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Finding County-Based Data from Hidden Sources Lisa Neidert Population Studies Center University of Michigan
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Page 1: Finding County-Based Data from Hidden Sources Lisa Neidert Population Studies Center University of Michigan.

Finding County-Based Data

from Hidden Sources

Lisa Neidert

Population Studies Center

University of Michigan

Page 2: 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

Page 3: Finding County-Based Data from Hidden Sources Lisa Neidert Population Studies Center University of Michigan.

American Community Survey (ACS)

Replacement for the census long-form questionnaire

3,000,000 households a year County-level data every year

Not quite

Page 4: Finding County-Based Data from Hidden Sources Lisa Neidert Population Studies Center University of Michigan.

ACS Products Schedule

Page 5: Finding County-Based Data from Hidden Sources Lisa Neidert Population Studies Center University of Michigan.

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

Page 6: Finding County-Based Data from Hidden Sources Lisa Neidert Population Studies Center University of Michigan.

Statistics based on ACS 1-year data: Unit is county

Page 7: Finding County-Based Data from Hidden Sources Lisa Neidert Population Studies Center University of Michigan.

Statistics based on ACS 3-year data: Unit is county

Page 8: Finding County-Based Data from Hidden Sources Lisa Neidert Population Studies Center University of Michigan.

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.

Page 9: Finding County-Based Data from Hidden Sources Lisa Neidert Population Studies Center University of Michigan.

Statistics based on ACS 3-year data: Unit is PUMA

Page 10: Finding County-Based Data from Hidden Sources Lisa Neidert Population Studies Center University of Michigan.

Convert PUMA-based statistics to county-based statistics

Page 11: Finding County-Based Data from Hidden Sources Lisa Neidert Population Studies Center University of Michigan.

PUMA-based statistic

Page 12: Finding County-Based Data from Hidden Sources Lisa Neidert Population Studies Center University of Michigan.

Converted to county-based statistic

Page 13: Finding County-Based Data from Hidden Sources Lisa Neidert Population Studies Center University of Michigan.

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

Page 14: Finding County-Based Data from Hidden Sources Lisa Neidert Population Studies Center University of Michigan.

Where do couples have egalitarian earnings profiles?

Micro-data step

Page 15: Finding County-Based Data from Hidden Sources Lisa Neidert Population Studies Center University of Michigan.

Where do couples have egalitarian earnings profiles?

Micro-data step Produce PUMA-specific results

Page 16: Finding County-Based Data from Hidden Sources Lisa Neidert Population Studies Center University of Michigan.

Where do couples have egalitarian earnings profiles?

Micro-data step Produce PUMA-specific results Convert PUMA-based results to county-based

using cross-walk

Page 17: Finding County-Based Data from Hidden Sources Lisa Neidert Population Studies Center University of Michigan.

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

Page 18: Finding County-Based Data from Hidden Sources Lisa Neidert Population Studies Center University of Michigan.

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

Page 19: Finding County-Based Data from Hidden Sources Lisa Neidert Population Studies Center University of Michigan.

Finished Product

Page 20: Finding County-Based Data from Hidden Sources Lisa Neidert Population Studies Center University of Michigan.

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


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