The growth of employment has been higher in metro areas than nonmetro areas since 2007. As of 2021, employment had not returned to pre-pandemic levels, but metro areas saw more significant growth between 2021 and 2022 than nonmetro areas did.

This polygon shapefile contains underserved area designations for census tracts in Metropolitan Statistical Areas (MSAs), nonmetropolitan parts of states and Federal and State American Indian Reservations and tribal and individual trust lands. The following are the definitions of underserved geographical areas based on HUDs housing goals regulations at 24 CFR Section 81.2. a. Central Cities and Other Parts of Metropolitan Areas (i) A census tract with median income at or below 120 percent of the median income of the metropolitan area (MSA) and a minority population of 30 percent or greater; or (ii) A census tract with median income at or below 90 percent of median income of the MSA. b. Nonmetropolitan Areas (i) A census tract with median income at or below 120 percent of the greater of the State nonmetropolitan median income or the nationwide nonmetropolitan median income and a minority population of 30 percent or greater; or (ii) A census tract with median income at or below 95 percent of the greater of the State nonmetropolitan median income or the nationwide nonmetropolitan median income. c. Tribal Lands in Metropolitan Areas (i) A Federal or State American Indian reservation or tribal or individual trust land with a median income at or below 120 percent of the median income of the MSA and a minority population of 30 percent or greater; or (ii) A Federal or State American Indian reservation or tribal or individual trust land with a median income at or below 90 percent of median income of the MSA. d. Tribal Lands in Nonmetropolitan Areas (i) A Federal or State American Indian reservation or tribal or individual trust land with a median income at or below 120 percent of the greater of the state nonmetropolitan median income or the nationwide nonmetropolitan median income and a minority population of 30 percent or greater; or (ii) A Federal or State American Indian reservation or tribal or individual trust land with a median income at or below 95 percent of the greater of the state nonmetropolitan median income or the nationwide nonmetropolitan median income. e. Tribal Lands that Cross Metropolitan / Nonmetropolitan Area and/or State Boundaries For certain Federal or State American Indian reservations or tribal or individual trust lands, the tribal area crosses an MSA or state boundary. In these cases, the median incomes of the MSA or MSAs, the nonmetropolitan area of the state or states, or the nationwide nonmetropolitan area that applies to the tract containing the tribal area determines whether the part of the Federal or State American Indian reservation or tribal or individual trust land is underserved. METHODOLOGY: Whether a tract has 30 percent or more minority population is determined by rounding 30 percent of the tracts population to the nearest person, and comparing this to the count of minority persons in the area. The applicable percentage of area median income and whether the tracts median income is below it is determined by rounding the applicable percentage of area median income to the nearest dollar and comparing this to tract median family income.

This data collection provides statistics gathered from a variety of federal agencies and national associations. Demographic, economic, and governmental data from both the federal government and private agencies are presented to enable multiarea comparisons as well as single-area profiles. Current estimates and benchmark census results are included. Data are available for five types of geographic coverage: (1) Metro Areas data cover 249 metropolitan statistical areas (MSAs), 17 consolidated metropolitan statistical areas (CMSAs), 54 primary metropolitan statistical areas (PSMAs), and 16 New England county metropolitan areas (NECMAs). Metro Areas data include the following general subjects: area and population, households, vital statistics, health, education, crime, housing, money income, personal income, civilian labor force, employment, construction, commercial office space, manufacturing, wholesale and retail trade, service industries, banking, federal funds and grants, and government employment. There are 14 parts for Metro Areas. (2) State Metro/Nonmetro data cover the United States, the 50 states, the District of Columbia, and the metropolitan and nonmetropolitan portions of these areas. State Metro/Nonmetro data include most of the subjects listed for Metro Areas. There are six parts for State Metro/Nonmetro. (3) Metro Counties data cover 336 metropolitan areas and their component counties and include topics identical to those presented in the State Metro/Nonmetro data. Six parts are supplied for Metro Counties. (4) Metro Central Cities data cover 336 metropolitan areas and their 522 central cities and 336 outside central cities portions. Metro Central Cities variables are limited to 13 items, which include area and population, money income, civilian labor force, and retail trade. There is one part for Metro Central Cities. (5) States data cover the United States, the 50 states, the District of Columbia, and census regions and divisions. States data include the same items as the Metro Areas data, plus information on social welfare programs, geography and environment, domestic travel and parks, gross state product, poverty, wealth holders, business, research and development, agriculture, forestry and fisheries, minerals and mining, transportation, communications, energy, state government, federal government, and elections. There are 101 parts for States.

