their 
employees.
    These changes generate questions that make collecting data 
more difficult. For example, who owns the assets? For example, 
who is the employer of record for the employee? These and many, 
many other sorts of questions are those that have to be 
resolved by the Census Bureau to produce good data. The Census 
Bureau is devoting substantial attention to developing 
strategies to cope with leasing in its data collection efforts. 
To the extent that we are successful, we should be able to give 
BEA better data to factor this new business practice into its 
picture of the economy.
    At the Census Bureau, we also collect data via information 
technology, and this approach has direct consequences for the 
completeness and quality of the data we provide to BEA. For 
close to a decade, we have collected some data through early 
stage electronic means, but now we hope to take the next 
obvious step, that is to say, offering the opportunity to 
report over the Internet to the 5 million companies that we 
will contact directly in the 2002 economic Census.
    From experience, we know that electronic collection of data 
pays off. For example, an increasing proportion of the data 
required to be filed with the government at the time goods are 
exported is now filed over electronic networks. About 50 
percent of the paper documents, the paper documents that were 
filed at the time of exporting, contained at least one error. 
Today, the error rate for documents filed electronically runs 
at 5 percent. The Census Bureau devotes substantial energy to 
inspecting and correcting incoming data to assure the accuracy 
of the data we release. Clearly, the cleaner the incoming data 
we receive, the more we will be able to concentrate our efforts 
to correcting the most troublesome data and the happier our 
customers, including BEA, will be.
    Finally, Mr. Chairman, there are some data projects that 
the Census Bureau will work on as we gain in the productivity 
of our programs. The projects would make the data that the 
Census Bureau provides to BEA more useful. I have in mind 
improved data on nonmerchant wholesalers, broader coverage of 
service sector industries, more timely data on capital 
expenditures by State and local governments, and more accurate 
valuation of export statistics.
    Mr. Chairman, that concludes my testimony. I thank you for 
this opportunity to appear before you.
    [The prepared statement of Mr. Knickerbocker follows:]

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    Mr. Miller. I thank you both for your statements, and I 
appreciate you being here giving us a chance to talk about 
this. I'm sorry some of my colleagues--because we adjourned 
yesterday afternoon--have left town already. Let me start off, 
first of all, about data collection and the quality of the 
data. You say you use 5 million, you mention 5 million 
businesses will be in next year's----
    Mr. Knickerbocker. The Economic Census, sir, is conducted 
every 5 years. It is conducted for the years ending in 2 and 7. 
At the time of the Economic Census, we collect data from 22 
million business locations in the United States. We collect 
data on between 15 and 16 million business locations basically 
through extracting certain data from tax records. We also 
contact firms directly. By ``contact directly,'' we send out 
questionnaires and/or we will deliver Internet questionnaires 
to between 5 and 6 million companies. So that was the 5 that I 
was referring to.
    Mr. Miller. How about small business versus large business 
as the cooperation and the quality of data. Small business is a 
significant portion of our economy, of course, and the growth 
of our economy, too. What is the challenge of small business 
data collection?
    Mr. Knickerbocker. That is one of the reasons that we make 
such extensive use of tax records. Tax records give us the 
name, the location, the nature of the activity and the revenue 
of the business. And then to flesh out detail on small 
businesses, we send out samples, let us say, of 60,000 firms, 
in particular categories of small businesses to get the 
details, like the typical purchase patterns of business, the 
typical customer, and things like that.
    So our first line of activity is basically to send as few 
questionnaires as possible to small business, to try to use 
what we refer to as administrative record, tax records, as an 
alternative source of data simply so that we don't have to 
pester small business persons. Then we use, as I say, sampling 
techniques to gather a rich sense of some of the subsidiary 
details of the small business.
    Mr. Miller. What about the monthly quarterly data? You 
don't use IRS data for that?
    Mr. Knickerbocker. No. Once every 5 years.
    Mr. Miller. Let switch over now to the monthly quarterly 
annual data, the sources of that data, say, for small business. 
How do you collect that data?
    Mr. Knickerbocker. We do not collect data on small 
businesses per se. We include small businesses in our samples, 
for example, our monthly collection of data on manufacturing or 
retail sales or wholesale, and in those cases, our sample 
frames are built up to reflect the composition of those 
industries, the number of small, medium and large size firms 
incorporated in those sample frames, pro rata in their shares 
of activity.
    Mr. Miller. How about underground economy? The nonreported 
income. Is that changing much in this country?
    Mr. Knickerbocker. I would have to defer to my colleague to 
the right because they have, for 10 or 15 years, been the most 
venturesome in trying to come to grips with that very difficult 
problem.
    Mr. Miller. Mr. Landefeld.
    Mr. Landefeld. By the way, I would say one thing about the 
small businesses. In days gone by, when I first started in 
statistics, you know you could collect a lot of dollars for the 
economy by going to three major auto companies. But when you 
begin to talk about things like auto repair services and other 
services, it is much more expensive in terms of number of 
firms. You have to survey to get that, which I think is one of 
the reasons why we still lack data, so intensively, as I said, 
in the services sector. For both the Census and BLS, those tend 
to be sectors that are hard to measure and part of the reason 
why they are not in our regular source data.
    With respect to the underground economy, what we generally 
do is try to measure just the portion of it which is not 
reported to the IRS authorities. That is one of our major data 
sources. So we use various data to estimate that. For example, 
proprietors' income, according to the last taxpayer compliance 
measurement program, which unfortunately is also known as the 
``tax audits from hell'' program, which was abolished by the 
Congress, but that was our last read on it. For every dollar 
proprietors reported to the IRS, there was another dollar they 
did not report.
    So we carry forward a lot of those incomes that are 
underground or simply not reported to the IRS in our estimates. 
And we currently have no estimate of that, and one would think 
that with the increasing reporting of everything from video 
store receipts, etc., that would have some impact on 
compliance. So that raises a lot----
    Mr. Miller. So those tax audits from hell were a good 
source of information for you that you are going to be lacking. 
So that was your source of----
    Mr. Landefeld. Right. Because the only way you can really 
find out that information is through a lifestyle audit, that is 
to find out if the person's receipts were far more than they 
reported.
    Mr. Miller. Talk about this sharing of data, and I know 
when we went through the whole issue of the decennial census, 
and the confidentiality of the data is absolutely crucial, as 
the Census Bureau believes, for the participation in the 
decennial. How much data sharing occurs now and how much needs 
to be made additional, and comment about that. A couple people 
mentioned data sharing in their statements, and then any impact 
that would have on the ability to collect accurate data.
    Mr. Landefeld. Perhaps I can comment first. From our 
viewpoint, where we are integrating all this data, it would be 
tremendously important because if you look at the data, for 
example, from the Bureau of Labor Statistics, which collects 
its own data and doesn't share it with the Census Bureau, 
versus the Census for the very same industry, same time period, 
significant differences in things such as sales and employment 
occur in those industries. As we try to piece together our 
picture of the economy, because most of our measures on one 
side are based on income, the other based on Census type data, 
we have very large problems in trying to integrate those 
various data sources, and it would go a long way toward solving 
many of the problems, including the discrepancies in the growth 
rate on the two sides and a number of issues we confront.
    Mr. Miller. What sources of data would you want to share? 
Does the IRS share as much as you want to share? Whether they 
should or not is another question.
    Mr. Landefeld. I think the first piece of information we 
would be interested in having shared would be the Census data 
and the BLS data, which are integral to our input and output, 
our national accounts, because we get different reads based on 
that data. And by looking inside it and seeing how companies 
are differently classified or what the differences in reporting 
are, we believe we could fix a lot of problems in our 
estimates. I mentioned that discrepancy where we have an income 
measure growing at 4.9 percent and a product-side measure 
growing at 4\1/2\, which causes no end of problems for 
forecasts. Those are the kind of things we would hope to be 
able to address. IRS data, we only can look at it selectively 
for corporate profit returns. Census can look at it more 
broadly than we can.
    Mr. Knickerbocker. We at the Census Bureau have been in 
support of the concept of data sharing. There have been, as I 
am sure you know, several bills introduced to effect that in 
the last several sessions and we have been quite supportive of 
that. The classic example would be that we at the Census Bureau 
maintain a business register of essentially every business 
place, the basic facts on every business place in the United 
States. At BLS they maintain a business register. Each of these 
are complicated files of 7 or 8 million firms with are all 
sorts of data on those. These are two parallel registers. To be 
sure, they do serve somewhat different purposes. I don't think 
if we had data sharing we could simply shut down one of the two 
registers, but I think there is no question but that there 
could be significant efficiencies gained in terms of how these 
two registers would go on because there is certainly some 
proportion of duplication right now.
    So I cite that as an obvious example of some of the gains 
from data sharing. We think that the quality of samples could 
be improved. That is to simply say by sharing information one 
could get an additional data point or two incorporated in our 
data that would help us generate better samples and, vice 
versa, for the agency to whom we might supply data. We should 
be able to quit asking companies the same data, the same 
questions, over and over again. Every questionnaire that goes 
outs requires the respondent to give us the name of the 
company, the location of the company, its EIN, plus five or six 
basic facts. How many times does the company have to keep 
saying the same thing over and over again? There ought to be 
one repository in government that has all the basic facts on 
companies, eliminating repetitive requests for data.
