# RECORD 90decb41b454a38dee63486b408022b766c2dc06
# TITLE: Effects of New Grocery Store Development on Inner-City Neighborhood Residential Prices
# YEAR: 2017.0  VENUE: Agricultural and Resource Economics Review  DOI: 10.1017/age.2016.29
# AUTHORS: Belkis Cerrato Caceres; J. Geoghegan
# PAGES: 16  CANDIDATE TABLE PAGES (1-based): [9, 10, 11, 12]
# ABSTRACT: A difference-in-differences approach is used to measure the impact of new inner-city grocery store developments on residential housing values in Worcester, Massachusetts. Using geocoded housing sales from 1988–2011, we develop a hedonic model, exploiting temporal and spatial discontinuities, to identify the effect of 12 new grocery stores on neighborhood housing prices. Results suggest these new stores were associated with an increase in sale prices of nearby homes, and these results could help inform current policies related to urban food deserts, in that new grocery stores have the potential to improve neighborhood wealth as well as health.


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Effects of New Grocery Store
Development on Inner-City
Neighborhood Residential Prices
Belkis Cerrato Caceres and Jacqueline Geoghegan
A difference-in-differences approach is used to measure the impact of new inner-
city grocery store developments on residential housing values in Worcester,
Massachusetts. Using geocoded housing sales from 1988–2011, we develop a
hedonic model, exploiting temporal and spatial discontinuities, to identify the
effect of 12 new grocery stores on neighborhood housing prices. Results suggest
these new stores were associated with an increase in sale prices of nearby
homes, and these results could help inform current policies related to urban food
deserts, in that new grocery stores have the potential to improve neighborhood
wealth as well as health.
Key words: difference-in-differences, grocery stores, hedonic models
The burgeoning obesity epidemic in the United States (Nguyen and El-Serag
2010, Flegal et al. 2012), with large disparities among different population
groups along ethnicity and socioeconomic lines (Wang and Beydoun 2007),
has highlighted the need for access to affordable healthy food throughout the
United States. The presence of strong residential segregation in housing
markets among these socioeconomic groups may affect the local food
environment, which potentially can be a factor in leading to these negative
health outcomes for disadvantaged groups. Geographic areas lacking in
affordable healthy food have been termed food deserts, and a growing
research literature from many academic disciplines has demonstrated that
these food deserts are more likely to occur in poorer neighborhoods (Powell
et al. 2007, Chen et al. 2010, Walker, Keane, and Burke 2010). These
geographic regions are more likely to have more convenience stores and fast
food outlets than grocery stores, resulting in less healthy food consumption
and worse health outcomes for their residents (Brown et al. 2008, Galvez
Belkis Cerrato Caceres is an Assistant Professor of Economics at Edgewood College. Jacqueline
Geoghegan is a Professor of Economics at Clark University. Correspondence: Belkis Cerrato
Caceres ▪Department of Social Science, Edgewood College ▪1000 Edgewood College Dr ▪Madison,
WI 53711 ▪Phone 508.793.7709 ▪Email bcerrato@edgewood.edu
The authors would like to thank John Brown, Wayne Gray and Wang Jin for advice and
suggestions, as well as two anonymous reviewers for very helpful comments.
In addition,
research support for this project from the Mosakowski Institute for Public Enterprise at Clark
University is gratefully acknowledged.
Agricultural and Resource Economics Review 46/1 (April 2017) 87–102
© The Author(s) 2017. This is an Open Access article, distributed under the terms of the Creative
Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits
unrestricted re-use, distribution, and reproduction in any medium, provided the original work is
properly cited.
https://doi.org/10.1017/age.2016.29 Published online by Cambridge University Press


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post-opening grocery store indicator are shown in Table 2. Column 1 includes
all the properties in the sample, column 2 excludes properties that had a sales
price in the top 1 percent of sales price observations, and column 3 excludes
properties that had a price in the top 5 percent of sales price observations.
Standard errors were clustered at the blockgroup level. The estimates of the
coefficients of the spatial variables suggest that properties located within
each of the two spatial buffers were associated with lower prices compared
to properties located more than 800 meters away. Each of the indicator
variables D0399:9
ij
and D400800
ij
has a negative and statistically significant
coefficient indicating that properties located within 800 meters from a
grocery store site sold at a price between 7 and 8 percent below the value of
comparable properties located more than 800 meters away from the store.
