American Community Survey

The ACS Group Quarters (GQ) sample was designed to produce state-level estimates of characteristics of the GQ population. However, GQ residents are a component of the total resident population, and characteristics of the total population are published for smaller areas. There is an insufficient GQ sample to produce estimates for these smaller areas. Data users had noticed large year-to-year fluctuations in estimates of counties, and a lack of representation of GQ sample across small areas had been documented. In order to address these concerns, the GQ population sample has been supplemented by a large-scale, whole person imputation into not-in-sample GQ facilities starting with the 2011 ACS data release, which includes the 2011 ACS 1-year, 2009-2011 ACS 3-year, and 2007-2011 ACS 5-year estimates. Roughly as many GQ persons are imputed as interviewed.

Estimates for substate geographies of the total GQ population and of characteristics of the total resident population will be more reliable than earlier years with the previous methodology. The state-level estimates of characteristics of the GQ population will be relatively unchanged by the new methodology.

Data users should notice little or no difference regarding ACS data products. In particular, the Census Bureau will continue to produce only state-level estimates of characteristics of the GQ population. We do not plan to release estimates of characteristics for substate areas for this population in the future. There is a break in series between the 2010 and earlier ACS data products and the 2011 ACS data products. Namely, the 2010 and earlier ACS data products only have sample GQ person data, whereas the 2011 ACS data products have both the imputed and sample GQ person data for years 2007-2011. This is particularly relevant for substate areas where the GQ population is a significant portion of the total resident population. For more information, read the full ACS Group Quarters Small Area Estimation user note [PDF 82.9KB].

The list of addresses the Census Bureau used to select the Puerto Rico Community Survey (PRCS) sample underwent substantial changes in 2010, and to a lesser extent, in 2011. These changes are the result of 2010 Census address canvassing and enumeration activities. Due to these changes and the lack of independent housing unit estimates to use as controls in the weighting process, the PRCS estimates of total housing units and households, as well as vacant housing units, changed significantly between 2009 and 2010 and also between 2010 and 2011.

In addition, as a result of the weighting methodology procedure to generate consistent estimates of householders, households and occupied housing units, users may see impacts in other PRCS characteristics such as relationship and marital status, and average household size due to the change in occupied housing units.

For these reasons, the Census Bureau recommends using caution when comparing PRCS estimates across these years. The Census Bureau is taking the following steps to address this issue for the future: 1) working with the Commonwealth of Puerto Rico to develop independent housing unit estimates that can be used as housing unit controls; and 2) revising the weighting methodology to address unexpected changes in the housing unit inventory.

Beginning with the 2011 ACS data release, the Census Bureau updated the model used to compute margins of error for zero-estimate counts. The constant, or k, value in this model has been revised from 400 to 223. Detailed information about this modified model may be found in the full user note [PDF 86.8KB].

On October 10, 2010 the Netherlands Antilles were dissolved. Bonaire, Saba, and Sint Eustatius became special municipalities of the Netherlands. Curaçao and Sint Maarten became constituent countries within the Kingdom of the Netherlands. For the 2011 ACS place of birth codes, Netherlands Antilles remains as code 336. Bonaire has been assigned new place of birth code 344, Curaçao is 345, Saba is 346, Sint Eustatius is 347, and Sint Maarten is 348.

Beginning with the 2010 ACS 1-year estimates, the Census Bureau changed the way it estimated income percentile limits in the creation of table B19080, switching from reported values to interpolated values.

In some areas, this change had a significant effect on income percentile limits of $250,000 or more. For instance, in the 2009 ACS 1-year estimates for New York County, NY, the published "Lower Limit of Top 5 Percent" of households was $448,387. In the 2010 ACS 1-year estimates, the same estimate was capped at $250,000 (published as "$250,000+").

This change was made to protect respondent confidentiality. The new method was also used in the creation of the 2008-2010 3-year estimates and the 2006-2010 5-year estimates, and will be used in subsequent ACS data releases.

The 2010 Census and the American Community Survey (ACS) both measure vacancy. Because they differ in their design and data collection methods, users should note that the results may also differ. For example, the 2010 Census shows a gross vacancy rate of 11.4 percent while the 2010 ACS 1-year estimates show a rate of 13.1 percent. Historically we have noted similar differences between census and survey results regarding vacancy rates.