    I would make this point, sir. We are very attracted to data 
sharing. We should, however, mention IRS. Practically all the 
data that the Census Bureau has--I should say the economic 
program has on businesses is either directly or indirectly 
derivative of certain IRS records and/or there is some IRS 
content in those records. IRS, I think for perfectly 
understandable reasons, has concerns about sharing, meaning 
that it takes a much more restrictive view toward the sharing 
of records than we do.
    So here is a consideration should Congress pass data 
sharing. My point is that Congress is going to have to 
confront, to find some way to conform IRS regulations to data 
sharing if data sharing is to be as fruitful as it might 
otherwise be.
    Mr. Miller. I guess it is also true with Census data that 
other agencies want to use to project into the future. Did you 
want to add something else?
    Mr. Landefeld. I will add an example. Congress once passed 
a piece of legislation that allowed BEA, BLS and Census to 
share data on foreign direct investment, and as a result of 
that sharing we were able to go, using our enterprise and their 
establishment data sets, from having data by State for 66 
industries to over 500 industries, a creation of a huge data 
set on foreign direct investment with no additional respondent 
burden, very little cost to the agencies overall. And that is 
one example of the type of advantage you can get out of sharing 
this kind of data.
    Mr. Miller. You are familiar with the American Community 
Survey. If it replaces the long form, it will be done on an 
annual basis. What impact will that have on your data?
    Mr. Landefeld. We mainly use that type of information on 
our regional accounts, and it is our hope that with that 
regular ongoing surveying that will go on as part of the 
American Community Survey--I must say I am no expert at all on 
this subject--but that regular surveying of larger geographic 
areas, we think we will be able to get much better, up-to-date 
types of information which we use in allocating data to the 
regions, States, municipalities in the United States.
    Mr. Miller. One of the things about data is the timeliness 
of the data, as you know there was a discussion with Mr. 
Greenspan, about how fast he can react and how accurate the 
data is and you come up with the best estimates you can and 
then you revise them. In our next panel I would like to talk 
about this, as well, is what happened in the 1990 recession 
period and the data and how the data changed. Would you comment 
about that? I know we are going through economic times now that 
Mr. Greenspan wants accurate data.
    Mr. Landefeld. One hates to extrapolate from that one 
episode. For most of the postwar period we have done a pretty 
good job, but that is indeed one of the misses we had in terms 
of the particular timing of that business cycle. We did show a 
turndown at that time, a slowdown in economic activity--but not 
nearly the decline that we had then. And I think that is 
somewhat worrisome because as I look right now, for example, at 
the data, one of the most important components of our estimates 
that is helping to hold up the economy in the current period is 
investment in computer software. And while the annual data on 
that are pretty good, I do worry about the quality, and we are 
working to try to improve the quality of the quarterly 
estimate. If the slowdown we saw in computers were also 
reflected in software, we would have seen several tenths at 
least taken off the real GDP growth rate in the last quarter, 
which I think psychologically would have been important because 
it would have put us below 1 percent growth rate in our 
estimates of the slowdown.
    So there are a number of components of that sort and 
services in many of the industries I have mentioned where we 
are using very crude extrapolators for a lot of components that 
are either new economy or in services. And that does worry you 
because it is only when we get the annual surveys, and in the 
case of many of those services only once every 5 years do we 
get data on all service industries as part of the quinquennial 
census. So there is an awful lot of extrapolation going on with 
all kinds of partial data that does worry you in terms of our 
ability to capture the timing changes in the U.S. economy.
    Mr. Miller. We had the problem with the CPI and the market 
basket problem and adjusting to that with the new economy, and 
they are making the adjustments and proceeding. You mention 
about changes taking place. Are you able to adjust quickly 
enough to changes in the economy? We are going through this 
change and I think Mr. Greenspan said we are perhaps 25 percent 
through this technology revolution. And I don't know whether we 
are at 50 percent or 10 percent or 75 percent, but obviously 
there are many changes going on. Are you able to quickly 
react--I shouldn't say quickly, but react properly to that type 
of change? As you say, there are new industries new products, 
everything.
    Mr. Landefeld. I don't mean to be a two-handed economist, 
but the answer is yes and no. We were one of the leaders in 
developing price indices and quantity indices where the weights 
changed every quarter, eliminating some of the biases that were 
and are now being addressed in the CPI. So with respect to that 
the Bureau was one of the leaders, and it actually eliminated a 
very large bias in real GDP. That was much larger than the bias 
we all heard about in the Consumer Price Index.
    So on that score the answer is yes, but in a very important 
way the answer is no, because for a lot of high-tech products 
and services that use high-tech products--insurance, the 
securities industry, the data we are using are those that I 
described as input-based or output-based estimates. And as a 
result, if we count output based on input, we get zero 
productivity growth by design and understate the rate of growth 
in real GDP in that industry and also overstate inflation in 
those industries. So we still have serious problems in keeping 
up with changes in the economy and high-tech sectors. We don't 
have quality-adjusted prices for local area networks and all 
kinds of things of that sort. We are working very hard at 
developing, as I mentioned in terms of cell phones and others, 
but an awful lot of work remains. The President of the American 
Economic Association, Dale Jorgenson, has made this point in a 
number of his papers in assessing the new economy, that a major 
part of the problem in assessing the new economy is the fact 
that there are so many sectors that are major users of IT and 
also products that are produced that are high-tech that are not 
appropriately measured, and that tends to bias the results one 
gets in looking at the, ``new economy.''
    Mr. Knickerbocker. If I could speak to that point. I 
mentioned in my testimony about e-business. Certainly the 
concept of the Internet was known throughout all the 1990's, 
but really the Internet as a way of doing commerce really took 
off in 1998. By late 1999 we were, as I indicated, gathering at 
least the first sorts of data on activity over the Internet, 
retail sales over the Internet. Were we gathering data on day 
one when it became important to gather data on the Internet? 
No, but we gathered data on it within a year of the time when 
it surfaced as an important element in our economy.
    So we are in the lead in gathering data, and we are 
certainly very mindful of the task. We are also aware of 
changes in business practice and of our obligation to generate 
some data on them as quickly as possible.
    Mr. Miller. How much of a problem does making adjustments 
in your data over time cause you? And to the comparability of 
the data?
    Mr. Landefeld. That is a major concern as one compares 
current periods to past periods. We at the BEA have prided 
ourselves in keeping a nice consistent time series. Every time 
we do a revision we go back to 1929. But I must say it is 
getting more and more difficult to do. You can only extend the 
series back so far. That is a major part of our job. The Bureau 
of Labor Statistics just introduced a new price index for 
securities brokers and dealers at our request. Unfortunately, 
they only gave us 6 months of data because they are in the 
current process of estimating current prices, and we have got 
to work to extend those backward. But we are finding 
increasingly our ability to do so is limited.
    Thank goodness, some of these products did not exist in the 
past so you only have to extend it so far back. But there is 
the whole question that many academics have pointed out, Bob 
Gordon in particular of Northwestern, that there were a lot of 
innovations back then that we may not have fully captured the 
impact of. So there may be some things we are missing in the 
past. Some of the examples like computers are so egregious you 
had to do something with them. And I think that is what we have 
tried to address, that is the examples where we really 
absolutely must do something because the rate of decline in 
both the price per unit of computers and the quality-adjusted 
price is so large you have to estimate for that. But we are not 
about to go out trying to adjust every price that is out there.
    Mr. Miller. Looking down the road when you start projecting 
5, 10 years in to the future, right now there is a lot of 
debate about tax cuts 10 years in the future in Congress, as 
you know, and 10 years ago what was the projection? How far 
would you have been off 10 years ago, from 1991 to today? Maybe 
the next panel would be able to answer that.
    Mr. Landefeld. I really can't tell you. All I can say right 
now, and I think Dick Berner may address this and certainly Bob 
Dennis from CBO, but most rules of thumb say over 10-year 
forecasts about a 0.1 percentage point error in real GDP can 
produce errors in 10-year projections of $200 billion or more, 
depending on whose rules of thumb you are using, CBO or OMB. 
That is the reason the differences in the growth rate are so 
important. It is just one-tenth of 1 percentage point that has 
those kind of $200 billion effects over time. That is why we 
are particularly worried about this 0.4 percentage point 
discrepancy between our two measures of growth.
    Mr. Miller. One more last question, because we need to go 
on to the next panel. An area that I have a great interest in 
is what is going on in biotechnology. How do you plug that into 
longevity, life expectancy, I mean, revolutionizing--the impact 
on the economy, on trade?
    Mr. Landefeld. Gee, I am kind of boggled. We are having 
enough problems just measuring pharmaceutical prices.
    Mr. Miller. But that is the future.
    Mr. Landefeld. Clearly that is another form of information 
technology investment which is becoming increasingly important. 
Our first crack at this kind of thing was the capitalization of 
computer software, but it obviously influences the market 
valuation of firms, that kind of biotechnology. So it is 
something we can and should be measuring. It is on our long-
term agenda. I think there is a recent Brookings study on 
exactly this issue of what those kinds of things are worth and 
their market value. I think that study panel urges us to move 
forward on that, but I must say our current concerns are so 
large that is a little down the road for us.
    Mr. Knickerbocker. If I could add to that, sir. What Steve 
is saying is what I see is our greatest challenge. It is 
relatively easy to collect data on physical capital, bricks, 
buildings, equipment, things like that, but today horsepower is 
becoming less important and brain power is becoming more 
important. Human capital, intellectual capital, and how we 
measure human capital, which is the driving force in business 
today, explaining human capital and collecting the basic facts 
on human capital that has got to be the No. 1 challenge that we 
have before us.
