Following the inauguration of Franklin D. Roosevelt, government relief spending increased drastically. In his first year in office, workers in major cities were receiving benefits equal to just over one-fifth of average manufacturing wages. By 1936, relief benefits had risen to over two-fifths of the value of manufacturing wages - this also coincided with a wage increase from around 17 U.S. dollars per week in 1933 to 23 U.S. dollars in 1936, which means that the total value of relief benefits more than doubled in these years.

About this dataset

Context

The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in Wakeman. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2013 and 2023, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..

Key observations

• White: In Wakeman, the median household income for the households where the householder is White increased by $1,930(2.81%), between 2013 and 2023. The median household income, in 2023 inflation-adjusted dollars, was $68,606 in 2013 and $70,536 in 2023.
• Black or African American: As per the U.S. Census Bureau population data, in Wakeman, there are no households where the householder is Black or African American; hence, the median household income for the Black or African American population is not applicable.
• Refer to the research insights for more key observations on American Indian and Alaska Native, Asian, Native Hawaiian and Other Pacific Islander, Some other race and Two or more races (multiracial) households

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Wakeman.
• 2010: 2010 median household income
• 2011: 2011 median household income
• 2012: 2012 median household income
• 2013: 2013 median household income
• 2014: 2014 median household income
• 2015: 2015 median household income
• 2016: 2016 median household income
• 2017: 2017 median household income
• 2018: 2018 median household income
• 2019: 2019 median household income
• 2020: 2020 median household income
• 2021: 2021 median household income
• 2022: 2022 median household income
• 2023: 2023 median household income
• Please note: All incomes have been adjusted for inflation and are presented in 2023-inflation-adjusted dollars.

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 Wakeman median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in Elk County, KS, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 10,271, while the mean income for the highest quintile (20% of households with the highest income) is 147,334. This indicates that the top earners earn 14 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 198,230, which is 134.54% higher compared to the highest quintile, and 1930% higher compared to the lowest quintile.

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:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

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 Elk County median household income. You can refer the same here

Graph and download economic data for Average of GDP and GDI, current dollars (PA0000091A225NBEA) from 1930 to 2024 about current dollars, GDI, average, income, GDP, rate, and USA.

The national gross income per capita in Nigeria decreased to 1,930 U.S. dollars compared to the previous year. Therefore, 2023 marks the lowest national gross income during the observed period. Gross national income (GNI) per capita is the total value of money received by a country, from both domestic or foreign sources, divided by the midyear population. The World Bank uses a conversion system known as the Atlas method, which implements a price adjusted, three year moving average, smoothing out fluctuations in exchange rates.Find more statistics on other topics about Nigeria with key insights such as gross national income (GNI), value of personal remittances paid, and personal remittances received.

Graph and download economic data for Real average of GDP and GDI (PB0000091A225NBEA) from 1930 to 2023 about GDI, average, income, real, GDP, rate, and USA.

Graph and download economic data for Wage and salary accruals per full-time equivalent employee: Domestic industries: State and local general government: Work relief (B4497C0A052NBEA) from 1930 to 1942 about accruals, social assistance, state & local, full-time, salaries, domestic, wages, government, employment, industry, GDP, and USA.

About this dataset

Context

The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in Martin. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2011 and 2021, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..

Key observations

• White: In Martin, the median household income for the households where the householder is White decreased by $1,930(4.38%), between 2011 and 2021. The median household income, in 2022 inflation-adjusted dollars, was $44,023 in 2011 and $42,093 in 2021.
• Black or African American: In Martin, the median household income for the households where the householder is Black or African American increased by $17,324(93.58%), between 2011 and 2021. The median household income, in 2022 inflation-adjusted dollars, was $18,513 in 2011 and $35,837 in 2021.
• Refer to the research insights for more key observations on American Indian and Alaska Native, Asian, Native Hawaiian and Other Pacific Islander, Some other race and Two or more races (multiracial) households