As examples of how the 2010 Census and the ACS differ, the 2010 Census measured vacancy as of April 1, 2010, while the 2010 ACS 1-year estimates measured vacancy throughout all of 2010 as of the date of interview. In addition, the ACS by necessity, had to draw a sample from our master address list before the 2010 Census operations had finished updating the address list. Thus, the 2010 ACS 1-year estimates do not measure the same universe of addresses as the 2010 Census. Also, the 2010 Census and the ACS differ in some of their data collection operations.

The 2010 Census results are useful for looking at small areas of geography while the 2010 ACS 1-year estimates are useful for looking at cross-tabulations of characteristics. For more information, read the report Comparing 2010 American Community Survey 1-Year Estimates of Occupancy Status, Vacancy Status, and Household Size with the 2010 Census - Preliminary Results [PDF 452KB].

Remote Alaska is a set of rural areas in Alaska that are difficult to access and for which all housing unit (HU) addresses are treated as unmailable. Due to the difficulties in field operations during specific months of the year, and the extremely seasonal population in these areas, data collection operations in Remote Alaska differ from the rest of the country.

All designated addresses are assigned to either January or September, and respondents receive a personal interview (no mail or telephone interview). The group quarter sample in Remote Alaska is assigned to January or September using the same procedure. Up to 4 months is allowed to complete the HU and GQ data collection for each of the two data collection periods. Learn more about the Remote Alaska sample in Chapter 4 of the Design and Methodology Report.

Unexpectedly, the estimates of margins of error (MOE) for a small number of 2005-2009 ACS characteristic estimates are larger than the MOEs for the same statistics based on 2007-2007 ACS estimates, and to a lesser extent the MOEs for the 2009 estimates at the national and state levels. For example, we are seeing the 5-year MOE for the estimate of total number of households is over twice the size of its 3-year MOE and is about one and a half times the size of its 1-year MOE. This is unexpected but does not necessarily reflect an error in processing. In theory, the 5-year MOEs should be smaller than both because the estimates are based on larger sample sizes. However, the estimates of MOE depend on other factors in addition to sample size.

The margins of error are estimated using replicate weights. Looking at various stages of the weighting process, we see a substantial increase in some multi-year MOEs occurring at a step known as g-weighting, a method that is not used for the 1-year estimates. This weighting step adjusts the housing unit population counts by demographics using auxiliary data from administrative data sources in an attempt to reduce both the bias and MOE of the estimates. For the 3-year estimates and for the 5-year estimates for small areas, the g-weighting adjustment generally reduces both the bias and estimated MOE. However for the 5-year estimates for large areas, g-weighting occasionally increases the estimated MOEs. That is, the impact of the g-weighting is different at the national and state levels than it is for small areas, such as census tracts. At this point, there is no evidence that the MOE estimates were computed incorrectly (i.e. not according to specifications) or that a processing error was made. Furthermore, the MOEs for national and state estimates are already so low that a modest increase will typically not affect inferences made with those estimates.

We have concluded that this unexpected phenomenon does not affect the 5-year estimates in any important way. The g-weighting adjustment is helping to reduce MOEs of the 5-year estimates at lower levels of geography (counties, places, and tracts) as expected. Further investigation of the properties of g-weighting for large area estimates is planned.

As a result of concerns raised about the ACS estimates of total and subgroup population in some incorporated places, the ACS has adopted subcounty total population controls. This change in methodology will affect the ACS estimate of the total number of people in a particular location, but the distribution of characteristics for the most part remains comparable across years. This change applies to the 2009 ACS 1-year estimates and all future ACS 1-year, 3-year, and 5-year estimates.

The basic method is to add a procedure that controls for total population at the subcounty level while controlling for total population and additional demographic characteristics at the county level. The controls for both the subcounty and county level come from the Population Estimates Program (PEP) which is released annually by the Census Bureau. Subcounty estimates used to construct weights in the multiyear ACS products rely on an average of PEP’s subcounty estimates over the 3- or 5-year period. In general, one should expect very close agreement between the ACS estimates and the PEP estimates, but they may not be exactly equal. As with any methodological change, a small number of places may observe changes in the distribution of characteristics that are the result of the new methods. To learn more about possible impacts on characteristics, see the Research Note  [PDF 28KB] on this new method.

