Neighborhood Study Indicators
Neighborhood Study Indicators Vacant properties The vacant property data used in the report's calculations was collected by Isles during the summer of 2019. The calculation that we used was the percentage of vacant Class 2 (one to four family) structures out of all Class 2 structures. Vacancy is a critical factor in looking at the health of a neighborhood. Vacancy rates above a range of 5% to 8% reflect a weakness in the area’s housing market, and the higher the vacancy rate, the weaker the market conditions in the area. Homeownership rate The homeownership rate is an important indicator of neighborhood stability. Not only is homeownership correlated with longer tenure, but it is also strongly associated with positive neighborhood features, including greater investment in one’s property, greater neighborhood engagement, and stronger social capital. We used data from the Trenton Tax Assessor’s file, which included information on all properties in Trenton through the end of 2020, including the address of the property, and the name and address of the owner of record to which property tax bills are sent. After screening out all but Class 2 properties, we then excluded all properties where the address of the property and the address of the owner were not the same, assuming that these were investor-owned. We then excluded properties where the owner name was clearly not an individual or couple; for example, “235 ChestnutStreet LLC” or “Flip-My-House, Inc.” The remaining properties were considered owner-occupied. Investor purchases The proportion of home purchases by investors rather than owner-occupant buyers has a significant bearing on neighborhood stability. Investors' fundamental criterion is whether the house represents an opportunity to make money, while homebuyers are planning to make both a personal and financial investment in the house and surrounding neighborhood. And when house prices are low, there is a significant risk that the market will draw ‘milkers,’ investors interested in pure short-term cash flow profits, who then abandon the property. The mix of investor and owner-occupant buyers was determined using deed record data, which is compiled and published by the County approximately once every month or two. (The deed records can also be accessed here -- set "Database" to "Deed/Sr1A".) Median sales price The price for which houses sell in a neighborhood or city is probably the single most direct measure of market performance – the higher the price for a comparable house, the stronger the market, and the more people in the market who value the neighborhood. Since the number of transactions in any one year is too small to be meaningful in many of the city’s smaller neighborhoods, we aggregated transactions from 2018 through 2020, using sales prices from the SR1A forms, and computed a median price for the three year period for the city and each neighborhood. Tax delinquency Property owners have certain obligations, including the responsibility to pay property taxes to the city; and, if they have taken out a mortgage, to make mortgage payments. Whether or not they do so is a function of two factors – their ability to do so, or hardship; and their desire to do so, which reflects how they feel about the value of holding onto the property and their confidence in the neighborhood. Since mortgage payments are typically larger than property taxes, and since banks tend to move more quickly than local governments, the hardship factor usually weighs more heavily with mortgages, and the confidence factor weighs greater with property taxes, although the extremely high property tax rate in Trenton may tilt the balance more toward hardship. Thus, the percentage of owners paying their property taxes offers a rough measure of property owners’ assessment of their neighborhood and its future prospects. To measure this factor, we use the percentage of properties which were delinquent on their taxes in 2021 for the minimum length of time needed to be placed on a tax sale list. Tax sale certificate purchases When the city puts tax delinquent properties up for tax sale, one of two things happens to each property: either the tax sale certificate is bought by an investor, who pays the city the outstanding taxes; or, if no investor offers the minimum bid on the property, it is ‘struck off ’ and becomes the property of the city. Thus, the percentage of properties that are struck off to the city because no investors bid on them is a good reflection of how the investor market sees the neighborhood -- this is the parallel to the tax delinquency indicator, which reflects how property owners see their neighborhood. This measure uses the share of tax sale certificates struck off to the City of Trenton in 2021. Violent crime Crime in general, and violent crime in particular, are important – perhaps the most important – factors in how people, both within and outside an area, assess a neighborhood. Both the actual crime level as well as the fear of crime exert a powerful influence on whether people choose to buy a home in a particular area; or if they live in that area, choose to stay if they have the economic means to move elsewhere. The Trenton Department of Public Safety provided data on reported crime incidents by the nature of the crime and the location, which were geo-coded and allocated by neighborhood and subarea. Research suggests that violent crime affects people’s perceptions of an area more than property crime. Our measure was the violent crimes that are part of the FBI index; specifically, homicide-murder, sexual assault, robbery (strong arm or with weapon), or aggravated assault (causing injury with a deadly weapon). In order to control for possible random upward or downward ‘blips’ from one year to the next in small areas, we combined all violent crime incidents reported from 2017 to 2019, a period during which the overall violent crime rate went down slightly for the city, to construct the measure. For reasons that we do not understand, the data provided to us by the City lists a much smaller number of crime incidents than appear to have actually taken place, or that were reported by the City to the FBI as part of the Uniform Crime Reporting system for the same years. For this reason, we have not made any attempt to compare the data to national violent crime levels, as we did in the 2015 analysis. For purposes of this study we have assumed, however, that the data is reasonably consistent by neighborhood; that is, while the data is underreported for the city as a whole, we are not aware of any reason that it should be more greatly underreported in certain neighborhoods rather than in others.
