Property Prices Research Articles

Form, Affect and Debt in Post-Celtic Tiger Irish Fiction: Ireland in Crisis by Eóin Flannery

Reviewed by: Form, Affect and Debt in Post-Celtic Tiger Irish Fiction: Ireland in Crisis by Eóin Flannery Kevin Hargaden (bio) Eóin Flannery, Form, Affect and Debt in Post-Celtic Tiger Irish Fiction: Ireland in Crisis (London: Bloomsbury, 2022), ix + 239 pages Ireland almost went bankrupt in 2008. The aftermath was marked by devastating unemployment, a return to mass emigration, and the establishment of policy commitments directly responsible for the present housing crisis, along with innumerable cuts in funding and limitations on social initiatives as part of the crushing austerity regime. It is surprising how quickly the death of the Celtic Tiger has been assumed into Irish discourse as an event we all acknowledge but do not particularly need to reference. The economists who boosted the bubble are back on our screens and in our broadsheets as commentators. The ten-year anniversary passed without much more than a few newspaper features1 and we have slipped happily back into economic buoyancy, marked by inflated property prices and semi-regular chastisements about the importance of keeping wages low to maintain the market’s confidence in our productivity. It is hard not to think that this period in our recent history warrants more attention. And in Form, Affect and Debt in Post-Celtic Tiger Irish Fiction, Eóin Flannery, from Mary Immaculate College in Limerick, offers a crucial intervention. It might seem that an assessment of this period from an English literature department would be marginal. Surely it is the economists and sociologists who must take the lead on understanding the significance of these events? But Irish novelists were examining the economic and social changes wrought by the Celtic Tiger through the boom days and into the period of barren bust. Flannery considers Chris Binchy’s Open-Handed (2008), Peter Cunningham’s Capital Sins (2010), Dermot Bolger’s Tanglewood (2015), Donal Ryan’s The Thing About December (2015) and The Spinning Heart (2012), his debut novel that preceded The Thing About December in terms of publication but exists in a subsequent text within the novels’ narrative chronology. He also considers Claire Kilroy’s The Devil I Know (2012), Justin Quinn’s Mount Merrion (2013), Deirdre Madden’s Time Present and Time Past (2013), and Paul Murray’s The Mark and the Void (2015), as well as discussing the poem The Celtic Tiger (1999) by the late Denis O’Driscoll. Throughout these discussions, Flannery is concerned with ‘how authors of Irish literary fiction grapple with the registration of debt and indebtedness in the Celtic Tiger period and its aftermath’ (p. 9). This is a fascinating way into [End Page 127] an essential conversation – the abstract concepts of neoliberal capitalism can be illuminated in a fresh light when set inside the plot of a novel. There is a logical progression through the different books discussed. We start with Binchy and Cunningham’s novels which present ‘not a clinical analysis of a crudely divisive economic system but a second-hand description of well-known commoditized types’ (p. 38, emphasis original). These may be entertaining novels, but they are structured so as to engage with the Celtic Tiger in a way that re-inscribes the consensus narratives which are grouped under the ‘we all partied’ and ‘a few bad apples’ clichés. We end with The Mark and the Void, a complex novel which confronts the reader directly with what we think a novel is and what it can do. The relationship established between the main characters – a novelist named Paul suffering writer’s block and a depressed financier named Claude – allows Murray to draw attention ‘to the fictive nature of the macrostructure of high finance’ (p. 181). This is a work of literary criticism before it is a work of social analysis and Flannery’s insights offer readers a renewed appreciation of the works under discussion. Dermot Bolger’s Tanglewood is the focus for the second chapter and Flannery unveils the role shame plays in the narrative, proposing that while not perfect, the novel offers ‘a prompt with which to commence renewed discussions regarding the possibilities of shame in the Irish context’ (p. 73). Flannery shows us how Donal Ryan’s novels formally...

Housing affordability, quality of life, and residential satisfaction in the Austrian cross-border suburban region of Bratislava, Slovakia

Abstract Bratislava’s satellites have experienced massive development in recent years. The population of a regional centre has moved into its Slovak hinterland. However, Bratislava’s cross-border suburbs have recorded spectacular population growth too. After 2008, housing in the EU became more affordable due to rising incomes and decreasing bank interest rates. Yet, the housing affordability index in the EU (and in the studied area) decreased in recent years due to increasing property prices and, more recently, a reverse tendency in bank interest rates. Through a questionnaire, we sought to establish a link between housing affordability and suburban residents’ expected quality of life. We assumed that a large proportion of the population had moved here specifically for a higher quality of life (residential satisfaction) and more affordable housing. Indeed, these were among the most common reasons for moving, with a large proportion of respondents choosing at least one. The Mann-Whitney U test showed that residents who moved to the Austrian suburbs of Bratislava for affordable housing were more satisfied with living in the municipality and housing costs. The article tries to fill the gap in the literature on housing affordability in suburban areas and on the quality of life of cross-border suburban residents.

