Introducing a new way to navigate by topics. Access the latest news, data, publications and more around topics of interest.
Our population statistics cover age, sex, race, Hispanic origin, migration, ancestry, language use, veterans, as well as population estimates and projections.
This section provides information on a range of educational topics, from educational attainment and school enrollment to school districts, costs and financing.
We measure the state of the nations workforce, including employment and unemployment levels, weeks and hours worked, occupations, and commuting.
Our statistics highlight trends in household and family composition, describe characteristics of the residents of housing units, and show how they are related.
Health statistics on insurance coverage, disability, fertility and other health issues are increasingly important in measuring the nation's overall well-being.
We measure the housing and construction industry, track homeownership rates, and produce statistics on the physical and financial characteristics of our homes.
The U.S. Census Bureau is the official source for U.S. export and import statistics and regulations governing the reporting of exports from the U.S.
The U.S. Census Bureau provides data for the Federal, state and local governments as well as voting, redistricting, apportionment and congressional affairs.
Search an alphabetical index of keywords and phrases to access Census Bureau statistics, publications, products, services, data, and data tools.
Geography provides the framework for Census Bureau survey design, sample selection, data collection, tabulation, and dissemination.
Geography is central to the work of the Bureau, providing the framework for survey design, sample selection, data collection, tabulation, and dissemination.
Find resources on how to use geographic data and products with statistical data, educational blog postings, and presentations.
The Geographic Support System Initiative will integrate improved address coverage, spatial feature updates, and enhanced quality assessment and measurement.
Work with interactive mapping tools from across the Census Bureau.
Find geographic data and products such as Shapefiles, KMLs, TIGERweb, boundary files, geographic relationship files, and reference and thematic maps.
Metropolitan and micropolitan areas are geographic entities used by Federal statistical agencies in collecting, tabulating, and publishing Federal statistics.
Find information about specific partnership programs and learn more about our partnerships with other organizations.
Definitions of geographic terms, why geographic areas are defined, and how the Census Bureau defines geographic areas.
We conduct research on geographic topics such as how to define geographic areas and how geography changes over time.
Visit our library of Census Bureau multimedia files. Collection formats include audio, video, mobile apps, images, and publications.
Collection of audio features and sound bites.
The Census Bureau packages data and information into easy-to-understand visuals.
Browse Census Bureau images.
Read briefs and reports from Census Bureau experts.
Watch Census Bureau vignettes, testimonials, and video files.
Read research analyses from Census Bureau experts.
Access data through products and tools including data visualizations, mobile apps, interactive web apps and other software.
Developer portal to access services and documentation for the Census Bureau's APIs.
Explore Census Bureau data on your mobile device with interactive tools.
Find a multitude of DVDs, CDs and publications in print by topic.
These external sites provide more data.
Download extraction tools to help you get the in-depth data you need.
Learn more about our data from this collection of e-tutorials, presentations, webinars and other training materials. Sign up for training sessions.
Explore Census data with interactive visualizations covering a broad range of topics.
Learn how we serve the public as the most reliable source of data about the nation's people and economy.
How we provide the best mix of timeliness, relevancy, quality, and cost for the data we collect.
Our researchers explore innovative ways to conduct surveys, increase respondent participation, reduce costs, and improve accuracy.
Our surveys provide periodic and comprehensive statistics about the nation, critical for government programs, policies, and decisionmaking.
Learn about other opportunities to collaborate with us.
Explore the rich historical background of an organization with roots almost as old as the nation.
Explore prospective positions available at the Census Bureau.
Explore Census programs targeted for particular needs.
Discover the latest in Census Bureau data releases, reports, and events.
The Census Bureau's Director writes on how we measure America's people, places and economy.
Find interesting and quirky statistics regarding national celebrations and major events.
Listen to audio files on fun facts, historical figures, and celebrations of the month.
Find media toolkits, advisories, and all the latest Census news.
See what's coming up in releases and reports.
State Model Changes
There were two important changes to the state models for 2004. First, a switch was made to using prior census data in the form of census residuals rather than census estimates for all but the model for 65 and over poverty ratios. (Census residuals come from the regression of the corresponding Census 2000 estimates on 1999 values of the other predictor variables in the model.) Second, we reintroduced the food stamp participation rate variable into the 0-4, 5-17, and 18-64 poverty ratio models. Following is discussion of these two changes, and of a less important change concerning estimation of sampling error variances.
The change noted to use prior census residuals as predictor variables in the models rather than prior census estimates was made because statistical comparisons of model fit for 2004 favored the models with census residuals, whereas for 2000-2003 the corresponding model fit comparisons had mostly favored models with prior census estimates. For the age 65 and over poverty ratios the model fit comparison for 2004 still favored use of prior census estimates, and so the change to census residuals was not made for 65 and over. Somewhat similar results were observed in the 1990s, although the model fit comparisons favored use of (1990) census residuals for ages 0-4, 5-17, and 18-64 earlier in the decade. (SAIPE did not start producing estimates until income year 1993, though model fits done for evaluation purposes with data for 1990-1992 show that the models with census residuals would have been favored even earlier.) The models for age 65 and over poverty ratios and for median household income were switched to using census residuals in income year 1998.
In general, it appears that "sufficiently close" to the census year models using prior census estimates tend to fit better while "sufficiently far" from the census year models using census residuals tend to fit better. However, the meanings of "sufficiently close" and "sufficiently far" from the census year have been different in this decade than in the 1990s.
Another change for the 0-4, 5-17, and 18-64 poverty ratio models was the reintroduction of the state food stamp participation rate as a predictor variable. This variable was previously used in these models until 1998, when it was dropped because its regression coefficients had become statistically insignificant. (For discussion, see the documentation of estimation procedure changes for 1998.) This remained the situation until this year, though in recent years this was partly due to the continued use of the models with previous census estimates as predictors. (The other predictors in the models are less important when census estimates, rather than census residuals, are used in the models.) But with the switch to use of census residuals for 2004, statistical model comparisons favored reintroduction of the food stamp participation rate variable in the 0-4, 5-17, and 18-64 poverty ratio models.
The estimation of sampling error variances of the direct CPS ASEC state estimates was complicated by the fact that for 2004 the estimates drew on samples from both the 1990 census based CPS design and the newly introduced census 2000 based design. Direct variance estimates were still produced, but the different nature of the sample for the 2004 estimates raised concerns about whether the design effect parameters in the sampling error models could be different in 2004 from other years. So, despite changing the sampling error models last year to use the same design effect parameters for all years (see documentation of estimation procedure changes for the 2003 estimates), this year we went back to using different design effect parameters for all years (though only those for 2004 get used in the 2004 state poverty ratio and median income models). Even so, the estimated design effect parameters for 2004 from the fitted sampling error models were not dramatically different from the corresponding design effect parameters for 2000-2003.