Cities 110 (2021) 103047
Available online 16 December 2020
0264-2751/© 2020 Elsevier Ltd. All rights reserved.
The influence of the new cultural infrastructure on residential property prices. Evidence from Ko ˇ sice ECoC 2013
Peter D ˇ zupka
*, Marek Gr ´ of
Technical University of Koˇsice, Faculty of Economics, Slovakia
A R T I C L E I N F O Keywords:
European Capital of Culture Hedonic models
Impact assessment
A B S T R A C T
The European Capital of Culture (ECoC) has become one of the most significant cultural activities in the EU, aiming to change cities through culture. There is still a broad discussion about how to estimate the impact or influence of cultural activities on a city. There are several approaches which evaluate the benefits of cultural activities and cultural infrastructure. This paper presents a unique opportunity to use the hedonic model for impact estimation of new cultural infrastructure built through the project Koˇsice ECoC 2013. The hedonic pricing model was constructed based on 1157 sales of flats between 2010 and 2018. The final hedonic model was constructed to determine the influence of new cultural infrastructure (Kulturpark barracks) on nearby flats prices. According to this model, the flats in this area a year before the renovation did not show any differences from the average flats in other localities. However, from the beginning of the renovation, they presented above- average prices till two years after the reconstruction. After four years the positive impact of the cultural infra- structure disappears and the price level of the flats returned to the levels before the reconstruction.
1. Introduction
The European City of Culture (ECoC) is one of the oldest, most suc- cessful and representative EU cultural initiatives. The ECoC is the EU’s most direct attempt, both practical and symbolic, at creating a European cultural space (Sassatelli, 2008). After more than 30 years and while the title of ECoC is still awarded to different European cities, a lot has changed in its impact on cities. The first period of the programme started with culturally and heritage-rich cities such as Paris, Athens and Flor- ence and was mainly focused on cultural activities (events). This changed with Glasgow ECoC 1990 when the project was primarily used as a catalyst for city transformation (Garcia, 2005). Since then, ECoC projects have become more focused on investments in cultural infra- structure. Cities have started to invest significant public sources in the construction of new cultural infrastructure. In some cases, like the Grande Rotonde in Luxembourg GR 2007, the Maison Folies of Lille 2004 and the new Arena in Liverpool 2008, this has had a substantial impact on the neighbourhood (Garcia & Cox, 2013). Thus, it is of in- terest to look at the impact of these public investments. One set of ap- proaches in impact measurement (used predominately by cultural economists) is focused on the estimation of “soft” impacts. Some studies have analysed the impact of cultural investment on culture accessibility
and participation, image and gentrification (Cicerchia, 2016; European Capital of Culture Policy Groupe, 2011; Evans, 2010). The second possible approach is to consider cultural infrastructure as an amenity and estimate the impact of this cultural infrastructure using hedonic pricing models. According to O’Brien (2010), this is one of the most used revealed preference techniques.
In the context of the analysis and utilization of hedonic real estate valuation models, there was a relatively unique opportunity in public investment found in the cultural infrastructure in Koˇsice. As part of the preparation for the ECOC in Koˇsice in 2013, extensive investments were made to restore both the transport and cultural infrastructure in the city.
Such a significant volume of investment in a relatively short time and proper public awareness created an excellent opportunity to monitor its impact. Therefore, the aim of this article is to investigate the impact of the most crucial investment in Koˇsice’s cultural infrastructure – Kul- turpark Barracks. The approach in this study is based on the hedonic pricing model, which can separate the influence of new cultural ame- nities on flats sales prices in the neighbourhood. There is a relatively large number of studies and articles which have used hedonic pricing models for estimating the impact of different amenities on real estate prices. However, studies dealing directly with cultural infrastructure have been rare and are primarily focused on cultural heritage. The
* Corresponding author.
E-mail addresses: Peter.Dzupka@tuke.sk (P. Dˇzupka), Marek.grof@tuke.sk (M. Gr´of).
Contents lists available at ScienceDirect
Cities
journal homepage: www.elsevier.com/locate/cities
https://doi.org/10.1016/j.cities.2020.103047
Received 16 April 2020; Received in revised form 21 August 2020; Accepted 26 November 2020
Kulturpark Barracks in Koˇsice can be considered to be new. It is modern cultural infrastructure situated in a residential area near the city centre, with many positive impacts as well as several potentially negative im- pacts such as noise and increased traffic. It was therefore of interest to investigate the impact of such new cultural infrastructure on flats prices in the neighbourhood.
From the methodological point of view, the model is constructed in such a way, that it is able to exclude the direct impact of the Kulturpark Barracks investment on flats prices in its surroundings. In fact, the prices before the renovation (ECoC investment) and after the renovation were examined with the aim of finding out the change in flats sales prices caused by the new cultural amenities in the neighbourhood.
These analyses are very important for the city and urban planners when considering the locality of new cultural infrastructure, and its funding from public sources (investment as well as the running costs). As far as it is known, this is the first and only application of the hedonic pricing model in evaluating the impact of a ECoC cultural investment project. The article is therefore a contribution to the scientific discussion on the use of the hedonic pricing models in evaluation of the long-term impact of the cultural infrastructure. The approach used in this article allows city representatives to evaluate the long term value of cultural infrastructure for city residents. Agenda 21 for culture (Duxbury et al., 2016) answers the question: “why must culture be at the heart of sus- tainable urban development?”, but at the same time the cities are facing policy issues with sustaining cultural infrastructure because of increasing prices of land value, higher demand for public funds etc.
Several policy initiatives (City of Sydney, 2020; Greater London Au- thority, 2019; Vancouver City Council, 2018) currently emerged to face these issues. The Koˇsice case can provide an example for city represen- tatives facing these policy issues concerning the long term positive (or at least stable) value of cultural infrastructure for city residents.