A small number of errors were detected in the 2008 ACS internal microdata file, leading to errors in the 2008 ACS 1-year PUMS files and the 2006-2008 ACS 3-year PUMS files. Corrected 2008 ACS microdata will be used to produce the 2005-2009 ACS 5-Year and the 2007-2009 ACS 3-year data products as well as all future multiyear PUMS products. The 2008 ACS 1-year PUMS files and the 2006-2008 3-year PUMS files were corrected to the extent they could be without posing a possible disclosure risk.

The following housing variables were corrected: telephone service (TEL), number of rooms (RMSP), number of bedrooms (BDSP), kitchen facilities (KIT), and their respective allocation flags. For more detail on these errors see Errata Note #53 and #54. The "speaking a language other than English at home" (HHL) variable was also corrected due to the editing error referred to in Errata Note #61.

The method used to make the correction involved extracting the corrected 2008 ACS microdata for these items along with the appropriate record identification. This extract was matched to the original 2008 ACS 1-year PUMS records and the incorrect data items were replaced with the corrected data items. The corrected 2008 1-year PUMS file was then used to recreate the 2006-2008 ACS 3-year PUMS file.

In addition, on the 2006-2008 3-year PUMS housing unit-level files, the variable FMVYP has been renamed FMVP so that it is consistent with the documentation and previous files.

The original PUMS files have been removed and replaced with the revised PUMS files for the affected releases. To request the original PUMS files, please send an e-mail to acso.users.support@census.gov.

There was a problem in the collection of the 2007 and 2008 travel time to work data for Manatí Municipio, Puerto Rico. No other characteristics appear to have been affected. The data tables containing travel time estimates for Manatí Municipio have been removed or altered on American FactFinder.

The tables for Puerto Rico will not be shown because the results of a cognitive evaluation of the Spanish language translation of the questions on plumbing and kitchen facilities indicated that respondents in the Puerto Rico Community Survey may not have clearly understood the intent of these revised questions introduced in 2008. This spreadsheet file (XLS) contains the full list of tables, table lines, and geographic areas that will not be released due to this problem.

In the 2008 ACS, there was a higher percentage of persons with Alaska as their state of residence one year prior, than the levels estimated in previous years. Investigation of the relevant cases has shown that a large proportion of these respondents had no additional residence 1 year ago geographic information below the state level (thus not allowing verification of the report of 'Alaska'). The exact source and cause of this change in the estimate has yet to be determined, but investigation is ongoing.

For certain group quarters (GQ) characteristics and GQ types, the item nonresponse rates do not meet the Census Bureau's quality standards. Missing data for a particular question is called item nonresponse. It will occur when a respondent fails to provide an answer to a question or when an invalid answer is provided. The Census Bureau uses allocation methods to correct for item nonresponse and thus, allocation rates are used to measure the magnitude of item nonresponse. The Census Bureau has established a standard that states users should be made aware of key data items with allocation rates exceeding 20 percent. Several GQ population characteristics in the subject tables did not meet this standard. For example, item allocation rates for characteristics such as year of entry and income were high for certain GQ types and for the GQ population as a whole. A separate document [XLS 21KB] with the item allocation rates for GQ characteristics that did not meet the Census Bureau's quality standard is provided. High item allocation rates can adversely impact final estimates for the GQ population and introduce bias if the characteristics of nonrespondents differ from those of respondents. If the GQ population makes up a large proportion of the total population for an area, the estimates for the total population can likewise be affected.

From April to September of 2008, the ACS reduced the number of cases included in the telephone Failed Edit Follow-up (FEFU) operation. In FEFU, households who have returned a mail form but whose data failed a completeness check are called to collect the missing data. This operation is designed to improve the final quality of mail-returned questionnaires. As expected, the reduced number of FEFU cases resulted in an increase in missing data among mail respondents and thus, an increase in item allocation rates. For more information about FEFU, please refer to Chapter 7, page 7-5 of the ACS Design and Methodology report at http://www.census.gov/acs/www/methodology/methodology_main/

There was an unusually large amount of missing data for the group quarters populations in Clearfield County, PA. The large amount of missing data coupled with the current edit and imputation procedures resulted in incorrect estimates for earnings and income for both the group quarters population and the total population. This spreadsheet file (XLS) contains the full list of tables, table lines, and geographic areas that will not be released due to this problem.

