# RECORD 89e86c34d31d60b83fe1893b6d6fc9985407503c # TITLE: From industry to center for arts and culture: the impact of industrial heritage transformation on neighborhood house prices # YEAR: 2025.0 VENUE: Frontiers in Sustainable Cities DOI: 10.3389/frsc.2025.1522520 # AUTHORS: Lasse Læbo Matthiesen; Marie Lautrup; T. Panduro # PAGES: 10 CANDIDATE TABLE PAGES (1-based): [6] # ABSTRACT: We examine how converting an industrial heritage site in Aarhus, Denmark, into a center for arts and culture affects nearby residents’ welfare. Using a hedonic house‑price model and a difference‑in‑differences design, we track apartment prices before and after the conversion. Prices within the neighborhood rose by 2.3–3 % relative to the rest of the city. This uplift represents a welfare gain of €17.5–21 million for the local community. As one of the few quasi‑experimental evaluations of creative‑led heritage revitalization, our study provides rigorous causal evidence of substantial indirect economic benefits. This evidence can guide future investments to convert disused industrial buildings into cultural and recreational spaces that serve local communities. ===== PAGE 1 (score 15, numeric-paren 0, table-words 0, var-words 15) ===== Frontiers in Sustainable Cities 01 frontiersin.org From industry to center for arts and culture: the impact of industrial heritage transformation on neighborhood house prices Lasse Læbo Matthiesen 1*, Marie Lautrup 2 and Toke Emil Panduro 3 1 Copenhagen Business School, Frederiksberg, Denmark, 2 Department of Food and Ressource Economics, University of Copenhagen, Copenhagen, Denmark, 3 Department of Environmental Science, Aarhus University, Aarhus, Denmark We examine how converting an industrial heritage site in Aarhus, Denmark, into a center for arts and culture affects nearby residents’ welfare. Using a hedonic house‑price model and a difference‑in‑differences design, we track apartment prices before and after the conversion. Prices within the neighborhood rose by 2.3–3 % relative to the rest of the city. This uplift represents a welfare gain of €17.5–21 million for the local community. As one of the few quasi‑experimental evaluations of creative‑led heritage revitalization, our study provides rigorous causal evidence of substantial indirect economic benefits. This evidence can guide future investments to convert disused industrial buildings into cultural and recreational spaces that serve local communities. KEYWORDS hedonic, valuation, culture investment, urban renewal, industrial, revitalization, heritage, gentrification regeneration 1 Introduction As urban landscapes shift in response to global economic trends, many former industrial sites emerge as contested spaces, torn between preservation and modernization (Loures, 2015). This evolution challenges city planners: How can these historically significant areas be rejuvenated in a contemporary context? One promising avenue is the conversion of these industrial relics into cultural and arts hubs (Evans, 2009). While the aesthetic and societal benefits of such conversions are apparent (Di Prete, 2020; Dinardi, 2019; Swensen and Skrede, 2018), their economic impact remains underexplored. This paper therefore investigates whether these cultural and arts transformations yield tangible economic benefits for the surrounding community. We use the conversion of an old freight train station in Aarhus, Denmark, as a case study to examine the economic implications of transforming industrial sites. This example underscores the important role that art and culture can play in the revitalization of industrial sites. In the early 2000s, the municipal council of Aarhus joined forces with a philanthropic foundation to spearhead the revitalization of Aarhus’s historic freight station. This initiative was not merely about refurbishment but a vision to elevate and nurture the city’s creative and artistic community. In addition to creating dedicated gallery, studio, and performance spaces, the project aimed to revitalize the district by improving pedestrian pathways and public spaces that link it to the adjacent neighborhood. It achieved this while preserving the station’s original brick facades, iron framework, and other defining industrial features (Culture Administration, 2008). OPEN ACCESS EDITED BY Wayne Gearey, The University of Texas at Dallas, United States REVIEWED BY Shanaka Herath, University of Technology Sydney, Australia Elisabetta Ginelli, Polytechnic University of Milan, Italy *CORRESPONDENCE Lasse Læbo Matthiesen llm.eco@cbs.dk RECEIVED 04 November 2024 ACCEPTED 14 May 2025 PUBLISHED 09 June 2025 CITATION Matthiesen LL, Lautrup M and Panduro TE (2025) From industry to center for arts and culture: the impact of industrial heritage transformation on neighborhood house prices. Front. Sustain. Cities 7:1522520. doi: 10.3389/frsc.2025.1522520 COPYRIGHT © 2025 Matthiesen, Lautrup and Panduro. