finding county-based data from hidden sources
DESCRIPTION
Finding County-Based Data from Hidden Sources. Lisa Neidert Population Studies Center University of Michigan. Three Problems. Produce county-based data from summary data Not all counties represented Produce county-based data from microdata County identifiers are not in microdata - PowerPoint PPT PresentationTRANSCRIPT
Finding County-Based Data
from Hidden Sources
Lisa Neidert
Population Studies Center
University of Michigan
Three Problems
Produce county-based data from summary data Not all counties represented
Produce county-based data from microdata County identifiers are not in microdata
Produce county-based data from microdata County identifier in data Some county populations are too small for reliable
data
American Community Survey (ACS)
Replacement for the census long-form questionnaire
3,000,000 households a year County-level data every year
Not quite
ACS Products Schedule
Distribution of US counties by size
1,321
1,033
788
0
500
1,000
1,500
2,000
2,500
3,000
3,500
1
65,000+
20.000 - 59,999
1 to 19,999
Statistics based on ACS 1-year data: Unit is county
Statistics based on ACS 3-year data: Unit is county
What are PUMAs?
Public Use Microdata areas
Combination of population geographies that sum to at least 100,000 population.
In rural areas, several counties will form a PUMA. In an urban area, a county will be subdivided into multiple PUMAs.
PUMAs do not cross state boundaries
Smallest geography available in the microdata.
Statistics based on ACS 3-year data: Unit is PUMA
Convert PUMA-based statistics to county-based statistics
PUMA-based statistic
Converted to county-based statistic
Example based on microdata
Previous example used a table from summary data Distribution of the baby boom population
Microdata allows user-generated table Distribution of earning equality among
couples
Where do couples have egalitarian earnings profiles?
Micro-data step
Where do couples have egalitarian earnings profiles?
Micro-data step Produce PUMA-specific results
Where do couples have egalitarian earnings profiles?
Micro-data step Produce PUMA-specific results Convert PUMA-based results to county-based
using cross-walk
What about microdata with county identifiers?
Identifiers on Natality Detail files 1968-1988 | all counties identified 1989-2005 | only counties > 100,000 2006+ | no state or county identifiers
Distribution of births by county (1988) <100 | 512 counties <500 | 1,998 counties <1000 | 2,498 counties
Some extreme cases Loving county, TX 2 births Hinsdale county, CO 3 births Petroleum county, MT 3 births
Solution
Cumulate small population counties by PUMA Calculate Fertility measures
Total Fertility Rate Timing of fertility events Non-marital childbearing
Use cross-walk to assign PUMA characteristic to counties
Finished Product
Future Directions
Cautionary Pseudo-county data Small population-based statistics County population may be incorrect weight
Web-based tool (PUMA to County) Input PUMA-based table Output County-based table GIS ready
Include indicator for multi-county PUMAs