|
| | |
PRESIDENTIAL
MANAGEMENT OF THE
REGULATORY STATE
John
D. Graham, Ph.D.
Administrator
Office of Information and Regulatory Affairs
Office of Management and Budget
Executive Office of the President of the United States
Remarks
to the Committee on National Statistics, National Research
Council/National Academy of Sciences, Washington, DC
May 10, 2002
INTRODUCTION
I am delighted
to have this opportunity to engage in a dialogue with the members of the
Committee on National Statistics and the leaders of our Nation’s
statistical agencies. As some of you know, I spent time here at the Academy
earlier in my career, and I have the deepest respect for the work that
is carried out by its many committees and panels. As an academic recently
turned “bureaucrat,” I also have a keen awareness of the contributions
that our university colleagues can and must make if we are to implement
our responsibilities in a competent and creative manner. And, to the agency
leaders, I would underscore my long term commitment to the necessity of
having the highest quality, unbiased information to guide our actions.
To ensure
that we have the critical statistical information that we need, I am lending
my support to initiatives that will fill critical gaps in our current
programs and introduce efficiencies in our work. Thus, for example, I
am an advocate of the emerging American Community Survey, an initiative
that shows promise of being a significant innovation in demographic data
collection – and that will provide decision-makers at every level
with far more current information to determine needs and allocate resources.
Similarly, I am a supporter of increments in funding to fill critical
gaps in our Nation’s economic statistics. And, though I am well aware
of the intricacies and sensitivities surrounding potential changes to
our measurements of income and poverty, I am hopeful that we will be able
to capitalize on the work of this committee and the efforts of the statistical
agencies to better address some of the longstanding criticisms of our
measures. Last but certainly not least, I am pleased that we have gained
a partner in the campaign to realize a long-held dream of the statistical
system. With new-found energy from the Council of Economic Advisers, we
are working in close collaboration with the Bureau of Economic Analysis,
the Bureau of Labor Statistics, the Bureau of the Census, and the Department
of the Treasury to craft and gain support for legislation that would provide
statutory protection for the confidentiality of all data collected for
statistical purposes, and would then permit the sharing of business data
among BEA, BLS and Census to improve the comparability and accuracy of
economic statistics.
Let me turn
now to the “advertised” topic of my remarks to you today –
our recent efforts related to a new mandate on “information quality.”
The Office of Management and Budget (OMB) is of course well known for
its role in budgetary matters and is becoming better known for its role
in regulatory policy. Yet OMB’s responsibilities in the field of
information and statistical policy are not widely recognized -- unless,
of course, you are the object of our designation of Metropolitan Statistical
Areas! Just as the importance of the word “Management” in OMB
is poorly appreciated, the importance of the word “Information”
in the title of my Office, the Office of Information and Regulatory Affairs
(OIRA), is poorly appreciated. And the steps that OMB is taking to improve
the quality of information that agencies disseminate to the public are
just beginning to be known and appreciated.
Before discussing
these steps, I should note that both Congress and OMB have a longstanding
interest in the field of information policy. OIRA was officially created
by Congress in the Paperwork Reduction Act of 1980, the law that established
the basic clearance processes for “information collections”
now required for all federal agencies. In the arguably obscure OMB Circular
A-130 entitled “Management of Federal Information Resources,”
OMB stated its strong support for dissemination of information to the
public.
It is certainly
true that Federal agencies have disseminated information to the public
for decades. Until recently, that dissemination was accomplished principally
by making paper copies of documents available to the public. With the
advent of the Internet, there has obviously been a revolution in communications
that has enabled agencies to disseminate an increasing volume of information
to users throughout the world.
A major
question we are currently addressing is “what steps should agencies
take to ensure a basic level of quality in the information that agencies
choose to disseminate to the public?” A recent law passed by Congress
gives urgency to finding answers to this question.
LEGISLATIVE
HISTORY OF THE INFORMATION QUALITY LAW
The story
begins toward the end of the previous Administration, when Congress enacted
a law requiring OMB to develop uniform guidelines establishing quality
standards for information disseminated by Federal agencies. The law was
enacted as a rider to our appropriations bill without any hearings or
extensive legislative history. I am told by my career staff that the quality
of information disseminated via agency web sites was a particular concern
at the time.
This information
quality law should not be confused with an earlier “information access”
law -- one with which I know the members of CNSTAT and your academic colleagues
are extremely familiar -- that amended the Freedom of Information Act
to provide greater public access to research data generated under Federal
research grants. OMB believes that the information access and information
quality laws are compatible and in fact are mutually reinforcing in the
way that they promote responsible public access to technical information
used by government agencies.
RATIONALE
FOR INFORMATION-QUALITY CONCERNS
There is
plenty of evidence that the quality of the information advanced for use
by government decision makers needs to be improved. In the scholarly literature
on what is called “science-policy”, there are entire books of
case studies demonstrating technical problems with the information collected,
used and published by federal regulatory agencies. Although my examples
are drawn primarily from environmental policy, where I did some previous
writing, all agencies have their share of information quality problems.
My field
of science, cost-benefit analysis, certainly has its share of quality
problems. An instructive example occurred in the late 1970's, when a contractor
for EPA reported that the extra cost of controlling water pollution at
municipal treatment plants was $1.20 per pound. Analysts at the Council
on Wage and Price Stability – a precursor office to OIRA – found
a technical error in the contractor’s work and produced a corrected
estimate of $0.30 per pound. When EPA was informed of the error, they
asked a Court to remand a pending case so that the cost estimate could
be corrected and the relevant regulation re-issued in revised form. In
this case, since the cost estimate was being used as a benchmark for controlling
pollution at pulp and paper mills, the revised standard at paper mills
became more cost-effective as a result of the correction.
