https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Median Household Income in New York (MEHOINUSNYA646N) from 1984 to 2023 about NY, households, median, income, and USA.
In 2023, the median household income in New York amounted to 81,600 U.S. dollars. This is an increase from the previous year, when the median household income in the state amounted to 75,910 U.S. dollars. The median household income for the United States can be accessed here.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Median Household Income in New York was 81600.00000 Current $ in January of 2023, according to the United States Federal Reserve. Historically, Median Household Income in New York reached a record high of 81600.00000 in January of 2023 and a record low of 22030.00000 in January of 1984. Trading Economics provides the current actual value, an historical data chart and related indicators for Median Household Income in New York - last updated from the United States Federal Reserve on June of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the median household income in New York. It can be utilized to understand the trend in median household income and to analyze the income distribution in New York by household type, size, and across various income brackets.
The dataset will have the following datasets when applicable
Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).
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.
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/.
Explore our comprehensive data analysis and visual representations for a deeper understanding of New York median household income. You can refer the same here
In 2023, the per capita personal income in New York was 82,323 U.S. dollars. Per capita personal income is calculated as the personal income of the residents of a given area divided by the resident population of the area.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the distribution of median household income among distinct age brackets of householders in New York County. Based on the latest 2018-2022 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in New York County. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.
Key observations: Insights from 2022
In terms of income distribution across age cohorts, in New York County, householders within the 25 to 44 years age group have the highest median household income at $139,760, followed by those in the 45 to 64 years age group with an income of $105,737. Meanwhile householders within the under 25 years age group report the second lowest median household income of $67,356. Notably, householders within the 65 years and over age group, had the lowest median household income at $55,984.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.
Age groups classifications include:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for New York County median household income by age. You can refer the same here
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Per Capita Personal Income in New York (NYPCPI) from 1929 to 2024 about personal income, NY, per capita, personal, income, and USA.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the mean household income for each of the five quintiles in Greece, New York, 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
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Greece town median household income. You can refer the same here
This statistic shows the median household income in the United States from 1990 to 2023 in 2023 U.S. dollars. The median household income was 80,610 U.S. dollars in 2023, an increase from the previous year. Household incomeThe median household income depicts the income of households, including the income of the householder and all other individuals aged 15 years or over living in the household. Income includes wages and salaries, unemployment insurance, disability payments, child support payments received, regular rental receipts, as well as any personal business, investment, or other kinds of income received routinely. The median household income in the United States varies from state to state. In 2020, the median household income was 86,725 U.S. dollars in Massachusetts, while the median household income in Mississippi was approximately 44,966 U.S. dollars at that time. Household income is also used to determine the poverty line in the United States. In 2021, about 11.6 percent of the U.S. population was living in poverty. The child poverty rate, which represents people under the age of 18 living in poverty, has been growing steadily over the first decade since the turn of the century, from 16.2 percent of the children living below the poverty line in year 2000 to 22 percent in 2010. In 2021, it had lowered to 15.3 percent. The state with the widest gap between the rich and the poor was New York, with a Gini coefficient score of 0.51 in 2019. The Gini coefficient is calculated by looking at average income rates. A score of zero would reflect perfect income equality and a score of one indicates a society where one person would have all the money and all other people have nothing.
In 2023, the per capita disposable personal income in New York stood at 68,435 U.S. dollars. This was a significant increase from the previous year, when the per capita disposable personal income in the state was 62,031 U.S. dollars.
Out of a total of 7.8 million housing units in New York City in 2021, approximately 924,700 homes had housing costs between 15 and 19 percent of the household budget. New York City is notoriously known for its shortage of affordable housing: Overall, for a large percentage of New York City residents, housing costs exceeded 35 percent.
Table of ACS Demographics and profile represented at the NTA level. NTAs are aggregations of census tracts that are subsets of New York City's 55 Public Use Microdata Areas (PUMAs)
https://www.newyork-demographics.com/terms_and_conditionshttps://www.newyork-demographics.com/terms_and_conditions
A dataset listing the 20 richest counties in New York for 2024, including information on rank, county, population, average income, and median income.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
IntroductionOur study explores how New York City (NYC) communities of various socioeconomic strata were uniquely impacted by the COVID-19 pandemic.MethodsNew York City ZIP codes were stratified into three bins by median income: high-income, middle-income, and low-income. Case, hospitalization, and death rates obtained from NYCHealth were compared for the period between March 2020 and April 2022.ResultsCOVID-19 transmission rates among high-income populations during off-peak waves were higher than transmission rates among low-income populations. Hospitalization rates among low-income populations were higher during off-peak waves despite a lower transmission rate. Death rates during both off-peak and peak waves were higher for low-income ZIP codes.DiscussionThis study presents evidence that while high-income areas had higher transmission rates during off-peak periods, low-income areas suffered greater adverse outcomes in terms of hospitalization and death rates. The importance of this study is that it focuses on the social inequalities that were amplified by the pandemic.
The New York City (NYC) Heat Vulnerability Index (HVI) is a measure of how the risk of heat-related illness or death differs across neighborhoods. Neighborhood risk factors that increase heat- vulnerability in NYC are: less home air conditioning less green space hotter surface temperatures and more residents who are low-income or non-Latinx Black. Differences in these risk factors across neighborhoods are rooted in past and present racism.HVI is calculated by summing the z scores of the following variables and then assigning the sum to quintile (1-5, with 5 being highest risk of death during heat events):• Median household income, (American Community Survey 2016-2020 5-year estimates)• Percent vegetative cover (trees, shrubs or grass) (2017 LiDAR, NYC DOITT)• Percent of population reported as Non-Hispanic Black on American Community Survey (2016-2020 5-year estimates)• Average surface temperature data from the NASA’s ECOSTRESS (2020)• Percent of households reporting Air Conditioning access, Housing ad Vacancy Survey, 2017This updated HVI is using the 2020 census boundaries.MODZCTA- A shapefile for mapping data by Modified Zip Code Tabulation Areas (MODZCTA) in NYC, based on the 2010 Census ZCTA shapefile. MODZCTA are being used by the NYC Department of Health & Mental Hygiene (DOHMH) for mapping COVID-19 Data.
