CREAT: Census Research Exploration and Analysis Tool

Applying Current Core Based Statistical Area Standards to Historical Census Data, 1940-2020

January 2025

Written by: Todd Gardner

Working Paper Number:

CES-25-10

Abstract

In the middle of the twentieth century, the Bureau of the Budget, in conjunction with the Census Bureau and other federal statistical agencies, introduced a widely used unit of statistical geography, the county-based Standard Metropolitan Area. Metropolitan definitions since then have been generally regarded as comparable, but methodological changes have resulted in comparability issues, particularly among the largest and most complex metro areas. With the 2000 census came an effort to simplify the rules for defining metro areas. This study attempts to gather all available historical geographic and commuting data to apply the current rules for defining metro areas to create comparable statistical geography covering the period from 1940 to 2020. The changes that accompanied the 2000 census also brought a new category, "Micropolitan Statistical Areas," which established a metro hierarchy. This research expands on this approach, using a more elaborate hierarchy based on the size of urban cores. The areas as delineated in this paper provide a consistent set of statistical geography that can be used in a wide variety of applications.

Document Tags and Keywords

Keywords Keywords are automatically generated using KeyBERT, a powerful and innovative keyword extraction tool that utilizes BERT embeddings to ensure high-quality and contextually relevant keywords.

By analyzing the content of working papers, KeyBERT identifies terms and phrases that capture the essence of the text, highlighting the most significant topics and trends. This approach not only enhances searchability but provides connections that go beyond potentially domain-specific author-defined keywords.
:
census data, metropolitan, country, area, region, urban, town, urbanization, city, geography, district, neighborhood, geographic, disparity

Tags Tags are automatically generated using a pretrained language model from spaCy, which excels at several tasks, including entity tagging.

The model is able to label words and phrases by part-of-speech, including "organizations." By filtering for frequent words and phrases labeled as "organizations", papers are identified to contain references to specific institutions, datasets, and other organizations.
:
Metropolitan Statistical Area, Service Annual Survey, Center for Economic Studies, Office of Management and Budget, Federal Register, American Community Survey, Core Based Statistical Area

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