Sometimes
poor interpretation of technical information can result in rules or standards
that are not adequately protective of public health. The safe level of
exposure to nitrates in drinking water, for example, is a case where scientific
peer reviewers of a draft EPA document found that published studies may
have been misinterpreted by EPA analysts. Peer reviewers persuaded the
agency that, in order to provide an adequate margin of safety for infants,
a key susceptible subgroup, the amount of allowable exposure to nitrates
in water needed to be smaller than originally thought.
Information
disseminated by EPA in support of its new air-quality standard for particulate
matter has been widely criticized as erroneous or unreliable. Two studies
by my faculty colleagues at the Harvard School of Public Health were especially
controversial because the original data were not made available for public
scrutiny. Yet an independent organization funded by the car companies
and EPA, the Health Effects Institute in Cambridge, Massachusetts, did
a major reanalysis of the two key studies and found no significant mathematical
errors. The HEI reanalysis did find that the quantified health risks of
pollution changed significantly when alternative methods of analysis were
employed. The HEI work also offers an intriguing model of how reproducibility
of analytic results can be achieved without insisting on public access
to original data. That model may prove to be useful under the OMB information-quality
guidelines. The controversy surrounding these particular health studies
continues and may not be dispelled until the ideal of public access to
original data -- with identifiers removed to protect confidentiality of
subjects -- is achieved.
In my own
work as a scholar, I must confess to a quality problem here and there
-- even in those papers published in good journals! For example, I projected
that a policy of mandatory airbags would save 9,000 lives per year in
this country. The best published estimates based on real-world crash data
are now around 3,000 lives saved per year. I also did not predict the
harmful effects of passenger airbags on young children.
In citing
these various examples of quality problems, I do not mean to suggest that
the work of scientists can be perfect. Even the best of scientists are
human. In addition, the scientific data may be ambiguous, allowing several
equally plausible interpretations. Science is an evolutionary process
where the work of one scientist is enhanced by the criticism of others.
What we are discussing is an organizational challenge motivated by the
reality that scientists and analysts are not perfect. How can we improve
the quality of information disseminated by federal agencies, including
disseminations that must covey scientific ambiguity?
PHASE
ONE: OMB’S 2002 GUIDELINES
The Bush
Administration is committed to vigorous implementation of the new information
quality law. We believe it provides an excellent opportunity to enhance
both the competence and accountability of government. Yet Section 515
charged OMB with a huge task: the development of government-wide guidelines
to ensure and maximize the quality of information disseminated by agencies.
The law covers both the independent agencies and the executive agencies
but provides few limitations on the scope or types of information that
are to be covered.
To make
a long story short, OMB has now published -- after two rounds of public
and interagency comment -- final guidelines in this area. These guidelines
take effect October 1st of this year. They impose three core
responsibilities upon all federal agencies.
First, agencies
must commit to embrace a basic standard of quality as a performance goal
and take appropriate steps to incorporate quality into their information
dissemination practices. Obviously, the act of dissemination is not readily
separated from the processes of generation and use of information -- particularly
given “sunshine” laws -- and thus the OMB guidelines have important
ramifications for all aspects of information management at agencies.
Second,
agencies are to develop information quality procedures that are applied
BEFORE information is disseminated. The practice of scientific peer review
plays an important role in the guidelines, particularly in establishing
a presumption that peer-reviewed information is “objective”.
We recognize peer review at scientific journals as an acceptable form
of peer review and offer some guidelines for assuring competent and credible
peer review at agencies.
Third, and
here is perhaps the key provision, Congress required each agency to develop
an administrative mechanism whereby affected parties can request that
agencies correct poor quality information that has been or is being disseminated
by agencies. The burden of proof is squarely on the affected parties:
They must demonstrate that a specific dissemination does not meet the
quality standards in the OMB guidelines or the agency-specific guidelines.
It is this opportunity for complaint and prompt correction that begins
in October of this year. The OMB guidelines stipulate that, if an agency
denies a correction request, an opportunity for appeal must be provided.
Needless to say, many procedural details need to be worked out.
As we meet
today, we are entering the public domain with “phase two” of
the information quality guidelines process. In particular, each Federal
department and independent agency was required to publish, by May 1st,
an announcement of the availability of its draft guidelines. At this juncture,
most of the Departments have published such notices, indicating where
their draft guidelines can be accessed for review. In general, the Departments
have indicated that they will receive comments for either 30 or 45 days.
It is noteworthy
that the statistical agencies were decidedly “out in front”
on this challenge. In a very real sense, they were perhaps most ready
to meet the challenge, for information quality standards historically
have been central to their work. What was especially remarkable, however,
was the fact that the statistical agencies voluntarily came together at
the earliest stages of this process to develop a common template for their
agency guidelines. Moreover, these agencies – the ones in this room
– are publishing a common Federal Register notice to draw the public’s
attention to their individual statistical agency guidelines.
CONCLUSION
I urge you
to examine the guidelines and provide feedback to the agencies. We have
already benefitted from informal discussions with many interested parties,
and from a workshop held in March here at the Academy. This is an ambitious
legislative mandate that we must turn into a process that is practical
at once for the agencies and for the public. I look forward to your comments
and questions.
|
|
|