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The market value of cultural heritage in urban areas: an application of spatial hedonic pricing

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Abstract

The current literature often values intangible goods like cultural heritage by applying stated preference methods. In recent years, however, the increasing availability of large databases on real estate transactions and listed prices has opened up new research possibilities and has reduced various existing barriers to applications of conventional (spatial) hedonic analysis to the real estate market. The present paper provides one of the first applications using a spatial autoregressive model to investigate the impact of cultural heritage—in particular, listed buildings and historic–cultural sites (or historic landmarks)—on the value of real estate in cities. In addition, this paper suggests a novel way of specifying the spatial weight matrix—only prices of sold houses influence current price—in identifying the spatial dependency effects between sold properties. The empirical application in the present study concerns the Dutch urban area of Zaanstad, a historic area for which over a long period of more than 20 years detailed information on individual dwellings, and their market prices are available in a GIS context. In this paper, the effect of cultural heritage is analysed in three complementary ways. First, we measure the effect of a listed building on its market price in the relevant area concerned. Secondly, we investigate the value that listed heritage has on nearby property. And finally, we estimate the effect of historic–cultural sites on real estate prices. We find that, to purchase a listed building, buyers are willing to pay an additional 26.9 %, while surrounding houses are worth an extra 0.28 % for each additional listed building within a 50-m radius. Houses sold within a conservation area appear to gain a premium of 26.4 % which confirms the existence of a ‘historic ensemble’ effect.

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Notes

  1. In British English, historic buildings which are part of the cultural heritage are called ‘Listed Buildings’ (grades I, II and III), which includes houses of architectural merit. In American English, the equivalent is ‘landmark’ for all types of historic buildings.

  2. Dutch heritage (In Dutch: Rijksdienst voor het Cultureel Erfgoed) is the government organization which determines which heritage should be listed.

  3. In the Netherlands, 65–70 % of all houses are sold by an NVM real estate agent.

  4. The density for various distances was calculated (0–50, 50–100, 100–150 and 150–200 m) and was used as variables in the regression. The results indicated that beyond 50 m, the effect of listed heritage is negligible and insignificant.

  5. OLS is easy to interpret and the results can be used to check for spatial dependence.

  6. To correct for this segmented market effect, we have created an own price index by using the year dummies of the simple OLS. In this way, we have corrected for the year effects.

  7. Different radius specifications were tested, but our results make it plausible to choose a relatively steep distance decay.

  8. The correlation between the heritage density and the conservation area is high with a value of 0.69.

  9. Spatial models have a more complicated interpretation than parameters of a linear regression. OLS allows a straightforward interpretation as the partial derivatives of the dependent variable with respect to the explanatory variable. Won Kim et al. (2003) have proved that with a spatial lag in the model, the outcome of the parameter estimates should be interpreted with care and that when the weight matrix is row standardized, the parameter outcomes multiplication with the multiplier is needed: \( \frac{1}{1 - \rho } \).

    Abreu et al. (2004), Pace and LeSage (2006) and LeSage and Pace (2009) show that this interpretation should be elaborated. In this paper, we follow the terminology of LeSage and Pace (2009). Their partial derivative interpretation leads to an average direct impact, an average indirect impact and an average total impact. This is a more valid basis for testing hypotheses as they show with an example where the estimated coefficient is negative and insignificant but the spatial impact is positive and significant.

  10. Apparently, there is some negative correlation between the monument density/ha at a 50-metre radius and the listed heritage dummy.

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Acknowledgments

We would like to thank the Dutch Association of Real Estate Brokers (NVM) for making available their data on house transactions for this study. Furthermore, we thank the Land Registration Office (Kadaster) for providing complete data on the heritage status. This paper was written in the context of the CLUE cultural heritage research programme at the VU University Amsterdam, and the NICIS project on the ‘Economic valuation of cultural heritage’. The authors would like to thank James LeSage along with two anonymous reviewers for their valuable comments.

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Authors and Affiliations

  1. Department of Spatial Economics, VU University Amsterdam, De Boelelaan 1105, 1081 HV, Amsterdam, The Netherlands

    Faroek Lazrak, Peter Nijkamp, Piet Rietveld & Jan Rouwendal

  2. A. Mickiewicz University, Poznan, Poland

    Peter Nijkamp

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  1. Faroek Lazrak
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  2. Peter Nijkamp
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  3. Piet Rietveld
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  4. Jan Rouwendal
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Correspondence to Faroek Lazrak or Peter Nijkamp.

Appendix: Variables and descriptive statistics

Appendix: Variables and descriptive statistics

See Tables 6 and 7.

Table 6 Variable names and definitions
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Table 7 Descriptive statistics: mean values and standard deviation Zaanstad (n = 19,891)
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Lazrak, F., Nijkamp, P., Rietveld, P. et al. The market value of cultural heritage in urban areas: an application of spatial hedonic pricing. J Geogr Syst 16, 89–114 (2014). https://doi.org/10.1007/s10109-013-0188-1

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