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Ben Hoffman

30 April 2009

The Evolution of the Hedonic Pricing Model as a Means for

Studying the Impact of Commercial Aircraft Noise on the Value of

Residential Properties

Introduction:

During any given moment, civilian airports are providing

myriad services to a massive global populace. Flights alone buoy

a vast array of business and civilian travel purposes, whether it

be the countless people who use aircraft around the world for

business purposes, the millions of people who rely on civilian

aircraft for general travel and leisure purposes, or the

thousands of pilots and flight attendants who work aboard

passenger jets on a twenty-four-seven, year-round basis.

Furthermore, airport services deliver employment opportunities to

a variety of individuals, including runway crews, airport shop

and restaurant employees, aviation control workers,

transportation service workers, and thousands of TSA

(Transportation Security Administration) employees.

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Civilian airports also tend to provide an enhancement for

local economies due to the impact on commercial and industrial

services within close proximity to the airport. This is because

the airport functions both as a means of transporting goods as

well as a mode for people in business to travel wherever they so

choose. For example, Chicago’s O’Hare Airport, which employs over

50,000 people both directly and indirectly and brings in over $40

Billion in annual revenue.1 In addition, According to Jan K.

Brueckner, airports facilitate effortless face-to-face contact

with businesses in other cities, attracting new firms to the

airport’s metro area and stimulating employment at established

enterprises.2 In other words, airports are of vital importance to

passengers, airport employees, industry and commerce, and state

economies.

Nevertheless, despite these well-established facts and

statistics concerning the ways airports benefit society, it is

just as incontrovertible in the ways airports harm society. For

while airports undeniably provide boosts across a wide economic 1 “Top 10 Airports,” ArabianBusiness.com 16 December 2008, 17 April 2009 <http://www.arabianbusiness.com/541101-top-10-airports>.2 Jan J. Brueckner, “Airline Traffic and Urban Economic Development,” Urban Studies July 2003, 16 April 2009 <http://usj.sagepub.com/cgi/reprint/40/8/1455>.

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spectrum and offer convenience to both leisurely travelers and

businesspeople alike, they also have a couple harmful effects.

The first is obvious: air pollution. Perhaps less obvious, but

also a severely problematic side effect of airport operations is

the output of noise pollution. For people living within close

proximity to an airport, noise pollution is indeed a major

hindrance to their overall wellbeing. According to Wyle Acoustics

Group, aircraft noise is disturbing to people because of several

different factors:

First, the sound may include a combination of low frequency rumble andhigher-pitched whine from jet engines, the throbbing of helicopters, orthe steady, annoying buzz of smaller aircraft. Second, unlike highwaynoise, which is generally constant and may fade into the background,each aircraft overflight is likely to be recognized as a distinct event,calling attention to itself when it interrupts speech or some otheractivity (Ehrlich, Burn, Morrow, and Stefaniw, pg. 10). In this instance, noise pollution is an externality; it

represents a cost imposed on a party that is not a direct

participant in market activities (in this instance, the market

activity is the airport’s operations). This noise pollution can

result in an assortment of simple annoyances, in addition to more

complicated psychological and health-related effects. It is

believed that the severity of these impacts can determine whether

or not an individual will choose to live in a home in close

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proximity to an airport. Indeed, evidence suggests that

commercial airport noise drives down the price of residential

real estate within close proximity to that given airport, and

this is largely due to reduced consumer demand. The goal of the

paper is to present a chronological evolution of that evidence in

addition to the primary hedonic pricing research that goes along

with it.

Noise Measurement Systems & Sound’s Harmful Health Impacts

It is important to recognize a few of the primary sound

measurement scales used in the research throughout this paper.

This will help to illuminate some of the key findings and

statistics that are shown at a later point. While there are over

a dozen sound measurement scales that one can apply for a

research study focusing on the impact of airport noise on

residential property values, this paper will include just three

major sound measurements. These are NEF (Noise Exposure

Forecast), DNL (Day Night Average Sound Level), and NNI (Noise

and Number Index). Each of these unique noise measurement scales

represents something slightly different, and indeed, different

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authors and researchers on the subject of airport noise seem to

prefer certain methods over others.

