Equitable Development Data Explorer

Community Data Methodology

Community Data contains demographic, housing, and quality of life data broken out by race and ethnicity (when available) at the neighborhood, borough, and citywide scales. Community Data also shows change over time between 2000 and 2020. See data sources below.

Displacement Risk Map Methodology

Local Law 78 of 2021 called for the creation of a displacement risk index or a map of the city that illustrates the level of displacement risk in different neighborhoods as compared to each other. Displacement refers to the involuntary movement of an individual or family from their home or neighborhood, whether as the result of eviction, unaffordable housing costs, or poor-quality housing. There are many factors that may contribute to residents' risk of displacement, though there is no standard methodology for how to measure it. Building on data points listed in Local Law 78 of 2021, DCP and HPD identified a complete set of data points and a methodology to combine the data points into an index based on research, precedents from other cities, and conversations with stakeholders.

The three major categories of data points in the displacement risk index include:

• Population Vulnerability: This category refers to the demographic and socioeconomic characteristics of a neighborhood's residents that may make them more susceptible to displacement. It includes data points such as race/ethnicity, income, and the share of a household's income spent on rent.
• Housing Conditions: This category refers to the characteristics of housing in a neighborhood that can either help stabilize households or lead to greater instability. It includes data points such as condition of the housing stock, whether a household rents or owns, and applicability of various programs or regulations limiting rent increases.
• Market Pressure: This category refers to the broader conditions affecting neighborhoods that tend to make it harder for lower-income residents to remain or find new housing in the area. It includes data points related to changes in the housing market and demographic composition of a neighborhood, among others.

Methodology to Combine the Data Points into an Index:

When incorporating the data into an index, individual data points or categories could be emphasized over others, depending on how strongly they contribute to the likelihood of residents' ability to stay in their homes. Because research suggests that demographic data are a stronger predictor of displacement risk than housing conditions or market pressure data, DCP and HPD focused on methodologies to combine the data while prioritizing population characteristics (e.g. race, income, English language proficiency, and rent burden).

Our selected methodology creates an overall risk level based on how neighborhood and housing conditions magnify or reduce population vulnerability. This methodology assumes that population vulnerability drives displacement risk and considers how it can be exacerbated by market pressure or mitigated by housing security.

See our Data Dictionary for more information on the methodology we used to combine the data points and an analysis that was conducted to compare the model to other data associated with displacement.