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- Existing Literature
- Summary of Data
Cities across the United States that have considerable vacant land are debating whether to foster community gardens on that land, while cities with land shortages are debating when to replace gardens with other uses. Meanwhile, many cities are looking for new ways to finance green spaces. Little empirical evidence about the neighborhood impacts of community gardens is available, however, to inform the debate or to help cities design financing schemes. This article estimates the impact of community gardens on neighborhood property values, using rich data for New York City and a difference-in-difference specification of a hedonic regression model. We find that gardens have significant positive effects, especially in the poorest neighborhoods. Higher-quality gardens have the greatest positive impact.
- Top of page
- Existing Literature
- Summary of Data
In recent years, controversies have erupted in many communities, perhaps most notably New York City, about the use of vacant lots for community gardens. The gardens often are initially warmly welcomed by communities as catalysts for the improvement of troubled neighborhoods, and they frequently become treasured by neighborhood residents. When private owners or public agencies then seek to reclaim the lots for development, support for the gardens often is pitted against other social goals such as affordable housing or other public uses.
In such controversies, advocates for the gardens have advanced many arguments about the value of the community gardens, claiming that gardens stabilize and improve their host neighborhoods, provide a focal point for community organizing and social networks, bring fresh produce to neighborhood where fresh fruits and vegetables often are not available and provide recreation and exercise for neighborhood residents. Advocates have cited anecdotal evidence that gardens increased the value of neighboring properties and spurred neighborhood revitalization. As proof of the value of such spaces, advocates also have pointed to efforts of several cities to develop small “pocket” parks through initiatives such as New York City's “Green Streets” program.
Little empirical evidence about the effect community gardens have on surrounding properties is available, however, to inform the debates over whether to foster the development of community gardens or when to replace community gardens with other uses. That gap is surprising, given that the benefits gardens and small urban green spaces provide, relative to alternative uses of the property, have played a key role in controversies over community gardens not just in New York City, but in Boston, St. Louis and many other communities.1 The value of gardens and small parks also is central to debates over the desirability of efforts to reduce sprawl by fostering infill development. More generally, local governments across the country face increasing controversy about how much and what types of green space and park land should be provided by the community or by developers proposing to build within a community. Further, many neighborhoods and cities are debating whether to charge developers impact fees to fund the provision of gardens and small parks within a development. In many states, the law requires that any such charges be based upon realistic assessments of the need for and value of such spaces. Similarly, local governments need reliable data about the economic impact of different kinds of parks and open space in order to decide whether to employ tax increment financing (TIF) to support the provision of parks and open space.2
Despite this critical need for information, relatively little is known about the economic value of gardens, small urban parks and other such green spaces. A number of studies have investigated the link between proximity to parks or other open space and property values, but because they focused on relatively low-density development, the results of those studies may not be transferable to the setting in which many community gardens or small urban parks are found. Further, the existing studies share methodological and data limitations that make it difficult to pinpoint the direction of the causality of any property value differences found.
In this article, we attempt to fill these gaps, using unique data from New York City and a difference-in-differences specification of a hedonic regression model to estimate the effect of community gardens on neighborhood residential property values.3 Impacts are estimated as the difference between property values in the vicinity of garden sites before and after a garden opens relative to price changes of comparable properties farther away, but still in the same neighborhood. We examine whether effects change over time or vary with neighborhood type and garden quality.
We find that the opening of a community garden has a statistically significant positive impact on the sales prices of properties within 1,000 feet of the garden and that the impact increases over time. Higher-quality gardens have the greatest positive impact. We also find that gardens have the greatest impact in the most disadvantaged neighborhoods. Finally, a simple cost–benefit analysis suggests that the gain in tax revenue generated by community gardens in the 1,000-foot ring may be substantial.
The article is organized as follows. The next section offers a review of relevant literature. The third section describes the models and empirical strategy. In the fourth section, we provide a description of the data, and in the fifth section we present results. The article ends with a summary of the key findings.