Based on literature review in this paper, cultural infrastructure in- fluences real estate prices in its neighbourhood. Some attributes of the cultural infrastructure influence the prices positively and some nega- tively. Current studies looked at cultural heritage and classical cultural infrastructure (museums, galleries, etc.). Our case is focused on modern cultural infrastructure with significant representation of contemporary art of different kind (dance, music, painting etc.). The infrastructure is widely open to the public with frequent and diverse public activates. So which impact, positive or negative will outweigh in this case? This is the academic question we try to answer in our paper.
The paper also aims to enlarge the theoretical knowledge of time stability of cultural infrastructure impact on property prices in neigh- bourhoods and in gentrification caused by culture led urban regeneration.
The paper is structured as follows: Section 2 reviews the literature of two areas. The first one deals with the overall impact of cultural infra- structure developed through ECoC projects on the city economy and its citizens. The second one is focused on analysing the available studies which deal with the impact of cultural and similar amenities on flats prices using hedonic models. Section 3 describes the object of evaluation – the cultural good – Kulturpark Barracks and data used in the evalua- tion. Section 4 describes the methodology and presents the results of the analysis. Section 5 summarizes the results and presents the discussion.
2. Literature review
A typical ECoC candidate city deals with the essential dilemmas of cultural investments in order to maintain sustainable development (Bianchini & Parkinson, 1993). These three dilemmas outline the de- cisions about the funding allocation of an ECoC project. The first dilemma is about how to distribute funding between cultural events and cultural infrastructure building or renovation. The economic dilemma is about whether to support cultural consumption activities or to focus more on local cultural production while the last dilemma is about how to distribute cultural activities between the city centre and the suburbs. In
many cases, these decisions are worth more than 100 million Euros and can influence particular city areas (neighbourhoods) positively as well as negatively. At the same time, activities which are carried out based on these decisions will influence real estate prices in the surrounding areas.
Most of the studies examining the cultural economy do not deal with this issue. Rather, their main focus is on estimating the impact through economic impacts (Herrero et al., 2006), different cultural indicators (European Capital of Culture Policy Groupe, 2011) social and economic impacts (Cicerchia, 2016), physical and cultural displacement (Evans, 2010). Another “soft” approach was introduced also by Vareiro (2014), where resident perceptions of the impacts of hosting the 2012 European Capital of Culture in Guimar˜aes was analysed. One study (Fiˇser & Koˇzuh, 2019) looked at the cultural and social impacts of the ECoC on the case of Maribor in Slovenia. People from Maribor show a stronger sense of community pride than Slovenes. An evaluation of the contribution of culture to local and regional development was also made in (Study on the contribution of culture to local and regional development - Evidence from the structural funds, 2010). According to this study, the positive impact of culture on the local economy can be summarized as follows:
• Culture has a critical role in making Europe and its regions more attractive places in which to invest and work;
• Cultural activities and facilities have an essential place in the development of the physical environment of towns and cities and, in particular, the rehabilitation of old industrial cities;
• Culture is seen to be important in the attraction and retention of people with high skill levels;
• There is some recognition given to the significance of natural and cultural assets and their interaction; cultural heritage is seen as sig- nificant in the development of rural areas, primarily through its contribution to rural tourism;
• In general, tourism is still regarded as necessary, as is culture’s contribution to its development, but there is greater emphasis on the role of culture in contributing to the delivery of sustainable, high- quality tourism that is well integrated into other activities.
The importance of culture and cultural infrastructure in urban development is well described in literature. Balas (2004) describes positive impact of cultural capital on producing cultural goods, which positively influences many aspects of economic and social life within the city. He also argues that in the urban context, a sustainable city must also focus on its cultural capital in both its tangible and intangible forms.
Local cultural resources contribute to social and economic change and enhance local resiliency and development potential (Duxbury et al., 2016).
Specific attention in the literature is dedicated to the issue of “cul- ture-led city regeneration”, where investment in cultural activities, culture infrastructure and cultural networks is the catalyst of change mostly in old industrial cities (Evans, 2005; García, 2004; Hudec &
Dˇzupka, 2016; Mooney, 2004). Another issue that can be recognized in the literature is the evaluation of the impact of cultural capital on city development. The demand for more specific evaluation approaches can be found in scientific papers (Balas, 2004; Owen, 2003) as well in policy papers (City of Sydney, 2020; Duxbury et al., 2016; Greater London Authority, 2019; Vancouver City Council, 2018).
Although the aim of this paper is not primarily focused on the issue of gentrification, this process cannot be excluded from the investigating of the impact of new cultural infrastructure on its neighbourhood. The normative statement of gentrification is connected to the negative consequences. Culture led urban regeneration triggers gentrification.
The locality starts to be more attractive for more affluent consumers and potential residents (Gainza, 2017). This usually increase property prices and rents (Guerrieri et al., 2013), which is one of the causes of gentri- fication. “Displacement imposes substantial hardships on some classes of displacees, particularly lower-income-groups and the elderly” (Gates &
Hartman, 1986). On the other hand, culture led regeneration can also
lead to “positive gentrification”, transformation can bring new people and life to the neighbourhood and the original population can benefit from new services and removal of the stigma attached to the locality (Cameron, 2003). Not all culture-led neighbourhood transformation must necessarily lead to gentrification. In Gainza (2017) a neighbour- hood transformation in San Francisco was investigated from the gentrification point of view. The article concluded that: “However, looking at the data it is hard to argue that displacement and the capture of the neighbourhood by middle classes have taken place, as the liter- ature on gentrification stresses.” (Cameron, 2003, p. 966).
As previously mentioned, most evaluations of ECoC cultural infra- structure impact is focused on indicators which describe the secondary impact on the city and its inhabitants. One of the main problems for estimating the impact of ECoC projects is how to also measure the long- term impact. Most of the presented studies have focused on estimating the short-term impacts. The hedonic pricing models, which are a well- established methodology for estimating an amenity’s impact on real estate sale prices, can be a useful tool for measuring the long-term impact of new cultural infrastructure built through ECoC projects.
