About this dataset

Context

The dataset tabulates the State Line population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of State Line across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of State Line was 37, a 2.63% decrease year-by-year from 2022. Previously, in 2022, State Line population was 38, an increase of 5.56% compared to a population of 36 in 2021. Over the last 20 plus years, between 2000 and 2023, population of State Line decreased by 22. In this period, the peak population was 61 in the year 2002. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the State Line is shown in this column.
• Year on Year Change: This column displays the change in State Line population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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 State Line Population by Year. You can refer the same here

From 2015 to 2020, around 14 percent of adults aged 45 years and older in Ohio had subjective cognitive decline. This statistic depicts the percentage of U.S. adults aged 45 years and older with subjective cognitive decline (SCD) from 2015-2020, by state.

In the Cook Islands in 2024, the population decreased by about 2.24 percent compared to the previous year, making it the country with the highest population decline rate in 2024. Of the 20 countries with the highest rate of population decline, the majority are island nations, where emigration rates are high (especially to Australia, New Zealand, and the United States), or they are located in Eastern Europe, which suffers from a combination of high emigration rates and low birth rates.

About this dataset

Context

The dataset tabulates the State Line population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of State Line across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of State Line was 39, a 0.00% decrease year-by-year from 2021. Previously, in 2021, State Line population was 39, an increase of 5.41% compared to a population of 37 in 2020. Over the last 20 plus years, between 2000 and 2022, population of State Line decreased by 20. In this period, the peak population was 61 in the year 2002. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the State Line is shown in this column.
• Year on Year Change: This column displays the change in State Line population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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 State Line Population by Year. You can refer the same here

This statistic shows the supermarket categories that declined the most in sales in 2018 compared to the previous year. For the 52 weeks ending December 29, 2018, dollar sales of frozen yogurt in supermarkets declined by 27.7 percent compared to the previous year.

In 2023, the resident population of California was 38.97 million. This is a slight decrease from the previous year, with 39.03 million people in 2022. This makes it the most populous state in the U.S. Californian demographics Along with an increase in population, California’s gross domestic product (GDP) has also been increasing, from 1.7 trillion U.S. dollars in 2000 to 3.23 trillion U.S. dollars in 2023. In the same time period, the per-capita personal income has almost doubled, from 33,403 U.S. dollars in 2000 to 77,339 U.S. dollars in 2022. In 2023, the majority of California’s resident population was Hispanic or Latino, although the number of white residents followed as a close second, with Asian residents making up the third largest demographic in the state. The dark side of the Golden State While California is one of the most well-known states in the U.S., is home to Silicon Valley, and one of the states where personal income has been increasing over the past 20 years, not everyone in California is so lucky: In 2023, the poverty rate in California was about 12 percent, and the state had the fifth-highest rate of homelessness in the country during that same year, with an estimated 46 homeless people per 10,000 of the population.

This paper documents a set of facts about the dramatic decline in birth rates in the United States between 2007 and 2020 and explores possible explanations for it. The overall reduction in the birth rate reflects both very large declines within certain groups of women, including teens and Hispanic women – and smaller declines among demographic groups that comprise a large population share, including college-educated white women. We explore potential economic, policy, and social factors that might be responsible for the overall decline. We conclude from our empirical examination of possible factors that there is not a readily identifiable economic or policy factor or set of factors this is likely responsible for a substantial share of the decline. Instead, the patterns observed suggest that widespread, hard to quantify changes in preferences for having children, aspirations for life, and the nature of parenting are more likely behind the recent decline in US births. We conclude with a brief discussion about the societal consequences for a declining birth rate and what the United States might do about it.

Over the past 30 years, the birth rate in the United States has been steadily declining, and in 2022, there were 11 births per 1,000 of the population. In 1990, this figure stood at 16.7 births per 1,000 of the population. Demographics have an impact The average birth rate in the U.S. may be falling, but when broken down along ethnic and economic lines, a different picture is painted: Native Hawaiian and other Pacific Islander women saw the highest birth rate in 2022 among all ethnicities, and Asian women and white women both saw the lowest birth rate. Additionally, the higher the family income, the lower the birth rate; families making between 15,000 and 24,999 U.S. dollars annually had the highest birth rate of any income bracket in the States. Life expectancy at birth In addition to the declining birth rate in the U.S., the total life expectancy at birth has also reached its lowest value in recent years. Studies have shown that the life expectancy of both men and women in the United States has declined as of 2021. Declines in life expectancy, like declines in birth rates, may indicate that there are social and economic factors negatively influencing the overall population health and well-being of the country.