    Mr. Miller. It affects trade data significantly, too, 
doesn't it? We are a major exporter of that.
    Mr. Knickerbocker. If we knew what our exports statistics 
were to the nearest 7 percent, we would be better off, sir.
    Mr. Miller. Let me thank you all. Do either of you want to 
make a concluding comment?
    Then we will move on to the next panel. It is a huge 
challenge you all have and you have got a great deal of 
credibility and respect. And I think the recognition that 
Congress finally gave you, an increase last year, and certainly 
my understanding is President Bush's budget will include a 
generous one next year, shows the recognition that we need to 
continue to work to improve, and it is an amazing challenge you 
have. So thank you all very much for being here. I look forward 
to working with you.
    Mr. Landefeld. Thank you, Mr. Chairman.
    Mr. Knickerbocker. Thank you, Mr. Chairman.
    Mr. Miller. We will take a second to allow you all to move 
and we will let the next panel have a seat.
    Welcome. Our second panel includes representatives of the 
Congressional Budget Office and industry associations who are 
active data users and advocates of the Federal statistical 
system. We have Bob Dennis, who is the Assistant Director of 
Macroeconomic Analysis of CBO, the primary source of budget 
information for Congress. Richards Berner is the current 
president of National Association of Business Economists, whose 
members have a vested interest in accurate and timely economic 
statistics. Diane Swonk is the chief economist and senior vice 
president for Bank One and the immediate past president of the 
NABE. Gordon Richard is an economist representing the 14,000 
member National Association of Manufacturers. And Professor 
Ernie Berndt joins us from MIT, Sloan School of Management. 
Professor Berndt also chairs an advisory committee to the 
Bureau of Economic Analysis, Bureau of Labor Statistics and the 
Census Bureau.
    I thank all of you for being here today. We will start with 
Mr. Dennis.

    STATEMENTS OF BOB DENNIS, CONGRESSIONAL BUDGET OFFICE, 
  ASSISTANT DIRECTOR, MACROECONOMIC ANALYSIS; RICHARD BERNER, 
PRESIDENT, NABE; DIANE SWONK, CHIEF ECONOMIST, BANK ONE, INC.; 
      GORDON RICHARDS, ECONOMIST, NATIONAL ASSOCIATION OF 
   MANUFACTURERS; AND DR. ERNST R. BERNDT, MIT, CHAIR OF THE 
         FEDERAL ECONOMIC STATISTICS ADVISORY COMMITTEE

    Mr. Dennis. Good afternoon, Mr. Chairman. Mr. Chairman and 
members of the subcommittee, I am pleased to be here today to 
discuss some of the major issues affecting the Bureau of 
Economic Analysis, which is the enormously respected keeper of 
the national income and product accounts. In my testimony I 
will focus on the crucial role that those accounts play in 
shaping public understanding of the U.S. economy and helping 
the Congressional Budget Office to construct its baseline 
budget projections. I will also note several ways in which 
BEA's data might be improved.
    It is not too much to say that the national income and 
product accounts are what make modern empirical macroeconomics 
possible. Those accounts are the organizing principle that 
enables us to see how the parts of the economy fit together. 
The accounts are also the foundation of CBO's economic 
forecast, which underlies the baseline budget projections that 
the Congress needs to do its work. We use those accounts both 
to track what has happened in the past and to ensure that our 
assumptions for the future are internally consistent.
    The economy of course does not stand still but keeps 
changing its structure. In the past decade, forecasters and 
analysts have had to cope with the sets of changes that have 
come to be called the new economy. And as we have heard, those 
changes have posed special challenges to the statisticians at 
BEA, who have done an excellent job of meeting them. However, 
CBO believes that some further progress can be made, and in my 
testimony I will suggest some areas for improvement. Many of 
those improvements would require changes in procedures not only 
at BEA but also at the agencies that provide BEA's source data.
    As we have heard, BEA is not by and large a data gathering 
agency but gets its data from the surveys and economic censuses 
at the Census Bureau, from the Bureau of Labor Statistics 
[BLS], from administrative records such as tabulations of the 
IRS, and from various private sources. Some data improvements 
may also require additional reporting by businesses. In those 
cases, of course, it would be necessary to assess any 
additional burdens that those requirements would impose, and we 
have not made any such assessments.
    Let me first briefly describe how CBO uses BEA data. Those 
data play a large role in CBO's budget projections because they 
provide the foundation of the economic projections, which in 
turn underlie both the revenue and outlay projections. BEA 
data, along with data from BLS or the Bureau of the Census, are 
the key supply-side inputs used to explain economic growth.
    Besides contributing to CBO's economic projections, BEA 
data also helps more directly in CBO's projections of revenues. 
Revenues are sensitive to the distribution of national income 
between wages and salaries and corporate profits. BEA provides 
measures of those incomes, and CBO projects those measures 
forward as part of its overall economic projections. BEA's 
estimates of the capital stock, moreover, which determine how 
much corporate income must be assigned to depreciation, also 
have an important influence on the relationship between output 
and revenues.
    Now let me turn briefly to the challenges of the new 
economy for forecasters and statisticians. What people mean by 
the new economy is a complex of developments, particularly over 
the last decade, including rapidly falling costs for 
information technology [IT] and consequently for information 
itself, changes in the organization of production as firms take 
advantage of the lower cost of information, and the 
proliferation of new companies doing new things, which are 
always among the hardest to track.
    To understand what is happening, forecasters need a 
statistical system that can keep pace with the changes in the 
economy. One of the main tasks of the statistical system is to 
separate economic growth into the share that reflects price 
changes and the remaining share, which reflects the real growth 
of the economy. Developing good price indexes is often 
difficult, however. The quality of most goods and services 
changes over time, and price indexes must take those changes 
into account.
    For example, even though a computer now may sell for 
roughly the same price as a computer last year, few people 
would be happy to purchase last year's model rather than this 
year's. The same number of dollars this year buys vastly more 
computing power than it did last year, and that improvement in 
quality has to be reflected in the price index. BEA has led the 
way in improving estimates of the contribution of computers. 
The estimates are often rough, but they are generally 
preferable to ignoring all of the available information about 
changes in quality.
    Nevertheless, there are still important areas where further 
improvements in the measurement of prices and quality could 
greatly improve our understanding of the new economy. One such 
area is communications equipment. According to a forthcoming 
CBO analysis, the lack of good quality adjustments for that 
same equipment may have resulted in an underestimate of real 
investment growth of about 0.6 percentage points per year, on 
average, between 1996 and 2000.
    There are also places outside the IT sector where current 
techniques could represent what is going on in the economy. For 
example--this has already been mentioned--two Federal Reserve 
economists found that reported productivity growth in many 
service industries was persistently negative between 1977 and 
1999, even though firms in the industries remained profitable. 
They found that if they replaced those unexpected negative 
productivity growth rates for several service industries with 
an estimate of zero, the overall productivity growth would then 
be reported about 0.3 percentage points higher. That is overall 
productivity growth.
    Finally, let me mention a couple of ways in which the 
statistical system could be even more helpful to CBO in doing 
its economic and revenue projections.
    First, we could use better and more current estimates of 
wages and salaries under withheld income and payroll taxes. 
Steve Landefeld mentioned the problem of data on supervisory 
and professional employees. Other problems arise from the 
exercise of certain stock options, which ought to be part of 
wages and salaries but which are not currently captured by any 
government statistics. The lack of data on stock options 
distorts our understanding both of the growth of wages and of 
tax trends. We understand that BEA is investigating ways to 
improve those data, and we look forward to its results.
    Second, contemporaneous information on the sources of 
withheld tax payments would be very helpful to CBO as well as 
to BEA. Employers are not asked to report contemporaneously on 
how much of the tax they withhold is due to payroll taxes, even 
though they have to calculate payroll taxes and income taxes 
separately in order to know how much to remit. As a result, BEA 
and tax analysts have to make do for more than a year with 
estimates of that split, which complicates the tracking of tax 
credits. Technological advances, however, may have made it 
cheaper for businesses to give us those data in real time.
    I have some additional discussions of these suggestions and 
others in my written testimony. BEA is already working on most 
of them, and indeed it has a much better and more comprehensive 
list than we do.
    I would just like finish with the following thought. The 
new economy poses severe problems for national income 
statisticians, but it may also offer an opportunity. The IT 
revolution has lowered the cost of information, and that is 
having dramatic effects on the way businesses produce and use 
information. The IT revolution also offers the opportunity for 
government statisticians to gather more useful data without 
intruding into or imposing excessive burdens on private 
business.
    Mr. Chairman, I will be glad to answer any questions.
    [The prepared statement of Mr. Dennis follows:]

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    Mr. Miller. Thank you.
    Mr. Berner.
    Mr. Berner. Mr. Chairman, thank you for this opportunity to 
appear before you. Today I am here in my role as president, as 
you indicated, of the National Association for Business 
Economics [NABE]. We are a professional organization for people 
who use economics in their work, and our mission is to provide 
leadership in the use and understanding of economics.