For starters, Jon P. Nelson, in his seminal article, Airports

and Property Values, describes the NEF produced at a given point as

the “sum of noise levels produced by different aircraft flying

different flight paths...[and] when summed on an energy basis

over all aircraft types and flight paths, noise exposure is a

function of the average perceived noise level, time of day, and

number of operation” (Airports and Property Values, pgs. 41-42).

The majority of the research used in this paper use NEF as the

primary method for noise measurement. DNL, or Day Night Average

Sound Level, is defined by Molly Espey and Hilary Lopez as an

annual energy mean sound level. Like NEF, it carries a 10-decibel

penalty for the hours between 10 PM and 7 AM. 3

NNI, is used more sparingly in research studies concerning

aircraft noise. The NNI, or Noise and Number Index, is similar to

the NEF in that it accumulates both loudness and number of events

into a single, aggregated index. It differs from NEF only

3 M. Espey and H. Lopez, “The Impact of Airport Noise and Proximity on Residential Property Values” Growth and Change 2000, 27 April 2009 <http://web.ebscohost.com/ehost/pdf?vid=4&hid=5&sid=3d4d7d97-e359-42c2-aefa-f470ca3087a0%40SRCSM2>.

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slightly, and this is due to the manner in which it measures the

maximum perceived noise level for a given event. According to

Daniel P. McMillen, NNI is the most commonly used noise

measurement scale in the United Kingdom.4 Problematically, all

three of these sound measurement scales have an averaging effect,

meaning that a single takeoff at 3 AM may be overshadowed by

relative quiet throughout the remainder of the measured time

period.5

The simplest measure of sound examined in this paper is the

weighted decibel dB(A) or decibel with “a weighting.”6 Figure 1

below shows the various levels of dB(A) and their health effects,

among other things:

Fig. 1

7

4 Daniel P. McMillen, “Airport Extensions and Property Values: the Case of Chicago O’Hare Airport” Journal of Urban Economics 9 January 2004, 27 April 2009 <http://www.oharenoise.org/news_page_files/Property_Values_OHare.pdf>. 5 Ibid. 6 Randall Bell, “The Impact of Airport Noise on Residential Real Estate” The Appraisal Journal July 2001, 27 April 2009 <http://www.realestatedamages.com/Articles/Randy/AirportNoise.pdf>. 7 Ibid.

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Note in the table above that as people move further

from urbanized locations, their noise tolerance decreases

considerably. Notice also that nighttime tolerance is less than

daytime tolerance. This makes sense, since nighttime noise tends

to aggravate sleep cycles, while daytime noise is more tolerable.

The table also displays the impact of different noise levels both

on estimated community responses above an “acceptable” noise

level of 35 – 40 dB(A) and the effects on human activity and

health. Of significance is the fact that a jet flying over a home

within close proximity to an airport emits a sound level of

approximately 70 dB(A) for about 5 seconds.8 For clarity sake,

this is roughly the sound emitted from a typical vacuum cleaner

from a distance of 10 feet.9 According to the bottom of the

table, residents who live in homes near airports and have both a

constant and consistent exposure to dB(A) in this range may

experience negative physiological effects. It is therefore quite

clear as to why living within close proximity to an airport might

impose devaluations in a home’s price. 8 Ibid. 9 Mary Ellen Eagan, “How do we Describe Aircraft Noise?” Federal Interagency Committee on Aviation Noise July 2006, 18 April 2009 <http://www.fican.org/pdf/aircraft_noise.pdf>.

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Research Studies Using Hedonic Pricing

The majority of the research on the topic of airport noise

and its impact on residential property values unequivocally use

the hedonic pricing technique for assessing a home’s valuation

more than any other method. This is especially true for older

research on this topic. A hedonic pricing model, as described by

Jeffrey P. Cohen, is such that the price of a residential unit is

a function of its attributes. Accordingly, these particular

attributes are comprised of anything ranging from the unique

physical characteristics of the given residential unit to

location characteristics, neighborhood and/or community

attributes, local taxes, crime rate, public school system and/or

proximity to schools, and in this instance, the proximity to an

airport or exposure to relative measures of airport noise.

Moreover, hedonic demand theory states that the price an

individual will pay for the residential unit reflects the sum of

the all of these characteristics.10

Clearly, living within close proximity, which is the same as

saying living within the noisier contours, of an airport should 10 Jeffrey P. Cohen, “Spatial Hedonic Models of Airport Noise, Proximity, and Housing Prices” Journal of Regional Science Dec. 2008: 859-878.

