# Presentation: 666773

## ACS Data Release Rules

- Doug Hillmer
- Data Products Area
- American Community Survey Office
- U.S. Census Bureau
- October 11, 2006

## Limitation of Disclosure Risk
The Census Bureau’s Disclosure Review Board (DRB) must clear all data products prior to their release to the public.
Assurance of Statistical Reliability
Data users need to be able to use ACS estimates as official Census Bureau data. Thus, some rules must be in place to ensure minimum reliability of estimates.
Statistical reliability is assured by:
Population size thresholds below which estimates are not released
Data release testing and collapsing of tables that fail

- The Census Bureau’s Disclosure Review Board (DRB) must clear all data products prior to their release to the public.
**Assurance of Statistical Reliability**
- Data users need to be able to use ACS estimates as official Census Bureau data. Thus, some rules must be in place to ensure minimum reliability of estimates.
**Statistical reliability is assured by:**
- Population size thresholds below which estimates are not released
- Data release testing and collapsing of tables that fail

**The Census Bureau Will Not Release All Available Estimates to the Public**

**Notes:**
While the goal of the Census Bureau has always been to release as much data as possible to the public, there are two main factors that prevent us from releasing all of our estimates to the public:

	Disclosure avoidance rules that estimates may fail to meet
	“Unacceptable” statistical reliability of the estimates

The first factor is under the control of the Census Bureau’s Disclosure Review Board.  The DRB is an independent body at the Census Bureau that answers only to the Director.  Therefore, we must abide by its dictates.

The second factor is what I will be concentrating on today.   In particular, I will introduce the “collapsing” concept via an example.

 Of course, ACS is not the only survey with data release requirements.  For example, CPS also has its own data release requirements.  However, CPS and, up until now, the ACS have been using what we could call “rules of thumb”.  And, frankly, these rules have been rather weak.   We decided that ACS had to have more defensible data release rules based on  statistical concepts.

## The ACS “Identity Crisis” on Reliability

**Ultimately, the 5-year estimates, with *****no “data release rules”***** acts as a long-form replacement**
**Single-year ACS sample is more like a current demographic survey – although much larger in size**
**Question to answer for single-year estimates:  Do we accept less detail in our measures of characteristics or do we allow more detail but with data release rules in place? Less detail punishes those areas with the diversity to support the detail.**

**Notes:**
Demographic, social, and economic characteristics are distributed very unequally across geographic areas.  Example: San Francisco has many more Asian and Native Hawaiian residents than any other city of comparable size in the U.S. (except Honolulu).  Farming-related occupations are virtually non-existent in Rhode Island (need to check this!), but they are well represented in Nebraska.

## Choices for displaying estimatesin ACS data products

**No suppression**
- Publish full detail with no suppression but higher pop threshold (eg., 500,000)
- Publish limited set of estimates for all areas with 65,000+ pop
- Published more detailed estimates for higher pop threshold and limited set for lower threshold
**With suppression or Warnings**
- Define a very detailed set of estimates for all geo areas with 65,000+ pop and suppress estimates that fail reliability test
- Define a very detailed set of estimates for all geo areas with 65,000+ pop and flag estimates that fail reliability test

## Filtering <<Data Release Rules >>

**Goal:  to identify “weak” tables**
**Some tables have many zero or “near zero” cells and relatively large standard errors**
**Filtering <<Data Release>> rule used during 2000-2004 ACS: drop tables if...**
- Universe is less than 500 (weighted)
- Average cell size is less than 2 cases (unweighted)
**filtering <<data release>> rule used now: **
- Accept if median coefficient of variation is less than or equal to 61%
- Otherwise, collapse and review again

**Notes:**
Universe – we use this term to describe the weighted count of all those cases that qualify for the distribution (or other measure) that is shown for some characteristic in a base table.  Thus, the estimate shown in the first cell of the table (usually labeled “Total:”) gives the estimated size of the universe of the table for a given geographic area.  Ex., total workers 16 years and over.

## Why not just use cell suppression as is done for the Economic products?

- Advantages
- Gets rid of the “bad” estimates
- Keeps the “good” estimates (depends on complementary suppression)
- Disadvantages
- Creates “holes” in distributions
- Makes new problems for combined estimates (eg., in derived products, such as data profiles)
- Produces a new set of problems for year-to-year comparisons

## Data Release Testing – Step by Step

**Compute coefficients of variation**
- Coefficient of variation = standard error / estimate
- Standard error = (upper bound – estimate) / 1.65
- If the estimate = 0 set coefficient of variation = 100%
**Ignore total and sub-total lines in base table**
**Sort coefficients of variation in descending order**
**Find the middle value (the median)**
**If the median is greater than 61% the table FAILS (median > 61% means more than half of the cells have a lower bound of 0; i.e., these cells are not statistically different from 0)**
**If the median is 61% or less the table PASSES**

## Collapsing

**Goal:  release a simplified version of a base table for a geographic area that otherwise would get nothing**
**Decisions on design of collapsed tables are made by subject-matter experts at the Census Bureau**
**For operational reasons, only one collapsed version of each base table will be available regardless of geographic area**

## How the Data Release Rules will  Work with Collapsed Versions of Base Tables

## More About Collapsing

**Collapsed Tables are designed to assure that derived products (profiles, ranking tables, subject tables,...) can still be sourced from the base tables**
**2005 Tables: if a table passes filtering and a collapsed version exists, publish both the original version and the collapsed version for that geographic area**

**Notes:**
We still have several months of work ahead of us on the collapsing, and we will be determining exactly how the collapsed versions of base tables will be integrated into the entire base tables product.  

Derived products such as profiles will continue to be “indirectly” filtered; I.e., if, for a geographic area, neither the original version nor the collapsed version of the table could be published, then the lines of the profile based on that table are suppressed for that area.

## Problems to fix in the current implementation of the data release rules

- Collapsed versions missing in some cases
- Collapsed versions that aren’t working
- Poor choices in “sourcing” for derived products (eg., profiles)