    As you have heard from some of the other people in this 
room, the national income and products accounts are really 
critical for evaluating the forecasting and understanding the 
U.S. economy. And I just want to leave you with the point that 
from our perspective it is essential that these data faithfully 
portray the rhythm of economic activity as well as the separate 
parts of a very complex $10 trillion economy. As Bob Dennis has 
noted and as Steve Landefeld also noted, these data are 
essential for your policy deliberations, particularly with 
regard to the budget. Steve and Bob have talked about some of 
the improvements that have been made in our Federal statistical 
infrastructure as they are used by BEA.
    I want to emphasize the fact that, as has already been 
said, our economy is constantly changing. The industrial 
economy of the past has given way to the very different 
knowledge-based information economy, and that constant 
evolution obviously requires both new sources of data and 
resources for agencies to collect and analyze them. While our 
statistics remain among the best in the world, lack of 
investment in our infrastructure has left us with a system that 
still does a better job of measuring infrastructure activity 
than information-based output.
    The new data initiatives that have already been discussed 
cover services and high tech industries more comprehensively 
and more accurately than only 4 years ago, yet major gaps 
remain. The most important industry in some statistical tables 
is still the one labeled ``all other.'' While BEA makes every 
effort to ensure that its four major set of accounts, national, 
industry, regional and international, tell consistent stories, 
holes in the data often make that impossible.
    Steve did not tell you, I don't think, that statisticians 
must estimate from a patchwork quilt source data roughly 20 
percent of the GDP. Moreover, it has been discussed already 
that data on prices that enable us to separate inflation from 
real growth are often lacking. Steve did mention the software 
investment is one area where he has incomplete data and where 
he has to make estimates. At my firm, Morgan Stanley, we have 
surveys of businesses that may tell a somewhat different story 
from the extrapolations that the BEA has to make.
    Now, here is the punch line: More and better data obviously 
require more funding. And you have heard that before. I want to 
tell you that business people and policymakers increasingly 
recognize that funding improved statistics in general, and the 
GDP accounts in particular will pay huge dividends. My friend 
to my right, predecessor as NABE president, Diane Swonk, will 
recount for you in a moment the broad support that these 
efforts have in the business community.
    For his part, Fed Chairman Greenspan also supported that in 
his comments last week.
    You asked a question just a moment ago about biotechnology. 
Fed Chairman Greenspan indirectly addressed that by asking 
whether or not when we consider the cost of medical procedures, 
how we should measure prices of those procedures given the 
advances in technology that have been made. And that is a 
question that Director Landefeld, Nick Knickerbocker, and 
others in our agencies will have to grapple with.
    Personally, we agree with Fed Chairman Greenspan that 
greater payoffs will probably come from better data than from 
more technique and so does our membership at NABE. Our members 
recognize the importance of funding constraints on enhanced 
data gathering. That fits our longstanding support for 
maintaining fiscal discipline. Our members consistently 
supported moving to a balanced budget since we began polling 
them on policy issues 25 years ago. However, we also recognize 
that the costs of incomplete and inaccurate information far 
exceed the combined budgets of our major statistical agencies.
    In a survey published just last week, 70 percent of NABE 
respondents favored increasing spending on economics 
statistics. They ranked such increases first among seven 
alternatives for increased Federal spending including education 
and infrastructure. Don't get us wrong, those are important. 
But these investments will pay huge dividends. That is not 
surprising. We have long been concerned about improving the 
quality and timeliness of these data. In 1985, NABE created a 
statistics committee, chartered to work for the improvement of 
the national statistical system. Along with Chairman Greenspan, 
we supported efforts to reduce bias in the consumer price 
index. And working closely with the Council of Economic 
Advisors, the committee developed recommendations for data 
improvement.
    I would add, Mr. Chairman, that we would welcome the 
opportunity to work with you toward that end.
    NABE believes that our national data collection efforts 
should be as efficient as possible. You will hear from me and 
others that toward that end we believe that Congress should 
mandate data sharing among the agencies solely for statistical 
purposes. As you know, confidentiality statutes that permit 
data to be seen only by the employees of a single agency 
present a formidable barrier to effective working relationships 
among the agencies. They virtually guarantee duplication of 
efforts and inconsistencies among related data sets that you 
have already heard about. Moreover they deny, in effect, 
agencies' resources from undertaking new analyses that could 
improve the information available to policymakers. This is not 
a cost-effective way to run any business--either public or 
private.
    Federal statistical agencies and others such as the Federal 
Reserve are already cooperating in several ways to improve our 
statistical infrastructure. But I believe that permitting data 
sharing would take that cooperation to a new level. 
Consequently NABE supports reintroduction of the Statistical 
Efficiency Act of 1999. It was passed unanimously by the House. 
This legislation would permit exchange of statistical 
information under specific statutory controls. In summary, Mr. 
Chairman, NABE supports enhanced funding for improved economics 
statistics; and we also support the efficient use of those 
funds through data sharing among Federal agencies. I would be 
happy to answer any questions you may have.
    Mr. Miller. Thank you.
    [The prepared statement of Mr. Berner follows:]

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    Mr. Miller. Diane Swonk, please.
    Ms. Swonk. Thank you for allowing me to speak on something 
that is so close and dear to my heart given the work that both 
Dick and I did last year to try to get people to recognize the 
issue on the U.S. statistical agencies and the funding that 
they need. I commend their efforts to try to improve the data 
in what was a harsh funding environment for so long. I am just 
going to provide some summary comments from my remarks as you 
already have them on file. And I am dyslexic so I am really bad 
at reading them any ways. Dyslexic economists are kind of 
dangerous since we flip numbers around as well.
    I would like to start with my view that economics is at its 
very heart the study of collective human behavior, one of the 
hardest concepts for us to even imagine measuring. I think, to 
paraphrase Chairman Greenspan, which all of us are doing since 
he gave such a timely speech last week at NABE meeting, he did 
talk about an economy that is increasingly dominated by ideas 
instead of material inputs or manual labor, as one that is 
putting significant stresses on our ability to--on our 
statistical systems. With that said the U.S. economic 
statistics many times represent our only true light in what is 
becoming an increasingly dense forest of global economic 
information. Business leaders and the press have already begun 
to recognize the magnitude of the issue and they realize that 
statistics shape everything from our own strategic risk 
assessment at the banks, strategic planning, to portfolio 
management. And just the rumor of one of these statistics being 
out of kilter from where many are expecting, we know can move 
billions of dollars around the world in a split second now.
    Moreover the gap left by what has been taken away in terms 
of what is now faulty or incomplete data provided by the U.S. 
statistical agencies has left many of us to rely on private-
sector information. Dick pointed out that his firm now does its 
own surveys which are commendable but there are many a survey 
that provide a sliver of information in what is really only a 
piece of a much larger, more complex puzzle. I think of things 
like the National Association of Purchasing Managers index--
which before the last Fed meeting just because it happened to 
come out before the January 3rd surprise inter-meeting Fed 
meeting, people all now think that is what moves the Fed which 
is utterly ridiculous that one number would move the Fed to do 
an inter-meeting move like that. Especially one number that is 
not held accountable to the same kind of accountability our 
U.S. statistical agencies are held accountable for.
    There is also today the Challenger, Gray & Christmas survey 
was released recording lay offs. These surveys never state when 
the lay offs are going to occur, whether they are due to 
attrition, how much they are going to show up in the 
unemployment statistics, and really tell us much more about 
structural change in the large corporate sector rather than, as 
you pointed out earlier, what is so importantly going on in the 
small business sector. Small businesses don't have to name how 
many people they hire or how many people they are able to hire 
now after complaining in other surveys they have not been able 
to hire for years and now finally have some workers to hire. So 
I find that an important point to make as well.
    At worse, some of these issues, in terms of these private 
surveys that are now becoming so popular, 15 years ago nobody 
even paid attention to some of these surveys, I might add, that 
are out there. They give a distorted, inaccurate view of the 
macro economy. It is not to say that they were put in 
unscrupulous private sectors hands. I represent the private 
sector, and I know incentives well. And knowing that your 
statistic might happen to move a market is an incredible 
temptation to take a position on before it actually comes out. 
That is one reason why I believe in the U.S. statistical 
agencies and that the data should come from the government. I 
don't believe a lot of things should from the government, but I 
believe in fiscal discipline but certainly with prudence 
funding the statistical agencies.
    In response to all these issues, businesses have taken 
things into their own hands investing in extraordinary 
information technologies. My own company, Bank One Corp., is 
now looking to increase its investment in the Intranet and 
Internet to be able to know real-time information on anything 
that is going on in any 1 of our 14 states of dominance in any 
one of our business lines. That is very important to us, but 
severely compromised now is our ability to be able to forecast 
some of the trends that helped shape the strategy of the bank 
when I first started.
    My first forecast that I ever made was in 1986 for the 
renaissance in the Midwest economy trying to get the bank 
focused on looking to the Midwest rather than New York to be a 
bank and looking at its own comparative advantage. I am not 
sure I can make that same forecast today given the lack of 
regional data and the lack of quality in the regional data that 
is now available, because as the statistical agencies have had 
to make cutbacks in their priorities, prioritize what they do 
cover, regional has often gotten short shifted. We do not know 
retail sales in any State in the country, your State, we do not 
know the retail sales in your State. It seems so utterly 
ridiculous when you are thinking about I helped many a State 
and local government try to forecast revenues and understand 
their economic environment with fewer and fewer economic 
information on that front is--I think is a huge problem.