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impose varying levels of irritation to the residents. This

irritation would then likely result in a downward shift in demand

for a residential unit within these noisier contours. As Ronald

W. Crowley points out, any change that occurs in land or property

prices is a function of either general or specific demand for

that land or property. Price changes of that land or property are

ultimately a direct reflection of factors that change the demand

for either an entire community, such as increasing incomes, or

factors that change the demand for a particular piece of land or

property, such as accessibility.11 Nevertheless, while it may

seem obvious that increased levels of irritation lead to reduced

demand for residential properties within close proximity to a

civilian airport, and in turn lower home prices, it is less clear

as to by how much these housing values change. That is the goal

of the hedonic pricing technique for this particular topic, to

quantify the level in which airport noise affects the value of a

residential property.

Nelson’s Airports and Property Values is not only a groundbreaking

article into the area of airport noise and its overall effect on

11 Ronald W. Crowley, “A Case Study of the Effects of an Airport on Land Values” Journal of Transport Economics and Policy May 1973: 144-152.

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residential property values, it is also the first major study in

this area to evaluate residential properties values using the

hedonic pricing technique. Nelson explains that the use of

hedonic pricing for this particular topic hinges on the idea that

there is a comparison between two residences that are nearly

identical with the exception that one is located within a closer

proximity to an airport, and is therefore exposed to a much

higher level of noise than the other residence. Accordingly, “if

two houses have different noise environments and are otherwise

identical, the difference in value is the expected discounted

present value of noise annoyance” (“Airports and Property

Values,” pg. 46). The choice of a residential location by the

consumer is the choice of the public good (quiet) consumption,

and is therefore the choice of externality (aircraft noise)

avoidance. As the level of Q, or environmental characteristics

within a given community, increases, so does the level at which a

resident is willing to keep it that way. Likewise, as seen in

Figure 2 below, the resident is paying more to keep noise levels

down in instances where they are exposed to greater levels of the

public good, quiet:

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Fig. 2

12

Nelson initially analyzes twelve previous studies on the

effect of airport noise on residential property values, all from

different airports across the world. The studies range from 1960

to 1976 and are mostly focused on single-family, owner-occupied

properties. Mean property values range from $15,200 to $27,600,

and sample sizes range from 35 to 1,270 observations, though the

typical final sample consists of between 90 and 400

observations.13 For the hedonic pricing model, factors taken into

12 Jon P. Nelson, “Airports and Property Values” Journal of Transport Economics and Policy January 1980: 37-50. 13 Ibid.

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consideration aside from airport noise exposure include measures

of house and/or lot size, neighborhood characteristics, and

public sector attributes such as property tax rates, public

school quality, and crime rates. In addition, these twelve

studies include a number of other factors relating to

accessibility such as distance in miles to airports, commercial

centers, highways, and schools. It is important to note that,

while each of these twelve previous studies are unique in regards

to the location and time period studied, the noise pollution

measurement used, the type of housing data collected, and the

model’s characteristics, they all have one thing in common: in

each study, the residential properties within a noisy contour of

a given airport has a net reduction in value when compared to a

similar home located inside a quieter contour.

Nelson tabulates the findings from the twelve studies and

translates all of the noise values for the samples into NDSI

values. NDSI, or noise depreciation sensitivity index, measures

the amount of housing depreciation per decibel. When averaged out

across the twelve studies, Nelson finds that the mean NDSI is

0.62%, which means that within noisier contours (where NEF is

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typically anywhere between 35 and 50, a level at which there is

considerable annoyance to the resident), a home’s value is

reduced by 0.62% in comparison to homes in quieter contours

(where NEF is typically between 15 and 25, a level at which there

little to no annoyance to the resident).14

After aggregating these values and reaching a single NDSI

figure, Nelson then takes a sample for six cities, whereby the

area around each individual airport is about two miles in radius

and contains NEF values from about 20 to 45. This sample keeps

other factors such as accessibility and public sector features

more consistent than in the twelve-study sample. In fact, this

sample excludes residential blocks of land that are near local

environmental features like parks or golf courses, certain

transport facilities other than airports such as freeways and

railroad tracks, and commercial developments such as shopping

centers. This reduces any biases that may come as a result of a

home being within close proximity to one of these features. The

pooled sample consists of 845 residential properties that have a

mean 1970 property value of $23,713 and a mean NEF level of 31.