For certain group quarters (GQ) characteristics and GQ types, the item non-response rates and coverage rates do not meet the Census Bureau's quality standards. The GQ coverage rate of 79.6 percent was below the standard of 80 percent. Most notably, the coverage rate for college dormitories was artificially low because data were collected throughout the entire year, including the summer months when many dormitories were vacant. This, in turn, lowers the coverage for the GQ population as a whole. Missing data for a particular question is called item nonresponse. It will occur when a respondent fails to provide an answer to a question or when an invalid answer is provided. The Census Bureau uses allocation methods to correct for item nonresponse and thus, allocation rates are used to measure the magnitude of item nonresponse. The Census Bureau has established a standard states that users should be made aware of items with allocation rates exceeding 20 percent. Several GQ population characteristics in the subject tables did not meet this standard. For example, item allocation rates for characteristics such as year of entry and income were high for certain GQ types and for the GQ population as a whole. A separate document [XLS] provides item allocation rates for GQ characteristics that did not meet the Census Bureau's quality standard. High item allocation rates and low coverage rates can adversely impact final estimates for the GQ population and introduce bias if the characteristics of nonrespondents differ from those of respondents. If the GQ population makes up a large proportion of the total population for an area, the estimates for the total population can likewise be affected.

Selected sections of the iterated SPPs by country of birth show a '0,' 'N,' '-,' or '**,' for estimates and margins of error that are not applicable and should have been represented with an '(X)'. This affects the native iteration and the region, subregion, and country of birth iterations for "Place of Birth, Citizenship Status and Year of Entry" and "World Region of Birth of Foreign Born." Also affected is the total foreign-born iteration for "Place of Birth, Citizenship Status and Year of Entry." For example, in the total foreign-born table, the estimate of natives under "Place of Birth, Citizenship Status and Year of Entry" was reported as '0' with a margin of error of '+/-267' when both measures should have received an '(X).' The corrected SPPs will be released prior to the release of 3-year estimates in December 2008.

The review of the 2007 ACS tabulations revealed large discrepancies between the final 2007 ACS estimate of total population and the 2007 population estimates from the Population Estimates Program for a set of places in Orange County, CA. These same areas showed a similar pattern of differences in the 2005 and 2006 ACS estimates. An additional adjustment to the weights was introduced in the weighting for Orange County to remove the source of the discrepancy. The adjustment was aimed at forcing the weighted distribution of housing units in the ACS sample to match the distribution of housing units on our sampling frame. The weighting adjustment was applied at the census tract level. As a result, it has eliminated most of the large discrepancies originally found for places in Orange County. This modification was also made to the 2006 ACS weighting methodology.

The review of the 2007 operational data discovered evidence that suggests a high incidence of misclassification of uninhabitable units as vacant units. The effect of misclassification was almost entirely removed through a modification in the weighting methodology for Orleans and St. Bernard Parishes. The effect of the weighting adjustment was to down-weight units that had the vacancy status of "Other Vacant". This modification resulted in more consistent and accurate ACS estimates of the number of vacant units and "persons per household" in these two parishes. This modification was also made to the 2006 ACS weighting methodology.

The weighting for the group quarters population is controlled at the state level. For that reason, users should expect that the ACS estimate for the group quarters population to be consistent with the Population Estimates Program only at the state level. At the county level, the ACS estimate will typically be different from the Population Estimates Program due to sampling variability. Like estimates of total population, data users who require an estimate of the group quarters population at the county level should use the official estimates from the Population Estimates Program.

The weighting for the group quarters (GQ) population is controlled at the state level, but not at sub-state levels. For this reason, users may observe greater fluctuations in year-to-year ACS estimates of the GQ population at sub-state levels than at state levels. The causes of these fluctuations typically are the result of either GQs that have closed or where the current population of the GQ is significantly different than the expected population as reflected on the sampling frame. Substantial changes in the ACS GQ estimates can impact ACS estimates of total population characteristics for areas where either the GQ population is a substantial proportion of the total population or where the GQ population may have very different characteristics than the total population as a whole. Users can assess the impact that year-to-year changes in sub-state GQ total population estimates have on the changes in total ACS population estimates by accessing Table B26001 on American Fact Finder. Users should also use their local knowledge to help determine whether the year-to-year change in the ACS estimate represents a real change in the GQ population or may be the result of the lack of adequate population controls for sub-state areas.

