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75–327 PDF 2001

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

(II)

COMMITTEE ON GOVERNMENT REFORM

DAN BURTON, Indiana, Chairman

BENJAMIN A. GILMAN, New York

CONSTANCE A. MORELLA, Maryland

CHRISTOPHER SHAYS, Connecticut

ILEANA ROS-LEHTINEN, Florida

JOHN M. MCHUGH, New York

STEPHEN HORN, California

JOHN L. MICA, Florida

THOMAS M. DAVIS, Virginia

MARK E. SOUDER, Indiana

JOE SCARBOROUGH, Florida

STEVEN C. LATOURETTE, Ohio

BOB BARR, Georgia

DAN MILLER, Florida

DOUG OSE, California

RON LEWIS, Kentucky

JO ANN DAVIS, Virginia

TODD RUSSELL PLATTS, Pennsylvania

DAVE WELDON, Florida

CHRIS CANNON, Utah

ADAM H. PUTNAM, Florida

C.L. ‘‘BUTCH’’ OTTER, Idaho

EDWARD L. SCHROCK, Virginia

——— ———

HENRY A. WAXMAN, California

TOM LANTOS, California

MAJOR R. OWENS, New York

EDOLPHUS TOWNS, New York

PAUL E. KANJORSKI, Pennsylvania

PATSY T. MINK, Hawaii

CAROLYN B. MALONEY, New York

ELEANOR HOLMES NORTON, Washington,

DC

ELIJAH E. CUMMINGS, Maryland

DENNIS J. KUCINICH, Ohio

ROD R. BLAGOJEVICH, Illinois

DANNY K. DAVIS, Illinois

JOHN F. TIERNEY, Massachusetts

JIM TURNER, Texas

THOMAS H. ALLEN, Maine

JANICE D. SCHAKOWSKY, Illinois

WM. LACY CLAY, Missouri

——— ———

——— ———

———

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

MARK E. SOUDER, Indiana

BOB BARR, Georgia

——— ———

WM. LACY CLAY, Missouri

CAROLYN B. MALONEY, New York

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

(III)

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

(1)

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 prod- uct 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

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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

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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 41⁄2 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.

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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

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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

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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 conVerDate 11-MAY-2000 10:17 Nov 16, 2001 Jkt 000000 PO 00000 Frm 00023 Fmt 6633 Sfmt 6633 C:\DOCS\75327.TXT HGOVREF1 PsN: HGOVREF1
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centrate 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,

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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.

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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 41⁄2, 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.

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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

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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.

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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.

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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.

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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.

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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.

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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.

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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 fundVerDate 11-MAY-2000 10:17 Nov 16, 2001 Jkt 000000 PO 00000 Frm 00056 Fmt 6633 Sfmt 6633 C:\DOCS\75327.TXT HGOVREF1 PsN: HGOVREF1
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ing 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.

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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 tryVerDate 11-MAY-2000 10:17 Nov 16, 2001 Jkt 000000 PO 00000 Frm 00062 Fmt 6633 Sfmt 6633 C:\DOCS\75327.TXT HGOVREF1 PsN: HGOVREF1
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ing 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 inVerDate 11-MAY-2000 10:17 Nov 16, 2001 Jkt 000000 PO 00000 Frm 00063 Fmt 6633 Sfmt 6633 C:\DOCS\75327.TXT HGOVREF1 PsN: HGOVREF1
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cluded 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

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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

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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

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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

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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.

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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 withVerDate 11-MAY-2000 10:17 Nov 16, 2001 Jkt 000000 PO 00000 Frm 00094 Fmt 6633 Sfmt 6633 C:\DOCS\75327.TXT HGOVREF1 PsN: HGOVREF1
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in 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

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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

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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

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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.

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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 chainweighting 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

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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

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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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