Expanding Access to Research Data Reconciling Risks and Opportunities (2005) / Chapter Skim
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3 Benefits of Access
3 Benefits of Access
Pages 36-49
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From page 36... ...
Thus, access to microdata by outside researchers is critical to both substantive and methodological work. This chapter discusses the role of data access in the scientific process, some of the specific ways access to research data have contributed to policy making, and the role of access in addressing the question of data quality.
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From page 37... ...
State and local governments, private foundations, and corporate and individual donations are also sources of social science research support at universities and private research organizations, including advocacy and public interest groups with a variety of policy preferences and perspectives. Federal statistical and other data collection agencies also carry out
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From page 38... ...
Research access provides opportunities for disparate academic and policy communities to communicate and learn from one another; it also provides valuable information to statistical agencies about their data. DATA ACCESS AND THE SCIENTIFIC PROCESS Empirical science includes not only data collection and use, but also data access and sharing.
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From page 39... ...
In contrast, much of the policy-related research that is commissioned by private interests is never published, so it cannot be corroborated or extended to new work. When data are shared along with study results, the research community and data collection agencies can improve and hone their own data collection methods and analytic capabilities.
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Some important data sets produced by statistical agencies pose particularly difficult challenges of confidentiality protection: they are therefore accessible only in a restricted access mode -- a secure research data center, a monitored remote access arrangement, or through a licensing agreement (see Chapter 2)
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. Data from the Health and Retirement Study (HRS)
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In contrast, McClellan and Skinner (2004) , using insurance claims and data from the census and the Panel Study of Income Dynamics (PSID)
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. Longitudinal data generally derive from three sources: surveys, administrative records, and policy experiments.
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From page 44... ...
For policy makers, the best-case scenario may appear to be one in which there is a brief policy intervention, the effects of interest are short run, and the data needed for evaluation are contained in routinely collected administrative records. The experiments that preceded the 1996 welfare reform legislation -- which replaced Aid to Families with Dependent Children with the Temporary Assistance to Needy Families (TANF)
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From page 45... ...
A 1978 CPS-SSA exactmatch file was the basis for another microsimulation model of retirement income, although that file was not made publicly available. Because linked data present challenges for minimizing the likelihood of re-identifying individuals, concerns about increasing nonresponse rates to government surveys and, subsequently, legislation (e.g., the 1976 Tax Reform Act, P.L.
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From page 46... ...
Gordon's application highlights the tradeoff between data precision and disclosure risks. Access to census tract-level geocoding permitted more sensitive construction of community and child care variables central to the study; however, it also increased the identifiability of individual NLSY records.3 The new Medicare drug benefit provides another example in which data linkage might contribute significantly to policy-relevant research and modeling.
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From page 47... ...
If survey designers know that links to administrative data can be made, they can limit the length of questionnaires as well. Yet statistical agencies have not made extensive use of linkages of administrative records and survey data in household surveys.
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ACCESS AND DATA QUALITY Researchers' access to and use of the complex data collected by federal statistical agencies are essential to maintain and improve data quality (Abowd and Lane, 2004)
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From page 49... ...
There is growing appreciation for the point of view that the largest single improvement that the U.S. statistical system could make is to enhance the capabilities for analysis of statistical data by researchers inside and outside of government, which, in turn, would enable statistical agencies to better understand and improve their data (see Abowd and Lane, 2003)
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