Cornell University
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Understanding Social and Economic Data

INFO 7470

Spring. 4 credits.

Letter grades only.

Enrollment limited to: graduate students.

J. Abowd, L. Vilhuber.

The course is designed to teach students basic and advanced techniques for acquiring and transforming raw information into social and economic data. The current version is particularly aimed at American Ph.D. students who are interested in using confidential U.S. Census Bureau data, and the confidential data of other American statistical agencies that cooperate with the Census Bureau. We cover the legal, statistical, computing, and social science aspects of the data “production” process. Major emphasis is placed on U.S. Census Bureau data that are accessible from the Bureau’s Research Data Center network. Graduate students and faculty who are planning to use RDC-based data, or are seriously considering it, should pay particular attention to the labs related to the proposal process. The RDC-accessible data products covered in the course include the internal files used to manage the Census Bureau’s household and establishment frames; the Longitudinal Employer-Household Dynamics (LEHD) micro data; the Longitudinal Business Database (LBD) and its predecessor the Longitudinal Research Database (LRD); internal versions of the Survey of Income and Program Participation (SIPP), Current Population Survey (CPS), American Community Survey (ACS), American Housing Survey (AHS), and the 1990, 2000, and 2010 Decennial Censuses of Population and Housing; the Employer and Non-employer Business Registers (BR and SSEL); the Censuses and Annual Surveys of Manufactures, Mining, Services, Retail Trade, Wholesale Trade, Construction, Transportation, Communications, and Utilities; Business Expenditures Survey; Characteristics of Business Owners; and others. Students will also be introduced to the NSF-sponsored Virtual Research Data Center and Social Science Gateway to XSEDE. This course is part of the dissemination activities of the National Science Foundation-Census Research Network (Cornell Node).