Understanding Census Geography Lisa Neidert NPC Workshop: Analyzing Poverty and Socioeconomic Trends Using the American Community Survey July 12 – July.

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Presentation transcript:

Understanding Census Geography Lisa Neidert NPC Workshop: Analyzing Poverty and Socioeconomic Trends Using the American Community Survey July 12 – July 15, 2010

Census Geography

Geographic Areas: with 1-year and 3-year data

What’s available in the ACS for single year data: via maps  Maps showing counties and places for each state (or the nation)  8_reference_maps.htm 8_reference_maps.htm

Counties with single year data: ACS 2008

Almost all counties: DE, MA

Few counties, no places: VT and WY

State with American Indian Places: AK, AL, LA, NC, OK

Counties with 3-year data: ACS

States where all counties are over 20,000  Connecticut  Delaware  District of Columbia  New Hampshire  New Jersey  Rhode Island

What geographies are available in the ACS

Geographical Areas (Texas): Covered in  ACS 2006=2008 Geographical Areas ACS 2006=2008 Geographical Areas

What’s available in the ACS: via Look-up tables  Geographic entities available for 1-year data (2008) Geographic entities available for 1-year data (2008)  Geographic entities available for 3-year data ( ) Geographic entities available for 3-year data ( )

Not ready for prime-time: census tracts and zip codes  Need 5-year estimates file 2005 – 2009 Available 2010 for Census Tracts; 2011 for Zip Codes  Annual updates thereafter 2006 – – 2011, etc.  Possible delay for 5-year data – only an unsubstantiated rumor

Example Census Tracts for community districts

Zip codes  Not census geography However, big demand for zip code data  Census Bureau builds ZCTAs via census blocks  ZCTA FAQs html  Fun resource

What to do with a 2011 release of zip code data?  See Exercise 4: e4_DealingWithDelays.pdf e4_DealingWithDelays.pdf  This exercise shows how to build zip code characteristics from census tract characteristics

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

PUMAs....  PUMAs do not have good comparability over time (1990, 2000).  PUMA geographies for the ACS are the same as the 2000 boundaries  PUMAs are reasonable substitutes for counties  Smallest geography available in the microdata.

PUMAs  Can be valuable for bypassing geographic restrictions when one wants national information at the county level  Create pseudo counties based on a cross-walk between PUMAs and counties

Statistics based on 1-year ACS data Unit is county

Statistics based on 3-year ACS data Unit is county

Statistics based on 1-year ACS data Unit is PUMA

Illinois example: PUMA to county example

PUMA to County Widget  Based on PDQ-Explore output  Based on American FactFinder output  Try one this week

Class Exercises Today   Poverty Hot-spots (ACS 2008)  Census tract data (Census 2000)  Bulk downloads, zip code (Census 2000)  Dealing with Delays: Creating zip code characteristics from census tract data

PUMAs via Maps  Reasonable tool for rural parts of a state  Somewhat unwieldy for urban areas  Multiple maps per state html

PUMAs via text  Describes PUMA composition  By: County County subdivision Place Census tract   /SUPERPUMA pct.html /SUPERPUMA pct.html

Metropolitan areas  Defined by Office Management Budget (OMB)  es/metrodef.html es/metrodef.html  Historical Definitions  es/pastmetro.html es/pastmetro.html  Researcher is free to follow own definitions  Census Bureau follows OMB definitions