- Top of page
- Existing Literature
- Summary of Data
Although we know of only one other study of the impact that community gardens have on surrounding properties, a number of studies have investigated the link between proximity to parks and other open spaces and property values. These studies vary widely in their methodology, ranging from simple surveys to hedonic modeling or matched-pair analysis. They have examined the influence of a wide range of open space types, such as golf courses, greenbelts, wetlands, agricultural spaces, urban parks and playgrounds. The studies that focus directly on parks of various kinds tend to show positive property value impacts. Crompton (2001) surveys the older literature, while Hobden, Laughton and Morgan (2004) summarize more recent literature. We review here the studies that focused on the small urban parks or other open spaces most analogous to community gardens.
Bolitzer and Netusil (2000) studied the effect of proximity to an open space (public and private parks, cemeteries and golf courses) in Portland, Oregon, using data on 16,402 sales of single-family homes between 1990 and 1992. Using a linear hedonic model, they found that a home located within 1,500 feet (71/2 blocks) of a 20-acre open space (the mean for the public parks in the area) sold for approximately $2,670 (in 1990 dollars) more than homes that were farther from a park. A semi-log model showed that proximity to any open space increased a home's sales price by 1.43%. When the authors estimated the effect of the different types of open space in the study area, however, the increase in value was limited to public parks and cemeteries; private parks had no statistically significant effect on home prices. Because the mean size of the public parks studied was 20 acres, while the mean size of the private parks was almost four acres, the finding that private parks did not have a statistically significant effect on neighboring properties is most relevant for our study of community gardens, which have a median size of 6,000 square feet (less than ¼ acre) in New York City.
Lutzenhiser and Netusil (2001) refined the approach taken in Bolitzer and Netusil (2000), using the same data from Portland, Oregon. Breaking the types of open space into five categories, they found that “urban parks” (those in which more than 50% of the area was landscaped or developed for uses such as swimming pools or ball fields) had a statistically significant effect of $1,214 (in 1990 dollars), or 1.8% of the mean house value, on the value of single-family residences within 1,500 feet of the park. That effect was far lower than the effect of both “natural area parks” in which a majority of the land was preserved in natural vegetation, and golf courses ($10,648 and $8,849, respectively). The authors estimated that the size of an urban park that would maximize its positive effect on a home's sales price would be 148 acres, almost 600 times larger than the median size of the community gardens in our study.
Espey and Owasu-Edusei (2001) used hedonic methods to investigate the effect proximity to 24 neighborhood parks had on the sales prices of single-family homes in Greenville, South Carolina, between 1990 and 1999. The authors broke the parks down into four categories. Type 1 parks ranged from 15,620 to 87,687 square feet and were essentially playgrounds with some grassy areas, but were not “particularly attractive.” Type 2 parks were small, attractive parks with playgrounds. Type 3 consisted of attractive medium-sized parks with both sports fields or courts and playgrounds but also some natural areas; and Type 4 parks were unattractive medium-sized parks with few amenities and no natural area. Using a semi-log model, the authors found that the Type 1 parks had a statistically significant negative effect on the sales prices of homes within 300 feet of the park, a significant positive effect of about 15% on the sales of houses between 300 and 500 feet and a significant positive effect of about 6.5% on the sales prices of homes located between 500 and 1,500 feet of the park. Small attractive parks (Type 2) had a statistically significant positive effect of 11% on the sales prices of houses within 600 feet of the park, but no statistically significant effect beyond that.
