In 2023, the metropolitan area of New York-Newark-Jersey City had the biggest population in the United States. Based on annual estimates from the census, the metropolitan area had around 19.5 million inhabitants, which was a slight decrease from the previous year. The Los Angeles and Chicago metro areas rounded out the top three. What is a metropolitan statistical area? In general, a metropolitan statistical area (MSA) is a core urbanized area with a population of at least 50,000 inhabitants – the smallest MSA is Carson City, with an estimated population of nearly 56,000. The urban area is made bigger by adjacent communities that are socially and economically linked to the center. MSAs are particularly helpful in tracking demographic change over time in large communities and allow officials to see where the largest pockets of inhabitants are in the country. How many MSAs are in the United States? There were 421 metropolitan statistical areas across the U.S. as of July 2021. The largest city in each MSA is designated the principal city and will be the first name in the title. An additional two cities can be added to the title, and these will be listed in population order based on the most recent census. So, in the example of New York-Newark-Jersey City, New York has the highest population, while Jersey City has the lowest. The U.S. Census Bureau conducts an official population count every ten years, and the new count is expected to be announced by the end of 2030.

This statistics shows a list of the top 20 largest-metropolitan areas in the United States in 2010, by land area. Riverside-San Bernardino-Ontario in California was ranked first enclosing an area of 70,612 square kilometers.

This statistics shows the top 20 fastest growing large-metropolitan areas in the United States between July 1st, 2022 and July 1st, 2023. The total population in the Wilmington, North Carolina, metropolitan area increased by 0.05 percent from 2022 to 2023.

FAF domestic region level datasets and products provide information for states, state portions of large metropolitan areas, and remainders of states. Metropolitan areas consist of Metropolitan Statistical Areas or Consolidated Statistical Areas as defined by the Office of Management and Budget. When a metropolitan area is entirely within a state or when a state's portion of a multi-state metropolitan area is large enough to support the sampling procedures in the Commodity Flow Survey, the area becomes a separate FAF region. Small single-state metropolitan areas and small portions of a multi-state metropolitan area are part of the State or Remainder of State. FAF has two metropolitan areas that are each divided into three FAF regions, four that are each divided into two FAF regions, and several that have small pieces combined with States or Remainders of States.

© United States Department of Transportation, Federal Highway Administration. For more information, see the site http://www.ops.fhwa.dot.gov/freight/freight_analysis/faf/faf3/userguide/index.htm This layer is sourced from maps.bts.dot.gov.

The spatial component of the FAF network is derived from National Highway System Version 2009.11 and contains state primary and secondary roads, National Highway System (NHS), National Network (NN) and several intermodal connectors as appropriate for the freight network modeling. The network consists of over 447,808 miles of equivalent road mileage. The data set covers the 48 contiguous States plus the District of Columbia, Alaska, and Hawaii. The nominal scale of the data set is 1:100,000 with a maximal positional error of ±80 meters.

© ederal Highway Administration Office of Freight Management and Operations and the Battelle Memorial Institute, Columbus, OH

In 2025, approximately 23 million people lived in the São Paulo metropolitan area, making it the biggest in Latin America and the Caribbean and the sixth most populated in the world. The homonymous state of São Paulo was also the most populous federal entity in the country. The second place for the region was Mexico City with 22.75 million inhabitants. Brazil's cities Brazil is home to two large metropolises, only counting the population within the city limits, São Paulo had approximately 11.45 million inhabitants, and Rio de Janeiro around 6.21 million inhabitants. It also contains a number of smaller, but well known cities such as Brasília, Salvador, Belo Horizonte and many others, which report between 2 and 3 million inhabitants each. As a result, the country's population is primarily urban, with nearly 88 percent of inhabitants living in cities. Mexico City Mexico City's metropolitan area ranks sevenths in the ranking of most populated cities in the world. Founded over the Aztec city of Tenochtitlan in 1521 after the Spanish conquest as the capital of the Viceroyalty of New Spain, the city still stands as one of the most important in Latin America. Nevertheless, the preeminent economic, political, and cultural position of Mexico City has not prevented the metropolis from suffering the problems affecting the rest of the country, namely, inequality and violence. Only in 2023, the city registered a crime incidence of 52,723 reported cases for every 100,000 inhabitants and around 24 percent of the population lived under the poverty line.