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Additional Info
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| Last Updated | March 25, 2026, 02:18 (UTC) |
| Created | March 25, 2026, 02:18 (UTC) |
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Domain / Topic
Domain or topic of the dataset being cataloged.
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Title
Title for the Dataset.
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Neighborhood Study Indicators |
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Description
A description of the dataset.
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Neighborhood Study Indicators Vacant properties The vacant property data used in the report's calculations was collected by Isles during the summer of 2019. The calculation that we used was the percentage of vacant Class 2 (one to four family) structures out of all Class 2 structures. Vacancy is a critical factor in looking at the health of a neighborhood. Vacancy rates above a range of 5% to 8% reflect a weakness in the area’s housing market, and the higher the vacancy rate, the weaker the market conditions in the area. Homeownership rate The homeownership rate is an important indicator of neighborhood stability. Not only is homeownership correlated with longer tenure, but it is also strongly associated with positive neighborhood features, including greater investment in one’s property, greater neighborhood engagement, and stronger social capital. We used data from the Trenton Tax Assessor’s file, which included information on all properties in Trenton through the end of 2020, including the address of the property, and the name and address of the owner of record to which property tax bills are sent. After screening out all but Class 2 properties, we then excluded all properties where the address of the property and the address of the owner were not the same, assuming that these were investor-owned. We then excluded properties where the owner name was clearly not an individual or couple; for example, “235 ChestnutStreet LLC” or “Flip-My-House, Inc.” The remaining properties were considered owner-occupied. Investor purchases The proportion of home purchases by investors rather than owner-occupant buyers has a significant bearing on neighborhood stability. Investors' fundamental criterion is whether the house represents an opportunity to make money, while homebuyers are planning to make both a personal and financial investment in the house and surrounding neighborhood. And when house prices are low, there is a significant risk that the market will draw ‘milkers,’ investors interested in pure short-term cash flow profits, who then abandon the property. The mix of investor and owner-occupant buyers was determined using deed record data, which is compiled and published by the County approximately once every month or two. (The deed records can also be accessed here -- set "Database" to "Deed/Sr1A".) Median sales price The price for which houses sell in a neighborhood or city is probably the single most direct measure of market performance – the higher the price for a comparable house, the stronger the market, and the more people in the market who value the neighborhood. Since the number of transactions in any one year is too small to be meaningful in many of the city’s smaller neighborhoods, we aggregated transactions from 2018 through 2020, using sales prices from the SR1A forms, and computed a median price for the three year period for the city and each neighborhood. Tax delinquency Property owners have certain obligations, including the responsibility to pay property taxes to the city; and, if they have taken out a mortgage, to make mortgage payments. Whether or not they do so is a function of two factors – their ability to do so, or hardship; and their desire to do so, which reflects how they feel about the value of holding onto the property and their confidence in the neighborhood. Since mortgage payments are typically larger than property taxes, and since banks tend to move more quickly than local governments, the hardship factor usually weighs more heavily with mortgages, and the confidence factor weighs greater with property taxes, although the extremely high property tax rate in Trenton may tilt the balance more toward hardship. Thus, the percentage of owners paying their property taxes offers a rough measure of property owners’ assessment of their neighborhood and its future prospects. To measure this factor, we use the percentage of properties which were delinquent on their taxes in 2021 for the minimum length of time needed to be placed on a tax sale list. Tax sale certificate purchases When the city puts tax delinquent properties up for tax sale, one of two things happens to each property: either the tax sale certificate is bought by an investor, who pays the city the outstanding taxes; or, if no investor offers the minimum bid on the property, it is ‘struck off ’ and becomes the property of the city. Thus, the percentage of properties that are struck off to the city because no investors bid on them is a good reflection of how the investor market sees the neighborhood -- this is the parallel to the tax delinquency indicator, which reflects how property owners see their neighborhood. This measure uses the share of tax sale certificates struck off to the City of Trenton in 2021. Violent crime Crime in general, and violent crime in particular, are important – perhaps the most important – factors in how people, both within and outside an area, assess a neighborhood. Both the actual crime level as well as the fear of crime exert a powerful influence on whether people choose to buy a home in a particular area; or if they live in that area, choose to stay if they have the economic means to move elsewhere. The Trenton Department of Public Safety provided data on reported crime incidents by the nature of the crime and the location, which were geo-coded and allocated by neighborhood and subarea. Research suggests that violent crime affects people’s perceptions of an area more than property crime. Our measure was the violent crimes that are part of the FBI index; specifically, homicide-murder, sexual assault, robbery (strong arm or with weapon), or aggravated assault (causing injury with a deadly weapon). In order to control for possible random upward or downward ‘blips’ from one year to the next in small areas, we combined all violent crime incidents reported from 2017 to 2019, a period during which the overall violent crime rate went down slightly for the city, to construct the measure. For reasons that we do not understand, the data provided to us by the City lists a much smaller number of crime incidents than appear to have actually taken place, or that were reported by the City to the FBI as part of the Uniform Crime Reporting system for the same years. For this reason, we have not made any attempt to compare the data to national violent crime levels, as we did in the 2015 analysis. For purposes of this study we have assumed, however, that the data is reasonably consistent by neighborhood; that is, while the data is underreported for the city as a whole, we are not aware of any reason that it should be more greatly underreported in certain neighborhoods rather than in others. |
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Keywords/tags categorizing the dataset.
