A sound investment? Traffic noise mitigation and property values

ABSTRACT

Traffic noise is a widespread problem that adversely affects health and well-being. A key policy question is how the benefit of noise mitigation compares with the cost. This study estimates the benefits of noise mitigation by its capitalization into property values. Using a dataset on properties considered for a noise mitigation programme, I estimate a difference-in-differences model that compares prices of properties receiving a measure to properties ineligible for the programme. Results show that noise mitigation raised property prices by 10–12 percent. The property price benefits exceed programme investment cost with each $1 spent on noise mitigation generating up to $1.7 in benefits.

KEYWORDS:

• Environmental policy
• hedonic valuation
• noise pollution
• property value

Acknowledgments

I appreciate helpful comments from Niclas Krüger and Jan-Erik Swärdh.

Disclosure statement

This research evaluates a policy implemented by the Swedish Road Administration and its successor, the Swedish Transport Administration. The author has received funding from the Swedish Transport Administration for another research project.

Notes

1 The population exposed to potentially harmful levels of noise exceeds 100 million in Europe (European Environmental Agency 2019)

2 Based on cost figures provided by the U.S. Department of Transportation https://www.fhwa.dot.gov/environment/noise/noise_barriers/inventory/ [accessed 10 October 2020].

3 Noise exposure has also been shown to disrupt cognitive behaviour and development (Clark and Paunovic 2018).

4 The programme was implemented through infrastructure bill 1996/97:53.

5 The equivalent noise level refers to the average sound pressure level during a specific time period, usually 24 hours, with weights given to sound occurring during different periods of the day. The maximum noise level refers to the maximum sound pressure level from a single event occurring during a specific time period, usually 24 hours.

6 Eight percent of the observations have missing values on the structural attributes due to matching failure. I impute these values using sample averages.

7 I omit apartment buildings because of the difficulty of identifying which units in a building that received a noise intervention. Only including transactions referring to a single property allows me to identify the type of property.

8 The main results remain the same on the sample that includes price outliers.

9 I take the average across residents in cases of multiple residents at a property in a year.

Additional information

Funding

This work was supported by the Jan Wallanders och Tom Hedelius Foundation under Grant number P19-0010.