Metro Ethernet Services Market Outlook

According to our latest research, the global Metro Ethernet Services market size in 2024 is valued at USD 68.5 billion, demonstrating robust expansion driven by escalating demand for high-speed, reliable, and scalable connectivity solutions across diverse sectors. The market is expected to grow at a CAGR of 10.2% during the forecast period, reaching approximately USD 164.6 billion by 2033. The accelerating adoption of cloud-based applications, digital transformation initiatives, and the proliferation of Internet of Things (IoT) devices are the primary growth factors fueling this market’s remarkable trajectory.

The growth of the Metro Ethernet Services market is predominantly propelled by the increasing need for high-bandwidth and low-latency connectivity among enterprises and service providers. As organizations embrace digital transformation, there is a mounting requirement for robust and agile network infrastructures that can support cloud computing, unified communications, and real-time data analytics. Metro Ethernet services, with their inherent scalability and flexibility, have emerged as the preferred choice for enterprises seeking to interconnect multiple locations within metropolitan areas. The rise of data-intensive applications, such as video conferencing, online collaboration tools, and big data analytics, further amplifies the demand for reliable and high-performance Metro Ethernet solutions.

Another critical growth driver for the Metro Ethernet Services market is the ongoing evolution of smart cities and the rapid expansion of IoT ecosystems. Governments and municipalities across the globe are investing heavily in smart infrastructure to enhance urban living, optimize resource management, and improve public safety. Metro Ethernet networks serve as the backbone for these smart city initiatives, enabling seamless connectivity for surveillance systems, traffic management, public Wi-Fi, and other IoT-enabled services. The increasing deployment of 5G networks also augments the need for robust Ethernet backhaul solutions, further strengthening the market outlook for Metro Ethernet services.

Moreover, the growing trend of remote and hybrid work environments has accelerated the adoption of Metro Ethernet services among businesses of all sizes. The COVID-19 pandemic underscored the importance of resilient and secure connectivity for maintaining business continuity and supporting distributed workforces. Enterprises are increasingly leveraging Metro Ethernet to establish secure connections between branch offices, data centers, and cloud platforms, ensuring uninterrupted access to critical applications and data. The flexibility to scale bandwidth on demand and the ability to support diverse applications make Metro Ethernet an indispensable component of modern enterprise networking strategies.

From a regional perspective, North America and Asia Pacific currently dominate the Metro Ethernet Services market, accounting for a substantial share of global revenue. North America’s leadership is attributed to the presence of advanced IT infrastructure, widespread adoption of cloud services, and a large concentration of technology-driven enterprises. Meanwhile, Asia Pacific is witnessing the fastest growth, driven by rapid urbanization, increasing investments in digital infrastructure, and the proliferation of connected devices. Europe, Latin America, and the Middle East & Africa are also experiencing steady growth, fueled by digitalization initiatives and rising demand for high-speed connectivity in both urban and rural areas.

Service Type Analysis

The Service Type segment of the Metro Ethernet Services market is categorized into E-Line, E-LAN, E-Tree, E-Access, and Others. Among these, the E-Line service type holds the largest market share, owing to its simplicity, cost-effectiveness, and widespread adoption among enterprises seeking point-to-point connectivity. E-Line services are particularly favored by organizations req

This web map shows annual Gross Domestic Product (GDP) by state and metro area in the USA for 2015. Clicking on the map reveals information about how the GDP has changed over time since 2001.The overlay of metro areas over states helps to put emphasis on where the country's GDP is coming from. The darkest green states produce the largest amount of GDP, and the largest circles show which major metropolitan areas contribute the most GDP within each state. Data is from the US Bureau of Economic Analysis and was downloaded from here. The state boundaries are generalized 2010 state boundaries from the Census Bureau's 2010 MAF/TIGER database. Note-- NAICS Industry detail is based on the 2007 North American Industry Classification System (NAICS).

Among the 81 largest metropolitan areas (by population) in the United States, Knoxville, Tennessee was ranked first with **** percent of residents reporting as white, non-Hispanic in 2023.

Annual population estimates as of July 1st, by census metropolitan area and census agglomeration, single year of age, five-year age group and gender, based on the Standard Geographical Classification (SGC) 2021.

Number of employees by North American Industry Classification System (NAICS) and census metropolitan area, last 5 years.

Provides information highlights by topic via key indicators for various levels of geography.

