Data are updated semiannually, at the end of the second and fourth quarters of each year.
Please see DCP’s annual Housing Production Snapshot summarizing findings from the 21Q4 data release here. Additional Housing and Economic analyses are also available.
The NYC Department of City Planning’s (DCP) Housing Database Unit Change Summary Files provide the net change in Class A housing units since 2010, and the count of units pending completion for commonly used political and statistical boundaries (Census Block, Census Tract, City Council district, Community District, Community District Tabulation Area (CDTA), Neighborhood Tabulation Area (NTA). These tables are aggregated from the DCP Housing Database Project-Level Files, which is derived from Department of Buildings (DOB) approved housing construction and demolition jobs filed or completed in NYC since January 1, 2010. Net housing unit change is calculated as the sum of all three construction job types that add or remove residential units: new buildings, major alterations, and demolitions. These files can be used to determine the change in legal housing units across time and space.
This dataset is comprised of the final assessment rolls submitted to the New York State Department of Taxation and Finance – Office of Real Property Tax Services by 996 local governments. Together, the assessment rolls provide the details of the more than 4.7 million parcels in New York State. The dataset includes assessment rolls for all cities and towns, except New York City. (For New York City assessment roll data, see NYC Open Data [https://opendata.cityofnewyork.us]) For each property, the dataset includes assessed value, full market value, property size, owners, exemption information, and other fields. Tip: For a unique identifier for every property in New York State, combine the SWIS code and print key fields.
This dataset identifies property managed partially or solely by NYC Parks. This data has been produced in whole or part using secondary data. Data accuracy is limited by the scale and accuracy of the original sources. Site-specific conditions should be field-verified.
Records are added as more land is designated under NYC Parks’ jurisdiction. Each record represents an acquisition.
User Guide: https://docs.google.com/document/d/1NExNJF5YKID04oOopi0fHainRuGG3Pz_jKSrMujPsPk/edit?usp=sharing
Data Dictionary: https://docs.google.com/spreadsheets/d/1Q4DBWu7riNFxWvy1vnTJHoOI3r2L9oW6eCN56jCNyCw/edit?usp=sharing
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 County. It can be utilized to understand the trend in median household income and to analyze the income distribution in New York County 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 County median household income. You can refer the same here
IMPORTANT! PLEASE READ DISCLAIMER BEFORE USING DATA. The Residential Existing Homes Program is a market transformation program that uses Building Performance Institute (BPI) Goldstar contractors to install comprehensive energy-efficient improvements. The program is designed to use building science and a whole-house approach to reduce energy use in the State’s existing one-to-four family and low-rise multifamily residential buildings and capture heating fuel and electricity-related savings. The Program provides income-based incentives, including an assisted subsidy for households with income up to 80% of the State or Median County Income, whichever is higher to install eligible energy efficiency improvements including building shell measures, high efficiency heating and cooling measures, ENERGY STAR appliances and lighting.
D I S C L A I M E R: Estimated Annual kWh Savings, Estimated Annual MMBtu Savings, and First Year Energy Savings $ Estimate represent contractor reported savings derived from energy modeling software calculations and not actual realized energy savings. The accuracy of the Estimated Annual kWh Savings and Estimated Annual MMBtu Savings for projects has been evaluated by an independent third party. The results of the impact analysis indicate that, on average, actual savings amount to 35 percent of the Estimated Annual kWh Savings and 65 percent of the Estimated Annual MMBtu Savings. The analysis did not evaluate every single project, but rather a sample of projects from 2007 and 2008, so the results are applicable to the population on average but not necessarily to any individual project which could have over or under achieved in comparison to the evaluated savings. The results from the impact analysis will be updated when more recent information is available. Many factors influence the degree to which estimated savings are realized, including proper calibration of the savings model and the savings algorithms used in the modeling software. Some reasons individual households may realize savings different from those projected include, but are not limited to, changes in the number or needs of household members, changes in occupancy schedules, changes in energy usage behaviors, changes to appliances and electronics installed in the home, and beginning or ending a home business. Beginning November 2017, the Program requires the use of HPXML-compliant modeling software tools and data quality protocols have been implemented to more accurately project savings. For more information, please refer to the Evaluation Report published on NYSERDA’s website at: http://www.nyserda.ny.gov/-/media/Files/Publications/PPSER/Program-Evaluation/2012ContractorReports/2012-HPwES-Impact-Report-with-Appendices.pdf.
The New York Residential Existing Homes (One to Four Units) dataset includes the following data points for projects completed during Green Jobs Green-NY, beginning November 15, 2010: Home Performance Project ID, Home Performance Site ID, Project County, Project City, Project Zip, Gas Utility, Electric Utility, Project Completion Date, Customer Type, Low-Rise or Home Performance Indicator, Total Project Cost (USD), Total Incentives (USD), Type of Program Financing, Amount Financed Through Program (USD), Pre-Retrofit Home Heating Fuel Type, Year Home Built, Size of Home, Volume of Home, Number of Units, Measure Type, Estimated Annual kWh Savings, Estimated Annual MMBtu Savings, First Year Energy Savings $ Estimate (USD), Homeowner Received Green Jobs-Green NY Free/Reduced Cost Audit (Y/N).
How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov.