Another critical issue in most cities is to demonstrate the positive impact of public investment in cultural infrastructure on local citizens. Building new cultural infrastructure in the city area has positive as well as negative aspects. It is therefore worth asking if one outweighs the other.
The hedonic pricing model can answer this by examining the relative price change of flats in the neighbourhood caused directly by the new cultural infrastructure and activities. The use of hedonic pricing models to measure the impact of cultural infrastructure on the price of flats is of great value and can help decision-makers to understand more and localize future cultural infrastructure within the city.
The use of hedonic pricing models to analyse the impact of public investment on property prices is relatively well developed in the liter- ature. There have been many studies including Gonzalez-Navarro and Quintana-Domeque (2010), which examined the impact of public infrastructure investments in Mexico. This demonstrated the significant impact of asphalting the streets in a residential area not only on the real estate value but also on the willingness of the public to make private investments. There was evidence of a so-called spill over effect on the surrounding streets. A similar spill over effect was presented in Chernoff and Craig (2018), which analysed investment in public transport.
Another example of this work is Wachter and Gillen (2005), in which the authors studied different forms of public investment and their impact on the quality of life in the population measured as a real estate price change. Lindsey et al. (2003) presented a complex hedonistic model of real estate, which also analysed the effect of public infrastructure in- vestments. This found out that although the impact of such investments is generally positive, the significance of this effect mainly depends on many other factors. Another study (Reh´ak & K´aˇcer, 2019) looked at the price gradient of flats in Bratislava based on different types of travel time measurement. They found out that even in a city with a complicated urban structure, Euclidean distance is the best proxy for distance to the city centre and it is not necessary to use a more demanding distance calculation in hedonic price models. In the field of sports infrastructure investment (Ahlfeldt & Kavetsos, 2010), the authors analysed the impact of the construction of football stadiums on the value of real estate in the neighbourhood. It was concluded that the prices not only reacted at the time of commissioning or construction but rather at the construction decision itself, that is, ahead of schedule. A review of applications of hedonic pricing models in the New Zealand housing market was made in another study (Fernandez, 2019). In New Zealand, hedonic models contribute to informing planners on how individuals value amenities and developers on how to design development projects that preserve profit-maximisation behaviour. Planners and policymakers may use these models to inform ongoing discussions about the direction and typology of growth that is sought by any city. In New Zealand, hedonic models are greatly used for different kinds of amenities – from sea views and parks to flood hazards, cellular phone base stations and towers,
transmission lines, windfarm visibility, school zones, and risk of explosions.
The application of hedonic pricing models in the valuation of cul- tural goods raises the question as to how the economic value of cultural goods can be measured. In general, there are two basic approaches. The first one is focused on measuring the impact of cultural goods with methodologies such as Economic impact assessment or footprint anal- ysis. The second approach is focused on valuing wider socio-economic benefits. Again, two approaches can be found. The first one is based on stated preferences, where the economic value of the cultural goods is directly stated by the target groups. In empirical studies, this approach is mainly represented by contingent valuation and coin join analysis. A relatively high number of studies with this approach can be found in the literature (Noonan, 2003; O’Brien, 2010). The second approach is based on revealed preferences. These revealed preferences methods are pre- dominately used for the valuation of infrastructural or environmental projects. The use of these methods for the valuation of cultural goods has not been as frequent although there are some empirical studies such as Lazrak et al. (2010) and Sheppard (2010) where revealed preferences methods have been used for the valuation of cultural goods. The most frequently used methodologies are the travel cost method and hedonic pricing models. The hedonic model is at the centre of the present study although using hedonic models in the field of culture is not so common.
There have been a few examples (Dai-Ling et al., 2018; Lazrak et al., 2014) which have valued cultural heritage in Taiwan and the Netherlands. Another study (Sheppard, 2010), looked at a public museum value in Kenosha, Wisconsin using a hedonic pricing model. In Andersson et al. (2019), the focus was on investigating two questions regarding the effect of cultural values on housing market prices. The first question looked at how large the price premium paid was for a building exhibiting cultural value? The second question looked at if there are any spill over effects of buildings with cultural values on the sales prices of neighbouring houses? The hedonic model was estimated based on the database of all buildings in the region of Halland combined with transaction data and proximity to three classes of culturally classified building – national, regional and local cultural interest. The findings showed that cultural classification plays a role in determining the price of property.
The price of real estate is influenced by several factors. When considering new, or significantly improved cultural infrastructure, these factors could be positive and negative. In study Benson et al. (1998), hedonic models were used to analyse the views in Washington. Wash- ington is a city with a variety of views including oceans, lakes and mountains. This allows for the differentiation of the view amenity ac- cording to both type and quality. The results from the hedonic model estimated that the willingness to pay for this amenity is quite high depending on the particular view. The highest-quality ocean views are found to increase the market price of an otherwise comparable home by almost 60%; the lowest-quality ocean views are found to add about 8%.
For ocean views of all quality levels, the value of a view is found to vary inversely with the distance from the water. Another next study (Sander
& Haight, 2012) estimated the economic value of the cultural ecosystem.
Several services provided by ecosystems, such as aesthetic quality (views), access to outdoor recreation and the benefits provided by tree cover in Dakota County, Minnesota were analysed. The results indicated that local residents valued these services and that hedonic pricing could be used to elicit at least a proportion of this value. The total view area as well as areas of some land cover types (water and lawns) positively influenced home sale prices. Moreover, the access to outdoor recreation areas significantly and positively influenced home sale prices. In Moro et al. (2013), the authors estimated several specifications of a hedonic price equation to establish whether the distance to and density of a cultural heritage site is capitalised into housing prices in Greater Dublin, Ireland. They used a very rich dataset of housing and neighbourhood characteristics and included 104 location fixed effects, which represent minimal areas, ensuring the identification of the price effects on similar
houses in similar areas. The results showed that some types of cultural heritage sites, such as historic buildings, memorials and Martello towers provided positive spill over to property prices while archaeological sites seemed to be an adverse amenity. They interpreted these premiums (or lack thereof) as capturing aesthetic beauty (Acharya & Bennett, 2001).
