Local Demographic Analysis: Using Census Data to Understand Changing Neighborhoods and People

1. Local Demographic Analysis:Using Census Data to Understand Changing Neighborhoods and People Todd Blickenstaff Hablamos Juntos Scottsdale, AZ January 8, 2003

2. Workshop Agenda • General Overview of Census • Understanding Census Geographic Categories • Demonstration of the American Factfinder website • Accessing the Data • Basic and Advanced Demographic Variables • Analyzing Your Results • Basic Information about Population, Race, Income, and Age • Tips on Presenting Data

3. What is the Census? • A census is an official count of the entire population and housing units. • Done every ten years. • Implications for House of Representatives, electoral college, and funding allocations. • Comprised of a short form and a long form.

4. Short Form- http://www.census.gov/dmd/www/pdf/d61a.pdf • Counts population and very basic demographic data • How Census treats Ethnicity vs. Race - • Ethnicity- #7, Hispanic Yes or No • Race- #8, subjective, social construction, shared physical characteristics (White, Black, American Indian, Asian, Pacific Islander, Other) • Age, sex, phone number, home ownership • Also called SF1 (Summary File), STF1, STF1A • To be asked of everyone in the US

5. Long Form- http://www.census.gov/dmd/www/pdf/d02p.pdf • Includes everything in SF1 plus: • detailed economic, education, income, social, transportation, workforce, ancestry, household amenity, and housing information • Sent to one in six households in US • Also called SF3, STF3, STF3A • Most commonly used data set

6. How accurate are Census data? • SF1 sent to 83% of housing units • SF3 sent to 17% of housing units • Together they form a “complete count” reflected in SF1 • National response rate was 67% (up from 65% in 1990) • Higher response rate than 1990 • forms translated into 5 languages • marketing campaign

7. Undercount • Sub-populations such as homeless, children, ESL, communities of color are undercounted at higher rates than the general population. • Bureau estimates it missed 1.2% of population (about 3.3 million people) • 1.1 million children • 20% of child undercount was Hispanic • 72,000 Hispanic children were missed in CA, 42,000 in TX • Each person not counted represents a loss of about $3000 in state and federal funds- (housing, community and economic development, transportation, job training, low income home energy assistance, Medicaid, foster care)

8. Levels of Census Geography • National • Regional- (e.g. Pacific, Statewide, Metropolitan Statistical Area MSA) • Local- (e.g. County, Zip Code, Census Tract, Block Group)

9. Most Commonly Used Census Geographic Categories • Zip code- defined by US Postal Service, based on density, service patterns, how much mail can be delivered, not updated regularly, use with caution • Census Designated Place (CDP)- closely settled, named, unincorporated communities (Kerr, MT pop. 17) • County- As defined by government • Census Tract- 2500 to 9000 people (usually 4000), tracts are good unit to use, 4 digits, 2 digit suffix (3508.01) • Block Group- about 1000 people, groups of blocks with the same first digit • Census Block- bound by physical elements like streets, railroad tracks, highways, ditches, or rivers; 4 digits • Factfinder- Enter a Street Address to determine census tract, block group, etc. http://factfinder.census.gov

10. Block 4002- Pomona, CA 2000

11. Block Group 4- Pomona, CA 2000

12. Census Tract 4026, Pomona, CA 2000

13. Most Commonly Used Census Geographic Categories Metropolitan Statistical Area (MSA) • Defined by Census as an urbanized area/city with 50,000+ inhabitants and a total metropolitan population of 100,000+. • The geographic area of an MSA is usually defined in terms of counties. • Lansing-East Lansing MSA consists of Clinton, Eaton, and Ingham Counties • Green Bay MSA is defined as Brown County.

14. Most Commonly Used Census Geography • Consolidated Metropolitan Statistical Area (CMSA)- consists of 2 or more adjoining MSA’s having a combined population of 1 million or more. e.g. Baltimore-Washington, DFW, LA-Orange-Riverside, Detroit-Ann Arbor-Flint • Primary Metropolitan Statistical Area (PMSA)- When combined into a CMSA, each component metropolitan area is referred to as a PMSA. For example, the Dallas-Forth Worth CMSA consists of the Dallas PMSA and the Fort Worth PMSA. Boston-Worcester-Lawrence CMSA consists of 10 PMSA’s

15. Income Data • Supplemental Security Income (SSI) payments • Free and reduced lunch recipients • Food stamp recipients • Received any public assistance • Percent of median income • 30% extremely low, 50% very/moderately low, 80% low • Poverty- 2001, $18,267 for a family of four, not adjusted regionally

16. Age • Available by single year and groupings • Age groups are fixed in age • 5 year olds • School-aged kids (5-17) • Seniors (64 years and older) • Cohorts have fixed membership by birth year • Baby Boomers- 1946-64 • Generation X- 1965-75 • Generation Y- 1976-82 • Generation I- 1983-2002

17. Housing Units • Tenure- own or rent • Overcrowding- rooms in unit/people per unit • Price of house • Rent • Duration of occupancy

18. Go towww.census.govClick on American FactFinder

19. Select a Data Set

20. Select Summary File 1 and click on Detailed Tables

21. Select MSA under Geographic type using the pull down menu, then select Phoenix-Mesa, AZ MSA

22. Use subject or keyword to locate tables Use subject or keyword to locate tables

23. -Select Total Population -Click Add, -Click Show Table

24. The Art of Presenting Data • Your exhibit should “click” within 10 seconds or else most readers won’t bother to figure it out. • Decide what type of graphic best fits your data • Table- 20 or fewer numbers • Graph- more than 20 numbers • Avoid “grid prison”– too many vertical lines • Map • Often good to round (29% instead of 28.76%) • Use ratios and indexes to save readers work • Unemployment rate is 15% instead of “Out of 200 people, 30 are unemployed”

25. The Art of Presenting Data • Focus attention on comparisons • Between populations (Latino vs. Asian) • Over time (1990 vs. 2000) • Avoid too much textual explanation