1# RECORD 89e86c34d31d60b83fe1893b6d6fc9985407503c2# TITLE: From industry to center for arts and culture: the impact of industrial heritage transformation on neighborhood house prices3# YEAR: 2025.0 VENUE: Frontiers in Sustainable Cities DOI: 10.3389/frsc.2025.15225204# AUTHORS: Lasse Læbo Matthiesen; Marie Lautrup; T. Panduro5# PAGES: 10 CANDIDATE TABLE PAGES (1-based): [6]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.789===== PAGE 1 (score 15, numeric-paren 0, table-words 0, var-words 15) =====1011Frontiers in Sustainable Cities120113frontiersin.org14From industry to center for arts 15and culture: the impact of 16industrial heritage transformation 17on neighborhood house prices18Lasse Læbo Matthiesen 1*, Marie Lautrup 2 and 19Toke Emil Panduro 3201 Copenhagen Business School, Frederiksberg, Denmark, 2 Department of Food and Ressource 21Economics, University of Copenhagen, Copenhagen, Denmark, 3 Department of Environmental 22Science, Aarhus University, Aarhus, Denmark23We examine how converting an industrial heritage site in Aarhus, Denmark, into 24a center for arts and culture affects nearby residents’ welfare. Using a hedonic 25house‑price model and a difference‑in‑differences design, we track apartment 26prices before and after the conversion. Prices within the neighborhood rose by 272.3–3 % relative to the rest of the city. This uplift represents a welfare gain of 28€17.5–21 million for the local community. As one of the few quasi‑experimental 29evaluations of creative‑led heritage revitalization, our study provides rigorous 30causal evidence of substantial indirect economic benefits. This evidence can 31guide future investments to convert disused industrial buildings into cultural and 32recreational spaces that serve local communities.33KEYWORDS34hedonic, valuation, culture investment, urban renewal, industrial, revitalization, 35heritage, gentrification regeneration361 Introduction37As urban landscapes shift in response to global economic trends, many former industrial 38sites emerge as contested spaces, torn between preservation and modernization (Loures, 392015). This evolution challenges city planners: How can these historically significant areas 40be rejuvenated in a contemporary context? One promising avenue is the conversion of these 41industrial relics into cultural and arts hubs (Evans, 2009). While the aesthetic and societal 42benefits of such conversions are apparent (Di Prete, 2020; Dinardi, 2019; Swensen and Skrede, 432018), their economic impact remains underexplored. This paper therefore investigates 44whether these cultural and arts transformations yield tangible economic benefits for the 45surrounding community.46We use the conversion of an old freight train station in Aarhus, Denmark, as a case study 47to examine the economic implications of transforming industrial sites. This example 48underscores the important role that art and culture can play in the revitalization of 49industrial sites.50In the early 2000s, the municipal council of Aarhus joined forces with a philanthropic 51foundation to spearhead the revitalization of Aarhus’s historic freight station. This initiative 52was not merely about refurbishment but a vision to elevate and nurture the city’s creative 53and artistic community. In addition to creating dedicated gallery, studio, and performance 54spaces, the project aimed to revitalize the district by improving pedestrian pathways and 55public spaces that link it to the adjacent neighborhood. It achieved this while preserving 56the station’s original brick facades, iron framework, and other defining industrial features 57(Culture Administration, 2008).58OPEN ACCESS59EDITED BY60Wayne Gearey, 61The University of Texas at Dallas, 62United States63REVIEWED BY64Shanaka Herath, 65University of Technology Sydney, Australia66Elisabetta Ginelli, 67Polytechnic University of Milan, Italy68*CORRESPONDENCE69Lasse Læbo Matthiesen 70 llm.eco@cbs.dk71RECEIVED 04 November 202472ACCEPTED 14 May 202573PUBLISHED 09 June 202574CITATION75Matthiesen LL, Lautrup M and 76Panduro TE (2025) From industry to center 77for arts and culture: the impact of industrial 78heritage transformation on neighborhood 79house prices.80Front. Sustain. Cities 7:1522520.81doi: 10.3389/frsc.2025.152252082COPYRIGHT83© 2025 Matthiesen, Lautrup and Panduro. 