Graph and download economic data for Resident Population in Little Rock-North Little Rock-Conway, AR (MSA) (LRSPOP) from 1970 to 2024 about Little Rock, AR, residents, population, and USA.

USNG is standard that established a nationally consistent grid reference system. It provides a seamless plane coordinate system across jurisdictional boundaries and map scales; it enables precise position referencing with GPS, web map portals, and hardcopy maps. USNG enables a practical system of geoaddresses and a universal map index. This data resides in the GCS 1983 coordinate system and is most suitable for viewing over North America.

The data is separated into three groups, Small Scale Grids, 1000m Grids, and 100m Grids. The small scale grid group contains grids shown at smaller scales including the 6 x 8 decimal degree grids, the 100000m grids, and the 10000m grids. The 1000m grid group shows 1,000 meter grid squares. Due to the large volume of 1000m data, the 1000m grids are separate into UTM zones. This speeds up the querying time of the 1000m grids. The 100m grid group contains 100m grids for various metropolitan area in the U.S. and Puerto Rico. These metropolitan areas are further separate into time zones so it's easier to navigate through the Table of Contents to find a metro area.

Sustainable cities depend on urban forests. City trees -- a pillar of urban forests -- improve our health, clean the air, store CO2, and cool local temperatures. Comparatively less is known about urban forests as ecosystems, particularly their spatial composition, nativity statuses, biodiversity, and tree health. Here, we assembled and standardized a new dataset of N=5,660,237 trees from 63 of the largest US cities. The data comes from tree inventories conducted at the level of cities and/or neighborhoods. Each data sheet includes detailed information on tree location, species, nativity status (whether a tree species is naturally occurring or introduced), health, size, whether it is in a park or urban area, and more (comprising 28 standardized columns per datasheet). This dataset could be analyzed in combination with citizen-science datasets on bird, insect, or plant biodiversity; social and demographic data; or data on the physical environment. Urban forests offer a rare opportunity to intentionally design biodiverse, heterogenous, rich ecosystems. Methods See eLife manuscript for full details. Below, we provide a summary of how the dataset was collected and processed.

Data Acquisition We limited our search to the 150 largest cities in the USA (by census population). To acquire raw data on street tree communities, we used a search protocol on both Google and Google Datasets Search (https://datasetsearch.research.google.com/). We first searched the city name plus each of the following: street trees, city trees, tree inventory, urban forest, and urban canopy (all combinations totaled 20 searches per city, 10 each in Google and Google Datasets Search). We then read the first page of google results and the top 20 results from Google Datasets Search. If the same named city in the wrong state appeared in the results, we redid the 20 searches adding the state name. If no data were found, we contacted a relevant state official via email or phone with an inquiry about their street tree inventory. Datasheets were received and transformed to .csv format (if they were not already in that format). We received data on street trees from 64 cities. One city, El Paso, had data only in summary format and was therefore excluded from analyses.

