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 National Science
Foundation Award #0549544 |
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Identification and Empirical Inference |
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| Investigator(s): |
Charles Manski (PI)
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| Sponsor: |
Northwestern University, IL 60208 8474913003
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| Start Date/Expiration Date |
2006-08-01 to 2007-07-31 (amended 2006-03-07) |
| Awarded Amount to Date: |
$69,669 |
| Abstract: The investigator plans to expand his recent research on treatment choice with partial knowledge of treatment response, which has developed out of his earlier work on partial identification. Part of the research will
address general methodological questions and another part will investigate specific substantive problems of
social planning. He also will continue his longstanding program of research on partial identification per se.
Intellectual Merit: The investigators research on identification is deliberately conservative. The traditional
way to cope with sampling processes that partially identify population parameters has been to combine the
available data with assumptions strong enough to yield point identification. Such assumptions often are not
well motivated, and empirical researchers often debate their validity. Conservative analysis enables
researchers to learn from the available data without imposing untenable assumptions. It enables establishment
of a domain of consensus among researchers who may hold disparate beliefs about what assumptions are
appropriate. It also makes plain the limitations of the available data.
The investigators analysis of treatment choice is similarly conservative. His research shows how
social planners and other decision makers can cope coherently with difficult problems of choice under
ambiguity induced by identification problems and the necessity of statistical inference from sample data,
without imposing untenable assumptions. This is achieved using well-established principles of statistical
decision theory, particularly through application of the minimax-regret criterion.
Broader Impacts: Many persistent public policy controversies reflect divergent beliefs about the effects of
government policy on society. Such divergent beliefs are often manifest in dueling policy studies that use
different analytical approaches or data sources to reach different policy conclusions. Each study may make
sense in its own terms, each combining data with conjectures to draw logically valid conclusions. However,
there may be no way to determine which study (if either) makes realistic conjectures and which (if either)
draws empirically correct conclusions. The investigators conservative approach to empirical inference and
treatment choice can enable the public to better evaluate the credibility of existing policy studies, enhance
the credibility of future policy research, and improve the quality of policymaking |
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| NSF Org: |
SES - Division of Social and Economic Sciences |
| Award Number: |
0549544 |
| Award Instrument: |
Continuing grant |
| Program Manager: |
Julia I. Lane
SES Division of Social and Economic Sciences
SBE Directorate for Social, Behavioral & Economic Sciences
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| NSF Program(s): |
ECONOMICS, METHOD, MEASURE & STATS |
| Field Application(s): |
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| Program Reference Code(s): |
UNASSIGNED, 0000 |
| Program Element Code(s): |
1320
METHOD, MEASURE & STATS, 1333 |
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