84This is an open-access article distributed 85under the terms of the Creative Commons 86Attribution License (CC BY). The use, 87distribution or reproduction in other forums is 88permitted, provided the original author(s) and 89the copyright owner(s) are credited and that 90the original publication in this journal is cited, 91in accordance with accepted academic 92practice. No use, distribution or reproduction 93is permitted which does not comply with 94these terms.95TYPE Original Research96PUBLISHED 09 June 202597DOI 10.3389/frsc.2025.15225209899100===== PAGE 6 (score 29, numeric-paren 8, table-words 8, var-words 4) =====101102Matthiesen et al.10310.3389/frsc.2025.1522520104Frontiers in Sustainable Cities10506106frontiersin.org1072.3–3% increase in apartment prices for the impacted 108neighborhood. Furthermore, both models have a reasonable 109explanation power.110The prices in the control and treatment areas did not differ before 111the event, as illustrated in Figure 2, which plots the difference-in-112differences estimates. This indicates that the assumption of a parallel 113trend of treated and not treated sales in difference-in-differences 114estimation holds (Huntington-Klein, 2022). The full model is found 115in Appendix Table 7.116To ensure the robustness of the model estimates, we varied the 117spatial outline of the neighborhood specification. We re-estimated 118the model using a 500 m ring buffer for a more restrictive 119neighborhood definition and an 800 m buffer for a broader definition. 120A pattern similar to the one presented in Table 1 was found for all 121alternative definitions of the treatment area.122We also tested the sensitivity of the model by introducing a 123pseudo-event in the city center of Aarhus during the period from 1242012 to 2018. This accounts for non-existing events in other areas of 125the city. We did not find an effect of the pseudo-event giving even 126further authority to the estimated effect of the opening of the freight 127train to the public. The treatment and event were modeled using a 128similar difference-in-difference approach as outlined in Equation 1. 129This test was done to ensure that the impact of the revitalization 130project found in the model was not part of a city-wide price trend. 131We found that the parameter estimates for completion of the 132revitalization project in Table 1 were stable with the additional 133pseudo-event specification.134As a final robustness check, we estimated the model without 135interacting the openingt variable with the other explanatory variables as 136proposed by Banzhaf (2021). This procedure slightly reduced the size of 137the parameters of the model but did not change the conclusion of the 138model significantly. Hence, the revitalization was a localized event that did 139not shift the overall hedonic price equilibrium, and the estimated results 140can be interpreted as a welfare-economic measure rather than a property 141capitalization event. Both sets of estimates can be obtained on request 142from the authors.143FIGURE 2144Difference-in-differences estimate for apartments sold in the freight train neighborhood relative to the control area year by year.145TABLE 1 Selected parameter estimates and model diagnostics for the two models.146Outer ring model147Inner ring model148Freight station neighborhood × 2011–20181490.030*** (0.013)1500.023** (0.011)151Info, ρ1520.167*** (0.006)1530.137*** (0.007)154Observations, n1559,7421567,112157R21580.6521590.596160Adjusted R21610.6521620.595163The 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.164165166===== PAGE 7 (score 16, numeric-paren 0, table-words 3, var-words 9) =====167168Matthiesen et al.16910.3389/frsc.2025.1522520170Frontiers in Sustainable Cities17107172frontiersin.org1738 Model interpretation174Following our estimation, we conduct a welfare-economic 175impact assessment based on hedonic estimates to quantify the 176project’s overall benefits. The intention is to show how hedonic 177studies can be used in policy applications such as cost–benefit 178analyses, cost-efficiency analyses, or other planning tools.179The model estimates in Table 1 indicate that apartment prices 180increased by 2.3–3% in the neighborhood close to the renewed 181freight train station, based on sales of privately owned 182apartments. There are 2,514 apartments located in this 183neighborhood. This number contains privately owned, 184community-owned, and non-profit apartments/public housing. 185Based on the estimated model, the apartments in the 186neighborhood close to the freight train station have predicted 187selling prices ranging from 0.05 to 2 million EUR with a mean 188price of 0.30 million EUR regardless of ownership type. Prices for 189each apartment in the freight train neighborhood were predicted 190by fixing the transaction date to June 2018. We applied the two 191hedonic models from Appendix B, with all estimates expressed in 1922018 prices. The predicted prices were multiplied by the 193parameter estimate for the interaction term between the project 194period and the freight station neighborhood dummy. These 195values were then aggregated across all 2,514 apartments. The 196estimated