    Also I think why shouldn't the statistical agencies have 
the same ability that we have given the private sector to 
automate and aggregate data that is now being collected in the 
private sector. This would far increase efficiencies and 
sometimes inaccuracies filled out by the wrong people by 
surveys in the private sector. I am very much in support of 
increased investment in infrastructure in the statistical 
agencies. This goes far beyond just supporting data collection 
and quality data. It is talking about really raising the bar on 
the kind of information we can collect in a new information 
world. And if we don't make those kinds of investments, the 
kind of data we are going to be getting is yesterday's data at 
best rather than today's data which is so critical to 
policymaking and other issues.
    I have already talked about some of the issues that we 
face. I think underscoring the risks, I think you referred to 
it a bit earlier, of faulty or lagging economic information you 
noted the 1990 situation where as late as October 1990 Chairman 
Greenspan was trying on record to reassure an increasingly 
skeptical public based on data that said we were still in a 
slow but economic expansion, not a recession. It wasn't until 2 
years later upon the revision of that data in 1992, that we 
actually saw in the data a recession acknowledged. A recession 
that actually began 2 months before Greenspan was making 
comments on record that he thought the economy was still 
expanding given the economic data.
    We don't know what history would have changed if that 
information had been available, but clearly it points out the 
need and the need for continual increases in the accuracy of 
the data.
    I also note the importance of the 1997 and 1998 financial 
crises that rocked global markets around the world certainly 
required the Fed and the Treasury to intervene in 1998 to 
stabilize what had been a liquidity freeze in our own financial 
markets in the United States because of, in part, faulty 
information around the world. The information that we see in 
the United States is the best in the world, is the most 
transparent, and the most accountable. Other countries that do 
not have or are not as well funded as we are even with our 
needs for funding have far less credible data and the 
transparency issues are clearly not there. People were making 
investments without clear information of what those investments 
were assuming they had the same kind of information that we had 
here and we got caught very hard by that issue.
    Also as has been already mentioned is the budget debate and 
how important the source data that goes into the debate is. 
Just having that data--know that it is going to be revised in 
and of itself makes this question the outlook. We could spend 
all day debating the assumptions on the forecast, but I think 
we would all agree at the end of the day that having the best 
source data possible is the only way to possibly get to any 
kind of a close and accurate end point in the data.
    I will return to where I started to some extent and say 
that efforts to improve the quality of U.S. statistics are 
commendable but still fall far short in catching what I think 
is a moving target: A rapidly evolving information-based 
economy.
    The statistical agencies have suffered from neglect and a 
lack of advocates. I noted in my comment that the word ``data'' 
appears to be the most uninteresting four-letter word in the 
human vocabulary, not attracting much attention out there. NABE 
has certainly, I hope, changed that. It was our goal when Dick 
and I sat down last year, our goal starting back in the mid-
1980's to make this a more national debate on statistics to 
underscore the importance. And I think we have raised the 
volume if nothing else.
    Dick pointed out how our diverse multinational membership, 
70 percent, agree. Do you know how hard it is to get 70 percent 
of economists to agree on anything? That is a really remarkable 
thing when--and it has been the same every year. The 
overwhelming majority of our members choosing that as their 
most important objective.
    Moreover I think what I have been stunned by is our allies 
in every corner. I mention in my comments, last year when I was 
working on the lobbying effort to increase funding for 
statistical agencies, actually had one CEO return a call from 
his vacation because he thought it was so important to get back 
to me to be included on a list of people writing letters in 
support of statistical funding. It spans party lines. I have a 
list that I started--actually I couldn't finish in time to get 
here because of my travel schedule but just in 1 day I was able 
to get seven CEOs that I called around and actually got a hold 
of personally to say please include me on the list, Diane.
    Every single person we have approached has come back to us 
with, of course, we support you. And many of these CEOs have 
also gone to great lengths to write many a letter to many a 
Congressperson in order to keep that support out there. I think 
that is really important. Our only--there are no enemies in 
this game of the statistics. There are no people out there 
against us. We are an advocate, but we don't have enemies.
    Our only true enemy is complacency. I urge--and this is 
certainly following after some of the things that you have 
heard from other people, but funding on quality and timeliness 
of the economic statistics really includes everything from 
funding for infrastructure to funding for competitive pay 
packages in this economy. Despite the slowdown, I was just out 
yesterday at a customer in Springfield, IL, who is paying 
$700,000 a month to temporary workers, double the wages of 
their existing workers, just to fill positions. This is very 
important to continue to have quality people to be able to work 
and fund in the funding of these agencies.
    I also encourage investments in infrastructure. Why 
shouldn't we share data between agencies? And investments in 
infrastructure could make the sharing of that data much more 
rapid, much more efficient, and much more accurate, frankly. 
Also I think it would also make--investments in infrastructure 
could make the collection of data much more accurate.
    Finally, I think it is important to point out funding for 
research techniques as well. One of the things that we do in 
this country better than others is we actually know how to 
survey for statistical information better. And not only do we 
need to continue to improve upon that, especially in an idea-
based economy, I think we also have a responsibility for 
ourselves that would payoff not only for the United States but 
for the global economy for many decades to come to continue to 
invest in the quality of research on statistics and export that 
technique abroad so that other economies we deal with are 
playing in the same playing field we are. This would mean 
enormous returns for our own financial markets and could add 
much stability where we have seen instability in the recent 
past.
    I guess my last quote from Chairman Greenspan, which has 
been quoted very much today because of his support on this, he 
said about a little over a year ago in a question asked of him 
to a Senate panel, that when it comes to statistical funding, I 
am extraordinarily reluctant to advocate any increase in 
spending so it has to be either very small and/or very 
formidable argument that is involved. He said, and I find in 
this case, regarding U.S. statistical agencies, both conditions 
are more than met.
    And I think that sums up our membership and certainly those 
of us who have to deal with this on a daily basis, and also 
every
CEO I talk to feels it is very important to their business 
lines and their conduct of business not only in this country 
but abroad. Thank you.
    Mr. Miller. Thank you.
    [The prepared statement of Ms. Swonk follows:]

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    Mr. Miller. Mr. Richards.
    Mr. Richards. Thank you, Mr. Chairman. As a professional 
statistician, I think that the BEA has done an excellent job; 
and as a statistician in the business world, we really put our 
money where our mouth is. We get inquiries from the 
manufacturing sector all the time as to what statistics they 
should be looking at, what time series they should be using for 
particular problems. And I always refer them to the government 
agencies.
    It is not always the BEA, as sometimes we think they should 
look more at the index of industrial production compiled by the 
Federal Reserve or the shipments data compiled by the Census 
Bureau, but I invariably tell them to rely on the government 
data. I get quite a few inquiries about some of the private-
sector surveys. I wasn't going to put this in my written 
statement, but I think many of the private-sector surveys 
provide misleading and inaccurate information. The government 
agencies have made much more of an effort to make the data 
accurate, reliable, and it is actually quite user friendly. The 
problem for the private sector is getting enough non-economists 
out there to be aware of the data sources and to give them some 
guidance as how to use that. In fact, this is one area in which 
the government data is vastly superior to most of the 
alternatives.
    As far as what I think the BEA has been doing right for the 
last 10 years, let me cite three examples. First of all is the 
adoption of chain-weighting in GDP, which is a major 
innovation. And we certainly see this in terms of say the 
relative difference between growth and inflation, that is, the 
share of nominal output that is compromised by growth and 
compromised by inflation. If we hadn't had chain-weighting we 
would be reporting a higher rate of inflation at a lower rate 
of growth. This has very clear policy implications for the 
Federal Government because transfer payments were indexed to 
the Consumer Price Index. As a result, the Federal Government 
ended up spending more than was absolutely necessary on these 
income transfers.
    The second big innovation the BEA has made is the 
redefinition of GDP to include software. And as any computer 
programmer can tell you, software should not be treated as an 
intermediate input such as raw material. It is a valuable 
productive tool which in turn can be used to generate value 
added.
    The third major innovation that the BEA has engaged in, 
which again we agree with completely, is the imputation of 
quality improvement to the computer sector. The way that they 
have done this is to take a weighted average of computer 
processing and capacity and add that to the real value of 
computers. If you do not do this quality imputation, which has 
been somewhat controversial, you end up with extremely low 
estimates for the rate of growth; and this, in turn, has very 
significant implications for policy decisions. Of those three 
innovations, I think the two most significant are the quality 
imputation to computers and the redefinition of GDP to include 
software.
    Throughout the 1990's, there has been a debate in which we 
have participated as to how fast the economy can grow at a 
stable inflation rate. For a long time, we had this situation 
in which the growth rates that were being reported were 
relatively low but the inflation rate was continuing to decline 
and national income was growing faster than national product.
    Now, the increase in income relative to product suggests 
that the cause might be hidden productivity. It was a paradox 
that was resolved when the BEA adopted these innovations and we 
discovered that the missing output wasn't missing at all. 
Rather it was the output that was being generated by the 
quality of computers and by the inclusion of software in the 
national income accounts.
    We have also done our own production function studies on 
this issue, and what we find is that using reasonable measures 
of technology, a theme I would like to return to in just a 
moment, we get estimates suggesting that the productivity trend 
in the United States could be sustained at something like 3 
percent per year over the next 10 years. There is quite a 
debate going on right now as to whether or not the increase in 
productivity that we have had since the mid-1990's is just a 
one-time event or is sustainable in the long term. And the 
econometric models that we have developed and in some instances 
had published in the journals clearly indicate that this is a 
long-term development. The BEA's innovations in compiling 
better GDP data were instrumental in deriving these estimates 
that indicate the trend in productivity is sustainable.
