Policy makers need information about the nationâ€"ranging from trends in the overall economy down to the use by individuals of Medicareâ€"in order to evaluate existing programs and to develop new ones. This information often comes from research based on data about individual people, households, and businesses and other organizations, collected by statistical agencies. The benefit of increasing data accessibility to researchers and analysts is better informed public policy. To realize this benefit, a variety of modes for data accessâ€" including restricted access to confidential data and unrestricted access to appropriately altered public-use dataâ€"must be used. The risk of expanded access to potentially sensitive data is the increased probability of breaching the confidentiality of the data and, in turn, eroding public confidence in the data collection enterprise. Indeed, the statistical system of the United States ultimately depends on the willingness of the public to provide the information on which research data are based. Expanding Access to Research Data issues guidance on how to more fully exploit these tradeoffs. The panel's recommendations focus on needs highlighted by legal, social, and technological changes that have occurred during the last decade.
Institutional review boards (IRBs) are the linchpins of the protection systems that govern human participation in research. In recent years, high-profile cases have focused attention on the weaknesses of the procedures for protecting participants in medical research. The issues surrounding participants protection in the social, behavioral, and economic sciences may be less visible to the public eye, but they are no less important in ensuring ethical and responsible research. This report examines three key issues related to human participation in social, behavioral, and economic sciences research: (1) obtaining informed, voluntary consent from prospective participants: (2) guaranteeing the confidentiality of information collected from participants, which is a particularly challenging problem in social sciences research; and (3) using appropriate review procedures for "minimal-risk" research. Protecting Participants and Facilitating Social and Behavioral Sciences Research will be important to policy makers, research administrators, research sponsors, IRB members, and investigators. More generally, it contains important information for all who want to ensure the best protectionâ€"for participants and researchers alikeâ€"in the social, behavioral, and economic sciences.
Americans are increasingly concerned about the privacy of personal dataâ€"yet we demand more and more information for public decision making. This volume explores the seeming conflicts between privacy and data access, an issue of concern to federal statistical agencies collecting the data, research organizations using the data, and individuals providing the data. A panel of experts offers principles and specific recommendations for managing data and improving the balance between needed government use of data and the privacy of respondents. The volume examines factors such as the growth of computer technology, that are making confidentiality an increasingly critical problem. The volume explores how data collectors communicate with data providers, with a focus on informed consent to use data, and describes the legal and ethical obligations data users have toward individual subjects as well as toward the agencies providing the data. In the context of historical practices in the United States, Canada, and Sweden, statistical techniques for protecting individuals' identities are evaluated in detail. Legislative and regulatory restraints on access to data are examined, including a discussion about their effects on research. This volume will be an important and thought-provoking guide for policymakers and agencies working with statistics as well as researchers and concerned individuals.
Recent years have seen a growing tendency for social scientists to collect biological specimens such as blood, urine, and saliva as part of large-scale household surveys. By combining biological and social data, scientists are opening up new fields of inquiry and are able for the first time to address many new questions and connections. But including biospecimens in social surveys also adds a great deal of complexity and cost to the investigator's task. Along with the usual concerns about informed consent, privacy issues, and the best ways to collect, store, and share data, researchers now face a variety of issues that are much less familiar or that appear in a new light. In particular, collecting and storing human biological materials for use in social science research raises additional legal, ethical, and social issues, as well as practical issues related to the storage, retrieval, and sharing of data. For example, acquiring biological data and linking them to social science databases requires a more complex informed consent process, the development of a biorepository, the establishment of data sharing policies, and the creation of a process for deciding how the data are going to be shared and used for secondary analysis-all of which add cost to a survey and require additional time and attention from the investigators. These issues also are likely to be unfamiliar to social scientists who have not worked with biological specimens in the past. Adding to the attraction of collecting biospecimens but also to the complexity of sharing and protecting the data is the fact that this is an era of incredibly rapid gains in our understanding of complex biological and physiological phenomena. Thus the tradeoffs between the risks and opportunities of expanding access to research data are constantly changing. Conducting Biosocial Surveys offers findings and recommendations concerning the best approaches to the collection, storage, use, and sharing of biospecimens gathered in social science surveys and the digital representations of biological data derived therefrom. It is aimed at researchers interested in carrying out such surveys, their institutions, and their funding agencies.