14 Ibid.

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15.4% of the observations have an NEF that is greater than or

equal to 40. From this sample, Nelson finds that the average NDSI

is about .50 to .55% per decibel. In other words, an increase in

the noise level by one decibel leads to, on average, a .525%

decrease in the home’s value.

Many hedonic pricing studies following Airports and Property

Values reference its findings. One such study is Aircraft Noise and

Residential Property Values Adjacent to Manchester International Airport, a hedonic

pricing study performed a decade following Nelson’s pioneering

work. This study, conducted by G. Pennington, N. Topham, and R.

Ward, analyzes 3,472 observations around the UK’s Manchester

International Airport during the time period of April 1985 to

March 1986. Unlike Nelson’s study, this one uses the Noise and

Number Index (NNI) as opposed to NEF; however, the NNI is set

across contours very similar in nature to NEF contours in the

area surrounding Manchester International Airport. An NNI below

40 indicates a low level of irritation, while one between 40 and

45 indicates a moderate level of irritation. An NNI of 45 and

above indicates a severe level of annoyance to the resident. Out

of the 3,472 homes in the study, 205 fall within the contours of

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an NNI level of 40 or above. According to the study, homes within

the three postal code areas that have the highest level of noise

exposure command, on average, prices 3.7% less than comparable

homes below the 40 NNI level, ceteris paribus. Furthermore, a

property in the area that has the absolute worst noise exposure

is approximately 6.09% less valuable than comparable homes below

the 40 NNI level, ceteris paribus.15

Nevertheless, when placing additional variables into the

regression, the reduction in home valuations decreases. In fact,

when the regression for the value of homes surrounding Manchester

International Airport is not held constant for airport noise, and

takes into account additional factors such as the structural

qualities of the home and the types of neighborhood (delineated

as an ACORN – A Classification of Residential Neighborhoods –

classified by housing characteristics and socioeconomic

characteristics of the neighborhood residents), there is only

a .15% reduction in home prices within the 40+ NNI contour.

However, this is dubious altogether since each ACORN is highly

15 G. Pennington, N. Topham, and R. Ward, “Aircraft Noise and Residential Property Values Adjacent to Manchester International Airport” Journal of Transport Economics and Policy January 1990, 27 April 2009 < http://www.bath.ac.uk/e-journals/jtep/pdf/Volume_XX1V_No_1_49-59.pdf>.

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unique in terms of the classifications of the housing and

resident characteristics, and thus attempting to compare a home

within a noisier contour with one outside of it may yield

misleading results.

Terrence J. Levesque attempts to mitigate such misleading

results in his hedonic pricing study, Modelling the Effects of Airport

Noise on Residential Housing Markets. In this paper, which also refers to

Nelson’s 1980 study, Levesque not only explains that airport

noise negatively impacts home values, but also extensively

elaborates on the idea that the NEF is merely a cumulative

measurement, and therefore fails to reveal anything directly

about the individual effects of the number of events and their

respective loudness. Hence, noise management strategies are not

necessarily as effective as they could be otherwise.16 Since

noise contour maps merely depict a cumulative NEF level, there is

no information given on the number of events and their respective

16 Terrence J. Levesque, “Modelling the Effects of Airport Noise on

Residential Housing Markets” Journal of Transport Economics and Policy May

1994, 27 April 2009

<http://www.bath.ac.uk/e-journals/jtep/pdf/Volume_XXV111_No_2_199-210.pdf>.

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loudness. Levesque’s research marks the first to attempt a

decomposition of these effects, and it does so by focusing on

EPNL, or effective perceived noise level, a measurement that is

actually a portion of the NEF’s formula. An EPNL above 75

indicates the frequency of a loud event, and an EPNL with a

higher standard deviation is one that has greater variation in

the level of noise incidents, and hence is more distracting to

residents. Ultimately, Levesque theorizes that exposure to either

a higher EPNL or one with higher variance will lead to lower

housing prices.