Pincetl et al. (2003) studied a neighborhood five miles from downtown Los Angeles in which most of the housing was multifamily, rental buildings. The neighborhood had no parks, but the authors examined the effect of greenery (as measured using aerial photographs) on 260 sales of single-family homes over an 18-month period. The authors found that an 11% increase in the amount of greenery (equivalent to a one-third acre garden or park) within a radius of 200 to 500 feet from the house increased the sales price of the house by approximately 1.5%.4
Hobden, Laughton and Morgan (2004) used a matched pairs methodology to measure the effect greenways had on adjacent properties. The authors grouped greenways into eight categories, based upon improvements to the greenways, and also distinguished between “small parks” in which the greenway was a narrow strip (often a pathway) of less than 50% of the area of the adjacent residential property. Using data from the years between 1980 and 2001, the authors identified 755 matched pairs. They found that adding a greenway increased the sales price of adjacent properties by 2.8%. Where the greenway was defined as a “small park,” the greenway increased the values of adjacent properties by 6.9%.
New Yorkers for Parks and Ernst & Young (2003) found, through case study methodology,5 that the values of single-family homes located near three well-improved parks in Brooklyn, Queens and Staten Island were 8 to 30% higher than values of homes farther from the parks.
Most directly relevant to our research, Tranel and Handlin (2006) used census data for 1990 and 2000 and a difference-in-difference methodology to assess the neighborhood effects of 54 community gardens in St. Louis, Missouri. They found that median rent, median housing costs (mortgage payments, maintenance costs and taxes) for owner-occupied housing as well as the homeownership rate increased in the immediate vicinity of gardens relative to the surrounding census tracts, following garden opening.
Second, the existing literature does not attempt, except in the most general way, to account for differences in the quality of the parks or gardens. See, for example, Espey and Owasu-Edusei (2001), which distinguishes between unattractive and attractive parks.
Moreover, in most previous studies, data limitations make it difficult to pinpoint the direction of causality. The existing studies usually employ cross-sectional techniques that compare sales prices and other neighborhood indicators in neighborhoods with open spaces to those in neighborhoods without, but it is difficult to know whether the two groups of neighborhoods truly are comparable. Therefore, their results could be interpreted to suggest that open spaces lead to improvements in the surrounding neighborhood, but could instead mean that such spaces are systematically located in strong neighborhoods. One exception is Tranel and Handlin (2006) who employ a difference-in-difference methodology to study the neighborhood impacts of community gardens. However, when estimating the impact the gardens have on rents and owner-occupied housing costs, they do not control for housing characteristics, thus raising questions about the comparability of the treatment and control areas. Moreover, their analysis is based on only two data points in time, one before and one after garden formation, and thus, it does not control for baseline (preexisting) trends, nor does it estimate the variation of garden impacts over time.
Finally, the existing literature does not address whether differences in the characteristics of the surrounding neighborhood affect the property value impacts of the parks or gardens.
Summary of Data
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- Existing Literature
- Summary of Data
To undertake the analysis outlined above, we obtained data from the Council on the Environment of New York City (CENYC) describing all the community gardens in the city.30 For each garden, this data set indicates the exact location (tax lot(s)), area, opening date and land ownership.31 Our main estimation sample of gardens includes 636 gardens, established between 1977 and 2000.32
As the CENYC database does not contain any qualitative data about the gardens, we inspected a subset of the city's gardens to obtain such information, as noted above. We chose to survey the gardens in the Bronx because Brooklyn had so many gardens that it was impossible to inspect them all, and we feared that gardens in relatively affluent and high-density Manhattan might not be representative of gardens across the City. The Bronx contains a mix of housing and building types, so is more representative of the City's average neighborhood (and the average neighborhood in most large cities across the nation) than is Manhattan. As shown in Table 3A, gardens in the Bronx are smaller, on average, than all New York City gardens, and were somewhat older than all New York City gardens (44.3% of the Bronx gardens were established before 1991, compared with 38.1% of all gardens). We have no reason to believe that the relationship between the quality of the garden and its impacts on surrounding property would be different in the Bronx than in the rest of the city.
