# Presentation: 721968

## The Lake County Challenge 

- Robert E. Fay
- U.S. Census Bureau

## General guidance on analyzing ACS

- NRC (2007) (Citro and Kalton, eds.)
-  Report examined approaches to analysis
-  10 guidelines in the Executive Summary
- 1st guideline: *Always examine margins of error before drawing conclusions from a set of estimates.** *

## General guidance

- Beaghen and Weidman (2007)
-  General overlap but some shift of emphasis
- Example from Lake County, Illinois:
*- % speak Spanish at home*
- - Universe: age 5+, including group quarters
- - Asked in 1990, 2000 censuses, ACS

## Lake County

## The Lake County Challenge

- Challenge in handout:
- - Lake County: 644,599 in Census 2000
- - Can we identify subcounty trends?
- - Best professional effort standard

## Draft paper

- Analyses for
- 18 Townships
- 5 PUMAs
- Doesn’t take up
- Places – too complicated geographically
- Tracts – too complicated statistically

## Ambition: second paper on tracts

- Benjamini and Hockberg (1995) JRSSB
- 	“Controlling the False Discovery Rate: a Practical and Powerful Approach to Multiple Testing”
- -  apply false discovery rate calculations to tract-level analysis

## Townships

## Townships

- Start with 1990 – 2000 trends
-  Increases in all 18 townships (a few n.s.)
-  ~ 1/2 in Waukegan
-  ~ 2/3 in Waukegan, Avon, and Zion
-      (26% of 2000 county population)

## Townships

- Propose (Table 1 from 1990/2000 data):
-  Group 4: Waukegan ~21% growth
-  Group 3: Avon+Zion  ~9% growth
-  Group 2: 7 townships with 3-6% growth
-  Group 1: 8 townships < 3% growth

## Townships

- 1-year ACS data can’t be used
- Table 2: 1999-2001 vs. 2003-2005
- Non-overlapping 3-year period estimates
- Gaps: 11 out of 18 townships

## Townships

- Table 3: 1999-2003 vs. 2001-2005
- Overlapping 5-year period estimates
- No gaps, can construct groups 1-4
-  Significant increases in all 4 groups
-  Group 2 now accounting for larger share of growth

## Townships

- Table 4: Comparing annualized change
- When trend nearly linear, annualized change for 11 townships *quite similar*
-  3-year 1999-2001 to 2003-2005 (4 years)
-  5-year 1999-2003 to 2001-2005 (2 years)
*Both for estimates and standard errors*

## PUMAs

- Public Use Microdata Areas
- ~ 100,000 population
- ACS publishes annually
- NRC (2007) recommended as possible level of analysis

## PUMAs

## PUMAs

- Start with 1990 – 2000 trends
-  Must approximate from townships
-  AFF doesn’t provide tables
-  Table 6 (in draft):

## Table 6  PUMAs 1990-2000

| PUMA | Pop 5+ 2000 | 1990 % | 2000 % | Increase in % | s.e. | Increase in # | s.e. |
| --- | --- | --- | --- | --- | --- | --- | --- |
| 03301 | 101,886 | 4.4% | 7.3% | 2.9% | 0.4 | 3,023 | 375 |
| 03302 | 120,967 | 15.4% | 32.6% | 17.2% | 0.7 | 23,413 | 702 |
| 03303 | 174,132 | 4.3% | 8.9% | 4.6% | 0.4 | 10,556 | 418 |
| 03304 | 97,328 | 4.3% | 9.0% | 4.7% | 0.5 | 5,407 | 366 |
| 03305 | 97,206 | 2.8% | 5.1% | 2.3% | 0.4 | 2,891 | 295 |

## PUMAs

- 1-year ACS data erratic, hard to analyze
- 3-year, 1999-2001 vs. 2003-2005,
-     - non-overlapping, in Table 7
- 5-year, 1999-2003 vs. 2001-2005,
-     - overlapping, in Table 8

## Table 9  Annualized Change

| PUMA | 1-yr rate pers/yr | s.e. | t-test | 1-yr rate pers/yr | s.e. | t-test |
| --- | --- | --- | --- | --- | --- | --- |
| 03301 | 418 | 225 | 1.9 | 334 | 268 | 1.2 |
| 03302 | 2,275 | 400 | 5.7 | 2,360 | 435 | 5.4 |
| 03303 | 2,140 | 358 | 6.0 | 2,156 | 348 | 6.2 |
| 03304 | 912 | 298 | 3.1 | 969 | 289 | 3.4 |
| 03305 | 75 | 210 | 0.4 | 108 | 209 | 0.5 |

## Discussion: Guidelines

-  Case study calls into question recommendation to avoid analysis of overlapping periods.
-  In other respects, does case study fall within NRC guidance?

## Discussion: Geographic level

-  NRC report suggests difficult to use ACS to track change, except for large areas
-  The case study appears to agree
-  grouped townships into larger areas
-  PUMA-level analysis possible

## Discussion: Helping users

-  Possible consideration: PUMA results from 1990 and 2000 censuses
-  Standard errors for simple aggregates
-  Possible displays of differences, trends?

## Discussion: Tools

-  The analysis was time consuming
-  Primarily in Excel, but new study would require almost starting over
-  Possible role for the R statistical software? Another approach?