In 2022, San Francisco had the highest median household income of cities ranking within the top 25 in terms of population, with a median household income in of 136,692 U.S. dollars. In that year, San Jose in California was ranked second, and Seattle, Washington third.

Following a fall after the great recession, median household income in the United States has been increasing in recent years. As of 2022, median household income by state was highest in Maryland, Washington, D.C., Utah, and Massachusetts. It was lowest in Mississippi, West Virginia, and Arkansas. Families with an annual income of 25,000 and 49,999 U.S. dollars made up the largest income bracket in America, with about 25.26 million households.

Data on median household income can be compared to statistics on personal income in the U.S. released by the Bureau of Economic Analysis. Personal income rose to around 21.8 trillion U.S. dollars in 2022, the highest value recorded. Personal income is a measure of the total income received by persons from all sources, while median household income is “the amount with divides the income distribution into two equal groups,” according to the U.S. Census Bureau. Half of the population in question lives above median income and half lives below. Though total personal income has increased in recent years, this wealth is not distributed throughout the population. In practical terms, income of most households has decreased. One additional statistic illustrates this disparity: for the lowest quintile of workers, mean household income has remained more or less steady for the past decade at about 13 to 16 thousand constant U.S. dollars annually. Meanwhile, income for the top five percent of workers has actually risen from about 285,000 U.S. dollars in 1990 to about 499,900 U.S. dollars in 2020.

Moldova MD: Employment To Population Ratio: Modeled ILO Estimate: Aged 15-24: Male data was reported at 18.514 % in 2017. This records a decrease from the previous number of 19.194 % for 2016. Moldova MD: Employment To Population Ratio: Modeled ILO Estimate: Aged 15-24: Male data is updated yearly, averaging 19.870 % from Dec 1991 (Median) to 2017, with 27 observations. The data reached an all-time high of 22.928 % in 1992 and a record low of 16.011 % in 1999. Moldova MD: Employment To Population Ratio: Modeled ILO Estimate: Aged 15-24: Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Moldova – Table MD.World Bank.WDI: Employment and Unemployment. Employment to population ratio is the proportion of a country's population that is employed. Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15-24 are generally considered the youth population.; ; International Labour Organization, ILOSTAT database. Data retrieved in September 2018.; Weighted average; Data up to 2016 are estimates while data from 2017 are projections. National estimates are also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.

Abstract

The 2011 Nepal Demographic and Health Survey is the fourth nationally representative comprehensive survey conducted as part of the worldwide Demographic and Health Surveys (DHS) project in the country. The survey was implemented by New ERA under the aegis of the Population Division, Ministry of Health and Population. Technical support for this survey was provided by ICF International with financial support from the United States Agency for International Development (USAID) through its mission in Nepal.

The primary objective of the 2011 NDHS is to provide up-to-date and reliable data on different issues related to population and health, which provides guidance in planning, implementing, monitoring, and evaluating health programs in Nepal. The long term objective of the survey is to strengthen the technical capacity of the local institutions to plan, conduct, process and analyze data from complex national population and health surveys. The survey includes topics on fertility levels and determinants, family planning, fertility preferences, childhood mortality, children and women’s nutritional status, the utilization of maternal and child health services, knowledge of HIV/AIDS and STIs, women’s empowerment and for the first time, information on women facing different types of domestic violence. The survey also reports on the anemia status of women age 15-49 and children age 6-59 months.

In addition to providing national estimates, the survey report also provides disaggregated data at the level of various domains such as ecological region, development regions and for urban and rural areas. This being the fourth survey of its kind, there is considerable trend information on reproductive and health care over the past 15 years. Moreover, the 2011 NDHS is comparable to similar surveys conducted in other countries and therefore, affords an international comparison. The 2011 NDHS also adds to the vast and growing international database on demographic and health-related variables.

The 2011 NDHS collected demographic and health information from a nationally representative sample of 10,826 households, which yielded completed interviews with 12,674 women age 15-49 in all selected households and with 4, 121 men age 15-49 in every second household.

This survey is the concerted effort of various individuals and institutions.

Geographic coverage

The primary focus of the 2011 NDHS was to provide estimates of key population and health indicators, including fertility and mortality rates, for the country as a whole and for urban and rural areas separately. In addition, the sample was designed to provide estimates of most key variables for the 13 eco-development regions.