United States CSI: Economic: Business Conditions Trends: Intermittent Decline data was reported at 13.000 % in May 2018. This records a decrease from the previous number of 14.000 % for Apr 2018. United States CSI: Economic: Business Conditions Trends: Intermittent Decline data is updated monthly, averaging 22.000 % from Jan 1978 (Median) to May 2018, with 485 observations. The data reached an all-time high of 44.000 % in Jan 2009 and a record low of 6.000 % in Apr 1998. United States CSI: Economic: Business Conditions Trends: Intermittent Decline data remains active status in CEIC and is reported by University of Michigan. The data is categorized under Global Database’s USA – Table US.H028: Consumer Sentiment Index: Economic Conditions.

This statistic outlines the projected short and long run decline in employment due to closing oil and gas rigs between January 2015 and March 2016 in selected U.S. states. The estimated short run decline in oil and gas employment in Texas is 19,955 jobs lost, while the estimated long run decline is 121,265 jobs lost.

The Asian financial crisis caused a decline in most states' exports of manufactured goods to East Asia during 1998, but the severity of the decline varied across states. In this article, the authors estimate the size of this export shock for all states. Primarily because western states tend to be more dependent on East Asian markets for export sales, they were hit the hardest by the sharp reduction in Asian demand for United States-produced manufactured goods. Of the states in which the decline in exports to East Asia lowered the growth of manufacturing output by more than 1 percent, two-thirds were western states. The export changes caused by the Asian crisis, however, were found to matter little for manufacturing employment growth across states during 1998. Meanwhile, states with a high concentration of manufacturing industries that use petroleum products extensively as an input tended to have larger manufacturing employment increases during 1998 than other states. Consequently, the authors conclude that the oil price declines during late 1997 and 1998, some portion of which can be attributed to the Asian crisis, appear to be more important than the export effects in influencing manufacturing employment across states.

This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

United States SB: OP: Change in Employees: Decreased data was reported at 9.900 % in 11 Apr 2022. This records an increase from the previous number of 9.300 % for 04 Apr 2022. United States SB: OP: Change in Employees: Decreased data is updated weekly, averaging 9.400 % from Nov 2020 (Median) to 11 Apr 2022, with 51 observations. The data reached an all-time high of 20.800 % in 23 Aug 2021 and a record low of 3.500 % in 31 May 2021. United States SB: OP: Change in Employees: Decreased data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S041: Small Business Pulse Survey: by State: South Region: Weekly, Beg Monday (Discontinued).

This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

United States SB: UT: CS: Demand: Large Decrease data was reported at 3.800 % in 14 Mar 2022. This records a decrease from the previous number of 5.900 % for 07 Mar 2022. United States SB: UT: CS: Demand: Large Decrease data is updated weekly, averaging 5.250 % from Feb 2022 (Median) to 14 Mar 2022, with 4 observations. The data reached an all-time high of 10.300 % in 28 Feb 2022 and a record low of 3.800 % in 14 Mar 2022. United States SB: UT: CS: Demand: Large Decrease data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S043: Small Business Pulse Survey: by State: West Region: Weekly, Beg Monday (Discontinued).

Prior to the American Civil War, New York, Pennsylvania, and Ohio were the most populous states in the Union, each with between two and four million inhabitants. Industrialization in the north was one of the key drivers of population growth during this period, through both internal and external migration, and Illinois saw the largest population growth during the 1860s largely due to the expansion of industry around Chicago. The gradual industrialization of the north in the early 1800s also contributed to the decline of slavery in the Union states, and the economic differences between the Union and Confederacy was a key factor in both the build-up to the Civil War, as well as the Union's eventual victory in 1865.

This dataset results from an anthropological project that investigated the mediations that advice enables between the state, the market, charitable initiatives, families and ordinary citizens in the UK as well as selected European sites affected by austerity politics, namely Spain and Switzerland. The welfare state is not just a political-economic but a moral formation, which creates multiple boundaries of inclusion and exclusion through a variety of actors, officials and institutions. These boundaries at times challenge, and at other times reproduce, dominant logics of extraction and accumulation. Advisers are often the last call for help for their clients/dependents who find themselves increasingly at the mercy of local authorities, immigration regimes, landlords, banks and debt collection agencies. But competing visions of moral worth and social justice continue to permeate the everyday deliberations of those who administer, support and advocate advice. Struggles and dilemmas over how best to instantiate social justice, provide assistance and balance individuals’ moral judgments against the collective good frequently occur. In analyzing advice as part of a broader landscape of governing the welfare state, our research explored both the dovetailing of and divergence between political, economic and legal imperatives and domains.

To accomplish our research, four main themes (1) Empathy and expertise, (2) Brokerage or self-help, (3) Shifting advice frameworks, and (4) Comparative insights on UK-based problems, were addressed through eight research sub-projects. (2) Ryan Davey ‘Debt advice in Plymouth’; (3) Tobias Eule ‘Face-to-Face Interactions at the State/Market interface in Germany/Switzerland’; (4) Alice Forbess ‘Housing and welfare advice in Portsmouth; (5) Ana Gutierrez Garza ‘Advice as social struggle: housing and debt in Spain’; (6) Deborah James ‘Debt advice in London’; (7) Insa Koch ‘Social housing and austerity politics on council estates in England’; (8) Anna Tuckett ‘Providing immigration advice in austerity UK’; (9) Matt Wilde ‘Advice and the UK Housing Crisis’. These include statements of methodology; tables of contents of fieldnotes; anonymized ethnographic interviews and anonymized fieldnotes.

