Identification and Decision

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The investigator plans to continue his research on decision making in settings with partial identification of relevant population parameters. A major continuing theme is treatment choice with partial knowledge of treatment response. He also will continue his longstanding program of research on identification per se. This 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 analysis by the investigator of decision making 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 conservative approach by the investigator to empirical inference and social planning 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