Analysis unit

Household, adult woman, adult man

Kind of data

Sample survey data

Sampling procedure

The primary focus of the 2011 NDHS was to provide estimates of key population and health indicators, including fertility and mortality rates, for the country as a whole and for urban and rural areas separately. In addition, the sample was designed to provide estimates of most key variables for the 13 eco-development regions.

Sampling Frame

Nepal is divided into 75 districts, which are further divided into smaller VDCs and municipalities. The VDCs and municipalities, in turn, are further divided into wards. The larger wards in the urban areas are divided into subwards. An enumeration area (EA) is defined as a ward in rural areas and a subward in urban areas. Each EA is classified as urban or rural. As the upcoming population census was scheduled for June 2011, the 2011 NDHS used the list of EAs with population and household information developed by the Central Bureau of Statistics for the 2001 Population Census. The long gap between the 2001 census and the fielding of the 2011 NDHS necessitated an updating of the 2001 sampling frame to take into account not only population growth but also mass internal and external migration due to the 10-year political conflict in the country. To obtain an updated list, a partial updating of the 2001 census frame was carried out by conducting a quick count of dwelling units in EAs five times more than the sample required for each of the 13 domains. The results of the quick count survey served as the actual frame for the 2011 NDHS sample design.

Domains

The country is broadly divided into three horizontal ecological zones, namely mountain, hill, and terai. Vertically, the country is divided into five development regions. The cross section of these zones and regions results in 15 eco-development regions, which are referred to in the 2011 NDHS as subregions or domains. Due to the small population size in the mountain regions, the Western, Mid-western, and Far-western mountain regions are combined into one domain, yielding a total of 13 domains. In order to provide an adequate sample to calculate most of the key indicators at an acceptable level of precision, each domain had a minimum of about 600 households.

Stratification was achieved by separating each of the 13 domains into urban and rural areas. The 2011 NDHS used the same urban-rural stratification as in the 2001 census frame. In total, 25 sampling strata were created. There are no urban areas in the Western, Mid-western, and Far-western mountain regions. The numbers of wards and subwards in each of the 13 domains are not allocated proportional to their population due to the need to provide estimates with acceptable levels of statistical precision for each domain and for urban and rural domains of the country as a whole. The vast majority of the population in Nepal resides in the rural areas. In order to provide national urban estimates, urban areas of the country were oversampled.

Sample Selection

Samples were selected independently in each stratum through a two-stage selection process. In the first stage, EAs were selected using a probability-proportional-to-size strategy. In order to achieve the target sample size in each domain, the ratio of urban EAs to rural EAs in each domain was roughly 1 to 2, resulting in 95 urban and 194 rural EAs (a total of 289 EAs).

Complete household listing and mapping was carried out in all selected EAs (clusters). In the second stage, 35 households in each urban EA and 40 households in each rural EA were randomly selected. Due to the nonproportional allocation of the sample to the different domains and to oversampling of urban areas in each domain, sampling weights are required for any analysis using the 2011 NDHS data to ensure the actual representativeness of the sample at the national level as well as at the domain levels. Since the 2011 NDHS sample is a two-stage stratified cluster sample, sampling weights were calculated based on sampling probabilities separately for each sampling stage, taking into account nonproportionality in the allocation process for domains and urban-rural strata.

Mode of data collection

Face-to-face

Research instrument

Three questionnaires were administered in the 2011 NDHS: the Household Questionnaire, the Woman’s Questionnaire, and the Man’s Questionnaire. These questionnaires were adapted from the standard DHS6 core questionnaires to reflect the population and health issues relevant to Nepal at a series of meetings with various stakeholders from government ministries and agencies, nongovernmental organizations, EDPs, and international donors. The final draft of each questionnaire was discussed at a questionnaire design workshop organized by the MOHP, Population Division on 22 April 2010 in Kathmandu. These questionnaires were then translated from English into the three main local languages—Nepali, Maithali, and Bhojpuri—and back translated into English. Questionnaires were finalized after the pretest, which was held from 30 September to 4 November 2010, with a one-week break in October for the Dasain holiday.

The Household Questionnaire was used to list all of the usual members and visitors in the selected households. Some basic information was collected on the characteristics of each person listed, including age, sex, education, and relationship to the head of the household. For children under age 18, the survival status of the parents was determined. The Household Questionnaire was used to identify women and men who were eligible for the individual interview and women who were eligible for the interview focusing on domestic violence. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as source of water, type of toilet facilities, materials used for the floor of the house, ownership of various durable goods, ownership of mosquito nets, and household food security. The results of salt testing for iodine content, height and weight measurements, and anemia testing were also recorded in the Household Questionnaire.