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Format (CSV, XLS, TXT, PDF, etc)
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Dataset Size
Dataset size in megabytes.
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19.83 |
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Metadata Identifier
Metadata identifier – can be used as the unique identifier for catalogue entry
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Published Date
Published date of the dataset.
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2023-11-28 |
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Time Period Data Span (start date)
Start date of the data in the dataset.
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Time Period Data Span (end date)
End date of time data in the dataset.
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GeoSpatial Area Data Span
A spatial region or named place the dataset covers.
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Access category
Type of access granted for the dataset (open, closed, service, etc).
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public |
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License
License used to access the dataset.
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License not specified |
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Limits on use
Limits on use of data.
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Location
Location of the dataset.
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https://restoring-trenton-tvs.hub.arcgis.com/datasets/b3d7f8bc64d543db8c12e7f6c2894d80 |
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Data Service
Data service for accessing a dataset.
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Owner
Owner of the dataset.
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restoring_trenton |
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Contact Point
Who to contact regarding access?
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Contact Point Email
The email to contact regarding access?
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Publisher
Publisher of the dataset.
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Publisher Email
Email of the publisher.
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Author
Author of the dataset.
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restoring_trenton |
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Author Email
Email of the author.
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Accessed At
Date the data and metadata was accessed.
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2023-11-28 |
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Identifier
Unique identifier for the dataset.
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b3d7f8bc64d543db8c12e7f6c2894d80 |
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Language
Language(s) of the dataset
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English |
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Link to dataset description
A URL to an external document describing the dataset.
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https://restoring-trenton-tvs.hub.arcgis.com/datasets/b3d7f8bc64d543db8c12e7f6c2894d80 |
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Persistent Identifier
Data is identified by a persistent identifier.
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Globally Unique Identifier
Data is identified by a persistent and globally unique identifier.
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Contains data about individuals
Does the data hold data about individuals?
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Contains data about identifiable individuals
Does the data hold identifiable data about individual?
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Contains Indigenous Data
Does the data hold data about Indigenous communities?
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Portal Type
Platform type of the source portal.
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Version
Version of the datatset
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None |
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Source
Source of the dataset.
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None |
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Version notes
Version notes about the dataset.
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Is version of another dataset
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Other versions
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Provenance Text
Provenance Text of the data.
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Provenance URL
Provenance URL of the data.
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Temporal resolution
Describes how granular the date/time data in the dataset is.
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GeoSpatial resolution in meters
Describes how granular (in meters) geospatial data is in the dataset.
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GeoSpatial resolution (in regions)
Describes how granular (in regions) geospatial data is in the dataset.
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Indigenous Community Permission
Who holds the Indigenous Community Permission. Who to contact regarding access to a dataset that has data about Indigenous communities.
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Community Permission
Community permission (who gave permission).
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The Indigenous communities the dataset is about
Indigenous communities from which data is derived.
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Number of data rows
If tabular dataset, total number of rows.
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Number of data columns
If tabular dataset, total number of unique columns.
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Number of data cells
If tabular dataset, total number of cells with data.
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Number of data relations
If RDF dataset, total number of triples.
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Number of entities
If RDF dataset, total number of entities.
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Number of data properties
If RDF dataset, total number of unique properties used by the triples.
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Data quality
Describes the quality of the data in the dataset.
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Metric for data quality
A metric used to measure the quality of the data, such as missing values or invalid formats.
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