Several changes in the United States over the past two decades have implications for diet, nutrition, and food safety, including patterns of food consumption that have produced an increase in overweight and obese Americans and threats to food safety from pathogens and bioterrorism. The changes raise a number of critical policy and research questions: How do differences in food prices and availability or in households' time resources for shopping and food preparation affect what people consume and where they eat? How do factors outside of the household, such as the availability of stores and restaurants, food preparation technology, and food marketing and labeling policies, affect what people are consuming? What effects have food assistance programs had on the nutritional quality of diets and the health of those served by the programs? Where do people buy and consume food and how does food preparation affect food safety? To address these and related questions, the Economic Research Service (ERS) of the U.S. Department of Agriculture (USDA) asked the Committee on National Statistics to convene a panel of experts to provide advice for improving the data infrastructure on food consumption and nutrition. The panel was charged to review data needs to support research and decision making for food and nutrition policies and programs in USDA and to assess the adequacy of the current data infrastructure and recommend enhancements to improve it. The primary basis for the panel's deliberations, given limited resources, was a workshop on Enhancing the Data Infrastructure in Support of Food and Nutrition Programs, Research, and Decision Making, which the panel convened on May 27-28, 2004. This report is based on the discussions at the workshop and the deliberations of the panel. The report outlines key data that are needed to better address questions related to food consumption, diet, and health; discusses the available data and some limitations of those data; and offers recommendations for improvements in those data. The panel was charged to consider USDA data needs for policy making and the focus of the report is on those needs.
This volume, a companion to Evaluating Welfare Reform in an Era of Transition, is a collection of papers on data collection issues for welfare and low-income populations. The papers on survey issues cover methods for designing surveys taking into account nonresponse in advance, obtaining high response rates in telephone surveys, obtaining high response rates in in-person surveys, the effects of incentive payments, methods for adjusting for missing data in surveys of low-income populations, and measurement error issues in surveys, with a special focus on recall error. The papers on administrative data cover the issues of matching and cleaning, access and confidentiality, problems in measuring employment and income, and the availability of data on children. The papers on welfare leavers and welfare dynamics cover a comparison of existing welfare leaver studies, data from the state of Wisconsin on welfare leavers, and data from the National Longitudinal Survey of Youth used to construct measures of heterogeneity in the welfare population based on the recipient's own welfare experience. A final paper discusses qualitative data.
Policy makers need information about the nation—ranging from trends in the overall economy down to the use by individuals of Medicare—in order to evaluate existing programs and to develop new ones. This information often comes from research based on data about individual people, households, and businesses and other organizations, collected by statistical agencies. The benefit of increasing data accessibility to researchers and analysts is better informed public policy. To realize this benefit, a variety of modes for data access— including restricted access to confidential data and unrestricted access to appropriately altered public-use data—must be used. The risk of expanded access to potentially sensitive data is the increased probability of breaching the confidentiality of the data and, in turn, eroding public confidence in the data collection enterprise. Indeed, the statistical system of the United States ultimately depends on the willingness of the public to provide the information on which research data are based. Expanding Access to Research Data issues guidance on how to more fully exploit these tradeoffs. The panel’s recommendations focus on needs highlighted by legal, social, and technological changes that have occurred during the last decade.
Reform of welfare is one of the nation's most contentious issues, with debate often driven more by politics than by facts and careful analysis. Evaluating Welfare Reform in an Era of Transition identifies the key policy questions for measuring whether our changing social welfare programs are working, reviews the available studies and research, and recommends the most effective ways to answer those questions. This book discusses the development of welfare policy, including the landmark 1996 federal law that devolved most of the responsibility for welfare policies and their implementation to the states. A thorough analysis of the available research leads to the identification of gaps in what is currently known about the effects of welfare reform. Evaluating Welfare Reform in an Era of Transition specifies what-and why-we need to know about the response of individual states to the federal overhaul of welfare and the effects of the many changes in the nation's welfare laws, policies, and practices. With a clear approach to a variety of issues, Evaluating Welfare Reform in an Era of Transition will be important to policy makers, welfare administrators, researchers, journalists, and advocates on all sides of the issue.
Beginning in 2006, the Census Bureau embarked on a program to reengineer the Survey of Income and Program Participation (SIPP) to reduce its costs and improve data quality and timeliness. The Bureau also requested the National Academies to consider the advantages and disadvantages of strategies for linking administrative records and survey data, taking account of the accessibility of relevant administrative records, the operational feasibility of linking, the quality and usefulness of the linked data, and the ability to provide access to the linked data while protecting the confidentiality of individual respondents. In response, this volume first examines the history of SIPP and reviews the survey's purpose, value, strengths, and weaknesses. The book examines alternative uses of administrative records in a reengineered SIPP and, finally, considers innovations in SIPP design and data collection, including the proposed use of annual interviews with an event history calendar.