They then used hedonic models to look at the impact of environmental quality on real estate prices. In this study, the positive correlation be- tween the price premium and the quality of the environment was demonstrated.
Above listed studies did not focus on change of impact over a period of time. Amenities analysed usually did not change during the time (view, cultural heritage), so most of the studies build hedonic models on one or two years’ data (Acharya & Bennett, 2001; Benson et al., 1998;
Sander & Haight, 2012). One study dealing with the cultural heritage effect on housing market in Dublin (Moro et al., 2013), build the model on six-year data of house sales. Although the quarterly dummies have been included to the model the study did not report any information about the impact change in time.
A further study (Kwong, 2003) carried out a critical review of liter- ature on hedonic price models and found several findings regarding the focus of the current article. On one hand, analysing culture as amenities usually shows a positive impact on sale prices in a neighbourhood. On the other hand, the increased noise, traffic and crime and vandalism can sometimes reduce the positive impact of these amenities.
Based on the example of this study, some theoretical issues and problems of this methodology can be explained. From the theoretical point of view, the basic idea behind hedonic pricing model is that real estate prices are influenced by the quality of an area (accessibility of schools, parks, etc.). Therefore, if there is a change in the analysed area, the change in real-estate prices can be expected. There is a very similar expectation when considering cultural infrastructure. If there is new cultural infrastructure in an analysed locality, a change in real estate prices can be expected. On the other hand, there are certain limitations when using hedonic models for evaluating cultural goods. According to Sheppard (2010), it is only possible to measure the benefits of cultural goods for residents of the analysed locality. Yet, cultural goods have far more extensive benefits including people living outside the analysed locality. It is not necessary to live near the place where Pablo Picasso painted his pictures to have a positive utility from his work. The second limitation is based on the fact that the hedonic pricing model only measures the total amount of money which an individual paid for the possibility of living in an area with better access to cultural infrastruc- ture. The hedonic model cannot measure the maximum price an indi- vidual would be willing to pay for living in this locality due to better access to cultural infrastructure. Other problems of the hedonic pricing model include the problem of selecting the correct function form and its specification (Butler, 1982), the assumption of perfect market infor- mation, immediate price changes and no interrelationships of attributes (Kwong, 2003) and the problem of data collection and reliability (Dusse
& Jones, 1998; Freeman, 1979). In spite of these and other problems, the
method is considered valid and is widely used in empirical studies.
In the case of the current study, the object of the analysis is the most significant investment under the ECoC 2013 project; the Kulturpark Barracks. The Kulturpark Barracks are located near the city centre in a high-density residential area. The investment brought several new im- pacts, both positive and negative. In the case of positive amenities, there is the view, access to culture and access to the new park. However, modern cultural infrastructure also brings negative impacts to the neighbourhood. The cultural events in the park produce a noise.
Moreover, large events have a negative impact on traffic and parking problems and a decrease in safety must also be taken into consideration.
As has been covered in the review, these factors can be evaluated using hedonic pricing models. The aim of this study is to find out which have had a greater impact in Kosice.
3. Data and methodology 3.1. Kulturpark Barracks in Koˇsice
Koˇsice is the second largest city in Slovakia, situated close to the eastern Schengen border with Ukraine with nearly 300,000 inhabitants.
It is the main economic, social and cultural centre in eastern Slovakia.
Koˇsice was one of the main centres of trade and culture in the Austro- Hungarian Empire and as the first town in Europe was granted its own coat of arms in 1369. Proof of the historical importance can be seen in the magnificent St Elizabeth’s Cathedral, Slovakia’s largest church, the easternmost Gothic cathedral in Europe. The cultural life at the end of the 20th century can be described as a mix of classical arts (theatre, philharmonic, museums and galleries) and the rural culture represented by the strong folklore background around Koˇsice. This started to change after 2008, when Koˇsice won the title Koˇsice ECoC 2013, with increasing proportion of contemporary and international art.
Kulturpark Barracks is the most significant investment which was carried out under the Koˇsice ECoC 2013 project. The original barracks area was built at the turn of the 19th centuries and served as a military food supply warehouse, including a bakery. Gradually, the Captain Jaros Barracks (the original name) lost their importance, and in the last years before the renovation, they were mainly used as warehouses in the city of Koˇsice. The barracks were surrounded by a high wall, were inacces- sible to the public and without any social benefit, despite the strategic location in the wider city centre. Fig. 1 shows the location of the Kul- turpark Barracks in relation to the city centre.
The basic idea of the Koˇsice ECoC 2013 project was to open the barracks to the public and use it for cultural purposes. The internal decision for new – cultural purpose of the army barracks was made in late 2007, whet city representative, also started to look for sourced of funding. The final decision covered by the available financial sources for reconstruction (approved EU structural funds) was made in late 2010. A complete renovation of the barracks was carried out in 2012 and 2013.
By the end of the renovation, Koˇsice had gained new modern cultural infrastructure which not only serves for a wide range of cultural and artistic activities, but also provides spaces for artistic production. The Central building ALFA (1) is a three-storey building which offers multifunctional halls (each with a capacity of 300 visitors), exhibition spaces, audio and video studios, as well as administrative facilities and facilities for performers. It is used for more significant cultural and social events.
The BRAVO (2) Culture and Creativity Support Centre is designed for local and foreign artists. This building has four floors and one under- ground floor which provides studios, workshops, exhibition spaces, studios and workshops. The children and young people’s library is also based in this building while the CHARLIE (3) building features the Steelpark Entertainment Center. There are installed multimedia and interactive exhibits presenting the different phases of steel production, as well as exhibits from the fields of physics, optics, geology, magnetism, metallurgy, biometrics, engineering and others. This centre was estab- lished in co-operation with U.S. Steel Koˇsice and Koˇsice universities. The centre is actively used by elementary schools in the city and the sur- rounding area as well as by visitors to the city. The DELTA (4) building serves as the information centre which is the point of contact for the visitors to Kulturpark Barracks. The smaller workshop pavilions of Echo (5), Foxtrot (6) and Oscar (7) mainly serve various community activities and are located among the greenery in the park. There are also multi- functional stages available for smaller art, entertainment or sports ac- tivities. At present, the Kulturpark Barracks are open to the public and are used by residents and visitors for relaxing. Fig. 2 shows the situa- tional plan of the Kulturpark Barracks (buildings are numbered throughout the text in brackets) while Fig. 3 present the barracks before and after the renovation respectively.