In New York City, one of the United States’ most iconic destinations, Airbnb has established itself as a key player in the accommodation market. In 2025, Airbnb customers booked an average of ** nights per stay, with an average price of *** U.S. dollars per night. Meanwhile, the average income per property was ***** U.S. dollars that year. Are Airbnb rentals expensive in New York City? As of early 2024, the most expensive Airbnb properties per night in the United States were in *************. This was followed by *************************. In comparison, the average cost of a night’s stay at an Airbnb property in New York City is less than half of the cost of a night in *************. How many Airbnb properties are there in New York City? In early 2024, the Airbnb market in New York City offered more than **** thousand properties accommodating to the different needs of visitors to the city. There are various types of Airbnb properties in New York City, the most common of which were entire homes and apartments, followed by private rooms. The majority of Airbnb listings also catered for longer-term stays, in light of city regulations on housing.
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Graph and download economic data for All-Transactions House Price Index for New York (NYSTHPI) from Q1 1975 to Q1 2025 about NY, appraisers, HPI, housing, price index, indexes, price, 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 New York County, NY, 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 New York County median household income. You can refer the same here
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Graph and download economic data for Housing Inventory: Active Listing Count in New York (ACTLISCOUNY) from Jul 2016 to Jul 2025 about active listing, NY, listing, 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 median household incomes for various household sizes in Big Flats, New York, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.
Key observations
https://i.neilsberg.com/ch/big-flats-ny-median-household-income-by-household-size.jpeg" alt="Big Flats, New York median household income, by household size (in 2022 inflation-adjusted dollars)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Household Sizes:
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 Big Flats town median household income. 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
Context
The dataset tabulates the Red House town 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 Red House town 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 Red House town was 30, a 0.00% decrease year-by-year from 2021. Previously, in 2021, Red House town population was 30, a decline of 0.00% compared to a population of 30 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Red House town decreased by 8. In this period, the peak population was 38 in the year 2000. 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).
When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).
Data Coverage:
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 Red House town Population by Year. 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
Context
The dataset presents median household incomes for various household sizes in Chester Town, Orange County, New York, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.
Key observations
https://i.neilsberg.com/ch/chester-town-orange-county-ny-median-household-income-by-household-size.jpeg" alt="Chester Town, Orange County, New York median household income, by household size (in 2022 inflation-adjusted dollars)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Household Sizes:
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 Chester town median household income. 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
Context
The dataset presents the mean household income for each of the five quintiles in Brighton Town, Franklin County, 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) 2019-2023 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 Brighton town median household income. 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
Context
The dataset presents median household incomes for various household sizes in Baldwin, New York, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.
Key observations
https://i.neilsberg.com/ch/baldwin-ny-median-household-income-by-household-size.jpeg" alt="Baldwin, New York median household income, by household size (in 2022 inflation-adjusted dollars)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Household Sizes:
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 Baldwin town median household income. 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
Context
The dataset presents median household incomes for various household sizes in New York Mills, NY, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.
Key observations
https://i.neilsberg.com/ch/new-york-mills-ny-median-household-income-by-household-size.jpeg" alt="New York Mills, NY median household income, by household size (in 2022 inflation-adjusted dollars)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Household Sizes:
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 Mills median household income. 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
Context
The dataset presents the distribution of median household income among distinct age brackets of householders in New York Mills. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in New York Mills. 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 2023
In terms of income distribution across age cohorts, in New York Mills, the median household income stands at $81,857 for householders within the 25 to 44 years age group, followed by $45,156 for the 65 years and over age group. Notably, householders within the 45 to 64 years age group, had the lowest median household income at $37,083.
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.
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 Mills median household income by age. 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
Context
The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Niskayuna town: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income brackets:
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 Niskayuna town median household income by age. 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
Context
The dataset presents median household incomes for various household sizes in Vestal, New York, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Household Sizes:
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 Vestal town median household income. 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
Context
The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Worth town: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income brackets:
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 Worth town median household income by age. 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
Context
The dataset presents the distribution of median household income among distinct age brackets of householders in Niskayuna town. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Niskayuna town. 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 2023
In terms of income distribution across age cohorts, in Niskayuna town, householders within the 45 to 64 years age group have the highest median household income at $161,316, followed by those in the 25 to 44 years age group with an income of $144,738. Meanwhile householders within the 65 years and over age group report the second lowest median household income of $101,000. Notably, householders within the under 25 years age group, had the lowest median household income at $95,455.
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.
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 Niskayuna town median household income by age. You can refer the same here
Data are updated semiannually, at the end of the second and fourth quarters of each year.
Please see DCP’s annual Housing Production Snapshot summarizing findings from the 21Q4 data release here. Additional Housing and Economic analyses are also available.
The NYC Department of City Planning’s (DCP) Housing Database Unit Change Summary Files provide the net change in Class A housing units since 2010, and the count of units pending completion for commonly used political and statistical boundaries (Census Block, Census Tract, City Council district, Community District, Community District Tabulation Area (CDTA), Neighborhood Tabulation Area (NTA). These tables are aggregated from the DCP Housing Database Project-Level Files, which is derived from Department of Buildings (DOB) approved housing construction and demolition jobs filed or completed in NYC since January 1, 2010. Net housing unit change is calculated as the sum of all three construction job types that add or remove residential units: new buildings, major alterations, and demolitions. These files can be used to determine the change in legal housing units across time and space.