How do you count a nation of more than 250 million peopleâ€"many of whom are on the move and some of whom may not want to be counted? How can you obtain accurate population information for apportioning the House of Representatives, allocating government resources, and characterizing who we are and how we live? This book attempts to answer these questions by reviewing the recent census operations and ongoing research and by offering detailed proposals for ways to improve the census.
U.S. agencies with responsibilities for enforcing equal employment opportunity laws have long relied on detailed information that is obtained from employers on employment in job groups by gender and race/ethnicity for identifying the possibility of discriminatory practices. The U.S. Equal Employment Opportunity Commission (EEOC), the Office of Federal Contract Compliance programs of the U.S. Department of Labor, and the Civil Rights Division of the U.S. Department of Justice have developed processes that use these employment data as well as other sources of information to target employers for further investigation and to perform statistical analysis that is used in enforcing the anti-discrimination laws. The limited data from employers do not include (with a few exceptions) the ongoing measurement of possible discrimination in compensation. The proposed Paycheck Fairness Act of 2009 would have required EEOC to issue regulations mandating that employers provide the EEOC with information on pay by the race, gender, and national origin of employees. The legislation was not enacted. If the legislation had become law, the EEOC would have been required to confront issues regarding currently available and potential data sources, methodological requirements, and appropriate statistical techniques for the measurement and collection of employer pay data. The panel concludes that the collection of earnings data would be a significant undertaking for the EEOC and that there might be an increased reporting burden on some employers. Currently, there is no clearly articulated vision of how the data on wages could be used in the conduct of the enforcement responsibilities of the relevant agencies. Collecting Compensation Data from Employers gives recommendations for targeting employers for investigation regarding their compliance with antidiscrimination laws.
Precise, accurate spatial information linked to social and behavioral data is revolutionizing social science by opening new questions for investigation and improving understanding of human behavior in its environmental context. At the same time, precise spatial data make it more likely that individuals can be identified, breaching the promise of confidentiality made when the data were collected. Because norms of science and government agencies favor open access to all scientific data, the tension between the benefits of open access and the risks associated with potential breach of confidentiality pose significant challenges to researchers, research sponsors, scientific institutions, and data archivists. Putting People on the Map finds that several technical approaches for making data available while limiting risk have potential, but none is adequate on its own or in combination. This book offers recommendations for education, training, research, and practice to researchers, professional societies, federal agencies, institutional review boards, and data stewards.
Federal government statistics provide critical information to the country and serve a key role in a democracy. For decades, sample surveys with instruments carefully designed for particular data needs have been one of the primary methods for collecting data for federal statistics. However, the costs of conducting such surveys have been increasing while response rates have been declining, and many surveys are not able to fulfill growing demands for more timely information and for more detailed information at state and local levels. Innovations in Federal Statistics examines the opportunities and risks of using government administrative and private sector data sources to foster a paradigm shift in federal statistical programs that would combine diverse data sources in a secure manner to enhance federal statistics. This first publication of a two-part series discusses the challenges faced by the federal statistical system and the foundational elements needed for a new paradigm.
This book evaluates changes needed to improve the usefulness and cost-effectiveness of the Survey of Income and Program Participation (SIPP). Conducted by the Census Bureau, SIPP is a major continuing survey that is designed to provide information about the economic well-being of the U.S. population and its need for and participation in government assistance programs (e.g., social security, Medicare, Medicaid, food stamps, AFDC). This volume considers the goals for the survey, the survey and sample design, data collection and processing systems, publications and other data products, analytical techniques for using the data, the methodological research and evaluation to implement and assess the redesign, and the management of the program at the Census Bureau.
The environment for obtaining information and providing statistical data for policy makers and the public has changed significantly in the past decade, raising questions about the fundamental survey paradigm that underlies federal statistics. New data sources provide opportunities to develop a new paradigm that can improve timeliness, geographic or subpopulation detail, and statistical efficiency. It also has the potential to reduce the costs of producing federal statistics. The panel's first report described federal statistical agencies' current paradigm, which relies heavily on sample surveys for producing national statistics, and challenges agencies are facing; the legal frameworks and mechanisms for protecting the privacy and confidentiality of statistical data and for providing researchers access to data, and challenges to those frameworks and mechanisms; and statistical agencies access to alternative sources of data. The panel recommended a new approach for federal statistical programs that would combine diverse data sources from government and private sector sources and the creation of a new entity that would provide the foundational elements needed for this new approach, including legal authority to access data and protect privacy. This second of the panel's two reports builds on the analysis, conclusions, and recommendations in the first one. This report assesses alternative methods for implementing a new approach that would combine diverse data sources from government and private sector sources, including describing statistical models for combining data from multiple sources; examining statistical and computer science approaches that foster privacy protections; evaluating frameworks for assessing the quality and utility of alternative data sources; and various models for implementing the recommended new entity. Together, the two reports offer ideas and recommendations to help federal statistical agencies examine and evaluate data from alternative sources and then combine them as appropriate to provide the country with more timely, actionable, and useful information for policy makers, businesses, and individuals.