In Abilene, TX, the Census Bureau has identified a large increase in the percent of Hispanics reporting their race as White Alone and a large decrease in the percent of Hispanics reporting their race as Some Other Race. This increase is likely the result of a problem in the data collection process and probably does not represent real change. Data users should use caution when interpreting the data for Hispanic respondents who reported their race as White or Some Other Race.

The review of the 2006 ACS tabulations revealed large discrepancies between the final 2006 ACS estimate of total population and the 2006 intercensal population estimates for a set of places in Orange County, CA. These same areas showed a similar pattern of differences in the 2005 ACS tabulated estimates. An additional adjustment to the weights was introduced in the weighting for Orange County to remove the source of the discrepancy. The adjustment was aimed at forcing the weighted distribution of housing units in the ACS sample to match the distribution of housing units on our sampling frame. The weighting adjustment was applied at the census tract level. As a result, it has eliminated most of the large discrepancies originally found for places in Orange County.

The review of the 2006 operational data discovered evidence that suggests a high incidence of misclassification of uninhabitable units as vacant units. The effect of misclassification was almost entirely removed through a modification in the weighting methodology for Orleans and St. Bernard Parishes. The effect of the weighting adjustment was to down-weight units that had the vacancy status of "Other Vacant". This modification resulted in more consistent and accurate ACS estimates of the number of vacant units and "persons per household" in these two parishes.

As a result of our continuous effort to improve the quality of the estimates the 2006 weighting methodology was modified in order to ensure total consistency between the estimates of householders, households, and occupied housing units. This has not been the case prior to 2006. With this data release, the estimates of occupied housing units, households, and householders will all be equal. In addition, the modification also reduces the differences between estimates of spouses and married-couple households and between the estimates of unmarried partners and unmarried-partner households. See the Changes to the Estimation (pdf) for detailed information regarding which tables are most affected and the impact on the estimates had this methodology been applied in 2005.

The weighting for the group quarters population is controlled at the state level. For that reason, users should expect that the ACS estimate for the group quarters population to be consistent with the Population Estimates Program only at the state level. For sub-state areas, the ACS estimate will typically be different from the Population Estimates Program due to sampling variability. Like estimates of total population, data users who require an estimate of the group quarters population at the county level should use the official estimates from the Population Estimates Program.

The 2003, 2004, and 2005 ACS 1-year PUMS files have been revised by applying a modified age perturbation edit to these files. This is the same revision that was made to the 2006 ACS 1-year PUMS files that is described in ACS Errata Note #50 .

Age perturbation is one of several disclosure avoidance techniques used in the creation of the ACS PUMS files. It disguises original data by randomly adjusting the reported ages for a subset of individuals. As discussed in Errata Note #47,this technique in some previous years of ACS PUMS processing resulted in inconsistent sex ratios for selected age groups, especially ages 65 and over. The modified age perturbation edit was applied to people aged 65 and over to reduce inconsistencies among this group. The revised file estimates for people 65 years and older align closer to the ACS full sample by single year of age for sex ratios, social security participation, labor force participation, person income and home ownership. The sex ratio inconsistencies for persons aged 65 and over will not be seen in the 2006-2008 ACS 3-year PUMS files since the 2006 ACS 1-year PUMS files were revised before the 2006-2008 3-year PUMS files were created.

Several other minor corrections were made to the 2005-2007 3-year PUMS files. The factor to adjust housing dollar amounts for inflation (ADJHSG) has been moved from the person-level files to the housing unit-level files, which will make it consistent with the documentation. The factor to adjust income and earnings dollar amounts for inflation (ADJINC) has been corrected for the 2007 cases on the 2005-2007 files. The occupation code (SOCP) for the 2005 cases on the person-level file have been updated to be consistent with the new occupation codes used for the 2006 and 2007 cases.

The original PUMS files have been removed and replaced with the revised PUMS files for the affected releases. To request the original PUMS files, please send an e-mail to acso.users.support@census.gov.