The study analyzes 1,635 properties, mostly detached houses,

within the area surrounding the Winnipeg International Airport

from January 1985 to December 1986. Interestingly, the findings

are not as Levesque had initially predicted. While houses exposed

to an EPNL of 75 or above sell at a discount compared to those

exposed to lower EPNL levels, houses sold at a premium when

variation in the number of individual event levels increases and

actually compensated for both higher EPNL levels and high average

loudness.17 Furthermore, while an increase in EPNL by one decibel

17 Ibid.

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between the range of 78-92 EPNL reduces home values by 1.3%

according to the NDSI, a one-time event within this same EPNL

range reduce only marginally. For instance, increasing the number

of takeoffs or landings from 80 to 400 would only reduce home

values by a staggeringly low .1%. Therefore, the number of

flights and the variability in single events are both less

significant than the overall loudness. Needless to say,

Levesque’s pioneering study on the decomposition of noise’s

effects on home values adds an extra dimension over similar

studies which use NEF.

Density of Residential Land Use and the Impact of Airport Noise, conducted

by Uyeno, Hamilton, and Biggs in 1993, also adds an extra

dimension over previous studies. This study, unlike Nelson’s,

does not focus exclusively on detached houses, but also on

multiple-unit residential condominiums. According to the authors,

it was previously thought that airport noise may affect multi-

unit condominiums less than detached houses for a few reasons,

the first of which is that they are supposedly better

soundproofed due to their higher density arrangements. Two other

conjectures were that condominiums generally have less land area

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per occupant, and thus allow fewer outdoor activities that could

potentially be disrupted by airport noise, and that the increased

propensity for mobility among condominium occupants meant a lower

discounted present level of noise annoyance.18 Yet, since

residential condominium units are, on average, less expensive

than detached houses, it is possible the percentage discount for

noise would actually be higher.

This study, which focuses on the area around the Vancouver

International Airport, includes a sample of 700 detached houses

and 919 condominium units in the cities of Vancouver and

Richmond. Within the hedonic price model, two public sector

characteristics are taken into consideration, and these are

accessibility to both public transport and public schooling.

Unlike Nelson’s sampling of the six cities, this study does not

screen for properties near local environmental features, major

transport facilities apart from the airport itself, or commercial

developments, and therefore, inaccuracies within the data may

result. The findings are nonetheless significant: for detached

18 D. Uyeno, S.W. Hamilton, and A.J.G. Biggs, “Density of Residential Land Useand the Impact of Airport Noise” Journal of Transport Economics and Policy January 1993, 27 April 2009 <http://www.bath.ac.uk/e-journals/jtep/pdf/Volume_XXV11_No_1_3-18.pdf>.

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houses with an NEF level of 25 or above, the regression shows

that a one-unit increase in the noise level results in a decrease

of approximately 0.65 percent in the property price.19

Condominiums with an NEF level of 25 or above, on the other hand,

decrease in value by approximately 0.90 percent given a one-unit

increase in the noise level. In addition, the higher R squared

value in comparison to detached houses indicates that the

likelihood of variability in the condominium regression is less

than that of detached houses, and is therefore likely more

accurate. This contrasts with previous views that detached houses

are affected to a greater degree than condominium units.

Interestingly, in Feitelson, et al., the authors find that

renters are actually less sensitive to noise levels than

homeowners, as seen in figure 3 on the following page:

19 Ibid.

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Fig. 3

20

Like Uyeno, et al and Levesque, Molly Espey and Hilary Lopez

performed what was, at the time, innovative research into a

burgeoning field. Like those studies before it, The Impact of Airport 20 E.I. Feitelson, R.E. Hurd, and R.R. Mudge, “The Impact of Airport Noise on Willingness to Pay for Residences” Transportation Research Apr. 1996: 1-13.

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Noise and Proximity on Residential Property Values looks into how airport

noise affects the value of a home. Unlike those studies before

it, it puts a monetary figure on the amount of value that is lost

to an increase in noise levels. Focusing on homes around the

Reno-Tahoe International Airport, Espey and Lopez use a sample of

1,417 homes from the time period of 1991-1995. The data focuses

on variables including home quality and the year it was built,

home size in square feet, garage type, number of bedrooms and/or

bathrooms in the home, and distance from the airport.