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. TYPE  Original Research PUBLISHED  09 June 2025 DOI  10.3389/frsc.2025.1522520 ===== PAGE 6 (score 29, numeric-paren 8, table-words 8, var-words 4) ===== Matthiesen et al. 10.3389/frsc.2025.1522520 Frontiers in Sustainable Cities 06 frontiersin.org 2.3–3% increase in apartment prices for the impacted neighborhood. Furthermore, both models have a reasonable explanation power. The prices in the control and treatment areas did not differ before the event, as illustrated in Figure 2, which plots the difference-in- differences estimates. This indicates that the assumption of a parallel trend of treated and not treated sales in difference-in-differences estimation holds (Huntington-Klein, 2022). The full model is found in Appendix Table 7. To ensure the robustness of the model estimates, we varied the spatial outline of the neighborhood specification. We re-estimated the model using a 500 m ring buffer for a more restrictive neighborhood definition and an 800 m buffer for a broader definition. A pattern similar to the one presented in Table 1 was found for all alternative definitions of the treatment area. We also tested the sensitivity of the model by introducing a pseudo-event in the city center of Aarhus during the period from 2012 to 2018. This accounts for non-existing events in other areas of the city. We did not find an effect of the pseudo-event giving even further authority to the estimated effect of the opening of the freight train to the public. The treatment and event were modeled using a similar difference-in-difference approach as outlined in Equation 1. This test was done to ensure that the impact of the revitalization project found in the model was not part of a city-wide price trend. We  found that the parameter estimates for completion of the revitalization project in Table  1 were stable with the additional pseudo-event specification. As a final robustness check, we  estimated the model without interacting the openingt variable with the other explanatory variables as proposed by Banzhaf (2021). This procedure slightly reduced the size of the parameters of the model but did not change the conclusion of the model significantly. Hence, the revitalization was a localized event that did not shift the overall hedonic price equilibrium, and the estimated results can be interpreted as a welfare-economic measure rather than a property capitalization event. Both sets of estimates can be obtained on request from the authors. FIGURE 2 Difference-in-differences estimate for apartments sold in the freight train neighborhood relative to the control area year by year. TABLE 1  Selected parameter estimates and model diagnostics for the two models. Outer ring model Inner ring model Freight station neighborhood × 2011–2018 0.030*** (0.013) 0.023** (0.011) Info, ρ 0.167*** (0.006) 0.137*** (0.007) Observations, n 9,742 7,112 R2 0.652 0.596 Adjusted R2 0.652 0.595 The full set of model estimates can be found in Appendix B. *p > 0.1; **p > 0.05; ***p > 0.01. Robust standard errors in parenthesis. Log (price) as the dependent variable. ===== PAGE 7 (score 16, numeric-paren 0, table-words 3, var-words 9) ===== Matthiesen et al. 10.3389/frsc.2025.1522520 Frontiers in Sustainable Cities 07 frontiersin.org 8 Model interpretation Following our estimation, we conduct a welfare-economic impact assessment based on hedonic estimates to quantify the project’s overall benefits. The intention is to show how hedonic studies can be used in policy applications such as cost–benefit analyses, cost-efficiency analyses, or other planning tools. The model estimates in Table 1 indicate that apartment prices increased by 2.3–3% in the neighborhood close to the renewed freight train station, based on sales of privately owned apartments. There are 2,514 apartments located in this neighborhood. This number contains privately owned, community-owned, and non-profit apartments/public housing. Based on the estimated model, the apartments in the neighborhood close to the freight train station have predicted selling prices ranging from 0.05 to 2 million EUR with a mean price of 0.30 million EUR regardless of ownership type. Prices for each apartment in the freight train neighborhood were predicted by fixing the transaction date to June 2018. We applied the two hedonic models from Appendix B, with all estimates expressed in 2018 prices. The predicted prices were multiplied by