Washington State, metropolitan statistical areas (MSA) and nonmetropolitan areas (NMA), 2020 OEWS is a program of the U.S. Department of Labor, Bureau of Labor Statistics (BLS). This federal-state cooperative program produces employment and wage estimates for nearly 867 occupations. The occupational employment and wage estimates are based on data collected from the OEWS survey. The survey includes employment counts, occupations and wages from more than 4,200 Washington state employers. Data from six survey panels are combined to create a sample size of more than 26,400 employers. Blanks in the data columns indicate suppressed data.

Only counties in nonmetropolitan areas may be eligible for HUBZone designated status. In order for a nonmetropolitan county to qualify: the median household income in the county must be less than 80% of the nonmetropolitan state median household income, or the unemployment rate in the county must be at least 140% of either the national or state unemployment rate, or the county is classified as a Difficult Development Area, as designated by HUD within Alaska, Hawaii, or any territory or possession of the United States, outside of the 48 contiguous states.

This data layer shows U.S. Department of Housing and Urban Development (HUD) annually designated non-metropolitan Difficult Development Areas (DDAs).Non-metropolitan DDAs are areas with high construction, land, and utility costs relative to area median gross income and are based on Fair Market Rents (FMR), income limits, the 2020 census counts, and 5-year American Community Survey data.The unit of geography for non-metropolitan DDAs is the non-metropolitan county or county equivalent area. Non-metropolitan DDAs are designated annually as updated income, and FMR data are made public.

The Occupational Employment and Wage Statistics (OES) program conducts a semi-annual survey to produce estimates of employment and wages for specific occupations. The OES program collects data on wage and salary workers in nonfarm establishments in order to produce employment and wage estimates for about 800 occupations. Data from self-employed persons are not collected and are not included in the estimates. The OES program produces these occupational estimates by geographic area and by industry. Estimates based on geographic areas are available at the National, State, Metropolitan, and Nonmetropolitan Area levels. The Bureau of Labor Statistics produces occupational employment and wage estimates for over 450 industry classifications at the national level. The industry classifications correspond to the sector, 3-, 4-, and 5-digit North American Industry Classification System (NAICS) industrial groups. More information and details about the data provided can be found at http://www.bls.gov/oes

Graph and download economic data for Real Per Capita Personal Income: Nonmetropolitan Portion for Ohio (OHNMPRPIPC) from 2008 to 2023 about rural, OH, personal income, per capita, personal, income, real, and USA.

Federal Housing Finance Agency's (FHFA) Underserved Areas establishes underserved area designations for census tracts in Metropolitan Areas (MSAs), nonmetropolitan parts of states and Federal and State American Indian Reservations and tribal and individual trust lands. These designations are applicable to Fannie Mae s and Freddie Mac s scoring of mortgage purchases toward their Underserved Areas housing and home purchase goals in 2009.