From a socio-economic point of view, the city and its inhabitants have gained a new attractive place through the renovation of an unused
and closed military complex. It allows cultural and social events to take place which was previously not possible due to the lack of adequate facilities and conditions. Therefore, the Kulturpark Barracks have become one of the most attractive places in Koˇsice. The research among citizens and visitors of Koˇsice presented in Hudec et al. (2019) has shown that prior to ECoC (2012), the most attractive place (sense of pace) in Koˇsice was the historic main street and cathedral. After ECoC (2017), the Kulturpark Barracks became one of the sense of place in Koˇsice.
3.2. Data
For the analysis, data was used from the real estate market for 1157 flats sold in Kosice between 2010 and 2018 provided by a two real estate agencies. There are no relevant data available to estimate number of flat sales in Koˇsice city, nor to estimate the market share of real estate agencies operating in Koˇsice region. Our data comes from two largest real estate agencies (according to the number of real estate agents) operating in Koˇsice city. According to our interview with the director of
one these two agencies, it is a problem for them to estimate the size of the market, but his qualified estimate is that our data should cover around 25% of all flats sold in the given timeframe, thus we considered our sample to be acceptable. The advantage of the dataset was in the availability of direct sales prices, the date of sale, and the exact location of the flats, not just to the advertised prices as is standard in this type of analysis. The disadvantage was the fact that the real estate agents did not record the state or possible renovation of the flats, which has to be taken into account when interpreting the results.
The variables from which the model was subsequently created and their descriptive statistics are presented in Table 1. It is worth noting the presence of several flats with low prices in the database. These flats were located in locations inhabited by ethnic minorities, making them almost unsellable in the ordinary market. Since there were only a few of them in the database, and later in the model with spatial aspects they could help explain prices in their immediate vicinity, they were not excluded from the analysis. Another fact to consider is that due to the character of flats block construction in Eastern Europe, the flats considered are of highly limited diversity. We divided them in to two basic categories forming the Fig. 1.Location of Kulturpark Barracks in relation to Koˇsice centre (using Open street maps under the Open Database Licence, https://www.openstreetmap.org/cop yright/en).
variable Construction, with brick and panel as possible categories, as explained further.
We considered a flat to be of brick construction, if it belonged to one of the 3 following categories, with examples presented in Fig. 4.
• A 4 stories high brick construction block of flats constructed mainly before 1970, characterized by above average floor space (often 30%+larger than equivalent panel construction flat), great thermal and noise properties, in most cases without an elevator or a balcony.
Fig. 2. Map of Kulturpark Barracks.
Fig. 3. Kulturpark Barracks before and after renovation.
All of them are localized in the wider city centre and Koˇsice-North (oldest city district), highly sought after and commanding a price premium.
• Flats directly in the historic city centre, often with extremely high floor space, without an elevator and a cellar, representing the most expensive flats in the city.
• New blocks of flats constructed in recent years, located all throughout the city. Mostly average floor space and with an elevator available but often with no cellar. Many of them represent gated communities belonging to the most expensive flats in the city. A negligible part of our sample, since new flat construction has accel- erated only in the past 2–3 years and most of the flats are sold by developers directly, thus not included in data provided by real estate agencies.
Flats of above average floor space with no elevator sold at a price premium are therefore characteristic for this category. The second category considered to be of panel construction contains most of the flats sold in the city, with only 2 main types of building and severely limited heterogeneity, examples presented in Fig. 5.
• 8 stories high block of flats constructed using prefabricated panels, with limited floor space of individual flats, contains an elevator and a cellars, with a balcony often available.
• 13 stories high tower block of flats constructed using prefabricated panels, with limited floor space of individual flats, contains an elevator and a cellars, with a balcony often available.
Table 1
Descriptive statistics and definition of variables.
Description Min Max Mean
Price Sale price in EUR 3500 352,127 67,202
Year Year of sale 2010 2018 –
No rooms Number of rooms in the flat 1 6 2327
Ownership Ownership status of the flat: 0 – private ownership (95.25%), 1 – cooperatively owned (4,75%)
– – –
Ground floor Is the flat located on the ground floor: 0 - no (92,91%), 1 - yes (7,09%)
– – –
Max floor Is the flat located on the top floor:
0 - no (87,04%), 1 - yes (12,96%) – – – Elevator Does the block of flats have an
elevator: 0 - no (16,08%), 1 - yes (83,92%)
– – –
Cellar Does the flat come with a cellar:
0 - no (36,21%), 1 - yes (63,79%) – – – Construction Construction of the block of flats:
0 - concrete panel (74,59%), 1 - brick (25,41%)
– – –
Balcony Does the flat come with a balcony:
0 - no (36,56%), 1 - yes (63,44%) – – – Area Floor space of the flat in m2 19,0 192,0 59,47 Centrum Distance from the city centre in m 52,21 6438,28 2579,47 Barracks Is the flat located within 1000 m
from the Kulturpark Barracks: 0 - no (86,43%), 1 - yes (13,57%)
– – –
Fig. 4. Brick construction blocks of flats typical for the city, pre 1970 4 stories block of flats on the left, historic city centre in the middle, new flats blocks on the right.
Fig. 5. Blocks of flats constructed using prefabricated panels typical for the city, 13 stories flats block on the left, 8 stories high flats block on the right.
A vast majority of flats contained in these two types of blocks of flats are either of the “Prague” or “Koˇsice” type constructed mainly between 1960 and 1989, with below average floor space, poor thermal and noise properties. These flats are often sold cheaper compared to an equivalent brick construction flat. It may be helpful to understand the specifics of these two categories, as it can significantly affect the interpretation of model results.