https://i.neilsberg.com/ch/martin-tn-median-household-income-by-race-trends.jpeg" alt="Martin, TN median household income trends across races (2011-2021, 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.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Martin.
• 2010: 2010 median household income
• 2011: 2011 median household income
• 2012: 2012 median household income
• 2013: 2013 median household income
• 2014: 2014 median household income
• 2015: 2015 median household income
• 2016: 2016 median household income
• 2017: 2017 median household income
• 2018: 2018 median household income
• 2019: 2019 median household income
• 2020: 2020 median household income
• 2021: 2021 median household income
• 2022: 2022 median household income
• Please note: 2020 1-Year ACS estimates data was not reported by Census Bureau due to impact on survey collection and analysis during COVID-19, thus for large cities (population 65,000 and above) median household income data is not available.
• Please note: All incomes have been adjusted for inflation and are presented in 2022-inflation-adjusted dollars.

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 Martin median household income by race. You can refer the same here

Graph and download economic data for Real gross domestic product per capita (A939RX0Q048SBEA) from Q1 1947 to Q4 2024 about per capita, real, GDP, and USA.

About this dataset

Context

The dataset illustrates the median household income in Dearborn County, 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 Dearborn County increased by $1,930 (2.52%), 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 7 years and declined for 4 years.

https://i.neilsberg.com/ch/dearborn-county-in-median-household-income-trend.jpeg" alt="Dearborn County, IN 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 Dearborn County median household income. You can refer the same here

Compared to the mid-20th century, wage increases in the United States' industrial sector did not change as drastically over the preceding 150 years. Industrial wages in the 1800s peaked in the final year of the American Civil War in 1865, and they were double the value of wages in 1830; yet wages did not exceed this value until the following century. Throughout the 1900s, however, the increase was much more pronounced; between 1943 and 1955 alone, industrial wages doubled, and quadrupled by 1972. In fact, wages in 1985 were over five times higher than they were in 1955, and ten times higher than in 1943. The only times during the 20th century when industrial wages fell was during the post-WWI recession in 1921, and again during the Great Depression in the 1930s.

In the build up to the Second World War, the United States was the major power with the highest gross domestic product (GDP) per capita in the world. In 1938, the United States also had the highest overall GDP in the world, and by a significant margin, however differences in GDP per person were much smaller. Switzerland In terms of countries that played a notable economic role in the war, the neutral country of Switzerland had the highest GDP per capita in the world. A large part of this was due to the strength of Switzerland's financial system. Most major currencies abandoned the gold standard early in the Great Depression, however the Swiss Franc remained tied to it until late 1936. This meant that it was the most stable, freely convertible currency available as the world recovered from the Depression, and other major powers of the time sold large amounts of gold to Swiss banks in order to trade internationally. Switzerland was eventually surrounded on all sides by Axis territories and lived under the constant threat of invasion in the war's early years, however Swiss strategic military planning and economic leverage made an invasion potentially more expensive than it was worth. Switzerland maintained its neutrality throughout the war, trading with both sides, although its financial involvement in the Holocaust remains a point of controversy. Why look at GDP per capita? While overall GDP is a stronger indicator of a state's ability to fund its war effort, GDP per capita is more useful in giving context to a country's economic power in relation to its size and providing an insight into living standards and wealth distribution across societies. For example, Germany and the USSR had fairly similar GDPs in 1938, whereas Germany's per capita GDP was more than double that of the Soviet Union. Germany was much more industrialized and technologically advanced than the USSR, and its citizens generally had a greater quality of life. However these factors did not guarantee victory - the fact that the Soviet Union could better withstand the war of attrition and call upon its larger population to replenish its forces greatly contributed to its eventual victory over Germany in 1945.

Over the first half of the 20th century, the Soviet Union's GDP per capita rose from 1,218 U.S. dollars to 2,8334 U.S. dollars. There was a slight decrease between 1913 and 1929 due to the devastation caused by the First World War and Russian Revolution and the transition to a communist government and socialist economic structure. However, GDP per capita grew over the following three intervals, and the Soviet Union's relative isolation in the 1920s and 1930s meant that it was relatively untouched by the Great Depression in the 1930s. At the end of the recovery period after the Second World War, in 1950, GDP per capita had already exceeded pre-war levels by a significant margin, and the Soviet Union emerged as one of the two global superpowers, alongside the United States.