Table 3A▪. Descriptive statistics on New York City gardens.
|Garden Area (×1,000 sq. ft.)|
| Median|| 6.0|
| % established between 1977 and 1980|| 8.8|
| % established between 1981 and 1990||29.3|
| % established between 1991 and 2000||61.8|
| % public||95.3|
| % private|| 4.7|
| Queens|| 6.1|
| Staten island|| 0.5|
|Number of gardens||636|
We deployed teams of students from NYU School of Law and NYU's Robert F. Wagner Graduate School of Public Service to visit these gardens and rank them on such criteria as the garden's accessibility to the general public, how well maintained the garden appears, whether there are social spaces in the garden and whether the garden appears to contain trash or other disamenities. We were able to obtain valid information for 86 gardens (out of the 147 Bronx gardens).33
We supplemented our data on community gardens with geocoded data from several other sources. First, through an arrangement with the New York City Department of Finance, we obtained a confidential database that contains sales transaction prices for all apartment buildings, condominium apartments and single-family homes over the period 1974–2003.34 Our sales sample includes 517,791 property sales, spread across 1,799 census tracts.35 Both because of the long time span of the data and New York City's size, this is a very large sample size compared with much of the literature.
Second, data on building characteristics were obtained from an administrative data set gathered for the purpose of assessing property taxes (the RPAD file). Unfortunately, the RPAD data contain little information about the characteristics of individual units in apartment buildings (except in the case of condominiums).36 Nonetheless, these building characteristics explain variations in prices surprisingly well, suggesting the data are rich enough for estimating hedonic price equations.37
Third, we use demographic data about the neighborhoods from the 1980 U.S. Census to compare the characteristics of neighborhoods in which gardens were opened to those of other neighborhoods. Because most of the gardens were opened since 1980, the 1980 Census data seemed most appropriate.
Finally, we utilize data on the location and characteristics of most federally- and city-assisted housing in New York City from a variety of sources.38 We obtained address-specific data from HUD USER on the number of units created through the Section 8 project-based, Section 202, LIHTC, BMIR and the Section 236 programs. From the New York City Housing Authority (NYCHA), we secured address-specific data on all public housing developments. New York City's Department of Housing Preservation and Development (HPD) provided address-specific data describing all of the city-assisted housing built between 1977 and 2000.
As mentioned above, identifying properties in the vicinity of garden sites was critical to our analyses. We used GIS techniques to measure the distance between garden sites and each property for which a sale appeared in our database. From these distance measures, we created a variable that identified properties within 1,000 feet of a garden. A continuous distance variable indicates the distance from the property sold to the closest garden site.39
Table 1 shows summary statistics for our sales sample. The first column shows the characteristics of our full sample of property sales; the second column shows the characteristics of transacting properties that were located or in the future would be located within 1,000 feet of a garden. Fifteen percent of the sales were located within 1,000 feet of a garden site. As shown, most of the sales in our sample were located in Brooklyn and Queens, largely because those boroughs include a relatively large share of smaller properties, which sell more frequently than larger ones. Over two-thirds of all buildings sold were either one- or two-family homes, and 87% were single-family homes, two-family homes or small apartments.
Table 1▪. Characteristics of residential properties sold.
| ||Percentage of All Property Sales||Percentage of Sales Within 1,000 Feet of Community Garden Sites|
| Manhattan|| 8.0||17.2|
| Staten island|| 5.4|| 0.7|
| Single-family detached||21.8||10.0|
| Single-family attached||13.9|| 9.0|
| Walk-up apartments||18.1||31.5|
| Elevator apartments|| 1.0|| 2.0|
| Loft buildings|| 0.0|| 0.0|
| Condominiums|| 7.7|| 9.2|
| Mixed-use, primarily residential (Includes store or office plus residential units)|| 4.3|| 6.7|
|Other structural characteristics|
| Built pre-World War II||78.4||89.4|
| Vandalized|| 0.0|| 0.2|
| Other abandoned|| 0.1|| 0.3|
| Corner location|| 7.3|| 7.5|
| Major alteration prior to sale|| 1.1|| 3.4|
The second column reveals some systematic differences between the transacting properties located close to garden sites and those that are not. Properties located within the 1,000-foot ring were more likely to be in Brooklyn and Manhattan than in the other boroughs. They were also older, less likely to be single-family homes and more likely to be walk-up apartments.