Table 1. Summary Statistics of Housing Data
All Residential
Properties
0–399.9
Meters
400–800
Meters
800 Meters
or More
Price 1988–2011
(Average)2
$175,759.3
$173,661.7
$171,136.9
$177,671
(76,329.54)
(77234.4)
(75530.63)
(76461.58)
lot size (sq ft)
1542.93
1166.54
1373.8
1641.18
(5893.29)
(3127.04)
(4267.75)
(6570.30)
Bathrooms
1.86
2.05
1.92
1.82
(0.87)
(0.94)
(0.95)
(0.83)
Bedrooms
4.05
4.84
4.58
3.78
(2.25)
(2.51)
(2.62)
(2.01)
Age
65.49
82.01
75.83
60.13
(37.05)
(34.31)
(36.84)
(36.11)
Annual median
household income
(2010 inflation-
adjusted $)
$58,196.42
$44,492.96
$49,115.13
$62,020.17
(25,373.01)
(15,694.31)
(18,382.09)
(26,702.95)
% of households that
own 1 or more cars
87.74
87.75
86.77
88.03
(12.28)
(9.61)
(10.9)
(12.83)
% White
70.71
56.47
63.97
73.87
(21.31)
(24.54)
(23.17)
(19.43)
Population density
per square mile
6186.43
7650.12
7512.05
5671.35
(4825.95)
(5236.47)
(5324.29)
(4525.45)
# Property Sales
33949
2211
8576
23162
2 This average excluded properties in the sample that had a sales price in the top 1 percent.
Cerrato Caceres and Geoghegan
Effects of New Grocery Store Development 95
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Overall, this suggests that grocery stores are located in lower priced
neighborhoods. The first row of Table 1 shows the average sales price of all
the properties sold between 1988 and 2011. Average sales price for
properties within the 800-meter buffers were below the city’s average sales
price and below the prices of properties located more than 800 meters away
from a grocery store. This could reflect the differences in housing structure
and neighborhood characteristics. Houses within the 800-meter buffers are
on average older and have a smaller lot size, and these neighborhoods are
more racially diverse and densely populated.
In terms of the impact of a new grocery store development on real estate
prices, the estimated coefficient of the interaction term Dd
ijPost iy identifies
the effect on sales price of a house located within a specific distance band
from the grocery store. The estimated coefficients of D0399:9
ij
Post iy and
D400800
ij
Post iy have positive magnitudes. In addition, the coefficient is larger
for properties located closest to the grocery store. For example, as shown in
columns 1–3 of Table 2, properties located within 399.9 meters from a
Table 2. Impact of Grocery Store Openings in Housing Prices
Sample
All
Observations
Excludes Properties
with Top 1% Prices
Excludes Properties
with Top 5% Prices
(1)
(2)
(3)
Variables
logprice
logprice
logprice
Grocery store distance
0–399.9 meters
0.076***
0.073***
0.072***
(0.028)
(0.027)
(0.027)
Grocery store distance
400–800 meters
0.081***
0.080***
0.076***
(0.018)
(0.018)
(0.017)
Grocery store distance
0–399.9 m*Post
Grocery store
0.073***
0.070***
0.071***
(0.024)
(0.024)
(0.024)
Grocery store distance
400–800 m*Post
Grocery store
0.039**
0.039**
0.037**
(0.019)
(0.019)
(0.018)
Housing Characteristics
Yes
Yes
Yes
Neighborhood
Characteristics
Yes
Yes
Yes
Clustered SE
Yes
Yes
Yes
N
33,849
33,583
32,619
R-squared
0.589
0.599
0.584
Robust standard errors in parentheses
*** p < 0.01, ** p < 0.05, þ p < 0.1
Note: All regressions control for year fixed effects
Agricultural and Resource Economics Review
96 April 2017
https://doi.org/10.1017/age.2016.29 Published online by Cambridge University Press


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grocery store experienced a 7 percent increase in price after the store opened,
while properties located within 400–800 meters from the grocery store
experienced approximately a 4 percent increase in value. As a comparison,
Pope and Pope (2015) found that a new Walmart store increases housing
prices between 2 and 3 percent for houses located within 0.5 miles of the
Table 3. Impact of Grocery Store Openings in Housing Prices for More
Disaggregated Buffers
Sample
All
Observations
Excludes Properties
with Top 1% Prices
Excludes Properties
with Top 5% Prices
(1)
(2)
(3)
Variables
logprice
logprice
logprice
Grocery store distance
0–199.9 meters
0.10366
0.10062
0.09851
(0.06349)
(0.06409)
(0.06452)
Grocery store distance
200–399.9 meters
0.07078**
0.06747**
0.06674**
(0.02840)
(0.02844)
(0.02763)
Grocery store distance
400–599.9 meters
0.0749***
0.0705***
0.0713***
(0.02149)
(0.02099)
(0.02115)
Grocery store distance
600–800 meters
0.0845***
0.0845***
0.0788***
(0.02107)
(0.02056)
(0.02026)
Grocery store distance
0–199.9 m*Post
Grocery store
0.09786þ
0.09685
0.09464
(0.05840)
(0.05965)
(0.05956)
Grocery store distance
200–399.9 m*Post
Grocery store
0.06805**
0.06516**
0.06703**
(0.02634)
(0.02617)
(0.02598)
Grocery store distance
400–599.9 m*Post
Grocery store
0.01695
0.01561
0.01632
(0.02448)
(0.02377)
(0.02409)
Grocery store distance
600–800 m*Post
Grocery store
0.05274**
0.05241**
0.04979**
(0.02271)
(0.02231)
(0.02200)
Housing Characteristics
Yes
Yes
Yes
Neighborhood
Characteristics
Yes
Yes
Yes
Clustered SE
Yes
Yes
Yes
N
33,849
33,583
32,619
R-squared
0.58925
0.59944
0.58413
Robust standard errors in parentheses
*** p < 0.01, ** p < 0.05, þ p < 0.1
Note: All regressions control for year fixed effects
Cerrato Caceres and Geoghegan
Effects of New Grocery Store Development 97
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store, while similar positive results for a new Walmart within a two-mile radius
of a residential prices can be found in Johnson et al. (2015).