Here is how we determine which sub-state geographic areas meet the ACS population threshold of 65,000 for publishing estimates for that area: Wherever possible, we use the most current estimate of the total resident population from official Census Bureau Population Estimates Program (PEP). This number includes both household and group quarters population. PEP provides this estimate for counties, incorporated places, and sub-county areas (e.g. townships), which have a functioning government. If the PEP estimate for any of these areas is 65,000 or more, then we publish ACS data products for that area. However, since the ACS sample is still a sample of the housing unit population, the ACS estimates will often be lower than the PEP estimates. In some cases, the ACS estimate of total (housing unit) population will be less than 65,000. This is an indication that the total resident population for that geographic area is over 65,000 (although probably very close to 65,000). There are 52 geographic areas where this occurs, and they are shown in the table below.

Data Release Rules

Even with the population size thresholds described earlier, in certain geographic areas some very detailed tables might include estimates whose reliability is unacceptable. Data release rules, based on the statistical reliability of the survey estimates, will be used starting with the 2005 ACS data released in the summer of 2006. These release rules apply only to the single-year and three-year data products.

The main data release rule for the ACS tables works as follows. Every base table consists of a series of estimates. If more than half the estimates are not statistically different from 0 (at a 90 percent confidence level), then the table fails. Each estimate is subject to sampling variability that can be summarized by its standard error. Dividing the standard error by the estimate yields the coefficient of variation (CV) for each of the estimates. (If the estimate is 0, a CV of 100 percent is assigned.) To implement this requirement for each table at a given geographic area, CVs are calculated for each of the table's estimates, and the median CV value is determined. If 13-11 the median CV value for the table is less than or equal to 61 percent, the table passes for that geographic area; if it is greater than 61 percent, the table fails. Tables that are too sparse will fail this test. In that case, the table will not be published for that geographic area. Whenever a table fails, a simpler table that collapses some of the detailed lines together can be substituted for the original, more detailed table. The data release rules are then applied to the simpler table. If it passes, the simpler table is released. If it fails, none of the estimates for that particular table is released for this geographic area. These release rules are applied to single-year period estimates and multi-year period estimates based on three years of sample data. No data release rules are applied to the estimates based on five years of sample data.

For more information go to the Design and Methodology document, the link to it is http://www.census.gov/acs/www/Downloads/survey_methodology/acs_design_methodology.pdf

Update October 2, 2008: Partial ACS data products are restored back to AFF. Detailed tables and reference maps for 2000-2004 and data profiles for 2002-2004 are now available. We will continue to restore the data and will provide more updates as the files become available.

On August 26, 2008, all ACS data products for the years 2000, 2001, 2002, 2003, and 2004 were removed from the American FactFinder (AFF) and placed on a special FTP site (http://www2.census.gov/acs/downloads/Core_Tables/). However, there were several problems that users discovered with the files on this site, and, based on the reports from users of these problems, on September 9, 2008 the Census Bureau decided to pull this site down until the problems can be fixed. We expect resolution soon, and we will make the FTP site available at that time.

In the meantime, for years 2002, 2003, and 2004, Detailed Tables, Profiles, and Ranking Tables are available for downloading on:

• http://www2.census.gov/acs2002/
• http://www2.census.gov/acs2003/
• http://www2.census.gov/acs2004/

Note: The following American Community Survey (ACS) tables are being removed from American FactFinder for the years 2000 and 2001 and use of data derived from these tables should be discontinued. (At the time of their release, these tables were part of a data set known as the "Census Supplementary Survey" for each year.)

• P042 - Residence 1 year ago for the population 1 year and over -- MSA/PMSA level
• P045 - Place of work for workers 16 years and over -- MSA/PMSA level
• PCT030 - Residence 1 year ago for the population 1 year and over -- MSA/PMSA level

These tables will not be published with 2002 ACS data.

MSAs/PMSAs are defined at the county level in states outside of New England. During the current demonstration period for ACS, the sample of counties has not been selected to be representative of the distribution of metropolitan and non-metropolitan areas separately within a state. The supplementary survey sample design does not support estimation for metropolitan /non-metropolitan domains. For this reason, these tables are being removed and users are encouraged to not use the data from these tables further.

It is important to note that this problem will not occur under the full implementation of the ACS, as there will be housing units sampled in all counties in the United States.