The Woman’s Questionnaire was used to collect information from women age 15-49. Women were asked questions on the following topics: - background characteristics (education, residential history, media exposure, etc.) - pregnancy history and childhood mortality - knowledge and use of family planning methods - fertility preferences - antenatal, delivery, and postnatal care - breastfeeding and infant feeding practices - vaccinations and childhood illnesses - marriage and sexual activity - work characteristics and husband’s background characteristics - awareness and behavior regarding AIDS and other sexually transmitted infections - domestic violence

The Man’s Questionnaire was administered to all men age 15-49 living in every second household in the 2011 NDHS. The Man’s Questionnaire collected much of the same information as the Woman’s Questionnaire but was shorter

description: Several investigators working on the food habits of the black duck (Anas rubripes), have reported the presence of soft clams (Mya arenaria), in their stomachs and necks. The extent of this feeding and its relation to the clam population is the purpose of the present investigation. At the request of the director of the U.S. Fish and Wildlife Service, this detail was started October 24, 1946, on the clam flats located within the Plum Island section of the Parker River National Wildlife Refuge, Essex County, Massachusetts. The investigation continued on the flats until December 10. Further examination of samples taken from the clam flats and duck stomachs before December 10 was continued at the field station of the U.S. Fish and Wildlife Service, Annapolis, Maryland, during the early part of 1947. The investigation was planned for this time to include in the observations any changes in the black duck population occurring during the Fall migrations or from the disturbances attributed to the hunting season that opened on October 26, 1946. The migration was well underway when this study was inaugurated and only minor changes in the population were noticed during the period of these observations. The black duck population of the area was estimated by various ornithologists and confirmed by Mr. Charles E Addy of the Fish and Wildlife Service as about 2,000 in September increasing during the Fall to about 4,000 in October and November when the black duck migration was in full swing.; abstract: Several investigators working on the food habits of the black duck (Anas rubripes), have reported the presence of soft clams (Mya arenaria), in their stomachs and necks. The extent of this feeding and its relation to the clam population is the purpose of the present investigation. At the request of the director of the U.S. Fish and Wildlife Service, this detail was started October 24, 1946, on the clam flats located within the Plum Island section of the Parker River National Wildlife Refuge, Essex County, Massachusetts. The investigation continued on the flats until December 10. Further examination of samples taken from the clam flats and duck stomachs before December 10 was continued at the field station of the U.S. Fish and Wildlife Service, Annapolis, Maryland, during the early part of 1947. The investigation was planned for this time to include in the observations any changes in the black duck population occurring during the Fall migrations or from the disturbances attributed to the hunting season that opened on October 26, 1946. The migration was well underway when this study was inaugurated and only minor changes in the population were noticed during the period of these observations. The black duck population of the area was estimated by various ornithologists and confirmed by Mr. Charles E Addy of the Fish and Wildlife Service as about 2,000 in September increasing during the Fall to about 4,000 in October and November when the black duck migration was in full swing.