As for the other available variables, the variables Cellar, Balcony and Elevator indicate if the flat has access to the given amenities and we would expect a positive impact on price in each case. The variable Year is used to account for any possible time trend in sale prices, with a dummy variable created for each year except for 2010, used as the base year. The variable Ownership determines if the flat being sold was pri- vately owned by the seller or was cooperatively owned by a housing cooperative. While a vast majority of flats are privately owned, a constantly increasing trend, there are still some belonging to either private, state or employer formed housing cooperatives. We expect cooperatively owned housing to be at a price disadvantage due to a range of issues. It is currently harder to obtain a mortgage to finance a purchase of a cooperatively owned flat and any modifications or reno- vations have to be approved by the cooperative. The fact, that when buying a cooperatively owned flat you are actually buying only the right of usage and you do not become the owner of the flat itself is also perceived very negatively, as there is still a very strong cultural pressure to owning rather than renting housing. The purchase of the flat from the cooperative into private ownership is often complicated if at all possible.
The variables No Rooms and Area are both a measure of flat size. While in the case of panel construction flats the floor area is expected to be proportional to the number of rooms (as the room size is relatively standardized in this case), for brick construction flats the floor area can vary to such an extent we do not expect an overlap significant enough to cause multicolinearity in the model. Another pair of variables included in the model are dummy variables Ground Floor and Max Floor, based on which floor the flat is located at. In both cases we expect a negative influence on the sales price. Most people perceive an increased security risk and a lower level of privacy associated with flats located on the ground floor, especially in the hillier areas of the city where these flats can have some windows directly on the street level. Flats located on the top floor are often prices lower due to perceived heat related problems in the summer and possible water leaks during the winter, where these problems are not uncommon especially in panel construction flats. The variable Centrum represents the distance from the city centre measured in meters. Finally, a dummy variable Barracks was created for each in- dividual year, to indicate whether a flat was located close to the Kul- turpark Barracks and was sold in the given year. A threshold of 1000 m was selected to provide enough flats in the proximity of the studied area to perform the analysis. The flats were close enough to the investment site to expect an impact on prices. The variables used in the analysis should be sufficient to cover the existing variability, with the notable exception of flat antiquity and the state of the renovation as previously stated.
The location of the flats was contained in the database in the form of addresses, so we used an automated geocoding process programmed in
the R environment using a ggmap package and accessed Google API to get accurate GPS coordinates. The geosphere package in the R program was used to calculate the exact distance in meters, both from the city centre and from the Kulturpark Barracks. Table 2 presents the number of observations and average prices for each year. Price averages and annual changes for the city are consistent with data published by real estate agencies and the National Bank of Slovakia, supporting representative- ness of the sample.
The exact location of the analysed flats along with the spatial dis- tribution of prices in the city is shown in Fig. 6.
3.3. Hedonic pricing model
The hedonic pricing model assumes that goods sold consist of a set of inherent attributes, therefore differences in their prices can be explained using differences in these attributes (Rosen, 1974). This is an often-used method for real estate valuation, as it assumes that even though real estate can be heterogeneous, the value of real estate is affected by a set of measurable variables describing structural characteristics (size, number of rooms, state of renovation) (Ball, 1973; Clark & Herrin, 2000; Lin- neman, 1980), location characteristics (amenities, distance to city centre, socioeconomic characteristics of the neighbourhood) (Dubin &
Sung, 1990; Follain & Jimenez, 1985) and environmental characteristics (air pollution, presence of parks or forests) (Dubin & Sung, 1990), with better characteristics validating a higher price (Freeman, 1979). A wide range of studies using the hedonic price model in the real estate market is available, with Berry et al. (2003), Can (1992), Ebru and Eban (2011), Janssen and Soderberg (2000), Kim et al. (2015), Sheppard (1999), and Wilhelmsson (2000) as examples among others. In this case, this model was first constructed as a linear model using the ordinary least squares approach and later as a spatial error model (Anselin & Lozano-Gracia, 2009; Bhattacharjee et al., 2012; Won Kim et al., 2003).
4. Analysis
In order to analyse the data, the hedonic model method was used, using all available variables as previously described. The first step was to create a classic model along the lines of Lazrak et al. (2014) using the least-squares method defined as:
Table 2
Number of observations and average prices by year for the whole city and within 1000 m of the Kulturpark Barracks.
Year City Near Kulturpark Barracks
No. flats Avg price No. flats Avg price
2010 38 51,283.23 6 55,633.33
2011 181 57,613.33 21 54,062.86
2012 155 59,613.26 17 69,081.73
2013 138 61,324.93 17 68,264.71
2014 164 67,048.88 25 83,973.21
2015 128 68,034.59 24 73,324.17
2016 178 74,428.32 25 79,399.03
2017 116 78,570.7 15 88,128.57
2018 59 95,024.4 7 92,357.14
ln(Pricei) =α+ ∑2018
n=2011
β1nYearin+β2No roomsi+β3Ownershipi+β4First floori
+β5Maxfloori+β6Elevatori+β7Cellari+β8Constructioni+β9Balconyi+β10ln(Areai) +β11ln(Centrumi) +
∑2018
m=2010
β12mBarracksim
(1)
Subsequently, the model was tested using the standard tests – the Breusch Pagan test for heteroscedasticity (p =0.0005732) and Vari- ance Inflation Factor (max of 3.869) for multi-collinearity. The pres- ence of Heteroscedasticity could indicate the presence of spatial dependence, which we tested for later. The model results are shown in Table 3.
From the presented results, the variables Year, Number of rooms, Ownership, Ground floor, Construction, Area and Centrum were statistically significant. In the case of the dummy variables for in- dividual years, a trend of rising real estate prices in recent years can be observed, with an increase in 2016 corresponding to high annual price increase that was nationwide and not specific for the city. This can be attributed to the general economic situation in the country.
