Inferring disability status from corrupt data
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The Department of Economic Science was founded in 1898 to teach economic theory as a truth of industrial life, and was very much concerned with applying economics to business and industry, particularly agriculture. Between 1910 and 1967 it showed the growing influence of other social studies, such as sociology, history, and political science. Today it encompasses the majors of Agricultural Business (preparing for agricultural finance and management), Business Economics, and Economics (for advanced studies in business or economics or for careers in financing, management, insurance, etc).
History
The Department of Economic Science was founded in 1898 under the Division of Industrial Science (later College of Liberal Arts and Sciences); it became co-directed by the Division of Agriculture in 1919. In 1910 it became the Department of Economics and Political Science. In 1913 it became the Department of Applied Economics and Social Science; in 1924 it became the Department of Economics, History, and Sociology; in 1931 it became the Department of Economics and Sociology. In 1967 it became the Department of Economics, and in 2007 it became co-directed by the Colleges of Agriculture and Life Sciences, Liberal Arts and Sciences, and Business.
Dates of Existence
1898–present
Historical Names
- Department of Economic Science (1898–1910)
- Department of Economics and Political Science (1910-1913)
- Department of Applied Economics and Social Science (1913–1924)
- Department of Economics, History and Sociology (1924–1931)
- Department of Economics and Sociology (1931–1967)
Related Units
- College of Agricultural and Life Sciences (parent college)
- College of Liberal Arts and Sciences (parent college)
- College of Business (parent college)
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Abstract
In light of widespread concerns about the reliability of self-reported disability, we investigate what can be learned about the prevalence of work disability under various assumptions on the reporting error process. Developing a nonparametric bounding framework, we find that inferences are highly sensitive to the maintained assumptions - especially to how one models po- tential inconsistencies between subjective self-assessments of work limitation and more objective measures of functional limitation. We estimate tight bounds under our strongest assumptions but then find that identification deteriorates rapidly as the assumptions are relaxed.