Data Cleaning All code used is in the zipped folder Data S5 in the eLife publication. Before cleaning the data, we ensured that all reported trees for each city were located within the greater metropolitan area of the city (for certain inventories, many suburbs were reported - some within the greater metropolitan area, others not). First, we renamed all columns in the received .csv sheets, referring to the metadata and according to our standardized definitions (Table S4). To harmonize tree health and condition data across different cities, we inspected metadata from the tree inventories and converted all numeric scores to a descriptive scale including “excellent,” “good”, “fair”, “poor”, “dead”, and “dead/dying”. Some cities included only three points on this scale (e.g., “good”, “poor”, “dead/dying”) while others included five (e.g., “excellent,” “good”, “fair”, “poor”, “dead”). Second, we used pandas in Python (W. McKinney & Others, 2011) to correct typos, non-ASCII characters, variable spellings, date format, units used (we converted all units to metric), address issues, and common name format. In some cases, units were not specified for tree diameter at breast height (DBH) and tree height; we determined the units based on typical sizes for trees of a particular species. Wherever diameter was reported, we assumed it was DBH. We standardized health and condition data across cities, preserving the highest granularity available for each city. For our analysis, we converted this variable to a binary (see section Condition and Health). We created a column called “location_type” to label whether a given tree was growing in the built environment or in green space. All of the changes we made, and decision points, are preserved in Data S9. Third, we checked the scientific names reported using gnr_resolve in the R library taxize (Chamberlain & Szöcs, 2013), with the option Best_match_only set to TRUE (Data S9). Through an iterative process, we manually checked the results and corrected typos in the scientific names until all names were either a perfect match (n=1771 species) or partial match with threshold greater than 0.75 (n=453 species). BGS manually reviewed all partial matches to ensure that they were the correct species name, and then we programmatically corrected these partial matches (for example, Magnolia grandifolia-- which is not a species name of a known tree-- was corrected to Magnolia grandiflora, and Pheonix canariensus was corrected to its proper spelling of Phoenix canariensis). Because many of these tree inventories were crowd-sourced or generated in part through citizen science, such typos and misspellings are to be expected. Some tree inventories reported species by common names only. Therefore, our fourth step in data cleaning was to convert common names to scientific names. We generated a lookup table by summarizing all pairings of common and scientific names in the inventories for which both were reported. We manually reviewed the common to scientific name pairings, confirming that all were correct. Then we programmatically assigned scientific names to all common names (Data S9). Fifth, we assigned native status to each tree through reference to the Biota of North America Project (Kartesz, 2018), which has collected data on all native and non-native species occurrences throughout the US states. Specifically, we determined whether each tree species in a given city was native to that state, not native to that state, or that we did not have enough information to determine nativity (for cases where only the genus was known). Sixth, some cities reported only the street address but not latitude and longitude. For these cities, we used the OpenCageGeocoder (https://opencagedata.com/) to convert addresses to latitude and longitude coordinates (Data S9). OpenCageGeocoder leverages open data and is used by many academic institutions (see https://opencagedata.com/solutions/academia). Seventh, we trimmed each city dataset to include only the standardized columns we identified in Table S4. After each stage of data cleaning, we performed manual spot checking to identify any issues.

Data on language used most often at work by other language(s) used regularly at work, mother tongue, industry - North American Industry Classification System (NAICS) 2017, highest certificate, diploma or degree and labour force status for the population aged 15 years and over who worked since 2020, in private households of Canada, provinces and territories, census metropolitan areas and census agglomerations with parts.

Canada's largest metropolitan area is Toronto, in Ontario. In 2022. Over 6.6 million people were living in the Toronto metropolitan area. Montréal, in Quebec, followed with about 4.4 million inhabitants, while Vancouver, in Britsh Columbia, counted 2.8 million people as of 2022.