    One issue that has come up recently and certainly in this 
hearing is the difficulty involved in measuring intellectual 
capital. So I would like to suggest one possible approach to 
this. This is more a suggestion than anything else. I think it 
is going to need to be debated. Right now there is very unusual 
discrepancy in the national income accounts. Research and 
development spending is counted in GDP if it is done by the 
government, it falls under government purchases, but if it is 
done by private industry, R&D is counted as an intermediate 
input and netted out.
    In my view, R&D can be taken as one measure of the 
increasing intellectual capital that is becoming increasingly 
important in the economy. In fact, if you add R&D spending into 
GDP and you also put R&D in as a production function you can 
explain an additional 0.6 percentage points per year of 
productivity growth. And of course that is quite an important 
issue from our point of view because productivity or output per 
hour we know has to come from physical capital and technology 
but the technology, component is poorly measured.
    So one thing that BEA should probably consider doing is 
redefining output to include R&D under business-fixed 
investment.
    Finally, I would like to conclude with one comment about 
the recent debate on income versus product and how serious the 
current economic slowdown is. The problem--the discrepancy 
between income and product during the mid-1990's was really 
resolved in favor of higher output. We saw income rising faster 
than product and it turned out that we were growing much more 
rapidly than we expected.
    Now, however, we have a situation in which the product side 
is reporting a pretty serious slowdown, growth is 1 percent in 
the most recent quarters, it will probably come in about 1 
percent when BEA releases it, and yet national income has been 
rising by more than $70 billion faster than national product 
for the last 2 years. So we are seeing again some indication 
that there may be hidden productivity out there, that there 
may, in fact, be higher out there.
    We don't know the source of the output. But there is 
clearly an indication that the American economy has a good deal 
of resiliency. There may be additional technical advance, 
additional productivity that isn't being measured in the 
product-side but is showing up on the income-side. That in turn 
suggests that once we are out of the current slowdown, we see a 
recovery in demand, that we can actually sustain the current 
expansion for a long period of time.
    Thank you, Mr. Chairman. I will be happy to answer any 
questions.
    Mr. Miller. Thank you very much.
    [The prepared statement of Mr. Richards follows:]

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    Mr. Miller. And finally, Professor Berndt.
    Mr. Berndt. Thank you. I thank the Chair for inviting me to 
appear today. Although I currently serve as chair of the 
Federal Economic Statistics Advisory Committee, called FESAC 
for short, I have not had the opportunity to share these 
remarks with them; and so my remarks today should be 
interpreted as my own and not necessarily those of my fellow 
FESAC members.
    As we all know, the last few decades have been marked by 
dramatic technological and economic changes. To make important 
decisions wisely within such a speedily changing environment, 
businesses, government policymakers, employees, retirees, 
students, homemakers, and even academic researchers rely very 
critically on data and information provided by our statistical 
agencies. A major challenge facing these agencies, as a number 
of speakers have already emphasized, is to track this moving 
target of current economic activity reliably, efficiently, and 
promptly.
    Let me begin with FESAC and the role FESAC plays in this. 
FESAC is an interagency advisory committee to three economic 
statistical agencies: BLS, the BEA, and Census. FESAC's mandate 
is to analyze issues involved in collecting, tabulating, and 
publishing Federal economic statistics, but particularly those 
issues that cut across the three statistical agencies and that 
could benefit from enhanced interagency cooperation and 
coordination.
    A goal of FESAC, therefore, is to foster greater efficiency 
within the Federal statistical system and thereby enable it to 
provide higher quality statistics in support of more informed 
economic and social decisionmaking.
    Let me now turn to the BEA which is the focus of today's 
hearing. Although probably best known for publishing our 
Nation's GDP data, the BEA is, in fact, a key provider of a 
wide variety of national, industry, regional, and international 
economic data on income, production, prices and international 
trade. In carrying out its mission, as a number of speakers 
have emphasized, the BEA relies on data from the Census and the 
BLS and, in turn, provides the BLS with data it needs in 
fulfilling its own responsibilities.
    In my brief remarks today, I would like to discuss with you 
several important issues facing the BEA. But I want to focus on 
issues that involve not just the BEA but also the Census and 
the BLS. Since my time is short, to illustrate the points I 
want to make, I want to focus on a measurement of but one 
important and widely observed economic indicator, labor 
productivity. And being an academic, I naturally had to put 
something on a blackboard exhibit.
    As can be seen in this exhibit, labor productivity is a 
simple ratio. In the numerator, we have inflation adjusted, or 
a real measure of output; and in the denominator on the bottom 
we have some measure of hours of labor input. BEA publishes the 
numerator and BLS publishes the denominator. And BLS computes 
the ratio and publishes the ratio as well. So you can think of 
it as BEA over BLS. Let's look at the numerator and denominator 
a little more carefully.
    First on the numerator, in producing its measure of real 
output, the BEA relies on Census to provide output figures in 
current dollars. In turn, Census collects sales data from a 
representative sample of establishments which it identifies 
utilizing a comprehensive register listing of establishments 
that serves as a sampling frame for all of the Census Bureau's 
business surveys. As an aside, what an establishment is, in a 
digital economy with increasing e-commerce, presents ever more 
complex issues. But we leave that for another day.
    To convert the Census sales figures in nominal dollars into 
real inflation-adjusted output data, which is what we need in 
that numerator, the BEA deflates them using a combination of 
price indexes provided by the BLS and in some cases those that 
it has constructed on its own. I might add that BEA was a 
pioneer in developing deflators for computers in collaboration 
with private-sector firms such as IBM, and more recently for 
software, in collaboration with a variety of academic and 
private-sector vendors.
    So in summary and referring still to the numerator, how one 
constructs reliable deflators and thereby measures real output 
for diverse industries such as banking, consulting, tax 
preparation, investment advice, and health care raises very 
challenging issues for all three agencies. FESAC is focusing 
considerable attention on such output measurement challenges.
    Let's briefly turn to the bottom to the denominator of 
labor productivity, the measures of hours worked by employees 
and by the self-employed. Like the Census, BLS has a list of 
establishments from which it selects those asked to provide 
essential economic data. Unfortunately, the universe list of 
establishments at the BLS and at the Census do not match 
precisely; and currently, data sharing is not permitted. More 
on that in a minute. Although BLS measures of hours worked by 
production and nonsupervisory workers are likely to be very 
reliable, those types of production workers are now a minority. 
A very distinct minority in our changing economy.
    Hours worked by others such as entrepreneurs and Internet 
startups, by telecommuting consultants, by sales reps and 
office workers using cell phones while driving to and from work 
and utilizing fax and modems at home are very difficult to 
measure reliably. Currently the BEA and BLS are both expending 
considerable efforts on creating better measures of hours 
worked and on how individuals allocate their time. These topics 
will be addressed in detail at our next FESAC meeting. A 
related set of issues on how one measures, and values, labor 
compensation when you have stock options, other deferred 
compensation and important non-wage benefits such as health 
insurance, are also of great concern to all three agencies and 
to FESAC.
    This simple example of this ratio of output over labor 
input illustrates, I think, some of the complexity involved in 
putting together the Nation's economic statistics. Clearly, 
constructing and publishing a measure such as labor 
productivity involves a great deal of coordination across our 
Federal statistical agencies. By and large Mr. Chairman, I 
believe this coordination works quite well. Each of the three 
principal economic statistical agencies has a reasonably well-
defined set of responsibilities. And each is committed to 
working collaboratively with the others to address issues of 
mutual interest such as those I have identified above. At the 
same time, I believe current arrangements do seem occasionally 
to involve some needless duplication and burden on the public.
    So let me conclude with an unabashed and blatant plea to 
this subcommittee. Current U.S. laws restrict agencies' ability 
to share information with one another even for only statistical 
purposes. These data-sharing restrictions and especially the 
inability of the agencies to share their business register 
lists with each other are very costly to our economy. Both 
Census and the BLS have universe lists of establishments, but 
these do not always agree, particularly in the context of a 
very rapidly changing economy when even the notion of what is 
an establishment can be called into question.
    BEA relies on both Census and BLS establishment data and 
must make refereeing choices when these data do not appear to 
agree with each other. I believe the sharing of universe lists 
and other data among appropriate Federal statistical agencies 
would not only achieve budget savings, greater efficiency, and 
increased accuracy, but that this would also reduce the 
reporting burden on the public and in small business in 
particular. Moreover the data sharing could be carried out in 
ways that protected the important confidentiality interests of 
those providing information.
    I strongly urge this subcommittee to support passage of 
legislation enabling the appropriate sharing of information 
among statistical agencies for statistical purposes. A good 
basis for such legislation would be the Statistical Efficiency 
Act of 1999 which was passed by the House in the last Congress 
as H.R. 2885 but was not considered by the Senate. Passage of 
such legislation would be an important good government victory 
in my view. Thank you.
    [The prepared statement of Mr. Berndt follows:]

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    Mr. Miller. I thank all of you for being here today and 
especially those who came from out of town. I appreciate it. I 
found all your statements very interesting.
    Let me start off, it has been such a dramatic change, 
historic change in our economy during the past decade. How do 
you rate the quality of the data you are getting today, many of 
you all have been doing this for a few years I know, to 10 
years ago or even 20 years ago? Especially as you know this 
economy is expecting--going through this technological 
revolution, whatever you want to call it, do you feel the data 
is as good today or is it better today than 10 years ago or 20 
years ago?