The National Children's Study (NCS) was authorized by the Children's Health Act of 2000 and is being implemented by a dedicated Program Office in the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD). The NCS is planned to be a longitudinal observational birth cohort study to evaluate the effects of chronic and intermittent exposures on child health and development in the U.S.. The NCS would be the first study to collect a broad range of environmental exposure measures for a national probability sample of about 100,000 children, followed from birth or before birth to age 21. Detailed plans for the NCS were developed by 2007 and reviewed by a National Research Council / Institute of Medicine panel. At that time, sample recruitment for the NCS Main Study was scheduled to begin in 2009 and to be completed within about 5 years. However, results from the initial seven pilot locations, which recruited sample cases in 2009-2010, indicated that the proposed household-based recruitment approach would be more costly and time consuming than planned. In response, the Program Office implemented a number of pilot tests in 2011 to evaluate alternative recruitment methods and pilot testing continues to date. At the request of Congress, The National Children's Study 2014 reviews the revised study design and proposed methodologies for the NCS Main Study. This report assesses the study's plan to determine whether it is likely to produce scientifically sound results that are generalizable to the United States population and appropriate subpopulations. The report makes recommendations about the overall study framework, sample design, timing, content and need for scientific expertise and oversight. The National Children's Study has the potential to add immeasurably to scientific knowledge about the impact of environmental exposures, broadly defined, on children\'s health and development in the United States. The recommendations of this report will help the NCS will achieve its intended objective to examine the effects of environmental influences on the health and development of American children.
The United States is responsible for nearly one-fifth of the world's energy consumption. Population growth, and the associated growth in housing, commercial floor space, transportation, goods, and services is expected to cause a 0.7 percent annual increase in energy demand for the foreseeable future. The energy used by the commercial and residential sectors represents approximately 40 percent of the nation's total energy consumption, and the share of these two sectors is expected to increase in the future. The Commercial Buildings Energy Consumption Survey (CBECS) and Residential Energy Consumption Survey (RECS) are two major surveys conducted by the Energy Information Administration. The surveys are the most relevant sources of data available to researchers and policy makers on energy consumption in the commercial and residential sectors. Many of the design decisions and operational procedures for the CBECS and RECS were developed in the 1970s and 1980s, and resource limitations during much of the time since then have prevented EIA from making significant changes to the data collections. Effective Tracking of Building Energy Use makes recommendations for redesigning the surveys based on a review of evolving data user needs and an assessment of new developments in relevant survey methods.
Americans are increasingly concerned about the privacy of personal dataâ€"yet we demand more and more information for public decision making. This volume explores the seeming conflicts between privacy and data access, an issue of concern to federal statistical agencies collecting the data, research organizations using the data, and individuals providing the data. A panel of experts offers principles and specific recommendations for managing data and improving the balance between needed government use of data and the privacy of respondents. The volume examines factors such as the growth of computer technology, that are making confidentiality an increasingly critical problem. The volume explores how data collectors communicate with data providers, with a focus on informed consent to use data, and describes the legal and ethical obligations data users have toward individual subjects as well as toward the agencies providing the data. In the context of historical practices in the United States, Canada, and Sweden, statistical techniques for protecting individuals' identities are evaluated in detail. Legislative and regulatory restraints on access to data are examined, including a discussion about their effects on research. This volume will be an important and thought-provoking guide for policymakers and agencies working with statistics as well as researchers and concerned individuals.
The U.S. economy is highly dynamic: businesses open and close, workers switch jobs and start new enterprises, and innovative technologies redefine the workplace and enhance productivity. With globalization markets have also become more interconnected. Measuring business activity in this rapidly evolving environment increasingly requires tracking complex interactions among firms, establishments, employers, and employees. Understanding Business Dynamics presents strategies for improving the accuracy, timeliness, coverage, and integration of data that are used in constructing aggregate economic statistics, as well as in microlevel analyses of topics ranging from job creation and destruction and firm entry and exit to innovation and productivity. This book offers recommendations that could be enacted by federal statistical agencies to modernize the measurement of business dynamics, particularly the production of information on small and young firms that can have a disproportionately large impact in rapidly expanding economic sectors. It also outlines the need for effective coordination of existing survey and administrative data sources, which is essential to improving the depth and coverage of business data.
