Saturday, November 9, 2013
:
3:30 PM
Salon III A (Ritz Carlton)
*Names in bold indicate Presenter
Robert Goerge, A. Rupa Datta and Kirk Wolter, University of Chicago
The National Survey of Early Care and Education (NSECE) is an integrated set of surveys with households with young children, institutions and individuals providing care for young children. The objective of the NSECE is to document the nation’s current utilization and availability of early care and education, and to deepen our understanding of the extent to which families’ needs and preferences coordinate well with providers’ offerings and constraints. The requirement to study the relationship between the needs of families and providers' offerings as well as the local nature of ECE usage underscore the importance of collecting and analyzing data from both the demand and supply side of ECE communities. In addition, study objectives required both nationally representative data as well as data linked closely to local conditions. To simultaneously meet these often-competing research objectives, the NSECE employs the first-ever “provider cluster” sampling design that allows for an integrated and cohesive collection of data in the field capturing household decision making, the availability of early care and education, and the workforce. The approach selects providers from a small geographic area surrounding the locations of sampled households. By exploiting census tracts and other layers of pre-defined geographical boundaries, a uniform application of the provider cluster definition provides flexibility in handling population density, square mileage of coverage area, and physical features such as lakes and highways into the modeling of how individuals access local services.
This paper describes the “provider cluster” sampling approach in detail, reports some of the characteristics of the clusters comprising the NSECE sample, explains an extension of the cluster definition being used in analyses of NSECE data to operationalize a flexible notion of a local community, and discusses the applicability of this approach to many other policy areas. The approach has broad relevance in situations where national estimates and local dynamics are both of interest, and where local use of services is likely, for example, in K-12 public schooling, access to grocery stores and other food sources, or access to emergency medical services.