This dataset is about countries per year in Central America. It has 512 rows. It features 3 columns: country, and rural population.

This study was undertaken to enable cross-community analysis of gang trends in all areas of the United States. It was also designed to provide a comparative analysis of social, economic, and demographic differences among non-metropolitan jurisdictions in which gangs were reported to have been persistent problems, those in which gangs had been more transitory, and those that reported no gang problems. Data were collected from four separate sources and then merged into a single dataset using the county Federal Information Processing Standards (FIPS) code as the attribute of common identification. The data sources included: (1) local police agency responses to three waves (1996, 1997, and 1998) of the National Youth Gang Survey (NYGS), (2) rural-urban classification and county-level measures of primary economic activity from the Economic Research Service (ERS) of the United States Department of Agriculture, (3) county-level economic and demographic data from the County and City Data Book, 1994, and from USA Counties, 1998, produced by the United States Department of Commerce, and (4) county-level data on access to interstate highways provided by Tom Ricketts and Randy Randolph of the University of North Carolina at Chapel Hill. Variables include the FIPS codes for state, county, county subdivision, and sub-county, population in the agency jurisdiction, type of jurisdiction, and whether the county was dependent on farming, mining, manufacturing, or government. Other variables categorizing counties include retirement destination, federal lands, commuting, persistent poverty, and transfer payments. The year gang problems began in that jurisdiction, number of youth groups, number of active gangs, number of active gang members, percent of gang members who migrated, and the number of gangs in 1996, 1997, and 1998 are also available. Rounding out the variables are unemployment rates, median household income, percent of persons in county below poverty level, percent of family households that were one-parent households, percent of housing units in the county that were vacant, had no telephone, or were renter-occupied, resident population of the county in 1990 and 1997, change in unemployment rates, land area of county, percent of persons in the county speaking Spanish at home, and whether an interstate highway intersected the county.

A collection of over 75 charts and maps presenting key statistics on the farm sector, food spending and prices, food security, rural communities, the interaction of agriculture and natural resources, and more.

How much do you know about food and agriculture? What about rural America or conservation? ERS has assembled more than 75 charts and maps covering key information about the farm and food sectors, including agricultural markets and trade, farm income, food prices and consumption, food security, rural economies, and the interaction of agriculture and natural resources.

How much, for example, do agriculture and related industries contribute to U.S. gross domestic product? Which commodities are the leading agricultural exports? How much of the food dollar goes to farmers? How do job earnings in rural areas compare with metro areas? How much of the Nation’s water is used by agriculture? These are among the statistics covered in this collection of charts and maps—with accompanying text—divided into the nine section titles.

The U.S. Department of Health and Human Services (HHS) via the Health Resources and Services Administration (HRSA) is releasing American Rescue Plan payments to providers and suppliers who have served rural Medicaid, Children's Health Insurance Program (CHIP), and Medicare beneficiaries from January 1, 2019 through September 30, 2020. The dataset will be updated as additional payments are released. Data does not reflect recipients’ attestation status, returned payments, or unclaimed funds.

Definitions of “urban” and “rural” are abundant in government, academic literature, and data-driven journalism. Equally abundant are debates about what is urban or rural and which factors should be used to define these terms. Absent from most of this discussion is evidence about how people perceive or describe their neighborhood. Moreover, as several housing and demographic researchers have noted, the lack of an official or unofficial definition of suburban obscures the stylized fact that a majority of Americans live in a suburban setting. In 2017, the U.S. Department of Housing and Urban Development added a simple question to the 2017 American Housing Survey (AHS) asking respondents to describe their neighborhood as urban, suburban, or rural. This service provides a tract-level dataset illustrating the outcome of analysis techniques applied to neighborhood classification reported by the American Housing Survey (AHS) as either urban, suburban, or rural.

To create this data, analysts first applied machine learning techniques to the AHS neighborhood description question to build a model that predicts how out-of-sample households would describe their neighborhood (urban, suburban, or rural), given regional and neighborhood characteristics. Analysts then applied the model to the American Community Survey (ACS) aggregate tract-level regional and neighborhood measures, thereby creating a predicted likelihood the average household in a census tract would describe their neighborhood as urban, suburban, and rural. This last step is commonly referred to as small area estimation. The approach is an example of the use of existing federal data to create innovative new data products of substantial interest to researchers and policy makers alike.