This book reviews the uses and abuses of microsimulation modelsâ€"large, complex models that produce estimates of the effects on program costs and who would gain and who would lose from proposed changes in government policies ranging from health care to welfare to taxes. Volume 1 is designed to guide future investment in modeling and analysis capability on the part of government agencies that produce policy estimates. It will inform congressional and executive decision makers about the strengths and weaknesses of models and estimates and will interest social scientists in the potential of microsimulation techniques for basic and applied research as well as policy uses. The book concludes that a "second revolution" is needed to improve the quality of microsimulation and other policy analysis models and the estimates they produce, with a special emphasis on systematic validation of models and communication of validation results to decision makers.
The Agricultural Resource Management Survey (ARMS) is the federal government's primary source of information on the financial condition, production practices, and resource use on farms, as well as the economic well-being of America's farm households. ARMS data are important to the U.S. Department of Agriculture (USDA) and to congressional, administration, and industry decision makers when they must weigh alternative policies and programs that touch the farm sector or affect farm families. ARMS is unique in several respects. As a multiple-purpose survey with an agricultural focus, ARMS is the only representative national source of observations of farm-level production practices, the economics of the farm businesses operating the field (or dairy herd, greenhouse, nursery, poultry house, etc.), and the characteristics of the American farm household (age, education, occupation, farm and off-farm work, types of employment, family living expenses, etc.). No other data source is able to match the range and depth of ARMS in these areas. American agriculture is changing, and the science of statistical measurement is changing as well. As with every major governmental data collection with such far-reaching and important uses, it is critical to periodically ensure that the survey is grounded in relevant concepts, applying the most up-to-date statistical methodology, and invested with the necessary design, estimation, and analytical techniques to ensure a quality product. ARMS is a complex undertaking. From its start as a melding of data collected from the field, the farm, and the household in a multiphase, multiframe, and multiple mode survey design, it has increased in complexity over the decade of its existence as more sophisticated demands for its outputs have been made. Today, the survey faces difficult choices and challenges, including a need for a thorough review of its methods, practices, and procedures. Understanding American Agriculture : Challenges for the Agricultural Resource Management Survey summarizes the recommendations of the committee who wrote the survey.
The retirement income security of older Americans and the cost of providing that security are increasingly the subject of major debate. This volume assesses what we know and recommends what we need to know to estimate the short- and long-term effects of policy alternatives. It details gaps in data and research and evaluates possible models to estimate the impact of policy changes that could affect retirement income from Social Security, pensions, personal savings, and other sources.
Americans are increasingly concerned about the privacy of personal data--yet we demand more and more information for public decision making. This volume explores the seeming conflicts between privacy and data access, an issue of concern to federal statistical agencies collecting the data, research organizations using the data, and individuals providing the data. A panel of experts offers principles and specific recommendations for managing data and improving the balance between needed government use of data and the privacy of respondents. The volume examines factors such as the growth of computer technology, that are making confidentiality an increasingly critical problem. The volume explores how data collectors communicate with data providers, with a focus on informed consent to use data, and describes the legal and ethical obligations data users have toward individual subjects as well as toward the agencies providing the data. In the context of historical practices in the United States, Canada, and Sweden, statistical techniques for protecting individuals' identities are evaluated in detail. Legislative and regulatory restraints on access to data are examined, including a discussion about their effects on research. This volume will be an important and thought-provoking guide for policymakers and agencies working with statistics as well as researchers and concerned individuals.
Policy makers need information about the nationâ€"ranging from trends in the overall economy down to the use by individuals of Medicareâ€"in order to evaluate existing programs and to develop new ones. This information often comes from research based on data about individual people, households, and businesses and other organizations, collected by statistical agencies. The benefit of increasing data accessibility to researchers and analysts is better informed public policy. To realize this benefit, a variety of modes for data accessâ€" including restricted access to confidential data and unrestricted access to appropriately altered public-use dataâ€"must be used. The risk of expanded access to potentially sensitive data is the increased probability of breaching the confidentiality of the data and, in turn, eroding public confidence in the data collection enterprise. Indeed, the statistical system of the United States ultimately depends on the willingness of the public to provide the information on which research data are based. Expanding Access to Research Data issues guidance on how to more fully exploit these tradeoffs. The panel's recommendations focus on needs highlighted by legal, social, and technological changes that have occurred during the last decade.
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