Key Table Information.Table Title.Nonemployer Statistics by Demographics series (NES-D): Owner Characteristics of Nonemployer Firms by Industry, Sex, Ethnicity, Race, and Veteran Status for the U.S., States, Metro Areas, Counties, and Places: 2022.Table ID.ABSNESDO2022.AB2200NESD04.Survey/Program.Economic Surveys.Year.2022.Dataset.ECNSVY Nonemployer Statistics by Demographics Characteristics of Business Owners.Source.U.S. Census Bureau, 2022 Economic Surveys, Nonemployer Statistics by Demographics.Release Date.2025-05-08.Release Schedule.The Nonemployer Statistics by Demographics (NES-D) is released yearly, beginning in 2017..Table Universe.Includes U.S. firms with no paid employment or payroll, annual receipts of $1,000 or more ($1 or more in the construction industries) and filing Internal Revenue Service (IRS) tax forms for sole proprietorships (Form 1040, Schedule C), partnerships (Form 1065), or corporations (the Form 1120 series).Data are also obtained from administrative records, the 2022 Economic Census, and other economic surveys..Methodology.Data Items and Other Identifying Records.Number of owners of nonemployer firmsPercent of number of owners of nonemployer firms (%)These data are aggregated at the owner level for up to four persons owning the largest percentages of the business by sex, ethnicity, race, and veteran status.Using administrative records, owner characteristics were assigned for the following categories: Place of Birth (USBORN) Owner was born in the U.S. Owner was born outside the U.S. U.S. Citizenship (USCITIZEN) Owner is a citizen of the U.S. Owner is not a citizen of the U.S. Owner Age (OWNRAGE) Under 25 25 to 34 35 to 44 45 to 54 55 to 64 65 or over Question Description codes for the topics are in parenthesis.Definitions can be found by clicking on the column header in the table or by accessing the Economic Census Glossary..Unit(s) of Observation.The reporting units for the NES-D are nonemployer companies or firms rather than establishments. A company or firm is comprised of one or more in-scope establishments that operate under the ownership or control of a single organization..Geography Coverage.The 2022 data are shown for the total of all sectors (00) and the 2- to 4-digit NAICS code levels for:United StatesIn addition, the total of all sectors (00) NAICS and the 2-digit NAICS code levels for:States and the District of ColumbiaThe remaining geographies are available at the total of all sectors (00):Metropolitan Statistical AreasMicropolitan Statistical AreasMetropolitan DivisionsCombined Statistical AreasCountiesEconomic PlacesFor information about geographies, see Geographies..Industry Coverage.The data are shown for the total of all sectors ("00"), and at the 2- through 4-digit NAICS code levels depending on geography. Sector "00" is not an official NAICS sector but is rather a way to indicate a total for multiple sectors. Note: Other programs outside of ABS may use sector 00 to indicate when multiple NAICS sectors are being displayed within the same table and/or dataset.The following are excluded from the total of all sectors:Crop and Animal Production (NAICS 111 and 112)Rail Transportation (NAICS 482)Postal Service (NAICS 491)Monetary Authorities-Central Bank (NAICS 521)Funds, Trusts, and Other Financial Vehicles (NAICS 525)Office of Notaries (NAICS 541120)Religious, Grantmaking, Civic, Professional, and Similar Organizations (NAICS 813)Private Households (NAICS 814)Public Administration (NAICS 92)For information about NAICS, see North American Industry Classification System..Sampling.NES-D nonemployer data are not conducted through sampling. Nonemployer Statistics (NES) data originate from statistical information obtained through business income tax records that the Internal Revenue Service (IRS) provides to the Census Bureau. The NES-D adds demographic characteristics to the NES data and produces the total firm counts and the total receipts by those demographic characteristics. The NES-D utilizes various administrative records (AR) and the Census Bureau data sources that include the Business Register (BR), Internal Revenue Service (IRS) tax Form 1040 data, tax Schedule K-1 data, Decennial Census and American Community Survey (ACS) data, Social Security Administration's database (Numident), and AR from the Department of Veterans Affairs (VA).For more information, see Nonemployer Statistics by Demographics Methodology..Confidentiality.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. P-7504866, Disclosure Review Board (DRB) approval number: CBDRB-FY25-0195).For the nonemployer data, the NES-D uses noise infusion as the primary method of disclosure avoidance for receipts, and In certain circumstances, some individual cells may be suppressed for additional disclosure avoidance. More information on nonemployer firm disclosure avoidance is available in the ...

The global metro car market is experiencing robust growth, driven by increasing urbanization, rising passenger traffic in metropolitan areas, and government initiatives promoting sustainable public transportation. The market, valued at approximately $25 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 7% from 2025 to 2033, reaching an estimated market size of $45 billion by 2033. This growth is fueled by several key trends, including the adoption of advanced technologies like automated train operation systems and lightweight materials to enhance efficiency and reduce energy consumption. Furthermore, the expansion of existing metro networks and the development of new lines in emerging economies are significantly contributing to market expansion. While challenges such as high initial infrastructure investment costs and potential supply chain disruptions exist, the long-term outlook remains positive, driven by the sustained need for efficient and sustainable urban transportation solutions. The market segmentation reveals a dynamic landscape. Type A, B, and C metro cars cater to varying operational needs and passenger capacities, with Type A cars (smaller capacity) holding a significant share due to their suitability for smaller cities and less congested routes. Large cities are currently the largest consumers of metro cars, however, medium and smaller cities are experiencing substantial growth reflecting the expanding urban footprint globally. Geographically, Asia-Pacific, particularly China and India, are major contributors to the market's growth, fueled by rapid urbanization and substantial investment in public transportation infrastructure. North America and Europe also represent significant markets, driven by upgrades and expansions of existing networks and the focus on sustainable transportation. Key players like CRRC, Knorr-Bremse, Bombardier, Alstom, Siemens, Hitachi, BEML Limited, and Skoda Transportation are actively involved in this growth, constantly innovating to meet evolving market demands.