One aim of the Soviet Union, and communist countries in general, was to achieve full employment. Official policy was designed to prevent unemployment, and the state stopped paying most unemployment benefits in the 1930s. Every citizen had the right (or requirement) to work, and jobs were allocated by the state, not competed for as they were in the west. People could apply for certain positions, based on their education, experience, or interests, but roles could often be distributed to meet employment demands, or preferential roles were distributed via nepotism. The socialist economic system removed job market competition, which provided increased job security but removed many of the incentives that boosted productivity (especially in later decades). In the 1970s and 1980s, average work weeks were under 35 hours long and people retired in their mid to late fifties. Compared to the U.S. in 1985, on average, work weeks were around four hours shorter in the USSR, and Soviet men retired five years earlier, while women retired nine years earlier than their American counterparts.

Wages In earlier years, wages had been tied to individual performance or output, however the de-Stalinization process of the 1960s introduced a more standardized system of payment; from this point onwards, base wages were more fixed, and bonuses had a larger impact on disposable income. Personal finances in the Soviet Union were very different from those in the west; wages were split into base salaries and bonuses, along with a social wage that was "paid" in the form of investments in housing, healthcare, education, and infrastructure, as well as subsidized vouchers for holidays and food. Many of these amenities were also provided by the state, which removed the individual costs that were required across the west and in post-Soviet states today. Overall, income and money in general had a much lower influence on daily life in the USSR than it did in the west, lessening factors such as financial stress and indebtedness, but restricting consumeristic freedom.

Gender differences A major difference between the East and West Blocs was the participation rate of women in the workforce. Throughout most of the USSR's history, women made up the majority of the workforce, with a 51.4 percent share in 1970, and 50.4 percent in 1989; in the U.S. figures for these years were 38 and 45 percent respectively. Although this was due to the fact that women also made up a larger share of the total population (around 53 percent in this period), Soviet women were possibly the most economically active in the world in these decades. When comparing activity rates of women aged between 40 and 44 across Europe in 1985, the USSR had a participation rate of 97 percent; this was the highest in the East Bloc (where rates ranged from 85 to 93 percent in other countries), and is much higher than rates in Northern Europe (71 percent), Western Europe (56 percent) and Southern Europe (37 percent).

About this dataset

Context

The dataset illustrates the median household income in Renville County, 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 Renville County increased by $1,930 (3%), 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 7 years and declined for 4 years.

https://i.neilsberg.com/ch/renville-county-mn-median-household-income-trend.jpeg" alt="Renville County, MN 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 Renville County median household income. You can refer the same here

About this dataset

Context

The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in Highlanding township. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2011 and 2021, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..

Key observations

• White: In Highlanding township, the median household income for the households where the householder is White decreased by $1,930(2.67%), between 2011 and 2021. The median household income, in 2022 inflation-adjusted dollars, was $72,189 in 2011 and $70,259 in 2021.
• Black or African American: As per the U.S. Census Bureau population data, in Highlanding township, there are no households where the householder is Black or African American; hence, the median household income for the Black or African American population is not applicable.
• Refer to the research insights for more key observations on American Indian and Alaska Native, Asian, Native Hawaiian and Other Pacific Islander, Some other race and Two or more races (multiracial) households

https://i.neilsberg.com/ch/highlanding-township-mn-median-household-income-by-race-trends.jpeg" alt="Highlanding Township, Minnesota median household income trends across races (2011-2021, 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.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Highlanding township.
• 2010: 2010 median household income
• 2011: 2011 median household income
• 2012: 2012 median household income
• 2013: 2013 median household income
• 2014: 2014 median household income
• 2015: 2015 median household income
• 2016: 2016 median household income
• 2017: 2017 median household income
• 2018: 2018 median household income
• 2019: 2019 median household income
• 2020: 2020 median household income
• 2021: 2021 median household income
• 2022: 2022 median household income
• Please note: 2020 1-Year ACS estimates data was not reported by Census Bureau due to impact on survey collection and analysis during COVID-19, thus for large cities (population 65,000 and above) median household income data is not available.
• Please note: All incomes have been adjusted for inflation and are presented in 2022-inflation-adjusted dollars.

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 Highlanding township median household income by race. You can refer the same here