Dates and locations of Callinectes blue crab samples from the coastal Atlantic waters of north and south America, Gulf of Mexico and Caribbean from Massachusetts to Uruguay from 2017 through 2019. Crab populations sampled using methods available to collaborating scientists, managers, and fishermen, as listed in the table. access_formats=.htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson acquisition_description="" awards_0_award_nid=739620 awards_0_award_number=OCE-1658466 awards_0_data_url=http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1658466 awards_0_funder_name=NSF Division of Ocean Sciences awards_0_funding_acronym=NSF OCE awards_0_funding_source_nid=355 awards_0_program_manager=Daniel Thornhill awards_0_program_manager_nid=722161 awards_1_award_nid=739627 awards_1_award_number=OCE-1658396 awards_1_data_url=http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1658396 awards_1_funder_name=NSF Division of Ocean Sciences awards_1_funding_acronym=NSF OCE awards_1_funding_source_nid=355 awards_1_program_manager=Daniel Thornhill awards_1_program_manager_nid=722161 awards_2_award_nid=739631 awards_2_award_number=OCE-1658389 awards_2_data_url=http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1658389 awards_2_funder_name=NSF Division of Ocean Sciences awards_2_funding_acronym=NSF OCE awards_2_funding_source_nid=355 awards_2_program_manager=Daniel Thornhill awards_2_program_manager_nid=722161 cdm_data_type=Other comment=Dates and locations of Callinectes blue crab samples from the coastal Atlantic waters of north and south America, Gulf of Mexico and Caribbean from Massachusetts to Uruguay from 2017 through 2019 PI: Eric Schott Version: 2020-01-16 Conventions=COARDS, CF-1.6, ACDD-1.3 data_source=extract_data_as_tsv version 2.3 19 Dec 2019 defaultDataQuery=&time<now doi=10.1575/1912/bco-dmo.785930.1 Easternmost_Easting=-36.5267 geospatial_lat_max=41.5317 geospatial_lat_min=-34.6285 geospatial_lat_units=degrees_north geospatial_lon_max=-36.5267 geospatial_lon_min=-97.199 geospatial_lon_units=degrees_east infoUrl=https://www.bco-dmo.org/dataset/785930 institution=BCO-DMO metadata_source=https://www.bco-dmo.org/api/dataset/785930 Northernmost_Northing=41.5317 param_mapping={'785930': {'Latitude': 'flag - latitude', 'Longitude': 'flag - longitude'}} parameter_source=https://www.bco-dmo.org/mapserver/dataset/785930/parameters people_0_affiliation=University of Maryland Center for Environmental Science people_0_affiliation_acronym=UMCES/IMET people_0_person_name=Eric Schott people_0_person_nid=739623 people_0_role=Principal Investigator people_0_role_type=originator people_1_affiliation=University of Florida people_1_affiliation_acronym=UF people_1_person_name=Donald Behringer people_1_person_nid=472641 people_1_role=Co-Principal Investigator people_1_role_type=originator people_2_affiliation=Shedd Aquarium people_2_person_name=Andrew Kough people_2_person_nid=739633 people_2_role=Co-Principal Investigator people_2_role_type=originator people_3_affiliation=University of Maryland Center for Environmental Science people_3_affiliation_acronym=UMCES/HPL people_3_person_name=Dr Louis V. Plough people_3_person_nid=627831 people_3_role=Co-Principal Investigator people_3_role_type=originator people_4_affiliation=Woods Hole Oceanographic Institution people_4_affiliation_acronym=WHOI BCO-DMO people_4_person_name=Mathew Biddle people_4_person_nid=708682 people_4_role=BCO-DMO Data Manager people_4_role_type=related project=Blue Crab Connectivity projects_0_acronym=Blue Crab Connectivity projects_0_description=NSF Award Abstract: Marine invertebrates use an array of strategies to survive, move, and reproduce across diverse and dynamic environmental conditions. This project investigates the intersection of these strategies and how they facilitate the persistence of blue crabs and a pathogenic virus along the Atlantic coast of North and South America. The widespread distribution of this crab-virus system makes it useful for investigating host-pathogen interactions. Blue crabs can reduce their activity level and induce winter dormancy in colder climates, but it is unclear how this alters progression and transmission of the pathogen. Conversely, year-round growth and reproduction of tropical blue crabs may be offset by higher pathogen abundance and activity. This project will use a combination of field and laboratory studies to reveal how crab life history and pathogen dynamics interact and adapt at the extremes of their range. Genetic sequencing, crab movement tracking and oceanographic models will be used to understand how crab-disease dynamics vary across temperate and tropical latitudes. The blue crab is an ecologically and economically important species and knowledge generated in this project will help provide management guidance to support sustainable fisheries. Best practices to avoid and limit disease will be communicated to commercial and artisanal harvesters through partnerships and workshops. Local high school and undergraduate students from underrepresented groups will be engaged through a variety of formal and informal educational programs. Public outreach will be implemented through a museum partnership with the Shedd Aquarium and will include the training of a science communication intern. This collaborative project will combine empirical field and laboratory experiments, population genomics, and biophysical modeling to explore the consequences of latitude-driven changes in life history and oceanic connectivity on a trans-hemispheric pathosystem comprised of the blue crab, Callinectes sapidus, and the pathogenic virus, CsRV1. The virulence of the CsRV1 virus from tropical and temperate latitudes and the impact of overwintering will be studied by experimental virus challenges of crabs transplanted between high and low latitudes. The impact of infection and virulence on crab movement will be investigated in laboratory raceway experiments of healthy and infected crabs and in the field with acoustically tagged crabs deployed in temperate and tropical locations. Population genetic studies using thousands of genome-wide RAD sequencing markers for crabs and whole-genome sequencing for the virus will define genetic connectivity of crab and virus populations across their range, and will investigate the possible latitudinal, seascape, and life history-driven changes in blue crab and virus genomes. The two population genomic data sets are expected to provide different inferences and scales of connectivity because CsRV1 virus genotypes are transmitted only among post-larval crabs while blue crab genotypes also move by a potentially long-range dispersive larval stage. Finally, integrated biophysical models will be used to investigate the relative contributions of adult and larval dispersal on the population structure of the crab and the pathogen across a broad swath of habitat between New England and Argentina with a decade of simulations. An open-source Lagrangian stochastic model will estimate pelagic larval transport, and spatially explicit biased-correlated random walk models will estimate adult movement. Models will be informed by experimentally-derived movement and behavior data, as well as information on crab larval and adult behavior and overwintering duration available in the published literature. Under a series of scenarios in which crab behavior is affected by latitude and virus infection, statistical comparisons will be made between biophysical model-based predictions of connectivity and genetic estimates of connectivity. These analyses will advance our understanding of the physical, environmental, and biological factors that shape the dynamics of the blue crab CsRV1 pathosystem. projects_0_end_date=2020-06 projects_0_geolocation=Atlantic coast of north and south America from Massachusetts to Southern Brazil, Caribbean projects_0_name=Collaborative research: Variation in life history and connectivity as drivers of pathogen-host dynamics and genetic structure in a trans-hemispheric pathosystem projects_0_project_nid=739621 projects_0_start_date=2017-07 sourceUrl=(local files) Southernmost_Northing=-34.6285 standard_name_vocabulary=CF Standard Name Table v55 version=1 Westernmost_Easting=-97.199 xml_source=osprey2erddap.update_xml() v1.3