This paper marks the first in this series of hedonic pricing

research that uses DNL, possibly because it correlates with

degrees of human response such as annoyance, communication

interference, and hearing loss. The maximum permissible yearly

outdoor DNL is 80, at which point long-term (yet temporary)

hearing loss may occur.21 A DNL of over 65 is deemed as

incompatible for residential housing areas by the FAA, but many

people still live in such areas. In this study, 30 homes fall

within the 70-75 DNL level, and 169 homes fall within the 65 DNL

contour. The findings indicate that homes within the 65 DNL

21 M. Espey and H. Lopez, “The Impact of Airport Noise and Proximity on Residential Property Values”

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contour cost, on average, $2400 less than homes in the 60 DNL

contour. Furthermore, the mean elasticity of price with respect

to distance is 0.55, which signifies that a home one mile away

from the airport is valued $5500 less than a home two miles away

from the airport.

“Hybrid” Hedonic Pricing Studies

Twenty-four years after writing his seminal paper, Airports

and Property Values, Nelson essentially builds on where he left off.

Only this time, he actually criticizes hedonic pricing for being

unable to produce a single value for the effects of airport noise

on property values given the differences in statistical methods,

samples, time periods, and urban locations.22 Nelson then

explains how a meta-analysis variation of hedonic pricing can

effectively display a singular value since it “requires a common

effect size measure of damages due to airport noise” (“Meta-

Analysis,” pgs. 6-7). In other words, Nelson is saying that to

get a singular value to express the effect of airport noise on

property values across different samples from various studies,

meta-analysis actually adjusts the measurements in each study to 22 Jon P. Nelson, “Meta-Analysis of Airport Noise and Hedonic Property Values;Problems and Prospects” Journal of Transport Economics and Policy July 2003: 1-27.

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a common metric, and in this case, it’s NDSI. Hence, while each

individual study may use different variables and noise

measurement schemes, Nelson aggregates these into a singular NDSI

value. By using a meta-analysis, one can isolate the effect that

airport noise has on home values and reduce the benefit transfer

problem which results from attempting to make an estimate for one

study location based solely off the results from another study

location.

The three hallmarks of a meta-analysis study, according to

Nelson, are completeness, comparability, and transparency. The

study is unquestionably complete, providing 33 NDSI estimates

from 23 different major civilian airports both in the Unites

States and Canada. The variable used in the regression are

airport, state and country, sample time period, sample size,

census data or individual sales data, and mean property value (in

2000 US dollars). The mean NDSI, or decrease in home value given

an one-unit increase in dB(A) is 0.75. When conducted again using

a fixed-effects regression analysis, Nelson dropped two of the

NDSI estimates and concluded that NDSI for US property values was

approximately .59% per dB(A), while Canadian markets had an NDSI

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of approximately .85% per dB(A), a higher number due to legal

rules, economic differences, or perhaps climate conditions.23 In

other words, in the United States, a $200,000 property located in

an area where the sound level is 75 dB(A) would sell for

approximately $22,000 less than in a comparable area where the

sound level is 55 dB(A).

The final and most recent hedonic pricing study on the topic

of airport noise and its overall effect on residential property

values is that by Jeffrey P. Cohen. The paper, titled Spatial

Hedonic Models of Airport Noise, Proximity, and Housing Prices, attempts to

resolve the question as to whether spatial effects such as

autocorrelation exist in regression data. Spatial autocorrelation

exists when the price of a particular home may depend on the

prices and characteristics of a nearby homes, especially those

which are highly comparable.24 Cohen states that he expects a

higher average sale price results in a higher sales price of a

nearby home. Ultimately, this creates a feedback loop, since

higher levels of airport noise will lead to a lower sales price

for a particular home, which in turn leads to lower sales prices 23 Ibid. 24 Jeffrey P. Cohen, “Spatial Hedonic Models of Airport Noise, Proximity, and Housing Prices”

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of other homes, and this creates even more downward pressure on

the price of the original home. Fortunately, Cohen’s regression

analysis allows isolation for each individual variable in

question. Hence, while it is indeed the case that autocorrelation

exists, it is only true when all other variables are being held

constant. Cohen uses this same exact isolation procedure to

examine the effect of airport noise on residential property

values.

