Data collection and analysis are essential parts of NNIP's work. Explore the pages below to see how NNIP partners are using these data sources in their local communities. We'll list additional data sources as our partners add new examples, so check back often. If you are interested in data sources not listed here, use the site's general search box.
Also see the Urban Institute's National Data Repository and
Guide to Online Data Access and Visualization Resources.
These data include call information to 211 and 311 systems, as well as resource lists maintained for these referral systems.
This entails primary data collection through surveys of residents or organizations in the community.
These data are derived from reports filed by all employers subject to unemployment compensation laws.
Video, audio, or other qualitiative sources of data such as interviews or focus groups
After the 2000 Census, the U.S. Census Bureau stopped using the long form in their decennial census. In its stead, they began collecting data continually in the form of the American Community Survey (ACS). Unlike the decennial census, which provides point in time estimates based on April 1st of the census year, the ACS estimates measure averages over a one-year, three-year, or five-year period. The ACS has approximately 250,000 respondents monthly, totaling 3 million per year. Because of the smaller sample size compared to the decennial census, we need to pay serious attention to standard errors and confidence intervals with the ACS.<br /><br />
<p><strong>You can download the data <a href="http://metrotrends.org/natdata/acs/index.cfm">here</a>.</strong></p>
Single-year data are only available for larger levels of geographies over 65,000, such as states and large metropolitan areas. Three-year estimates represent 36 month averages, and are available for areas with geographies with populations over 20,000. Finally, five-year estimates represent five-year averages, and are available for all geographies down to the census tract level. If you need special tabulations, ACS also publishes microdata for the Public Use Microdata Area (PUMA) geography.
Tract-level estimates were not available using the ACS until 2010. These estimates represent five year averages of the time period between January 1, 2005 and December 31, 2009.
Birth indicators shed light on a range of critical neighborhood issues, such as teen pregnancy, infants with multiple risk factors, demographic change, and projected school enrollments. Over three-quarters of our partners have birth data at the address or small area level drawn from Vital Statistics files.
Indicators on mortality and causes of death shed light on the health, economic, and safety conditions of our communities . Three-quarters of our partners have or make use of cause of death data from vital statistics files.
Every ten years through 2000, the Census Bureau conducted a national household survey. The federal government uses Decennial Census data for apportioning congressional seats, for identifying distressed areas, and for many other activities. Census data was collected using two survey forms: the short form and the long form. Short form information is collected on every person and includes basic characteristics, such as age, sex, and race. The long form was sent to one out of every six households and collects more detailed information, such as income, housing characteristics, and employment. (The American Community Survey has since replaced the Long Form data.) Most of the indicators in the summary file are from the long form, and are thus estimates based on the sample of households. These values may differ considerably from the same indicators based on the Short Form data, particularly for small areas. For more information, visit the Census web site at http://www.census.gov/main/www/cen2000.html.
Every ten years through 2000, the Census Bureau conducted a national household survey. The federal government uses Decennial Census data for apportioning congressional seats, for identifying distressed areas, and for many other activities. Beginning with the 2010 Census, the Census Bureau included only the short form (the long form was replaced by the ACS). Short form information is collected on every person and includes basic characteristics, such as age, sex, and race.
The Home Mortgage Disclosure Act (HMDA) requires most lending institutions to report mortgage loan applications, including the outcome of the application, information about the loan and applicant, and location of the property. In 2004, FFIEC expanded the data to include structure type, lien status, and if the loan had high interest rates. FFIEC collects the data in order to determine whether financial institutions are meeting a community’s housing credit needs; to target community development funds to attract private investment; and to identify possible discriminatory lending patterns. The reporting requirements are based on the level of institutional assets and the number of loans originated in metro areas.<br /><br />
<p><strong>You can download the data <a href="http://metrotrends.org/natdata/hmda/index.cfm">here</a>.</strong></p>
Integrated Data Systems (IDS) link individual level data from multiple agencies such as schools, juvenile justice, and human services, often with a focus on children. The systems can be used for case management or for program monitoring and evaluation. For more resources and a catalog of IDS please click <p><strong><a href="http://neighborhoodindicators.org/resources-integrated-data-systems-ids">here</a>.</strong></p>.
The DataPlace Internal Revenue Service (I.R.S.) data files are compiled from zip code data supplied by three divisions within the agency: Statistics of Income (SOI), E-file program, and the Stakeholder Partnership Education and Communication Office (SPEC). The I.R.S. indicators are derived from individual income tax returns, and thus describe characteristics of tax filers, not households or persons. I.R.S. indicators include information about: filer’s age, income level and sources, tax credits and deductions, and tax preparation method. Counts with less than 10 observations are suppressed to protect confidentiality. Adjustments to the data were made in linking the I.R.S. data reported for zip codes to Zip Code Tabulation Areas (ZCTAs).
This category includes a variety of resources for finding local business data. Find the resource that best suits your data needs using descriptions of different available resources and feedback from NNIP partners.
New time series data created under the federal-state Local Employment Dynamics (LED) Partnership provide details about America's jobs, workers, and local economies and communities. LED creatively integrates existing data from state-supplied administrative records on workers and employers with existing censuses, surveys, and other administrative records. State-of-the-art methods to protect the confidentiality of the original respondents allow LED to release valid data for local or regional areas beyond traditional boundaries for public use on the Internet. LED data is available down to the block group, but because raw data is provided on a voluntary basis, state by state, the availability of data for various geographies varies greatly.
National Center for Education Statistics (NCES) conducts an annual survey of state education agencies to obtain data for every public elementary and secondary school in the United States and its territories, which it then compiles and publishes as the Common Core of Data Public Elementary/Secondary School Universe Survey (CCD). The CCD has two main purposes: 1) to provide an official listing of public elementary and secondary schools and school districts in the nation as a basis for samples for other NCES surveys; and 2) to provide basic descriptive statistics on public elementary and secondary schools. Mostly derived from administrative records, data cover school characteristics such as the school level, grades taught, student-teacher ratio, and federal Title I funding eligibility, and also provide information on enrolled student characteristics, including race/ethnicity, free/reduced price lunch eligibility, migrant status, and gender. <br /><br />
<p><strong>You can download the data <a href="http://metrotrends.org/natdata/nces/index.cfm">here</a>.</strong></p>
Tracking property sales volume and prices enables partners to document how the housing boom and bust is playing out in different types of neighborhoods. Over 70% of the partners have address-level sales data, which are generally obtained from local Assessors’ records. These data are updated more frequently than most other administrative data – ten of those with sales data receive it monthly or quarterly.
This category includes primary data collection about characteristics of individual properties that are missing or incomplete from administrative data sources, such as each property's land use, building condition, or occupancy status.
HUD has entered into an agreement with the United States Postal Service (USPS) to receive quarterly aggregate data on addresses identified by the USPS as having been "vacant" or "No-Stat" in the previous quarter. HUD is making these data available for researchers and practitioners to explore their potential utility for tracking neighborhood change on a quarterly basis. The potential power of these data is that they represent the universe of all addresses in the United States and are updated every three months. Under the agreement with the USPS, HUD can make the data available publicly at the Census Tract level provided users agree to the terms and conditions of the click-on sublicense.
The U.S. Census Bureau's Business Patterns series is produced annually and provides sub-national economic data by industry. The series is useful for studying the economic activity of small areas; analyzing economic changes over time; and benchmarking statistical series, surveys, and databases between economic censuses. The Business Patterns series provides information on number of establishments and employment.
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<p><strong>You can download the data <a href="http://metrotrends.org/natdata/businesspatterns/index.cfm">here</a>.</strong></p>