In 2023, just over 50 percent of Americans had an annual household income that was less than 75,000 U.S. dollars. The median household income was 80,610 U.S. dollars in 2023. Income and wealth in the United States After the economic recession in 2009, income inequality in the U.S. is more prominent across many metropolitan areas. The Northeast region is regarded as one of the wealthiest in the country. Maryland, New Jersey, and Massachusetts were among the states with the highest median household income in 2020. In terms of income by race and ethnicity, the average income of Asian households was 94,903 U.S. dollars in 2020, while the median income for Black households was around half of that figure. What is the U.S. poverty threshold? The U.S. Census Bureau annually updates its list of poverty levels. Preliminary estimates show that the average poverty threshold for a family of four people was 26,500 U.S. dollars in 2021, which is around 100 U.S. dollars less than the previous year. There were an estimated 37.9 million people in poverty across the United States in 2021, which was around 11.6 percent of the population. Approximately 19.5 percent of those in poverty were Black, while 8.2 percent were white.

This collection contains five modified data sets with mortality, population, and other demographic information for five American cities (Baltimore, Maryland; Boston, Massachusetts; New Orleans, Louisiana; New York City (Manhattan only), New York; and Philadelphia, Pennsylvania) from the early 19th century to the early 20th century. Mortality was represented by an annual crude death rate (deaths per 1000 population per year). The population was linearly interpolated from U.S. Census data and state census data (for Boston and New York City). All data sets include variables for year, total deaths, census populations, estimated annual linearly interpolated populations, and crude death rate. The Baltimore data set (DS0001) also provides birth and death rate variables based on race and slave status demographics, as well as a variable for stillbirths. The Philadelphia data set (DS0005) also includes variables for total births, total infant deaths, crude birth rate, and infant deaths per 1,000 live births.