The study focuses on 343 homes surrounding Atlanta’s

Hartsfield-Jackson International Airport. Approximately 29

percent of the homes fall within the 65 DNL contour, and about 16

percent of these homes fall within the 70 DNL zone. Variables

looked at include housing characteristics such as number of

bedrooms and stories, in addition to distance in miles from the

airport, lot size and which municipality the home is in. The

regression results show that, while the variable for 65 DNL is

statistically insignificant, it is still negative. The variable

for 70 DNL, on the other hand, is both negative and statistically

significant. In fact, homes within the 70 DNL zone sold for a

staggering 20.8 percent less than comparable homes in areas below

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the 65 DNL level, ceteris paribus. Therefore, the noise discount is

20.8 percent.25 Furthermore, through an evaluation of a marginal

change from a 70 DNL zone to a 65 DNL zone, Cohen calculated that

an individual be willing to pay over $33,000 more to live in the

65 DNL zone as opposed to the 70 DNL zone. This research is

significant, because it not only quantifies how airport noise

affects home values and how much an individual is willing to pay

for a home within a certain noise contour, it also isolates the

different variables to see how each individually impacts the

valuation of a home.

Analysis and Conclusions:

Despite the many developments in research on this subject,

a couple of looming question remain. The first of which is how

positive attributes of living within close proximity to an

airport may affect these studies. For instance, close proximity

to an airport is an attractive detail for potential business or

leisure travelers.26 In this case, a shorter commute to a

civilian airport translates to a decrease in real travel costs

and a reduction in the opportunity costs of time and effort.

25 Ibid. 26 Ibid.

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Additionally, since civilian airports provide myriad employment

opportunities, houses with greater accessibility to airports may

have higher prices than those with less accessibility. As Nelson

explains, “if an airport were nonpolluting, land rentals would be

expected to decline with increased distance from the airport,

reflecting capitalized values of increased commuting costs”

(“Airports and Property Values,” pg. 41). Cohen also notes that

access to airport employment and services are capitalized into a

home’s value, and that failing to do so may lead to biased

estimates on the impact of noise.27 In fact, he finds that a 1

percent increase in the distance (in miles) from the airport

leads to a 0.15 percent decrease in the sales price of that a

home, ceteris paribus. Yet, when compared to the 20.8 percent

decrease in home values for homes within the 75 DNL zone, and the

fact that individuals would be willing to pay over $33,000 to

move from the 75 DNL zone to the 65 DNL zone, 0.15 percent seems

quite miniscule. Either way, this is one shortcoming of hedonic

pricing and it is why newer research tends to use methods such as

spatial hedonic pricing or meta-analysis.

27 Jefrey P. Cohen, “Spatial Hedonic Models of Airport Noise, Proximity, and Housing Prices”

Hoffman 29

The second pervasive question regarding the effect that

airport noise has on residential property values revolves around

possible airport expansions and their impact on property tax

revenues. After all, if airport noise lowers the value of homes,

then it is imperative to determine how it most likely lowers

their respective property taxes, as well.28 This is an especially

pertinent consideration when bearing in mind the possibility of

an airport expansion. Hence, these research studies are

incredibly important, because it provides governments with a

basic idea of the impact decreasing home values might have on

property tax revenues. In addition, it provides an incentive to

increase noise abatement regulations to minimize any possible

decreases in tax revenue.29

Aside from issues regarding benefits and/or questions

concerning property taxes, there is also the problem of deciding

how best to solve the problem of airport noise. One

consideration, as posed by Feitelson, et al. in The Impact of Airport

Noise on Willingness to Pay for Residences is to compensate the residents

for the total value of damages accrued to them. These damages 28 M. Espey and H. Lopez, “The Impact of Airport Noise and Proximity on Residential Property Values”29 Ibid.

Hoffman 30

include the property depreciation, the loss of utility by

residents who remain in their homes, and the relocation costs and

loss of place-specific utility by residents that move following

an increase in noise exposure.30 Figure 4 below shows a MWTP

(marginal willingness to pay) curve:

Fig. 4

31

30 E.I. Feitelson, R.E. Hurd, and R.R. Mudge, “The Impact of Airport Noise on Willingness to Pay for Residences” 31 Ibid.

Hoffman 31

In the graph above, rent (indicated by R0 at starting point

A) decreases as noise increases due to the residential unit

losing value. To compensate for an increase in the noise level

from N0 to N1, the airport will pay the household dW, which is

actually greater than the loss in rent, designated as dR. This is

to compensate not only for the decreased value in rent, but also

for the loss of utility to the resident for remaining in his or

her residential unit. In this instance, the household bid curve

represents a MWTP curve in that the resident is initially

“paying” for an increasing level of noise while remaining in the

same residence. The main problem with compensation, however, is

“getting people to reveal their relative preferences for

different levels of nuisance” (Whitbread, pg. 203).