Abstract (en): The Public Use Microdata Sample (PUMS) 1-Percent Sample contains household and person records for a sample of housing units that received the "long form" of the 1990 Census questionnaire. Data items include the full range of population and housing information collected in the 1990 Census, including 500 occupation categories, age by single years up to 90, and wages in dollars up to $140,000. Each person identified in the sample has an associated household record, containing information on household characteristics such as type of household and family income. All persons and housing units in the United States. A stratified sample, consisting of a subsample of the household units that received the 1990 Census "long-form" questionnaire (approximately 15.9 percent of all housing units). 2006-01-12 All files were removed from dataset 85 and flagged as study-level files, so that they will accompany all downloads.2006-01-12 All files were removed from dataset 83 and flagged as study-level files, so that they will accompany all downloads.2006-01-12 All files were removed from dataset 82 and flagged as study-level files, so that they will accompany all downloads.2006-01-12 All files were removed from dataset 81 and flagged as study-level files, so that they will accompany all downloads.2006-01-12 All files were removed from dataset 80 and flagged as study-level files, so that they will accompany all downloads.1998-08-28 The following data files were replaced by the Census Bureau: the state files (Parts 1-56), Puerto Rico (Part 72), Geographic Equivalency File (Part 84), and Public Use Microdata Areas (PUMAS) Crossing State Lines (Part 99). These files now incorporate revised group quarters data. Parts 201-256, which were separate revised group quarters files for each state, have been removed from the collection. The data fields affected by the group quarters data revisions were POWSTATE, POWPUMA, MIGSTATE and MIGPUMA. As a result of the revisions, the Maine file (Part 23) gained 763 records and Part 99 lost 763 records. In addition, the following files have been added to the collection: Ancestry Code List, Place of Birth Code List, Industry Code List, Language Code List, Occupation Code List, and Race Code List (Parts 86-91). Also, the codebook is now available as a PDF file. (1) Although all records are 231 characters in length, each file is hierarchical in structure, containing a housing unit record followed by a variable number of person records. Both record types contain approximately 120 variables. Two improvements over the 1980 PUMS files have been incorporated. First, the housing unit serial number is identified on both the housing unit record and on the person record, allowing the file to be processed as a rectangular file. In addition, each person record is assigned an individual weight, allowing users to more closely approximate published reports. Unlike previous years, the 1990 PUMS 1-Percent and 5-Percent Samples have not been released in separate geographic series (known as "A," "B," etc. records). Instead, each sample has its own set of geographies, known as "Public Use Microdata Areas" (PUMAs), established by the Census Bureau with assistance from each State Data Center. The PUMAs in the 1-Percent Sample are based on a distinction between metropolitan and nonmetropolitan areas. Metropolitan areas encompass whole central cities, Primary Metropolitan Statistical Areas (PMSAs), Metropolitan Statistical Areas (MSAs), or groups thereof, except where the city or metropolitan area contains more than 200,000 inhabitants. In that case, the city or metropolitan area is divided into several PUMAs. Nonmetropolitan PUMAs are based on areas or groups of areas outside the central city, PMSA, or MSA. PUMAs in this 1-Percent Sample may cross state lines. (2) The codebook is provided as a Portable Document Format (PDF) file. The PDF file format was developed by Adobe Systems Incorporated and can be accessed using PDF reader software, such as the Adobe Acrobat Reader. Information on how to obtain a copy of the Acrobat Reader is provided through the ICPSR Website on the Internet.

Graph and download economic data for Real Personal Income: Nonmetropolitan Portion for Michigan (MINMPRPI) from 2008 to 2023 about rural, MI, personal income, personal, income, real, and USA.

HUBZone Qualified Nonmetropolitan Counties

A Difficult Development Area (DDA) for the Low Income Housing Tax Credit program is an area designated by the U.S. Department of Housing and Urban Development (HUD) with high construction, land, and utility costs relative to its Area Median Gross Income (AMGI). All designated DDAs in Metropolitan Statistical Areas (MSA) or Primary Metropolitan Statistical Areas (PMSA) may not contain more than 20% of the aggregate population of all MSAs/PMSAs, and all designated areas not in metropolitan areas may not contain more than 20% of the aggregate population of the non-metropolitan counties.

Graph and download economic data for Real Per Capita Personal Income: Nonmetropolitan Portion for Georgia (GANMPRPIPC) from 2008 to 2023 about rural, GA, personal income, per capita, personal, income, real, and USA.