North America Wall Beds Market size was valued at USD 2.95 Billion in 2024 and is projected to reach USD 4.97 Billion by 2032, growing at a CAGR of 6.6% from 2026 to 2032.Key Market DriversIncreasing Urban Population and Smaller Living Spaces: The growing urban population and trend toward compact living spaces in major North American metropolitan areas have significantly boosted the demand for space-saving furniture solutions such as wall beds. According to the U.S. Census Bureau's American Community Survey (2022), the average apartment size in major U.S. metropolitan areas decreased by 9.7% between 2020 and 2022, from 941 square feet to 850 square feet..Rise in Remote Work and Home Office Requirements: The COVID-19 pandemic fundamentally transformed work arrangements across North America, with remote and hybrid work models becoming permanent fixtures for many companies. The U.S. Bureau of Labor Statistics reported that 27.6% of the American workforce operated in hybrid or fully remote arrangements by the end of 2022, compared to just 5.7% pre-pandemic (2019)..

Release Date: 2022-11-10.The Census Bureau has reviewed this data product for unauthorized disclosure of confidential information and has approved the disclosure avoidance practices applied (Approval ID: CBDRB-FY22-308)...Release Schedule:.Data in this file come from estimates of business ownership by sex, ethnicity, race, and veteran status from the 2021 Annual Business Survey (ABS) collection. Data are also obtained from administrative records, the 2017 Economic Census, and other economic surveys...Note: The collection year is the year in which the data are collected. A reference year is the year that is referenced in the questions on the survey and in which the statistics are tabulated. For example, the 2021 ABS collection year produces statistics for the 2020 reference year. The "Year" column in the table is the reference year...For more information about ABS planned data product releases, see Tentative ABS Schedule...Key Table Information:.This is one of four tables in the ABS series to provide select economic and demographic characteristics of businesses (CB) for U.S. employer firms that reported the sex, ethnicity, race, and veteran status for up to four persons owning the largest percentage(s) of the business. The data include U.S. firms with paid employees operating during the reference year with receipts of $1,000 or more, which are classified in the North American Industry Classification System (NAICS), Sectors 11 through 99, except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered. Employer firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. and state totals for all sectors. Firms are asked to report their employees as of the March 12 pay period...Data Items and Other Identifying Records:.Data include estimates on:.Number of employer firms (firms with paid employees). Percent of employer firms (%). Sales and receipts of employer firms (reported in $1,000s of dollars). Percent of sales and receipts of employer firms (%). Number of employees (during the March 12 pay period). Percent of employees (%). Annual payroll (reported in $1,000s of dollars). Percent of annual payroll (%)...These data are aggregated by the following demographic classifications of firm for:.All firms. Classifiable (firms classifiable by sex, ethnicity, race, and veteran status). . Sex. Female. Male. Equally male/female. . Ethnicity. Hispanic. Equally Hispanic/non-Hispanic. Non-Hispanic. . Race. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Minority (Firms classified as any race and ethnicity combination other than non-Hispanic and White). Equally minority/nonminority. Nonminority (Firms classified as non-Hispanic and White). . Veteran Status (defined as having served in any branch of the U.S. Armed Forces). Veteran. Equally veteran/nonveteran. Nonveteran. . . . Unclassifiable (firms not classifiable by sex, ethnicity, race, and veteran status). ...Data Notes:.. Business ownership is defined as having 51 percent or more of the stock or equity in the business. Data are provided for businesses owned equally (50% / 50%) by men and women, by Hispanics and non-Hispanics, by minorities and nonminorities, and by veterans and nonveterans.. The detail may not add to the total or subgroup total because a Hispanic or Latino firm may be of any race, and because a firm could be tabulated in more than one racial group. For example, if a firm responded as both Chinese and Black majority owned, the firm would be included in the detailed Asian and Black estimates but would only be counted once toward the higher level all firms' estimates.. References such as "Hispanic- or Latino-owned" businesses refer only to businesses operating in the 50 states and the District of Columbia that self-identified 51 percent or more of their ownership in 2020 to be by individuals of Mexican, Puerto Rican, Cuban or other Hispanic or Latino origin. The ABS does not distinguish between U.S. residents and nonresidents. Companies owned by foreign governments or owned by other companies, foreign or domestic, are included in the category "Unclassifiable."...Business Characteristics:.The ABS was designed to include select questions about business characteristics from multiple reference periods and to incorporate new content each survey year based on topics of relevance...Respondent firms include all firms that responded to the characteristics tabulated in this dataset and reported sex, ethnicity, race, or veteran status, or that were not classifiable by sex, ethnicity, race, or veteran status. Percentages are for r...