A dataset listing the richest zip codes in New York per the most current US Census data, including information on rank and average income.

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.

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.

Graph and download economic data for Per Capita Personal Income in New York (NYPCPI) from 1929 to 2024 about NY, personal income, per capita, personal, income, and USA.

In 2023, the per capita disposable personal income in New York stood at ****** U.S. dollars. This was a significant increase from the previous year, when the per capita disposable personal income in the state was ****** U.S. dollars.

Comprehensive demographic dataset for New York, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

New York was the state with the greatest gap between rich and poor, with a Gini coefficient score of 0.52 in 2023. Although not a state, District of Columbia was among the highest Gini coefficients in the United States that year.

About this dataset

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 New York. 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 New York, the median income for all workers aged 15 years and older, regardless of work hours, was $50,625 for males and $36,094 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 29% between the median incomes of males and females in New York. With women, regardless of work hours, earning 71 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thestate of New York.

- Full-time workers, aged 15 years and older: In New York, among full-time, year-round workers aged 15 years and older, males earned a median income of $75,212, while females earned $65,688, resulting in a 13% gender pay gap among full-time workers. This illustrates that women earn 87 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the state of New York.

Interestingly, when analyzing income across all roles, including non-full-time employment, the gender pay gap percentage was higher for women compared to men. It appears that full-time employment presents a more favorable income scenario for women compared to other employment patterns in New York.

Content

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:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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

Beginning with tax year 2015, the Department of Taxation and Finance (hereafter “the Department”) began producing a new annual population data study file to provide more comprehensive statistical information on New York State personal income tax returns. The data are from full‐year resident, nonresident, and part‐year resident returns filed between January 1 and December 31 of the year after the start of the liability period (hereafter referred to as the “processing year”). The four datasets display major income tax components by tax year. This includes the distribution of New York adjusted gross income and tax liability by county or place of residence, as well as the value of deductions, exemptions, taxable income and tax before credits by size of income. In addition, three of the four datasets include all the components of income, the components of deductions, and the addition/subtraction modifications. Caution: The current datasets are based on population data. For tax years prior to 2015, data were based on sample data. Data customers are advised to use caution when drawing conclusions comparing data for tax years prior to 2015 and subsequent tax years. Further details are included in the Overview.

About 50.4 percent of the household income of private households in the U.S. were earned by the highest quintile in 2023, which are the upper 20 percent of the workers. In contrast to that, in the same year, only 3.5 percent of the household income was earned by the lowest quintile. This relation between the quintiles is indicative of the level of income inequality in the United States. Income inequalityIncome inequality is a big topic for public discussion in the United States. About 65 percent of U.S. Americans think that the gap between the rich and the poor has gotten larger in the past ten years. This impression is backed up by U.S. census data showing that the Gini-coefficient for income distribution in the United States has been increasing constantly over the past decades for individuals and households. The Gini coefficient for individual earnings of full-time, year round workers has increased between 1990 and 2020 from 0.36 to 0.42, for example. This indicates an increase in concentration of income. In general, 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. Income distribution is also affected by region. The state of New York had the widest gap between rich and poor people in the United States, with a Gini coefficient of 0.51, as of 2019. In global comparison, South Africa led the ranking of the 20 countries with the biggest inequality in income distribution in 2018. South Africa had a score of 63 points, based on the Gini coefficient. On the other hand, the Gini coefficient stood at 16.6 in Azerbaijan, indicating that income is widely spread among the population and not concentrated on a few rich individuals or families. Slovenia led the ranking of the 20 countries with the greatest income distribution equality in 2018.

In 2023, about 14.2 percent of New York's population lived below the poverty line. This accounts for persons or families whose collective income in the preceding 12 months was below the national poverty level of the United States. The poverty rate of the United States can be found here.

Beginning with tax year 2015, the Department of Taxation and Finance (hereafter “the Department”) began producing a new annual population data study file to provide more comprehensive statistical information on New York State personal income tax returns. The data are from full‐year resident, nonresident, and part‐year resident returns filed between January 1 and December 31 of the year after the start of the liability period (hereafter referred to as the “processing year”). The four datasets display major income tax components by tax year. This includes the distribution of New York adjusted gross income and tax liability by county or place of residence, as well as the value of deductions, exemptions, taxable income and tax before credits by size of income. In addition, three of the four datasets include all the components of income, the components of deductions, and the addition/subtraction modifications. Caution: The current datasets are based on population data. For tax years prior to 2015, data were based on sample data. Data customers are advised to use caution when drawing conclusions comparing data for tax years prior to 2015 and subsequent tax years. Further details are included in the Overview.

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.

U.S. Census Bureau QuickFacts statistics for New York. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

In 2023, the GDP of the New York metro area amounted to *** trillion chained 2017 U.S. dollars. This is an increase from 2021, when the GDP of the New York metro area was **** trillion dollars. New York CityThe New York metro area’s GDP has steadily risen in the last two decades from *** trillion U.S. dollars in 2001 to **** trillion U.S. dollars in 2023. In September 2023, the New York- Newark-Jersey City area had an unemployment rate of *** percent. It also had the highest population in the country in 2022 at ***** million people. New York City’s economy is one of the greatest in the country and is home to many Fortune 500 companies, including Big Pharma’s Bristol-Myers Squibb. Industries such as media, real estate, fashion and entertainment are some of the most prominent in the area. The finance industry in New York City, also known as Wall Street, is one of the leading financial centers of the world and houses the New York Stock Exchange and NASDAQ. The region is also home to one of the largest trading industries in the country at the Port of New York and New Jersey. This port includes a large estuary, regional airports, and a plethora of rail and road networks. Silicon Alley is one of the country’s largest technology industry hubs, including internet, telecommunications, and biotechnology. In 2022, there were some ****** business establishments in the region that focused on professional, scientific, and technical services.

IntroductionTo design effective policy and interventions, public health officials must have an accurate and granular picture of the state of multiple chronic conditions (MCC) in their region. The objective of this research is to describe the prevalence and distribution of MCC in New York State.MethodsWe performed a secondary data analysis of the Behavioral Risk Factor Surveillance System (BRFSS) from 2011 through 2016 for New York adults (n = 76,186). We analyzed the self-reported prevalence of individuals having 0, 1, 2, or ≥ 3 chronic conditions by sex, race/ethnicity, age, health insurance type, annual household income, and whether respondents lived in New York City. We also examined the most common condition dyads and triads. Finally, we assessed the prevalence of MCC (2 or more chronic conditions) by county across New York State, and neighborhood within New York City.ResultsDuring 2011–2016, 25.2% of adults in New York State had zero chronic conditions, 24.1% had 1 condition, 18.4% had 2 conditions, and 32.4% had 3 or more. The most prevalent dyad was hypertension and high cholesterol in 17.0% of individuals. The most prevalent triad was hypertension, high cholesterol, and arthritis in 4.5% of individuals. County prevalence of MCC ranged from 42.6% in Westchester County to 66.1% in Oneida County. The prevalence of MCC in New York City neighborhoods ranged from 33.5% in Gramercy Park—Murray Hill to 60.6% in High Bridge—Morrisania.ConclusionThis research contributes to the field’s understanding of multiple chronic conditions and allows policy and public health leaders in New York to better understand the prevalence and distribution of MCC.

U.S. Census Bureau QuickFacts statistics for Monsey CDP, New York. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

U.S. Census Bureau QuickFacts statistics for South Valley Stream CDP, New York. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

U.S. Census Bureau QuickFacts statistics for Woodbury CDP, New York. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

U.S. Census Bureau QuickFacts statistics for Fairview CDP, New York. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.