BackgroundGeographic inequality in US mortality has increased rapidly over the last 25 years, particularly between metropolitan and nonmetropolitan areas. These gaps are sizeable and rival life expectancy differences between the US and other high-income countries. This study determines the contribution of smoking, a key contributor to premature mortality in the US, to geographic inequality in mortality over the past quarter century.MethodsWe used death certificate and census data covering the entire US population aged 50+ between Jan 1, 1990 and Dec 31, 2019. We categorized counties into 40 geographic areas cross-classified by region and metropolitan category. We estimated life expectancy at age 50 and the index of dissimilarity for mortality, a measure of inequality in mortality, with and without smoking for these areas in 1990–1992 and 2017–2019. We estimated the changes in life expectancy levels and percent change in inequality in mortality due to smoking between these periods.ResultsWe find that the gap in life expectany between metros and nonmetros increased by 2.17 years for men and 2.77 years for women. Changes in smoking-related deaths are responsible for 19% and 22% of those increases, respectively. Among the 40 geographic areas, increases in life expectancy driven by changes in smoking ranged from 0.91 to 2.34 years for men while, for women, smoking-related changes ranged from a 0.61-year decline to a 0.45-year improvement. The most favorable trends in years of life lost to smoking tended to be concentrated in large central metros in the South and Midwest, while the least favorable trends occurred in nonmetros in these same regions. Smoking contributed to increases in mortality inequality for men aged 70+, with the contribution ranging from 8 to 24%, and for women aged 50–84, ranging from 14 to 44%.ConclusionsMortality attributable to smoking is declining fastest in large cities and coastal areas and more slowly in nonmetropolitan areas of the US. Increasing geographic inequalities in mortality are partly due to these geographic divergences in smoking patterns over the past several decades. Policies addressing smoking in non-metropolitan areas may reduce geographic inequality in mortality and contribute to future gains in life expectancy.

The 2013 Rural-Urban Continuum Codes form a classification scheme that distinguishes metropolitan counties by the population size of their metro area, and nonmetropolitan counties by degree of urbanization and adjacency to a metro area. The official Office of Management and Budget (OMB) metro and nonmetro categories have been subdivided into three metro and six nonmetro categories. Each county in the U.S. is assigned one of the 9 codes. This scheme allows researchers to break county data into finer residential groups, beyond metro and nonmetro, particularly for the analysis of trends in nonmetro areas that are related to population density and metro influence. The Rural-Urban Continuum Codes were originally developed in 1974. They have been updated each decennial since (1983, 1993, 2003, 2013), and slightly revised in 1988. Note that the 2013 Rural-Urban Continuum Codes are not directly comparable with the codes prior to 2000 because of the new methodology used in developing the 2000 metropolitan areas. See the Documentation for details and a map of the codes. An update of the Rural-Urban Continuum Codes is planned for mid-2023.

This statistic shows the percentage of adults who had a usual place to go for medical care in the U.S. in 2017, by metropolitan statistical area (MSA) status. In that year, 86.4 percent of adults not living in an MSA had a usual place to go for medical care.

Graph and download economic data for Real Per Capita Personal Income: Nonmetropolitan Portion for California (CANMPRPIPC) from 2008 to 2023 about rural, personal income, per capita, CA, personal, income, real, and USA.

The US Department of Housing and Urban Development (HUD) designates Qualified Census Tracts (QCTs) for purposes of the Low-Income Housing Tax Credit (LIHTC) program. The LIHTC program is defined in Section 42 of the Internal Revenue Code of 1986. The LIHTC is a tax incentive intended to increase the availability of affordable rental housing. The LIHTC statute provides two criteria for QCT eligibility. A census tract must have either: 1) a poverty rate of at least 25 percent; or 2) 50 percent or more of its householders must have incomes below 60 percent of the area median household income. The area corresponds to a metropolitan or a non-metropolitan area. Further, the LIHTC statute requires that no more than 20 percent of the metropolitan area population reside within designated QCTs (This limit also applies collectively to the nonmetropolitan counties in each state). Thus, it is possible for a tract to meet one or both of the above criteria, but not be designated as a QCT. With respect to the census tracts, the Census Bureau defines them in cooperation with local authorities every ten years for the purposes of the decennial census and, following a public comment period, has recently completed defining tract boundaries for the 2010 Census. Note that when census tract boundaries are set, they remain unchanged for the next decade. Thus, tract boundaries will not be changed until the 2020 Decennial Census.This is a MD iMAP hosted service. Find more information at https://imap.maryland.gov.Feature Service Link:https://mdgeodata.md.gov/imap/rest/services/BusinessEconomy/MD_HousingDesignatedAreas/FeatureServer/1