    Mr. Berner. Mr. Chairman, why don't I start. I think that 
the data today really suffers from fact that, as I mentioned in 
my prepared remarks, we do have a big hole in the data; 20 
percent are based on estimates, and unfortunately that 20 
percent often comes from the area that is most dynamic and most 
rapidly changing. We talked about software a little bit and 
talked a little bit about the surveys that not only my firm but 
others do in the private arena to try to get a better 
understanding of what is happening in that area.
    Just to mention it, 43 cents of every IT spending-dollar is 
now, according to Steve Landefeld's statistics, accounted for 
by software and it has been growing like a weed. So it is a 
very important component of capital spending. And it is a very 
important innovation to include that in our data.
    Having better data on software outlays, particularly in the 
wake of what we have seen with the preparation for Y2K and its 
aftermath and other areas would be very important. So that the 
challenge is not that the quality of the data have 
deteriorated, the challenge comes from the things that we have 
all talked about, namely that the economy is changing far more 
rapidly today and requires a much more flexible statistical 
infrastructure in order to deal with it.
    Mr. Miller. You mentioned 20 percent is estimated. Is that 
what it was 10, 20 years ago and has that 20 percent changed?
    Mr. Berner. Well Steve Landefeld can talk about that, but 
let me answer the second question. The composition of the 20 
percent has really changed. But there is an important area 
besides software, obviously that is critical, and that is in 
the service arena. And BEA and the other two major statistical 
agencies and the Federal Reserve have made major efforts to 
expand their coverage of services and to develop new concepts 
and new metrics for gauging what is going on in services and to 
try to improve the measurement of productivity in that arena.
    But it is a constant challenge because services are broad, 
diverse, and certainly cannot be lumped into any one category; 
and that diversity obviously has to be dealt with in coming up 
with these, both concepts and metrics, in measuring this part 
of our economy.
    Ms. Swonk. I would like to add to that. I certainly echo 
the issue that services are one of the areas where we are not 
measuring things as we could. And it has always been a problem. 
I was talking to you before about the size of my economics 
department and its shrinkage and how much we still produce 
relative to its prior size. So obviously we have had some major 
productivity gains within our department and certainly within 
our bank we now handle more assets with fewer people than ever 
before and do it effectively, I hope, depending on which day 
you look at my stock price.
    With that said, one of the things that is my concern is as 
much as there were faults in a lot of regional data, and my hat 
originally before being just the chief economist at Bank One 
was being the regional economist at Bank One, is the gaps that 
are left because of priority choices that had to be made. And 
there is a lot of data that is not being collected now. And for 
all of its faults it was all we had. It was not perfect by any 
means.
    And I know that priority decisions had to be made given the 
budget cuts. But to not be able to as a large regional firm 
that crosses many regions in this country, to not be able to 
assess the characteristics of the consumer or business climate 
in an accuracy level that you feel confident with that we are 
now turning to our own information which is, frankly, faster 
and more real-time information than I can get from the 
government, that is a real problem.
    And it also means that I can't share all of my analysis as 
I want to with some of the policymakers that I talk to because 
much of it is private, our own private analysis of our own 
economic information inside the bank. And that is just not the 
direction we want these things to go. It has really left many 
people at the regional level scrambling for ways to figure out 
what their revenues are going to be, what you know retail sales 
revenues are going to be.
    Many have tried to make up different kinds of measurements, 
many of the regional Feds have tried to make up different 
measurements of retail sales. I am using that as one example. 
But clearly we have lost some things in the mix. I won't even 
begin to go into the mortgage data and how important that has 
become. Here we are in the mist of another mortgage refinancing 
boom and our group has done significant work on mortgage 
refinancing and its contribution to the U.S. economy which is 
not included in income but, boy, it is spent. The mortgage data 
is very compromised at this point in time because of priority 
decisions that had to be made earlier on.
    Mr. Berner. Mr. Chairman, if I could, let me just mention 
one other area and that is the international arena. Nick 
Knickerbocker mentioned as an aside that if we knew how to 
measure our exports to within the tolerance of 7 percent we 
would be much better off.
    You can imagine what the discrepancies are in the service 
areas of our international accounts which are perhaps even more 
compelling at this point in time. And that is because not only 
does our economy have a more global look to it but obviously 
the huge wave of foreign investment in the United States in the 
last several years has made the sharing of data and the sharing 
of information about the income exchanges from that direct 
investment much more important.
    It now appears, for example, that the European economies 
are slowing down much more rapidly than most people had 
anticipated. One reason for that may be that European 
corporations are responding to the slowdown and the results 
that they are seeing in the United States and that is having an 
impact on their business.
    If we had better data on foreign direct investment on the 
reported income flows associated with those, and the BEA and 
other agencies make every effort to improve those data, then we 
would be able to analyze that better. And I think that points 
to one other issue which is data sharing perhaps at least 
cooperation across borders. And as I am sure you know, both 
Steve and Nick and Cathy Abraham at BLS are making every effort 
to do that and to cooperate. But obviously more resources would 
permit them to cooperate more effectively with their 
counterparts overseas.
    Ms. Swonk. I wanted to add one extra point too and that is 
one of the things that we have seen is because of gaps left in 
the data this reliance on more private sector unreliable data. 
And I am rather stunned. I have been on many a talking head 
show where an economist or economic analyst, whatever they may 
title themselves, tries to analyze data that they don't 
understand.
    Not only do they not understand it because they haven't 
researched it, and haven't been taught it because we have lost 
much of that, but also it is private-sector data that doesn't 
have the same accountability. If you really want to understand 
the flaws and the gaps in the U.S. statistical agency's data, 
you can understand that. They provide that for you. They tell 
you. They are accountable. So you could say this could be a 
seasonal factor. This could be because it snowed last month. 
They tell you that information.
    Where on the private-sector data that is coming to dominate 
some of the financial market moves, there is no accountability 
whatsoever. I really fear that some of the gaps that are left 
are being filled by the private sector. As much as I believe in 
the private sector, this is just not one place they belong. 
They don't have the same incentives. They can discontinue data 
series if they go out of business. There are all kinds of areas 
where there are some real severe problems.
    Mr. Miller. What competition is there for BEA? I mean you 
mentioned the private sector. Is there potential for someone to 
offer competing data?
    Ms. Swonk. I don't think there is any way that a private 
sector could get the kind of confidential information that a 
U.S. Government agency could get to provide overall economic 
data. But I am stunned in the last decade to see how many 
reports come by or people trying to sell me their information 
of their particular survey on the world and what the 
information--trying to tell me what that information provides. 
I look at it and realize it doesn't provide what they are 
telling me it provides. So I don't think there is any real 
competition in the sense that I don't think any private-sector 
firm would be trusted with the kind of, you know, intimate data 
that corporations provide and small businesses provide to the 
U.S. Government under confidentiality agreements.
    However, it is amazing how much is even worse in terms of 
the private-sector data that is coming out, how much is being 
pedaled out there in terms of more economic information to try 
to fill in this picture of the economy that is increasingly 
finding gaps in it.
    Mr. Richards. I would like to pick up on something that 
Diane said about the unreliability about private-sector data. A 
lot of the data that is being held up as competitive with BEA's 
data is not very reliable.
    Here is an example: In November and December, consumer 
confidence as measured by some surveys dropped by about 17 
percent which seemed to imply that consumer spending was poised 
for a major slowdown but what we actually observed in January 
was a significant rebound in consumer spending. So that not 
only did the consumer confidence data give a false reading it 
could not even call the direction of change correctly. 
Nonetheless, it is clear that the stock markets were reacting 
to the consumer confidence numbers.
    There are many other examples of private sector surveys 
that are poorly put together and contain false and misleading 
information, but unfortunately that false and misleading 
information is moving the markets in a significant way.
    Mr. Berndt. Let me just add to that, if I may disagree 
slightly with some of my colleagues. I think there are some 
industries that have much deeper coverage from private-sector 
sources than the government, because of the govdernment's 
sampling procedures. Let me take an area that I know 
particularly well, which is health care. And there are a number 
of--for example pharmaceutical industry data sources which have 
samples of products that are in the hundreds of thousands each 
month whereas the BLS's sampling procedures can only be about 
500 products a month. So it varies, I think. But certainly 
there is nothing in the private sector that can rival the 
comprehensiveness that the accounts from the BEA and BLS and 
Census Bureau provide.
    Mr. Miller. Don't individual States--a lot of times the 
State universities--I remember when I was back in graduate 
school, they would have their own departments generating that 
type of information. For those individual States, talking about 
Florida and Louisiana, two of the States where I went to 
school. But it seems like they still crank out the data. How 
reliable is that State-type of data?
    Ms. Swonk. It is interesting because, on a regional basis, 
I rely more and more on those kinds of departments to get a 
feel for--Florida is a big State for us, for Bank One. I rely 
more and more on that information and what the Federal Reserve 
puts out to get a feel for economic information.
    The problem is even there much of that State, the business 
departments or the business research groups, they base their 
information off of employment data coming out by the State or 
by the Federal Government and I have seen gaps in their data 
sources as well. So they are now having to make assumptions on 
top of assumptions to get to those conclusions.