In an effort to better describe the small neighborhoods that host community gardens, we replicated the above comparisons using all properties in rings, not just those that sold. The same picture emerged using these statistics (available upon request from the authors). We also present in Table 2 statistics on the presence of publicly subsidized housing in the vicinity of garden sites. This table shows that the share of each type of assisted housing—except Mitchell Lama—in the total housing stock in the rings around garden sites is much larger than the share outside the rings. For example, 14.1% of the housing stock in rings consists of public housing units, but only 7.1% of the total city housing stock is public housing. Subsidized housing in the aggregate accounts for 46% of the housing stock in rings but only for 24% of the total stock.
Table 2▪. Subsidized housing within 1,000 feet of community gardens.
|Within 1,000 Feet of Garden||Total|
|Number||% of All Residential||Number||% of All Residential|
|Public housing|| 90,189|| 14.1|| 169,569|| 7.1|
|Other federally subsidizeda|| 50,257|| 7.9|| 90,068|| 3.7|
|City-subsidized homeownership|| 24,699|| 3.9|| 38,413|| 1.6|
|City-subsidized rental|| 93,914|| 14.7|| 163,746|| 6.8|
|Mitchell lama rental|| 15,710|| 2.5|| 53,576|| 2.2|
|Mitchell lama co-op|| 18,208|| 2.8|| 60,378|| 2.5|
Table 3 shows descriptive statistics for the sample including all of New York City gardens formed between 1977 and 2000, as well as for the subsample of Bronx gardens covered by our survey. Whereas the mean area of the city's gardens is 35,000 sq. ft., the median area is only 6,000 sq. ft., suggesting that the area distribution is highly skewed to the right. Most of the gardens are relatively new—62% were established within the last decade—and the overwhelming majority (95%) is sited on publicly owned land. Most of the gardens are located in Brooklyn, Manhattan and the Bronx, with Brooklyn exhibiting the highest concentration (43%). The gardens we surveyed regarding quality are remarkably similar to the whole New York City sample in terms of median area, completion year and land ownership.
Table 3B▪. Descriptive statistics on surveyed gardens in the Bronx.
|Garden Area (× 1,000 sq. ft.)|
| Mean|| 9.7|
| Median|| 6.1|
| % established between 1977 and 1980|| 8.2|
| % established between 1981 and 1990||36.1|
| % established between 1991 and 2000||55.8|
| % public||95.3|
| % private|| 4.7|
|Overall quality of garden|
| % gardens with acceptable overall qualitya||76.7|
| % gardens with acceptable overall qualityb||60.5|
|Detailed garden quality|
| % gardens with acceptable community access||67.4|
| % gardens with acceptable fencing/security||64.0|
| % gardens with acceptable cleanliness||55.8|
| % gardens with acceptable landscaping||93.0|
| % gardens with (non-seasonal) decorations||53.5|
| % gardens with social spaces||34.9|
|Number of gardens||86|
Table 4 compares the average 1980 characteristics of census tracts that include gardens to those that do not have a garden but are in a subborough area that does have at least one garden.40 It shows that gardens were generally located in distressed neighborhoods.41,42 As compared to the average census tract without gardens, tracts with gardens had much lower mean family incomes, much higher poverty rates (twice as high) and unemployment rates, lower educational attainment, much lower homeownership rates (2.5 times lower) and higher vacancy rates. The tracts with gardens housed much greater shares of Hispanic and Black residents than the average tract without gardens. Finally, other demographic statistics indicate that the garden neighborhoods had smaller shares of foreign-born population, a younger population and smaller shares of residents with stable neighborhood tenure.