If aggregating tract-level probabilities to larger areas, users are strongly encouraged to use occupied household counts as weights.

We recommend users read Section 7 of the working paper before using the raw probabilities. Likewise, we recognize that some users may:

prefer to use an uncontrolled classification, or

prefer to create more than three categories.

To accommodate these uses, our final tract-level output dataset includes the "raw" probability an average household would describe their neighborhood as urban, suburban, and rural. These probability values can be used to create an uncontrolled classification or additional categories.

The final classification is controlled to AHS national estimates (26.9% urban; 52.1% suburban, 21.0% rural).

  For more information about the 2017 AHS Neighborhood Description Study click on the following visit: https://www.hud.gov/program_offices/comm_planning/communitydevelopment/programs/, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. 

Data Dictionary: DD_Urbanization Perceptions Small Area Index.

The proposed project aims to determine how social conditions for Alaska Natives living in small arctic communities have changed since 2000, and differ among communities and small regions. The Census Long Form Survey historically provided much of the data for measuring social and economic conditions in the United States. Its replacement with the American Community Survey (ACS) after the 2000 Census has raised serious concerns about whether Census data continue to provide accurate measures of well-being in rural Alaska communities, at a time when the region faces unprecedented environmental and socio-economic change. The project addresses the uncertainty with ACS data by developing a new set of social, economic, and cultural indicators with increased capability to detect differences at local scales. Specific objectives include: (1) systematically examine the reliability of ACS data for rural Alaska by disaggregating published margins of error into components expressing dispersion across communities, years, and individuals; (2) construct socio-economic indicators for rural Alaska communities and regions with substantially smaller margins of error than published results; (3) estimate key indicators for communities where observations are sparse or missing entirely; and (4) test whether communities and regions have changed or differ significantly with respect to one or more indicators. The project pursues these objectives through modeling and statistical analyses of multiple primary data sources, including individual interview data from the ACS and the previous censuses in cooperation with the United States Census Bureau. Project outputs include a set of socio-economic indicators with improved reliability over published ACS figures that can help state and local governments and non-governmental organizations allocate funds, plan, and evaluate social service and economic development programs. A pioneering application of data assimilation with a social system model aids arctic social observing system design by revealing highest priority targets for new data collection for observing and understanding social change in arctic communities.

Analysis of ‘American Rescue Plan (ARP) Rural Payments’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/6e67ec90-70b3-4b96-9c2d-2e91e5b257db on 11 February 2022.

--- Dataset description provided by original source is as follows ---

The U.S. Department of Health and Human Services (HHS) via the Health Resources and Services Administration (HRSA) is releasing American Rescue Plan payments to providers and suppliers who have served rural Medicaid, Children's Health Insurance Program (CHIP), and Medicare beneficiaries from January 1, 2019 through September 30, 2020. The dataset will be updated as additional payments are released. Data does not reflect recipients’ attestation status, returned payments, or unclaimed funds.

--- Original source retains full ownership of the source dataset ---

App to explore American Community Survey data for Alaskan communities, including age, race, and sex composition of communities, and household and family incomes. Covers ACS data from the 2007-2011 period to the most current period. DCRA updates our version of the data annually when ACS releases the raw data.

VITAL SIGNS INDICATOR Migration (EQ4)

FULL MEASURE NAME Migration flows

LAST UPDATED December 2018

DESCRIPTION Migration refers to the movement of people from one location to another, typically crossing a county or regional boundary. Migration captures both voluntary relocation – for example, moving to another region for a better job or lower home prices – and involuntary relocation as a result of displacement. The dataset includes metropolitan area, regional, and county tables.

DATA SOURCE American Community Survey County-to-County Migration Flows 2012-2015 5-year rolling average http://www.census.gov/topics/population/migration/data/tables.All.html

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) Data for migration comes from the American Community Survey; county-to-county flow datasets experience a longer lag time than other standard datasets available in FactFinder. 5-year rolling average data was used for migration for all geographies, as the Census Bureau does not release 1-year annual data. Data is not available at any geography below the county level; note that flows that are relatively small on the county level are often within the margin of error. The metropolitan area comparison was performed for the nine-county San Francisco Bay Area, in addition to the primary MSAs for the nine other major metropolitan areas, by aggregating county data based on current metropolitan area boundaries. Data prior to 2011 is not available on Vital Signs due to inconsistent Census formats and a lack of net migration statistics for prior years. Only counties with a non-negligible flow are shown in the data; all other pairs can be assumed to have zero migration.