The Inflation Reduction Act of 2022 (IRA) became law on August 8, 2022. Under the law, new qualifying renewable and/or carbon-free electricity generation projects constructed in certain areas of the US, called energy communities, are eligible for bonus worth an additional 10% to the value of the production tax credit or a 10 percentage point increase in the value of the investment tax credit. The IRA does not explicitly map or list these specific communities. Instead, eligible communities are defined by a series of qualifications:

a brownfield site,

a metropolitan statistical area (MSA) or non-metropolitan statistical area with either (a) 0.17% or greater employment or (b) 25% or greater local tax revenues related to the extraction, processing, transport, or storage of coal, oil, or natural gas; and an unemployment rate at or above the national average for the previous year, or

a census tract containing or adjacent to (a) a coal mine closed after December 31, 1999 or (b) a coal-fired electric generating unit retired after December 31, 2009.

These maps and data layers contain GIS data for coal mines, coal-fired power plants, fossil energy related employment, and brownfield sites. Each record represents a point, tract or metropolitan statistical area and non-metropolitan statistical area with attributes including plant type, operating information, GEOID, etc. The input data used includes:

Brownfields – Source: EPA. No analysis was performed on this data layer. However, tract polygon layers have a column denoting brownfield presence (0 for no brownfield site, 1 if the tract contains a brownfield somewhere within the polygon).

Eligible Employment MSAs (“Final_Employment_Qualifying_MSAs”) – Source: US Census County Business Patterns. MSAs and non-MSA regions with employment over 0.17% in the fossil fuel industry (defined here as NAICS codes 211, 2121, 213, 23712, 324, 4247, and 486) and unemployment greater than or equal to 3.9% (the average national unemployment rate in 2021, according to the Bureau of Labor Statistics).

--Possibly Eligible MSAs (“FossilFuel_Employment_Qualifying_MSAs”) are MSA and non-MSA regions that meet or exceed the 0.17% employment in the fossil fuel industry threshold but do not exceed the unemployment threshold.

--Relevant columns include:

  a) SUM_nhgis0: Total employment in 2020.


  b) SUM_nhgis1: Total unemployment in 2020.


  c) P_Unemp: Percent unemployment in 2020.


  d) Q_Unemp: Boolean column indicating if the MSA or non-MSA’s unemployment rate is at or above the national average of 3.9%.


  e) FF_Qual: Boolean column indicating if the MSA or non-MSA had employment in the fossil fuel industry at or above 0.17% in the past 11 years.


  f) final_Qual: Boolean column indicating if an MSA or non-MSA qualifies for both unemployment rate and fossil fuel employment under the IRA.

Retired Power Plants – Source: EIA via HFLID. Qualifying power plants were selected by use of coal in at least one generator, and if they were retired (RET_DATE) on or after January 1, 2010. This data goes through December 2021.

--Adjacent tract data was derived by Cecelia Isaac using ESRI ArcGIS Pro.

Abandoned Coal Mines – Source: MSHA. Mines labeled “Abandoned”, “Abandoned and Sealed” or “NonProducing” between January 1, 2000 and September 2022.

--Adjacent tract data was derived by Cecelia Isaac using ESRI ArcGIS Pro.

5) US State Borders– Source: IPUMS NHGIS.

Also included here are polygon shapefiles for Onshore Wind and Solar Candidate Project Areas from Princeton REPEAT. These files have been updated to include columns related to the energy communities.

New columns include:

CoalPlantTract: Boolean column indicating if the CPA is within a tract that qualifies because of a retired coal plant.

CoalMineTract: Boolean column indicating if the CPA is within a tract that qualifies because of a closed coal mine.

FossilFuelEmp: Boolean column indicating if the CPA is within an MSA or non-MSA with greater than or equal to 0.17% employment in the fossil fuel industry.

UnempQualification: Boolean column indicating if the CPA is within an MSA or non-MSA with greater than or equal to 0.17% employment in the fossil fuel industry.

MSA_non_to: The code of the MSA or non-MSA area that contains the CPA.

P_Unemp: The percent unemployment of the MSA or non-MSA that contains the CPA in 2021.