The positive coefficient for the variable Number of rooms is an ex- pected result as well as the positive coefficient for the variable Area.
Both reflect the higher prices for larger flats, although due to the different types of flats described previously, they are not a total equivalent when considering flat size. An interesting result is the negative coefficient for the Ownership variable, where flats in cooperative ownership have on average a lower sale price than flats in private ownership. Based on experience, it can be assumed that this result reflects the greater difficulty in obtaining mortgage credit financing for cooperative housing, as well as the fact that most
cooperatively owned flats fall into a lower price range. The negative coefficient of Ground floor was expected as discussed previously. The negative coefficient of the Centrum variable indicates the declining property prices with rising distance from the city centre which was also an expected result. Positive coefficient for the Construction variable was also expected, representing the higher average prices of brick construction flats. Of particular interest for us were the dummy Barracks variables for individual years, indicating a positive effect of the investment on flat prices, but only for a limited time. At a 10%
significance level we can perceive a positive impact on prices from 2012 up to 2015, meaning that the effect could be present right from the start of the reconstruction, and lasted up to 2 more years after completion, slowly evening out with time just as the nationwide price increase in 2016 caught up. The next step was to test for spatial dependence. Using the exact GPS coordinates of the flats, a distance matrix was calculated for all pairs of flats. Inverting this matrix, we calculated the Moran’s I with a result of p =0.000000714. We pro- ceeded by performing the diagnostic tests for spatial dependence according to Anselin (2003), with results in Table 4.
Based on the presented results, the spatial error model (SEM) was chosen, with the matrix of spatial weights for this model calculated using the method of the 3 nearest neighbours. The results are shown in Table 5, with the specification form as follows:
Fig. 6. Exact location and price distribution of the analysed flats in Koˇsice.
The results of this model do not differ much from the least-squares model, with the exception of the variable Max floor, which was previ- ously not significant. The negative coefficient is in line with our ex- pectations, as discussed previously. The only other difference is that now the dummy variable Barracks for the year 2015 is significant on the 5%
level. The rest of the interpretations remain the same, although the AIC has improved. Out of interest, the error distribution for both models was compared as seen in Fig. 7. While the differences in error distribution can only be seen in a few areas, it is enough to eliminate spatial auto- correlation according to the tests performed.
5. Discussion
The paper aims to enlarge theoretical knowledge in two areas. The first is the time stability of cultural infrastructure impact on property prices in neighbourhoods. The second is the question of gentrification caused by culture led urban regeneration.
According to Leishman (2013) each submarket within the city rea- ches a different price equilibrium, which can be sustained over long periods of time. Standard application of hedonic models is based on the assumption of stabile preferences over long periods of time regarding the change, whose impact on property prices are investigated (flood protection, new park, proximity to the forest, etc.). Studies listed in the literature review, do not deal with this issue and assume stabile impact
of investigated amenities on property prices. In the case of cultural infrastructure, especially new type of modern infrastructure with high share of contemporary art, the stability of preferences in time cannot be assumed. This type of cultural infrastructure has positive but also negative impacts, which can change in time according to performed activities, but also preferences of inhabitants. The change of these im- pacts in time can also change the preference of inhabitants and their willingness to live near the new cultural infrastructure. Therefore, this type of cultural infrastructure can be considered a “live organism” within the neighbourhood with changing impact on it. Our research proved, that the impact of this specific type of cultural infrastructure on property prices is not time stable and can change over time.
The Kulturpark Barracks is the largest city investment in cultural infrastructure in Koˇsice city, made with the aim of supporting culture led urban regeneration. The effect of concentration of different cultural
Table 3
Results of the OLS hedonic price model.
Estimate Std. error t statistic Probability
Intercept 8.302258 0.147185 56.407 0***
Year 2011 0.370893 0.062531 5.931 0***
Year 2012 0.361859 0.062854 5.757 0***
Year 2013 0.355933 0.063384 5.616 0***
Year 2014 0.366547 0.062746 5.842 0***
Year 2015 0.379799 0.06344 5.987 0***
Year 2016 0.511677 0.062636 8.169 0***
Year 2017 0.595265 0.066637 8.933 0***
Year 2018 0.707663 0.06534 10.83 0***
No rooms 0.030369 0.010983 2.765 0.006**
Ownership −0.09674 0.024199 − 3.998 0***
Ground floor −0.07617 0.020345 − 3.744 0***
Max floor −0.02785 0.015502 − 1.797 0.073
Elevator 0.036553 0.019058 1.918 0.055
Cellar −0.01564 0.012546 − 1.246 0.213
Construction 0.045433 0.016908 2.687 0.007**
Balcony −0.00334 0.011927 − 0.28 0.779
log(Area) 0.739242 0.030482 24.252 0***
log(Centrum) −0.09734 0.010171 − 9.57 0***
Barracks 2010 0.060315 0.038271 1.576 0.115
Barracks 2011 −0.0194 0.040241 − 0.482 0.63
Barracks 2012 0.087211 0.044748 1.949 0.052
Barracks 2013 0.089377 0.045013 1.986 0.047*
Barracks 2014 0.179218 0.034494 5.196 0***
Barracks 2015 0.067029 0.040376 1.66 0.097
Barracks 2016 0.054642 0.034682 1.576 0.115
Barracks 2017 0.112131 0.071076 1.578 0.115
Barracks 2018 −0.07403 0.069837 − 1.06 0.289
Degrees of freedom 1129
R2 0.7839
Adjusted R2 0.7789
* denotes a 5% level of significance, ** a 1% level and *** a 0,1% level
Table 4
Results of the diagnostic for spatial dependence.
Lagrange multiplier diagnostics for spatial dependence
LMerr =37.739 df =1 p-Value =8.087e− 10
LMlag =14.846 df =1 p-Value =0.0001167
RLMerr =23.101 df =1 p-Value =1.537e− 06
RLMlag =0.20823 df =1 p-Value =0.6482
SARMA =37.947 df =2 p-Value =5.752e− 09
Table 5
Results of the hedonic spatial error model.