computer-assisted personal interview (CAPI); computer-assisted telephone interview (CATI)This data collection was previously distributed by the National Endowment for the Arts (NEA) from their website. The SPPA 2012 was originally released in September 2013. This previous release has been revised to reflect changes in how the 2012 SPPA counted "interviews." Specifically, the Census revisions count "yes," "no," and "don't know" as interviews, in accordance with estimates generated from the 2008 and earlier waves of the SPPA. Alternatively, the September 2013 estimates provided by the U.S. Census Bureau had included respondents who "refused to answer" as interviews--an action that clouded comparisons with previous SPPA waves. Many of the 2012 SPPA estimates were unaffected by these revisions. And of those that were affected, most changes to participation rates were marginal, often in the range of 1-2 tenths of a percentage point. Users are strongly encouraged to refer the CPS User Guide (produced by the Census Bureau), which contains additional detailed technical documentation regarding the CPS study design, sampling frame used, and response rates. Users are also encouraged to read the SPPA User Guide (produced by the Urban Institute) for information about the SPPA, including the design, dealing with missing respondent data, weights, and multi-variable analysis.The universe statements for each variable are defined in the basic or supplement record layouts found in Attachment 6 and 7, respectively, of the CPS User Guide. The SPPA provides estimates for 32 states: Alabama; California; Colorado, Connecticut; Florida; Georgia; Illinois; Iowa; Kansas; Maine; Maryland; Massachusetts; Michigan; Minnesota; Missouri; Nebraska; Nevada; New Jersey; New York; North Carolina; North Dakota; Ohio; Oregon; Pennsylvania; Rhode Island; South Carolina; South Dakota; Texas; Virginia; Washington; West Virginia; and Wyoming. In addition, the SPPA can reliably supply arts participation estimates for 11 metropolitan areas: Boston-Worchester-Manchester, MA-NH; Chicago-Naperville-Michigan City, IL-IN; Dallas-Fort Worth, TX; Denver-Aurora-Boulder, CO; Detroit-Warren-Flint, MI; Los Angeles-Long Beach-Riverside, CA; Miami-Fort Lauderdale-Miami Beach, FL; New York-Newark-Bridgeport, NY-NJ-CT-PA; Philadelphia-Camden-Vineland, PA-NJ-DE-MD; San Jose-Francisco-Oakland, CA; and Washington-Baltimore-Northern Virginia, DC-MD-VA-WV. Users cannot do analysis that combines variables from Core 1 and Core 2 because respondents were assigned to either complete Core 1 or Core 2, but never Core 1 and Core 2. Also, analyses cannot use variables from more than two modules in the same runs since no respondent answered more than 2 modules. So doing such analyses can raise sample size concerns.Users must use appropriate weights to analyze the SPPA 2012 data. For online analysis, subsets of the data were created, each with the variables that need to be used with the 1 SPPA weight variable. The Part 2 dataset contains CPS variables and SPPA Core 1 questions including those about asked respondents' and their spouse/partners' artistic activity and frequency of participation in the past year. The Part 3 dataset contains CPS variables and SPPA Core 2 experimental questions including those about asked respondents' and their spouse/partners' artistic activity and frequency of participation in the past year. The Part 4 dataset contains CPS variables and SPPA modules A1 and D questions that asked respondents and their spouse/partners about reading, film, and sporting event attendance as well as creating, performing, and other artistic activities in the past year. The Part 5 dataset contains CPS variables and SPPA Module A2 questions that asked respondents about other live performances attendances and music listening preferences in the past year. The Part 6 dataset contains CPS variables and Modules B, C, and E questions including those that asked respondents about accessing art through media and frequency of participation through the media in the past year, creating arts through the media in the past year, and participation in arts education in the past year.The "PC" variables (e.g. JAZZ_PC) should be used to match the SPPA 2012 published results.Information regarding data processing for this data collection is in the "Codebook Notes" page(s) in the ICPSR Codebook. Most notably: For this data collection, ICPSR created the CASEID variable which is a unique case identifier. The "Basic CPS Record Layout" section in the CPS User Guide (see Attachment 6) contains many FILLER variables and a couple PADDING variables with column locations. Also, only 1 FILLER variable was found in the data that ICPSR received, and ICPSR removed the FILLER variable. As a result, the column locations in any ICPSR-released data product (e.g., codebook and setup files) will have column locations that are not consistent with locations described in the CPS User Guide. Please note that miss...

In 2023, the District of Columbia had the highest reported violent crime rate in the United States, with 1,150.9 violent crimes per 100,000 of the population. Maine had the lowest reported violent crime rate, with 102.5 offenses per 100,000 of the population. Life in the District The District of Columbia has seen a fluctuating population over the past few decades. Its population decreased throughout the 1990s, when its crime rate was at its peak, but has been steadily recovering since then. While unemployment in the District has also been falling, it still has had a high poverty rate in recent years. The gentrification of certain areas within Washington, D.C. over the past few years has made the contrast between rich and poor even greater and is also pushing crime out into the Maryland and Virginia suburbs around the District. Law enforcement in the U.S. Crime in the U.S. is trending downwards compared to years past, despite Americans feeling that crime is a problem in their country. In addition, the number of full-time law enforcement officers in the U.S. has increased recently, who, in keeping with the lower rate of crime, have also made fewer arrests than in years past.

In 2023, the real median household income in the state of Alabama was 60,660 U.S. dollars. The state with the highest median household income was Massachusetts, which was 106,500 U.S. dollars in 2023. The average median household income in the United States was at 80,610 U.S. dollars.