Other methods for solving the problem of airport noise

include soundproofing and relocation. Soundproofing is generally

less costly than moving, as it is the minimum action a household

can take aside from doing nothing at all.32 Nevertheless, it only

partially mitigates airport noise, as the deleterious effects of

increased noise exposure outweighs any reductions in noise 32 Michael Whitbread, “Measuring the Costs of Noise Nuisance from Aircraft” Journal of Transport Economics and Policy May 1978, 2 May 2009 <http://www.bath.ac.uk/e-journals/jtep/pdf/Volume_X11_No_2_202-208.pdf>.

Hoffman 32

exposure which may result due to soundproofing a home. Obviously,

a household’s willingness to dole out money for soundproofing

measures depends largely on how long that household plans to

remain at the residence in question. Oftentimes, an airline

company, a local government, or the airport itself will provide

grants for soundproofing materials and installation including

foam insulation and soundproof windows.33 According to Cohen,

Atlanta’s Hartsfield-Jackson International Airport has paid

nearly $175 million in sound insulation materials and insulation

costs since the 1980’s.34 Relocation, on the other hand, is a

more costly method of dealing with airport noise. It involves

acquiring the residence from the homeowners and finding a

relocation for the residents in an area that is quieter. This can

be quite expensive; since the 1980’s, Atlanta’s Hartsfield-

Jackson International Airport has paid over $170 for the

relocation of residents, including the acquisition of over 2,700

units.

Besides the obvious solution of quieter jet engines, a

solution which is currently in a costly research and development 33 Ibid. 34 Jeffrey P. Cohen, “Spatial Hedonic Models of Airport Noise, Proximity, and Housing Prices”

Hoffman 33

process, there is also the option of having airport authorities

landing fees for airlines. This essentially translates into a

Pigouvian tax, whereby airlines are levied based on the amount of

noise they emit. This allows airlines to alter their flight paths

as well as the airports that they travel to on a regular basis.

Doing so equalizes the airline’s private marginal benefits with

the social marginal costs, as opposed to equalizing the airline’s

private marginal benefits with their own private marginal costs.

It is evident that the topic of airport noise on residential

property values has evolved considerably in the context of a

hedonic pricing model. Beginning with Nelson’s Airports and Property

Values and finishing with Cohen’s paper, each author looked at

this topic from a slightly different angle in an effort to prove

something original. While it is obvious from looking at the data

that airport noise has a negative effect on the value of homes

within either a closer proximity or a higher noise contour, it is

now more clear than ever as to how airport noise impacts certain

home types in comparison to others.

For instance, in Aircraft Noise and Residential Property Values, Alan

Collins and Alec Evans find that detached homes are much more

Hoffman 34

sensitive to airport noise than either semi-detached or terraced

homes, despite the fact that airport noise negatively impacts the

respective values of each of these.35 Likewise, in Uyeno, et al.,

condominiums are more sensitive than detached homes in terms of

the impact that airport noise has on home prices. In addition,

Cohen found that airport noise tends to affect Canadian

properties more than those within the United States, while

Levesque noted that homes exposed to noise levels with a high

degree of variability are not impacted to nearly the same extent

as those homes exposed to constant loud noise. Altogether, the

sum of this research leads to the convincing conclusion that

airport noise has a negative impact on residential property

values. The future of this research will focus on key policy

ideas revolving around property tax issues, airport expansions,

and the several different modes by which certain parties can

mitigate airport noise pollution.

Works Cited

Bell, Randall. "The Impact of Airport Noise on Residential Real

Estate." The Appraisal Journal (2001): 312-21. Bell Anderson

35 A. Collins and A. Evans, “Airport Noise and Residential Property Values” Journal of Transport Economics and Policy May 1994: 175-196.

Hoffman 35

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Cohen, Jeffrey P. "Hedonic Models of Airport Noise, Proximity,

and Housing Prices." Journal of Regional Science 48 (2008):

859-78.

Collins, Alan, and Alec Evans. "Aircraft Noise and Residential

Property Values." Journal of Transport Economics and Policy

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(1973): 144-52.

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Espey, Molly, and Hilary Lopez. "The Impact of Airport Noise and

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Hoffman 37

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Hoffman 39