This annual study provides selected income and tax items classified by State, ZIP Code, and the size of adjusted gross income. These data include the number of returns, which approximates the number of households; the number of personal exemptions, which approximates the population; adjusted gross income; wages and salaries; dividends before exclusion; and interest received. Data are based who reported on U.S. Individual Income Tax Returns (Forms 1040) filed with the IRS. SOI collects these data as part of its Individual Income Tax Return (Form 1040) Statistics program, Data by Geographic Areas, ZIP Code Data.
The Department of Housing Preservation and Development (HPD) receives a sub-allocation of 9% Low Income Housing Tax Credits and allocated its credits through one competitive round each calendar year. It is also charged with allocating 4% Low Income Housing Tax Credits to projects receiving tax exempt bonds through New York City Housing Development Corporation. Each entry represents an allocation to a low income housing development project with households at or below 60% of Area Median Income.
For the Low Income Housing Tax Credits Awarded by HPD: Building-Level (4% Awards) dataset, please follow this link
The Heat Vulnerability Index (HVI) shows neighborhoods whose residents are more at risk for dying during and immediately following extreme heat. It uses a statistical model to summarize the most important social and environmental factors that contribute to neighborhood heat risk. The factors included in the HVI are surface temperature, green space, access to home air conditioning, and the percentage of residents who are low-income or non-Latinx Black. Differences in these risk factors across neighborhoods are rooted in past and present racism. Neighborhoods are scored from 1 (lowest risk) to 5 (highest risk) by summing the following factors and assigning them into 5 groups (quintiles): Median Household Income (American Community Survey 5 year estimate, 2016-2020) Percent vegetative cover (trees, shrubs or grass) (2017 LiDAR, NYC DOITT) Percent of population reported as Non-Hispanic Black on Census 2020 Average surface temperature Fahrenheit from ECOSSTRESS thermal imaging, August 27,2020 Percent of households reporting Air Conditioning access, Housing ad Vacancy Survey, 2017
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Alma town. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.
Key observations: Insights from 2023
Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Alma town, the median income for all workers aged 15 years and older, regardless of work hours, was $33,750 for males and $30,536 for females.
Based on these incomes, we observe a gender gap percentage of approximately 10%, indicating a significant disparity between the median incomes of males and females in Alma town. Women, regardless of work hours, still earn 90 cents to each dollar earned by men, highlighting an ongoing gender-based wage gap.
- Full-time workers, aged 15 years and older: In Alma town, among full-time, year-round workers aged 15 years and older, males earned a median income of $57,083, while females earned $37,083, leading to a 35% gender pay gap among full-time workers. This illustrates that women earn 65 cents for each dollar earned by men in full-time roles. This level of income gap emphasizes the urgency to address and rectify this ongoing disparity, where women, despite working full-time, face a more significant wage discrepancy compared to men in the same employment roles.Remarkably, across all roles, including non-full-time employment, women displayed a lower gender pay gap percentage. This indicates that Alma town offers better opportunities for women in non-full-time positions.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.
Gender classifications include:
Employment type classifications include:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Alma town median household income by race. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
ObjectivesTo test the feasibility, acceptability, and potential efficacy of a mHealth intervention tailored for Chinese immigrant families with type 2 diabetes (T2D).MethodsWe conducted a pilot randomized controlled trial (RCT) with baseline, 3-, and 6-month measurements. Participating dyads, T2D patients and families/friends from NYC, were randomized into the intervention group (n = 11) or the wait-list control group (n = 12). Intervention includes 24 videos covering T2D self-management, behavioral techniques, and family-oriented sessions. Feasibility and acceptability were measured respectively by the retention rate and video watch rate, and a satisfaction survey. Patients’ HbA1c, weight, and self-management were also assessed to test potential efficacy.ResultsMost T2D patients (n = 23; mean age 56.2±9.4 years; 52.2% male) and families/friends (n = 23, mean age 54.6±11.2 years; 52.2% female) had high school education or less (69.6% and 69.6%), annual household income < $25,000 (65.2% and 52.2%), and limited English proficiency (95.7% and 95.7%). The retention rates were not significantly different between the intervention and the control groups for both the patients (90.91% vs 83.3%, p = 0.589); and their families/friends (3-month: 90.9% vs 75%, p = 0.313; 6-month: 90.9% vs 83.3%, p = 0.589). The mean video watch rate was 76.8% (7%). T2D patients and families/friends rated satisfaction as 9.4 and 10 out of 10, respectively. Despite no between-group differences, the intervention group had significantly lower HbA1c (p = 0.014) and better self-management (p = 0.009), and lost 12 lbs. on average at 6 months (p = 0.079), compared to their baseline levels.ConclusionsA culturally-tailored, family-based mHealth intervention is feasible and acceptable among low-income, limited English-proficient Chinese families with T2D in NYC. Significant changes in HbA1c and self-management within the intervention group indicate this intervention may have potential efficacy. Given the small sample size of this study, a future RCT with adequate power is needed to test efficacy.
Not seeing a result you expected?
Learn how you can add new datasets to our index.
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Median Household Income in New York (MEHOINUSNYA646N) from 1984 to 2023 about NY, households, median, income, and USA.