Table 4▪. The 1980 characteristics of census tracts with and without gardens.
| ||Tracts With Gardens||Tracts Without Gardens But in SBA With Gardens|
|Mean family income||29,649||45,593|
|Mean poverty rate||36.7||18.8|
|Mean unemployment rate||13.2|| 8.1|
|Mean homeownership rate||12.7||31.5|
|Mean vacancy rate|| 5.8|| 2.9|
|Mean percentage of 25+yr old residents with some college education||16.8||25.2|
|Mean percentage black||49.8||25.1|
|Mean percentage Hispanic||31.8||18.8|
|Mean percentage foreign born||17.9||24.0|
|Mean percentage kids (age < 5 years)||10.0|| 7.8|
|Mean percentage age 5–17||23.2||18.4|
|Mean percentage age 18–64||57.1||59.9|
|Mean percentage old (age 65+)|| 9.7||13.9|
|Mean percentage of 5+yr old people who did not change address within last 5 years||57.3||61.0|
- Top of page
- Existing Literature
- Summary of Data
We find that community gardens have, on average, significant positive effects on surrounding property values, and that those effects are driven by the poorest of host neighborhoods (where a garden raises neighboring property values by as much as 9.4 percentage points within five years of the garden's opening). Those findings should help local governments make sounder decisions about whether (and how much) to invest in (or to encourage private investment in) community gardens and other green spaces. Such investments have a sizeable payoff for the surrounding community, and ultimately for the city itself, as it realizes additional property tax revenues from the neighborhood.
Our findings also will help local governments considering whether to use tax increment financing (TIF) to estimate the potential benefits of investments in urban parks and gardens. Our results show that such gardens can lead to increases in tax revenues of about half a million dollars per garden over a 20-year period. Finally, local governments may use our results to justify the imposition of impact fees to finance the provision of gardens or urban parks, by showing the benefits the developers' properties will receive as a result of proximity to such spaces.
Given that our study focuses exclusively on New York City, we are cautious in generalizing our findings and their implications to other settings, especially those outside of urban environments. That said, the great diversity of New York City's neighborhoods and gardens means that the estimated impacts reflect the impact of a variety of gardens in a range of neighborhoods, and that increases our confidence that similar results can be obtained in other cities. Moreover, preliminary results from our ongoing comparative analysis of the location of gardens and other open spaces suggest that garden impacts do not vary much with the amount of open space available in the larger community, which again bolsters our view that these findings may be relevant to less dense settings.
We would like to thank Caroline Bhalla, XuFeng Chen and Drew Schinzel for their hard work and good spirits in securing and processing the data necessary for the project; Geoff Davenport and the team of students he lead to conduct the garden quality survey (Amanda Garcia, Ilmi Granoff, Keilem Ng, Gila Jones, Josh Frankel, Tammy Kim, Dave Gunton, Margaret Barry, Ansley Samson, Uma Deshmukh, Avery Wentzel, Matthew Johnston, Peter Hyun, Ed Kim, Marissa Soto and Katie Renshaw); and Caroline Bhalla, Ingrid Gould Ellen, Solomon Greene, Rachel Meltzer, Sesha Pochiraju, Richard Revesz, Drew Schinzel, Amy Ellen Schwartz and participants in the NYU Law and Economics Workshop, the NYU Colloquium on the Law, Economics and Politics of Urban Affairs, the University of Michigan Law School Law and Economics Workshop, the University of Connecticut Storrs Lecture Series, the Georgia State University 2006 Law Review Symposium, the Furman Center Round Table on Community Gardens and the 2006 AREUEA Mid-Year Meeting for their helpful critiques of the study. The financial support of the Max and Filomen D'Agostino Research Fund and the Furman Center for Real Estate and Urban Policy is gratefully acknowledged.
The views expressed in this article are those of the authors and do not necessarily reflect those of the Office of the Comptroller of the Currency or the Department of the Treasury. Ioan Voicu contributed to this article while a research scholar at the Furman Center for Real Estate and Urban Policy, New York University.