additional price increase after project completion for 197the average apartment corresponds to 27,000–29,000 EUR 198relative to similar apartments that were not impacted by the 199revitalization project. In total, the aggregated increase in price for 200the 2,514 apartments ranges from 17.5 to 21.4 million EUR, 201depending on the model/control area.202The effect of the revitalization project was calculated using 203Equation 2:204 205β206=207=208∗209∑21042111212ˆ213ˆ214N215i216i217Impact218P219 220(2)221In a welfare-economic context, the price increase can 222be interpreted as the lower-bound of the actual change in welfare 223(Banzhaf, 2021; Kuminoff and Pope, 2014). The implication is that 224the 17.5–21.4 million EUR represents a lower-bound estimate of the 225true welfare-economic impact for all houses in the neighborhood. 226This does not include the use-value for visitors not living in 227the neighborhood.228In contrast to the welfare gains estimated in Table 2, the project 229was funded with € 8.24 million from Realdania (2025). Our 230calculation indicates that this investment in the revitalization of the 231freight train station has been a net benefit from a welfare-economic 232point of view.2339 Discussion234Living in the neighborhood affected by the revitalization of the 235industrial freight train station has become more attractive following 236the opening of the arts and culture center. Apartment prices in this 237area rose by 2.3–3% relative to the rest of Aarhus, reflecting the 238neighborhood’s enhanced appeal. This increase can be interpreted 239as an aggregated welfare gain of 17.5–21.4 million EUR for all 240households in the impacted neighborhood. The increase in house 241prices is in line with some of the previous findings on the impact of 242industrial heritage (Van Duijn et al., 2016) and non-industrial 243cultural heritage (Koster et al., 2016), but contradicts the study by 244Mesthrige et al. (2018), who does not find a positive externality if 245revitalization. Koster et al. (2016) find a 3.5% price premium for 246apartments with a view of a historic building. Van Duijn et al. 247(2016) find an effect of 3% price increase after the completion of the 248revitalization in the preferred model specification. Van Duijn et al. 249(2016) estimate a total effect of 129–484 million EUR (in 2013) for 25025 projects throughout the Netherlands. The positive effect of 251industrial renewal in the Netherlands is persistent - or even 252increasing - over time but driven only by projects in larger cities. 253Although this approach can indicate some general trends for 254projects of this type, local differences between projects might lead 255to false conclusions as the result is an average estimate. As a result, 256they only include projects from the largest cities in their cost–257benefit analysis. In contrast, our study only includes one site, which 258makes the result easier to use for single-site benefit transfer studies, 259as the similarity of sites is easier to judge (Johnston et al., 2015). 260Given the absence of consensus on the welfare-economic effects of 261industrial revitalization, our study offers a valuable contribution 262this sparse body of literature.263We assume that the revitalization of the old freight train 264station into an arts and culture center is a bundled good for 265residents in the neighborhood. The bundled good is a combination 266of access to arts and cultural services, the removal of industrial 267activities and brownfields, and increased livability and services in 268the area, potentially leading to gentrification. The estimated price 269changes are likely due to a combination of all these distinct 270characteristics. Our estimate reflects the value of the revitalization 271as a unified bundle of interdependent features, enabling its 272application to and comparison with similar industrial heritage 273conversion projects.274As property prices increase, low-income residents may be forced 275to move out due to rising rents, house prices, and living costs. Studies 276suggest that minorities and low-income individuals have fewer 277options to relocate within the city compared to wealthier residents 278(Hwang and Ding, 2020). When they are forced to move, they often 279end up in neighborhoods with lower socioeconomic status, which 280exacerbates segregation and residential sorting.281TABLE 2 Effect of the Freight train station project on the 2,514 apartments.282Model283Min. price284Mean price285Median price286Max. price287Capitalization impact288Outer ring2890.0012900.272910.262920.5329321.4294Inner ring2950.0032960.292970.282980.4629917.5300All prices are in mill. EUR in 2018 prices (1 EUR = 7.5 DKK). The prices are predicted based on the models.301