This two-year anthropological study, building on earlier research by the principle investigator and others, undertakes an ethnographic investigation of advice. Under conditions of continuing economic crisis, scholars and policy-makers are having to reshape their assumptions about the nature of society: particularly in respect of who receives assistance and who funds and arranges it. Where the 'usual' targets of welfare and benefits were the poor or destitute, they now include those who work but cannot make ends meet, and who experience increasing numbers of complex problems for which they need advice. And where the 'usual' provider of such things, at least in the post-war years, has been the state, this is increasingly not the case. As the economic crisis proceeds apace and the state's role is being whittled down, access to the counsel of experts is nonetheless increasingly essential. Without prejudging the outcomes, the project will investigate novel arrangements and their unintended consequences. It will explore innovations in advice giving provided by existing offices (under more traditional state-funded regimes), by new sources and novel agencies (under non-governmental and market-driven schemes), and by the social movements, self-help and informal network-based arrangements to which many are increasingly having to turn for counsel and support. The project proposes intensive research along two axes. Firstly, it explores in detail selected sites and cases in the UK (specifically England where a very particular set of legal/welfare arrangements is in operation), 'drilling down' to examine specific institutional settings, themes and topics at a range of different scales and levels. Topics and sites include a focus on the three specific areas of housing, debt and immigration advice, both within and beyond particular institutional settings, and law courts where litigants have started to engage in self-representation. Secondly, it uses two carefully-selected cross-national comparisons in order to illuminate, and gain a critical perspective on, aspects of UK welfare-related advice processes which are often taken as natural/inevitable by local policy-makers. Across these different settings, the project will: (1) document the ongoing effects on advice giving of the withdrawal of legal aid funds, including the rise of self-litigation; (2) explore the new roles assumed by bureaucrats, intermediaries and self-help groups, who are increasingly important in the advice encounter; (3) investigate whether funding cuts have caused the dwindling of the much-vaunted empathy that advice-givers are often required to deliver and whether, in the process, advisers are becoming less effective at shaping the...

Census Tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity that are updated by local participants prior to each decennial census as part of the Census Bureau's Participant Statistical Areas Program. The Census Bureau delineates census tracts in situations where no local participant existed or where state, local, or tribal governments declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of statistical data.Census tracts generally have a population size between 1,200 and 8,000 people with an optimum size of 4,000 people. A census tract usually covers a contiguous area; however the spatial size of census tracts varies widely depending on the density of settlement. Census tract boundaries are delineated with the intention of being maintained over a long time so that statistical comparisons can be made from census to census. Census tracts occasionally are split due to population growth or merged as a result of substantial population decline.Census tract boundaries generally follow visible and identifiable features. They may follow non-visible legal boundaries, such as minor civil division (MCD) or incorporated place boundaries in some states and situations, to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. Tribal census tracts are a unique geographic entity defined within federally recognized American Indian reservations and can cross state and county boundaries. Tribal census tracts may be completely different from the census tracts and block groups defined by state and county.Download: https://www2.census.gov/geo/tiger/TGRGDB24/tlgdb_2024_a_us_substategeo.gdb.zip Layer: Census_TractMetadata: https://meta.geo.census.gov/data/existing/decennial/GEO/GPMB/TIGERline/Current_19115/series_tl_2023_place.shp.iso.xml

This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

Introduction: Though awareness of climate change rose globally with the release of former Vice President Al Gore’s movie and book An Inconvenient Truth in 2006, there has seemingly never been a connection drawn between Gore’s works and subsequent fertility trends in the United States, particularly along political lines. Objectives: The primary objective of this project is to determine whether the release of the movie and book An Inconvenient Truth in 2006 sparked an inflection point within a year or two in the United States for birth rates, and whether those rates differ between red and blue states. The secondary objective is to determine whether there was a drop in birth rates after that inflection point. Methods: This project used natality data – birth rates per state per year from 2003-2020 – from the Centers for Disease Control and Prevention, joined with state political party data from the 2020 Presidential election from Wisevoter. Data were cleaned using Excel and analyzed using Tableau visualizations. Results: The year 2007 was indeed an inflection point in the United States for birth rates, as both red and blue states recorded their highest birth rates at this point in the 2003-2020 span. The birth rate in red states was higher than that of blue states throughout the span but both rates had a positive correlation, running parallel throughout the span. Conclusions: The United States birth rate declined after 2007 in both red and blue states, but it is unclear whether the release of An Inconvenient Truth influenced this decline.