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Noise expectations and house prices: the reaction of property prices to an airport expansion


We examine the effects of an airport expansion on the prices of houses and apartments located under the planned flight paths. We focus on the role of expectations of aircraft noise during the expansion of Berlin-Brandenburg International Airport. The publication of the flight paths can be seen as an exogenous event. It provides local residents and potential home buyers with reliable information in a situation that is characterized by uncertainty. The flight paths greatly influence the expectation of the noise level. We find that property listing prices were reduced substantially in the affected areas after the flight paths were published. The loss of value of the affected properties was found to be 9.6 % on average within a slant distance of 3 km from a planned flight path. If the flight altitude is below 1,000 m, the discount is between 11.8 and 12.8 %, whereas for higher flight altitudes, the average decline in prices is estimated to be 8.3 %.

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Fig. 1


  1. 1.

    See for details. Schönefeld is located just outside the south-eastern city limits of Berlin.

  2. 2.

    The DFS is a company organized under private law, but owned completely by the federal state, see

  3. 3.

  4. 4.

  5. 5.

    The divergence triggered an inquiry and a declaration in the parliament of Brandenburg, see and In question 12 of the inquiry, the Green Party (die Grünen) asked whether the projected flight paths were going to be followed closely or whether divergence from the paths was likely to occur more frequently. From the perspective of the local residents, there seemed to be a high degree of uncertainty about how to deal with the existing information such as the flight paths and noise projections throughout the planning process.

  6. 6.

  7. 7.

    The NDI is a measure for the relative loss of value per dB, see Nelson (2008).

  8. 8.

    We would like to thank an anonymous referee for pointing this out.

  9. 9.

    The modeling of expectations has its own problems that are discussed below.

  10. 10.

    Unfortunately, there are no data available from the years prior to 2011. Therefore, it is not possible for us to examine prices before the decision in favor of Schönefeld was made.

  11. 11.

    For details on the data, the reader is referred to Kholodilin and Mense (2011).

  12. 12.

    We use takeoffs rather than landings because landing paths are much less variable due to safety regulations. Since the location of the airport has been public information at least since 2004, it is likely that prices had adjusted to the landing paths prior to 2010.

  13. 13.

    See for example,10809148,11418040.html,,

  14. 14.

    See Ibbeken (2011) and Ibbeken (2012) for details.

  15. 15.

    For an observation of December 2012, it is known whether it remained online in January 2013 or not.

  16. 16.

    As a robustness check, a model was estimated in which all treatment variables were interacted with the \(TOM\) dummy described above. The estimates suggest that the bias is small.

  17. 17.

    In a sense, this would be in line with the findings of Kiel and McClain (1995) who find a significant reaction of home owners to “hard” information during the siting of an incinerator, but a much smaller and instable reaction to “rumors”. Although the plans preferred by the DFS in September 2010 still had to be approved of, they were not merely “rumors”. It must have been clear to the affected persons that forcing the DFS to change their plans would require heavy protesting and lobbying.

  18. 18.

    We would like to thank an anonymous referee for pointing this out.

  19. 19.

    SXF is IATA code for Schönefeld Airport.

  20. 20.

    Modeling distance variables in this way reduces multicollinearity, while the variation in prices introduced by these local amenities is captured in the area where it is most important, following Tobler’s “first law of geography”. The choice of the cut-off point is arbitrary, but the results are robust to this choice.

  21. 21.

    We also tested models that used distance bounds instead of the nearest neighbors approach, and they produced similar results. These can be obtained from the authors upon request.

  22. 22.

    The SLM was also estimated by the spatial two-stage least squares procedure, and the SEM was estimated by GMM, with very similar results. See Kelejian and Prucha (1998), Kelejian and Prucha (2010), Arraiz et al. (2010), Piras (2010) for details about the estimators. We do not report these estimates, but they can be obtained from the authors upon request.

  23. 23.

    For dummy variables, the percentage price discounts were calculated as \(100 \times (\exp {\{b\}} - 1)\).

  24. 24.

    The decomposition of impacts for the spatial models were calculated using the approach proposed by (LeSage and Pace (2009), p. 38, eq. 2.46).

  25. 25.

    The marginal effects estimates of the SLM are much higher than the marginal effects estimates from the OLS or SEM models. The feedback mechanism is responsible for this difference. However, this mechanism might be driven by observations from the control group. Therefore, the SLM introduces an identification problem that is absent if the reasoning behind the SEM is accepted.

  26. 26.

    For group B, there are not enough observations with flight altitudes above 1,000 m in the sample, so we did not split this group.

  27. 27.

    The variance inflation factors for group B, the noise variables, and the group A dummies are all larger than 9 in this model (not reported).

  28. 28., pp. 98–99.


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Our thanks go to trainee Dmitry Chervyakov for his excellent research assistance. We also like to thank the two anonymous referees for their very helpful comments. Furthermore, the paper benefited from the remarks of Jürgen Kähler and Anne Spiroch.

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Correspondence to Andreas Mense.

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Mense, A., Kholodilin, K.A. Noise expectations and house prices: the reaction of property prices to an airport expansion. Ann Reg Sci 52, 763–797 (2014).

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JEL Classification

  • R31
  • Q53
  • R41