The estimated coefficients on the control variables have the expected signs
and are statistically significant: homes with more bedrooms and bathrooms
sell at a higher price, as do properties with larger lots. Homes in
neighborhoods with lower income, lower education levels and higher
percentages of minorities sell at lower prices.
In order to test the robustness of these results, we further disaggregated the
800-meter distance into four mutually exclusive rings (0–199.9 meters, 200–
399.9 meters, 400–599.9 meters, and 600–800 meters) centered around each
of the grocery stores. One of our hypotheses was that a new grocery store
would have a nonmonotonic effect on neighboring housing prices, where
properties in close proximity to a grocery store experienced a negative impact,
and properties located further away experienced a positive distance-decaying
effect. However, as shown in Table 3, this relation was not observed across the
coefficients of the interaction terms. In fact, the coefficients of the interaction
terms D0199:9
ij
Post iy and D400599:9
ij
Post iy are not statistically significant.
Table 4. Falsification Tests of Grocery Store Opening Year and Impact on
Housing Prices
Number of Years Grocery Store Opening
Date is Shifted
3 years
earlier
4 years
earlier
5 years
earlier
(1)
(2)
(3)
Variables
logprice
logprice
Logprice
Grocery store distance 0–399.9 meters
0.124***
0.121**
0.111**
(0.030)
(0.034)
(0.035)
Grocery store distance 400–800 meters
0.097***
0.102***
0.103***
(0.019)
(0.020)
(0.021)
Grocery store distance 0–399.9 m*Post
Grocery store
0.044
0.036
0.020
(0.031)
(0.037)
(0.040)
Grocery store distance 400–800 m*Post
Grocery store
0.018
0.024
0.024
(0.016)
(0.017)
(0.018)
Housing Characteristics
Yes
Yes
Yes
Neighborhood Characteristics
Yes
Yes
Yes
Clustered SE
Yes
Yes
Yes
R-squared
0.592
0.592
0.592
N
26,724
26,724
26,724
Robust standard errors in parentheses
*** p < 0.01, ** p < 0.05, þ p < 0.1
Note: All regressions control for year fixed effects
Agricultural and Resource Economics Review
98 April 2017
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Finally, falsification tests were conducted to identify whether the observed
increase in housing prices was due to a grocery store opening a short
distance from the property. One of the concerns is that there may be
confounding factors affecting the price of houses close to the grocery store’s
site before its announcement and opening date. Hence, similar to Pope and
Pope (2015), we constructed false opening dates for the grocery stores and
shifted the opening years of grocery stores three, four, and five years prior to
the actual opening years3. If the grocery store had an impact on property
values, we should observe a positive effect when the grocery store is
announced and opened, and not in prior years. The results of these tests are
shown in Table 4. None of the coefficients of the interaction terms provide
evidence of property values near a grocery store’s site increasing in value
three, four, and five years before the store’s actual opening year. Thus, these
results suggest that the opening of a new grocery store does have a positive
effect on nearby residential property values.
Conclusions
In this study, we investigated the effect of the opening of a new grocery store on
housing prices in Worcester, Massachusetts for the period 1988–2011. Using
geocoded housing sales data of single-family homes, different mutually
exclusive neighborhoods were created around each new store opening. A
hedonic model with a difference-in-differences econometric specification was
developed to test the impact of the opening of each new grocery stores on its
neighboring property values. Our results indicate that properties located
between
400–800 meters
and 0–399.9 meters
from
a
grocery store
experienced between 4 and 7 percent increase, respectively, in the level of
prices relative to similar properties located across the city and more than
800 meters away from a grocery store.
Our results also suggest that grocery stores in Worcester were in lower
property-valued neighborhoods. In particular, our results suggest that prices
of properties located within 800 meters from a grocery store were between 7
and 8 percent below the value of properties located more than 800 meters
away. Although our analysis does not incorporate an empirical analysis
specific to food desert areas due to data limitations, many of the grocery
stores were established in the city’s low-income census blockgroups. In fact,
most grocery stores were in neighborhoods where household income was
below the city’s average median income and where minorities made up a
3 Pope and Pope (2015) found that the average Walmart in their sample took about 1.5 years to
be built after its construction and opening were announced. As our dataset includes only the year
in which the grocery store opened, we shifted the grocery store opening by three, four, and five
years. This allowed us to reduce possible changes in housing prices due to announcement
rather than the opening of the grocery store.
Cerrato Caceres and Geoghegan
Effects of New Grocery Store Development 99
https://doi.org/10.1017/age.2016.29 Published online by Cambridge University Press