the parameter estimate for the interaction term between the project period and the freight station neighborhood dummy. These values were then aggregated across all 2,514 apartments. The estimated additional price increase after project completion for the average apartment corresponds to 27,000–29,000 EUR relative to similar apartments that were not impacted by the revitalization project. In total, the aggregated increase in price for the 2,514 apartments ranges from 17.5 to 21.4 million EUR, depending on the model/control area. The effect of the revitalization project was calculated using Equation 2: β = = ∗ ∑ 4 1 ˆ ˆ N i i Impact P (2) In a welfare-economic context, the price increase can be interpreted as the lower-bound of the actual change in welfare (Banzhaf, 2021; Kuminoff and Pope, 2014). The implication is that the 17.5–21.4 million EUR represents a lower-bound estimate of the true welfare-economic impact for all houses in the neighborhood. This does not include the use-value for visitors not living in the neighborhood. In contrast to the welfare gains estimated in Table 2, the project was funded with € 8.24 million from Realdania (2025). Our calculation indicates that this investment in the revitalization of the freight train station has been a net benefit from a welfare-economic point of view. 9 Discussion Living in the neighborhood affected by the revitalization of the industrial freight train station has become more attractive following the opening of the arts and culture center. Apartment prices in this area rose by 2.3–3% relative to the rest of Aarhus, reflecting the neighborhood’s enhanced appeal. This increase can be interpreted as an aggregated welfare gain of 17.5–21.4 million EUR for all households in the impacted neighborhood. The increase in house prices is in line with some of the previous findings on the impact of industrial heritage (Van Duijn et  al., 2016) and non-industrial cultural heritage (Koster et al., 2016), but contradicts the study by Mesthrige et al. (2018), who does not find a positive externality if revitalization. Koster et al. (2016) find a 3.5% price premium for apartments with a view of a historic building. Van Duijn et al. (2016) find an effect of 3% price increase after the completion of the revitalization in the preferred model specification. Van Duijn et al. (2016) estimate a total effect of 129–484 million EUR (in 2013) for 25 projects throughout the Netherlands. The positive effect of industrial renewal in the Netherlands is persistent  - or even increasing - over time but driven only by projects in larger cities. Although this approach can indicate some general trends for projects of this type, local differences between projects might lead to false conclusions as the result is an average estimate. As a result, they only include projects from the largest cities in their cost– benefit analysis. In contrast, our study only includes one site, which makes the result easier to use for single-site benefit transfer studies, as the similarity of sites is easier to judge (Johnston et al., 2015). Given the absence of consensus on the welfare-economic effects of industrial revitalization, our study offers a valuable contribution this sparse body of literature. We assume that the revitalization of the old freight train station into an arts and culture center is a bundled good for residents in the neighborhood. The bundled good is a combination of access to arts and cultural services, the removal of industrial activities and brownfields, and increased livability and services in the area, potentially leading to gentrification. The estimated price changes are likely due to a combination of all these distinct characteristics. Our estimate reflects the value of the revitalization as a unified bundle of interdependent features, enabling its application to and comparison with similar industrial heritage conversion projects. As property prices increase, low-income residents may be forced to move out due to rising rents, house prices, and living costs. Studies suggest that minorities and low-income individuals have fewer options to relocate within the city compared to wealthier residents (Hwang and Ding, 2020). When they are forced to move, they often end up in neighborhoods with lower socioeconomic status, which exacerbates segregation and residential sorting. TABLE 2  Effect of the Freight train station project on the 2,514 apartments. Model Min. price Mean price Median price Max. price Capitalization impact Outer ring 0.001 0.27 0.26 0.53 21.4 Inner ring 0.003 0.29 0.28 0.46 17.5 All prices are in mill. EUR in 2018 prices (1 EUR = 7.5 DKK). The prices are predicted based on the models.