This paper discusses the critical need, in social sciences, for the development of a database infrastructure that captures the complex interactions among households and businesses at the micro level and characterizes the dynamics of the modern economy. The creation of such an infrastructure has posed a major challenge to national statistical institutes. Since most institutes collect, store, and disseminate data on the engines of economic growth--businesses and households--in twin data silos, proposals to integrate the two face technical, monetary, legal, and policy obstacles that go far beyond the norm of data collection activities. Recent efforts at the Longitudinal Employer-Household Dynamics (LEHD) Program at the U.S. Census Bureau have finally made this critical data infrastructure achievable and accessible.

Integrated Longitudinal Employee-Employer Data for the United States

Theoretical work on minimum wage policy emphasizes labor market dynamics, but the resulting implications for worker mobility remain largely untested. We show that in the teenage labor market minimum wages reduce worker flows and increase job stability. Furthermore, we find that the employment effects of the minimum wage vary considerably across markets that exhibit different degrees of labor market tightness. Our results help explain the small effects of minimum wages on employment commonly found in the aggregate data and are consistent with labor market involving search frictions.

Getting Handcuffs on an Octopus: Minimum Wages, Employment, and Turnover

Theoretical work on minimum wage policy emphasizes labor market dynamics, but the resulting implications for worker mobility remain largely untested. The authors show that in the teenage labor market, higher minimum wage standards reduce worker flows and increase job stability. Furthermore, they find that the employment effects of a relatively higher minimum wage vary considerably across markets with different levels of turnover and labor market tightness. Results help to explain the small effects of minimum wage standards on employment commonly found in the aggregate data and are consistent with labor market models that involve search frictions.

Getting Handcuffs on an Octopus

The authors wish to acknowledge funding received through NSF grants BCS 0941226 (CDI), SES 9978093, ITR 0427889, SES 0922005, and SES 1131848 (NCRN)

/pdf/a-new-method-for-protecting-interrelated-time-series-with-lwwvco6gw4.pdf

A New Method for Protecting Interrelated Time Series with Bayesian Prior Distributions and Synthetic Data

Social science researchers increasingly make use of data that is confidential because it contains linkages to the identities of people, corporations, etc. The value of this data lies in the ability to join the identifiable entities with external data, such as genome data, geospatial information, and the like. However, the confidentiality of this data is a barrier to its utility and curation, making it difficult to fulfil US federal data management mandates and interfering with basic scholarly practices, such as validation and reuse of existing results. We describe the complexity of the relationships among data that span a public and private divide. We then describe our work on the CED2AR prototype, a first step in providing researchers with a tool that spans this divide and makes it possible for them to search, access and cite such data.

/pdf/data-management-of-confidential-data-ll1pb4yv1l.pdf

Data Management of Confidential Data

The Census Bureau’s Quarterly Workforce Indicators (QWI) provide detailed quarterly statistics on employment measures such as worker and job ows, tabulated by detailed worker characteristics in various combinations. The data are released for detailed NAICS industries and for several levels of geography, the lowest aggregation of which are counties. OnTheMap, another Census Bureau product, provides a subset of these tabulations at the tract level. Disclosure avoidance methods are required to protect the information about individuals and businesses that contribute to the underlying data. The QWI disclosure avoidance mechanism we describe here relies heavily on the use of noise infusion through a permanent multiplicative noise distortion factor, used for magnitudes, counts, dierences

/pdf/dynamically-consistent-noise-infusion-and-partially-439dhlbd61.pdf

Dynamically consistent noise infusion and partially synthetic data as confidentiality protection measures for related time-series

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Dynamically consistent noise infusion and partially synthetic data as confidentiality protection measures for related time-series