Estimate Std. error t statistic Probability
Intercept 8.325394 0.155483 53.5453 0***
Year 2011 0.368586 0.06021 6.1217 0***
Year 2012 0.35894 0.060632 5.92 0***
Year 2013 0.348444 0.061176 5.6958 0***
Year 2014 0.355423 0.060524 5.8725 0***
Year 2015 0.376196 0.061128 6.1543 0***
Year 2016 0.514638 0.060272 8.5386 0***
Year 2017 0.594794 0.063693 9.3385 0***
Year 2018 0.696218 0.062884 11.0715 0***
No rooms 0.033356 0.011011 3.0293 0.002***
Ownership − 0.0922 0.023999 −3.8417 0***
Ground floor − 0.08313 0.019937 −4.1694 0***
Max floor − 0.03249 0.015082 −2.1545 0.031*
Elevator 0.036941 0.019529 1.8915 0.059
Cellar − 0.01162 0.012566 −0.9247 0.355
Construction 0.058186 0.017628 3.3007 0.001***
Balcony − 0.00617 0.011723 −0.5262 0.599
log(Area) 0.727161 0.030773 23.63 0***
log(Centrum) − 0.09484 0.012011 −7.8957 0***
Barracks 2010 0.05130 0.038972 1.3165 0.188
Barracks 2011 − 0.02264 0.041662 −0.5433 0.587
Barracks 2012 0.08221 0.04499 1.8273 0.068
Barracks 2013 0.089563 0.044525 2.0115 0.044*
Barracks 2014 0.177359 0.03522 5.0357 0***
Barracks 2015 0.085254 0.041332 2.0627 0.039*
Barracks 2016 0.040127 0.035666 1.1251 0.261 Barracks 2017 0.090206 0.069323 1.3012 0.193 Barracks 2018 − 0.04525 0.068055 −0.665 0.506
Lambda 0.20639
AIC: −822.02 AIC for lm: −790.33
* denotes a 5% level of significance, ** a 1% level and *** a 0,1% level ln(Pricei) =α+ ∑2018
n=2011
β1nYearin+β2No roomsi+β3Ownershipi+β4First floori+β5Maxfloori+β6Elevatori+β7Cellari+β8Constructioni+β9Balconyi +β10ln(Areai) +β11ln(Centrumi) +
∑
2018 m=2010
β12mBarracksim+εi εi=λWε+μi (2)
functions in a relatively small area usually leads to gentrification. As stated in literature, culture led urban regeneration usually trigger gentrification due to several factors. Redeveloped locality starts to be more attractive for more affluent consumers and potential residents, what usually increases the property prices and rents. Original in- habitants, especially those from vulnerable groups, may be displaced.
On the other hand, literature review shows that not all regeneration activities, especially those based on culture, must necessarily lead to gentrification. Although the aim of this paper was not directly focused on gentrification, our findings suggest, that in the case of Kulturpark Barracks in Koˇsice, new cultural infrastructure does not increase the property prices over a long period of time. Therefore in this case, the increase of property prices cannot be the reason for gentrification caused by cultural infrastructure. This short term impact on property prices can be explained by not reaching the critical mass as discussed in Cameron (2003). On the contrary, original inhabitants gain new amenities through the culture led regeneration, which they can benefit from.
Another question is the policy issues of sustaining the cultural infrastructure. As stated in the introduction, several cities are facing this issue. The city of London issued its Cultural Infrastructure Plan in March 2019 (Greater London Authority, 2019), containing a clear description of “How London’s cultural infrastructure is at risk”. The report identifies five individual issues (Land value increases; National planning system;
Business rate increases; Licensing restrictions and Funding reductions), which often overlap and worsen the situation. These issues often lead to shortage of cultural premises and business closures. Similar policy issues can also be found in the City of Vancouver report - Making Space for Arts and Culture: 2018 Cultural Infrastructure Plan (Vancouver City Council, 2018). This report summarizes the issues with sustaining the cultural infrastructure within the city. Based on a survey among cultural pro- viders, the main issues were the lack of affordable spaces to live, create and present, rapid pace of development displacing existing spaces and little property ownership and control. The last analysed report was from
Sydney – Making space for Culture in Sydney – Cultural infrastructure study 2020 (City of Sydney, 2020), where again the decrease of cultural infrastructure – comparing to city growth was identified and described.
The policy issues identified in these studies can be generalized as follows:
• Cultural infrastructure is a very important part of the city, with a positive socio-economic impact
• Cultural infrastructure is now at risk due to funding problems and increasing pressure from other sectors (housing, hotel and retail)
• There is a lack of clear evidence base to drive decision making.
A very similar situation is in Koˇsice city, where city representatives face the issue of how to justify sustaining the Kulturpark Barracks as the main cultural centre in Koˇsice city, especially when pressure from other sectors is increasing due to increasing land prices around the city centre.
Many examples of this issue can be found: “The Parr’s Head, Camden Town was one of many London pubs redeveloped for residential use in the past decade. While it was worth approximately £500k as a pub, with approval for conversion into residential property it was sold to a developer for £1.3m, and as six completed flats it was worth nearly £3m”
(Greater London Authority, 2019). “Hudson Ballroom. Formerly Plan B and Goodgod Small Club before that, this inner-city basement operated as a live music venue under various guises from 2010 until renovation of the heritage building into a boutique hotel forced the termination of the venue’s lease in 2018” (City of Sydney, 2020).
As stated above, cultural infrastructure often cannot compete in urban development with other commercial sectors (flats constructions, hotels, etc.). It needs “protection” and support from local authorities and local authorities need many good arguments for supporting cultural infrastructure from public sources. Hedonic pricing models can serve as one of the approaches that will provide good and quantified evidence for decision-makers to favour building, or sustaining cultural infrastructure Fig. 7. Comparison of error distribution for basic OLS model and spatial error model. Left – OLS model, right – spatial error model.