Given that the vast majority of migration out of the region was to other counties in California, California counties were bundled into the following regions for simplicity: Bay Area: Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, Sonoma Central Coast: Monterey, San Benito, San Luis Obispo, Santa Barbara, Santa Cruz Central Valley: Fresno, Kern, Kings, Madera, Merced, Tulare Los Angeles + Inland Empire: Imperial, Los Angeles, Orange, Riverside, San Bernardino, Ventura Sacramento: El Dorado, Placer, Sacramento, Sutter, Yolo, Yuba San Diego: San Diego San Joaquin Valley: San Joaquin, Stanislaus Rural: all other counties (23)

One key limitation of the American Community Survey migration data is that it is not able to track emigration (movement of current U.S. residents to other countries). This is despite the fact that it is able to quantify immigration (movement of foreign residents to the U.S.), generally by continent of origin. Thus the Vital Signs analysis focuses primarily on net domestic migration, while still specifically citing in-migration flows from countries abroad based on data availability.

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in Rural Valley, PA, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Rural Valley, PA reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Rural Valley households based on income levels.

Key observations

• For Family Households: In Rural Valley, the majority of family households, representing 25.56%, earn $100,000 to $124,999, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 0.0%, have incomes falling $40,000 to $44,999, representing a smaller but still significant segment of the community.
• For Non-Family Households: In Rural Valley, the majority of non-family households, accounting for 24.51%, have income $20,000 to $24,999, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 0.0%, earn $40,000 to $44,999, representing a smaller, yet notable, portion of non-family households in the community.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Rural Valley, PA (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in Rural Valley, PA
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in Rural Valley, PA
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Rural Valley, PA

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Rural Valley median household income. You can refer the same here

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in Rural Retreat, VA, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Rural Retreat, VA reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Rural Retreat households based on income levels.

Key observations

• For Family Households: In Rural Retreat, the majority of family households, representing 16.97%, earn $100,000 to $124,999, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 0.0%, have incomes falling $125,000 to $149,999, representing a smaller but still significant segment of the community.
• For Non-Family Households: In Rural Retreat, the majority of non-family households, accounting for 14.5%, have income $20,000 to $24,999, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 0.0%, earn $125,000 to $149,999, representing a smaller, yet notable, portion of non-family households in the community.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Income Levels:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Rural Retreat, VA (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in Rural Retreat, VA
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in Rural Retreat, VA
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Rural Retreat, VA

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Rural Retreat median household income. You can refer the same here

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in Rural Hall, NC, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Rural Hall, NC reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Rural Hall households based on income levels.

Key observations

• For Family Households: In Rural Hall, the majority of family households, representing 21.68%, earn $75,000 to $99,999, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 0.0%, have incomes falling $40,000 to $44,999, representing a smaller but still significant segment of the community.
• For Non-Family Households: In Rural Hall, the majority of non-family households, accounting for 17.2%, have income $15,000 to $19,999, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 0.0%, earn $40,000 to $44,999, representing a smaller, yet notable, portion of non-family households in the community.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Income Levels:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Rural Hall, NC (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in Rural Hall, NC
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in Rural Hall, NC
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Rural Hall, NC

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Rural Hall median household income. You can refer the same here

About this dataset

Context

The dataset illustrates the median household income in Rural Valley, spanning the years from 2010 to 2021, with all figures adjusted to 2022 inflation-adjusted dollars. Based on the latest 2017-2021 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.

Key observations:

From 2010 to 2021, the median household income for Rural Valley increased by $9,480 (16.52%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $4,559 (6.51%) between 2010 and 2021.

Analyzing the trend in median household income between the years 2010 and 2021, spanning 11 annual cycles, we observed that median household income, when adjusted for 2022 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 6 years and declined for 5 years.

https://i.neilsberg.com/ch/rural-valley-pa-median-household-income-trend.jpeg" alt="Rural Valley, PA median household income trend (2010-2021, in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Years for which data is available:

• 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021

Variables / Data Columns

• Year: This column presents the data year from 2010 to 2021
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific year
• YOY Change($): Change in median household income between the current and the previous year, in 2022 inflation-adjusted dollars
• YOY Change(%): Percent change in median household income between current and the previous year

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Rural Valley median household income. You can refer the same here