    And again there is no consistency across States. You are 
getting to issues--I mean I want to compare data that is in 
Florida produced for Florida that compares to data in Michigan 
prepared for Michigan. And when you get to the individual 
research institutions, although they are extremely valuable and 
I rely on them very heavily when I do regional analysis, there 
is not the--they are not always comparable in terms of what it 
is they are analyzing, what their purposes are. Some of them 
have more purposes to advise State government, some of them 
have purposes to attract more investment to the State. So the 
inconsistencies there just again make the problem more complex 
in terms of what the information is actually telling us.
    Mr. Miller. You mentioned about the BLS and BEA and census 
and you talked about the funding. You know this is an 
authorizing committee not an appropriation committee. I happen 
to sit on both. Actually I sit on both appropriation committees 
that fund BLS and Census Bureau and BEA. It is hard always to 
explain how the government operates in a way because I sit on 
the Labor HHS subcommittee which is where BLS is funded. But I 
happen to sit on the Commerce, Justice, State, and the 
Judiciary appropriation subcommittee which is where the Census 
Bureau, BEA is.
    And you mention about--there has always been the question 
of consolidation of statistical agencies. We are not here to 
discuss that, debate that issue specifically. But there is--
when you have different appropriations subcommittees, you have 
different authorizing committees, and yet there is competition 
between agencies collecting data. I think you--Mr. Berndt, you 
mentioned the problems of not sharing the data. But yet, there 
is somehow the advantage of having competing sources of data 
are there? And what would you recommend? Do you think--that 
is--I am interested. I was not fully aware that there is an 
advisory committee that represents that cross of all of the 
agencies between departments and how that operates too.
    Mr. Berndt. Let me start to answer that. But you open up a 
wide topic on which we could have hearings for some time. There 
are historical reasons why we have the different agencies. I 
think in general I agree with you that having some competition 
among agencies is, in some sense, a good thing. I think, 
however, in quite a few instances, there really is actual 
duplication and replication. I think we could proceed quite 
wisely and prudently by defining, identifying some of those 
areas and without getting into a big argument of whether we 
want to have a statistics United States like Statistics Canada, 
but rather are there opportunities where we can efficiently 
share data and avoid duplication and use our public-sector 
dollars more prudently. That would be important first steps to 
take. There are those opportunities now, particularly as we 
have the information technology revolution where we have common 
standards of collecting and reporting data, and it makes it 
much easier now to do that. So I want to shy away from your big 
question.
    Mr. Miller. I really don't even want to bring that one up 
either, I guess. But----
    Mr. Berndt. I would like to suggest I think there are 
enormous numbers of small steps that together could improve our 
interagency coordination and make our public-sector dollars for 
data collection spent more wisely.
    Mr. Miller. One of the concerns has been about 
confidentiality of data, whether it is just basic census data 
or financial information. We are in an age where with the 
technology revolution going on that access to data but then 
confidentiality of it and being able to--what impact that has 
on participation and supplying data. What is the challenge 
there about the--I mean, one of things--I am a former 
businessman. I remember getting forms in the mail. The 
University of Florida would send me something or the State. And 
you know I was a relatively small business back home; we didn't 
have an economics department certainly.
    Ms. Swonk. We hardly do too.
    Mr. Miller. So how do you complete that data? Of course 
when I was in the business we--technology has made it a little 
easier to generate that data. But this whole issue of 
confidentiality and willingness to participate on small 
business is a real challenge, I think. How do you overcome all 
that?
    Ms. Swonk. You know I agree 100 percent with that. My 
husband is actually a small business owner and just completed 
one of the forms that he had to complete for a survey actually. 
I asked him if he did complete it himself because he is the CEO 
of his small firm, and he said he did. I said good for you 
because often it is passed down to someone's secretary, and 
that is where a lot of the problems are. He didn't find the 
questions that intrusive. He thought there could have been more 
questions. Of course, he has got a little bias in his 
background given his marriage to me.
    But I think one of the things he did say, he said why isn't 
this automated. I could have just e-mailed it back. Why 
couldn't I have done this? Or why couldn't I have done that? We 
do have small business surveys out there like the National 
Federation of Independent Business, another one of our former 
presidents, Bill Dunkelberg, heads up that survey. And small 
businesses are very willing to share information when they--
when it is very narrowly defined and also when they see a 
benefit that it could help them. And I think again, making 
this, data, the least interesting word in English language and 
making more people aware of how important that is to policy 
would help.
    Education is one of the key issues here in terms of the 
small business sector. And there are many organizations that 
represent small business that can be friends to the statistical 
agencies to try to then help them, I think, in that arena. You 
are right, the ease with which these forms can be filled out 
even in a large corporation, I am appalled at some times some 
of the stuff that comes in. We were asked to be part of 
something that the Fed was encouraging our organization to 
become a part of and they called and asked me should we do 
this. I said, are you kidding? Of course, we should do this. 
And then they were going to try to put it on a low level 
person. I said no it has to be by someone at a high enough 
level that knows the information. These are always challenges 
and the more that we can make these automated and easier and 
simpler and blind, more of a feeling of blindness in terms of 
aggregating the data back to the government I think the more 
participation you will have.
    Mr. Miller. Let me go back to my first question as we 
conclude here. That is the quality of the data you get today 
and the ability to do forecasting versus 10 years ago. Have we 
improved?
    Mr. Richards. Mr. Chairman, I think that we have improved 
in very significant ways. Ten years ago we did not have chain-
weighting in the national income accounts. Ten years ago we 
were not including software. Ten years ago we did not have 
quality imputations for computers. So it is a question of is 
the glass half full or half empty. I think it is half full. But 
there are still some improvements that we have to make. It is 
not so much the manufacturing sector which I represent which is 
covered very well, it is in the service sector where, in many 
cases, industries like banking finance and real estate there is 
no direct measure of output. So the BEA has no choice except to 
develop some kind of imputation. And that is very difficult to 
do.
    And I think you know there clearly is room for quality 
improvement. I have been critical of the private-sector data 
but some of data that is collected directly by the private 
sector such as transactions conducted at ATM machines which, of 
course, are recorded by banks could be given to government 
agencies which could then develop better measures of what the 
service sector is doing. I think the data has improved 
significantly, but there is room for further improvement.
    Ms. Swonk. I would echo that. We are chasing a moving 
target. So no matter how much you improve the data you have to 
improve it more to catch this moving target. The clear issue 
that I leave is with catching that moving target some pieces of 
data have been left behind.
    Mr. Miller. One question for Professor Berndt about the 
cooperation between the three agencies that you work with. How 
often does your advisory committee meet?
    Mr. Berndt. Our advisory committee was formed last year. We 
meet twice a year.
    Mr. Miller. So it is fairly new, then, the creation of it. 
Have you seen any improvement because of the short time you 
have been existence? Or has there been a problem? Is that the 
reason it was created between the agencies?
    Mr. Berndt. Each of the agencies had their own advisory 
committees in the past. I believe this was recognized: there 
were significant opportunities for coordinating better, and it 
was under that sort of a rationale that this particular 
committee was created.
    Mr. Miller. OMB do you--is OMB involved in this loop? She 
is nodding yes. Were they the impetus that created this?
    Mr. Berndt. They were part of the impetus, yes. But it was 
the agencies themselves that also recognized that it is time to 
do this.
    Mr. Miller. What is the objective of this?
    Mr. Berndt. The objective, I think, is to find some issues 
on which all three agencies need better data and can work 
together on putting together survey forms that match their 
common needs better, that reduces their reporting burden on the 
public, that reduces the duplication. And that what some of the 
folks here have talked about utilize some of the state-of-the-
art thinking in how do you measure some of these difficult 
concepts, like how do you measure output in our health care 
sector where we have improved outcomes and extended life spans. 
So it is issues like that that cut across the various agencies 
that this subcommittee or this advisory committee is trying to 
address. We will be happy to report back to you in the future.
    Mr. Berner. If I could, I think one of the things we are 
learning here is not only do we endorse data sharing among our 
statistical agencies but perhaps we should have data sharing 
among the panels who advise and oversee them in their work. So, 
you know, Professor Berndt and I will probably get together 
after this meeting and talk about ways that we can cooperate 
because we have a statistics committee at our organization that 
obviously has provided advice in the agencies in the past and 
will continue to do so in the future. And to the extent that we 
overlap, we can make a much more efficient set of 
recommendations to the agencies.
    Mr. Miller. All right. Let me once again thank you all for 
participating here today. I find it very informative and 
enlightening to have this. As I mentioned earlier, I am 
delighted that the administration's budget proposal--I assume 
that is coming from the work of Kathy Wallman over there--
allowed for the increase that was--you know, shows the 
attention and interest and now the commitment of government to 
that. This information is very valuable for the future of our 
country.
    So I thank you very much for your contribution and your 
support for it and the information provided here today. So on 
behalf of the subcommittee, I say thank you for appearing here 
today.
    I ask unanimous consent that all Members and witnesses that 
have written opening statements be included in the record. And 
without objection so ordered.
    [The prepared statement of Hon. Wm. Lacy Clay follows:]

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    Mr. Miller. In case there are additional questions Members 
may have for our witnesses, I ask unanimous consent that the 
record remain open for 2 weeks for Members to submit questions 
for the record and that witnesses submit written answers as 
soon as practicable. Without objection so ordered.
    Thank you all very much for being here today. We stand 
adjourned.
    [Whereupon, at 3:59 p.m., the subcommittee was adjourned.]

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