Influence of macroeconomic variables on financing of mortgage products by commercial banks in Kenya

Various macroeconomic variables including gross domestic product (GDP), interest rate, inflation,money supply, and exchange rate, among others, have implication on financing of mortgage byfinancial institutions including Banks. In this paper, these variables are incorporated so as to analyze the influence of macroeconomic variables on mortgage financing by commercial banks. This studysought to determine the influence of macroeconomic variables on the financing of mortgage marketproducts among commercial bank in Kenya. The study surveyed 196 head of documentation, creditoperations, credit manager, legal, finance, relationship manager and head of retail sales from 28commercial banks that offer mortgage products. Data was collected by the use of structuredquestionnaire. Findings on the effect of macroeconomic variables on the level of mortgage productsfinancing showed that that there is a statistically significant correlation between financing of mortgageproducts and macroeconomic variables (r=.731, p<.0.000). In addition, results showed thatmacroeconomic variables explain the variations of 53.5% of the mortgage financing. Based on theresults, this paper concludes that macro-economic variables in terms of general price levels, grossdomestic product, exchange rate and interest rate have a statistically significant influence on financingof mortgage products. Results are also conclusive that the additional costs on property price discouragebuyers in acquiring property. The exchange rate applied at any given time affects financing ofmortgages. This study recommends that commercial banks should develop a system that constantlymonitors the macroeconomic environment to determine if the conditions are favorable for mortgageprovision. The system should be developed to monitor macroeconomic indicators such as income level,inflation, interest levels, and exchange rates. Importantly, commercial banks should set favorable downpayment, that clients can afford to payment at once and clear the balance in installments.

Assessment of the Contribution of Environmental Attributes to Residential Property Rental Value in Abuja

The contribution of environmental attributes in residential price determination is premised on the issue relating to inefficient attributes pricing. The study analysed three environmental attributes such as structural, neighbourhood and natural attributes of the environment with a view to determining its hedonic value upon which residential property price is derived. In order to achieve the aim of the study, a sample size of 2401 was drawn out of 104166 properties using estimation method; 50% estimation rate and precision range of ±4 were adopted in estimating the sample size. The study administered two set of structured questionnaires; one to Estate Surveyor and Valuer firms to collect data on rental values (2008-2019) and second questionnaires were administered on the respondents to collect information on condition of environmental attributes using the census and simple random sampling method technique. Hedonic regression was employed to analyse the data. Environmental attributes were scored based on current condition and ratio scale was used alongside the average property value. The result revealed that neighbourhood attributes contributed between 60.3% -71.6%, natural attributes contributed between 60.3%-71.7% while structural attributes contributed between 66.8%-75.1% in determining the property values across the selected areas. The result of mixed regression analyses further revealed that environmental attributes contributed about 70.1% in determining the value of property in the selected areas. Environmental attributes such as natural and man-made water supply, road, quality wall-structure and floor, landscape, bathroom and streetlight contributed significantly in the determination of property values across the study areas. The study therefore concludes that the value of environmental amenity should be captured in the price of residential properties close to it. It is recommended that every stakeholders in the built environmental advocate for quality and even distribution of common environmental facilities that are key to development of property market in Nigeria.

Stranded houses? The price effect of a minimum energy efficiency standard

Climate policies aimed at reducing greenhouse gas emissions can lead to decreases in the values of assets, risking them to become “stranded”. We study the price effects of the introduction of a specific climate policy, a minimum energy efficiency standard, in the housing market. Leveraging a unique data set of the population of all residential house transactions in England and Wales, we show that prices of energy-inefficient properties affected by this policy decreased on average by about £5k to £9k relative to efficient ones. We interpret this evidence as being consistent with semi-strong market efficiency in the housing market.

Unpriced climate risk and the potential consequences of overvaluation in US housing markets

Climate change impacts threaten the stability of the US housing market. In response to growing concerns that increasing costs of flooding are not fully captured in property values, we quantify the magnitude of unpriced flood risk in the housing market by comparing the empirical and economically efficient prices for properties at risk. We find that residential properties exposed to flood risk are overvalued by US$121–US$237 billion, depending on the discount rate. In general, highly overvalued properties are concentrated in counties along the coast with no flood risk disclosure laws and where there is less concern about climate change. Low-income households are at greater risk of losing home equity from price deflation, and municipalities that are heavily reliant on property taxes for revenue are vulnerable to budgetary shortfalls. The consequences of these financial risks will depend on policy choices that influence who bears the costs of climate change.

Transaction price prediction of second-hand houses in Wuhan based on GA-BP model

The significance of the used housing market to the stability of people's lives and social development is increasing, and the prediction of its prices is becoming a key concern for society. In this paper, BP neural network model is used to predict the price of second-hand properties. In view of the disadvantages of slow convergence and the tendency to obtain local optimal solutions, the BP neural network model's input layer is optimized by a genetic algorithm to speed up the convergence speed and accuracy of the BP neural network model. The experimental results show that the improved GA-BP neural network has high prediction accuracy, with RMSE and MAE of 398.72 and 170.18, respectively. The difference between the actual and predicted values is small, which can provide a more stable tool for predicting house prices in the second-hand property market and broaden a new channel for the practical application of GA-BP neural network.

Practical Applications of Climate Risk and Real Estate Prices: What Do We Know?

In <b><i>Climate Risk and Real Estate Prices: What Do We Know?</i></b> from the October 2021 Special Real Estate Issue of <b><i>The Journal of Portfolio Management</i></b>, <b>Jim Clayton</b> of <b>York University</b> and <b>Steven Devaney</b>, <b>Sarah Sayce</b>, and <b>Jorn Van de Wetering</b>, all of the <b>University of Reading</b>, find that growing awareness of climate risks to real estate has had a sustained, if imprecise, effect on decision-making, including property pricing and lending practices. The authors analyze the connections between property values and extreme-weather events and climate risk. They review existing, often ambiguous, studies on climate risk’s effects on (primarily residential) property values and on associated real estate market activities. They then derive conclusions about how these risks, and perceptions thereof, may affect commercial property markets and investors. Because much of the existing research concerns the residential market and the mostly short-term impacts on pricing after weather events, more research is needed. Still, there are conclusions that real estate stakeholders can draw from the existing research: Property prices often modestly decline after weather events; climate change might have longer-term impacts on values, often depending on stakeholder beliefs; and sustained risk-mitigating government involvement might limit price declines in areas subject to increased climate risk.

The relationship between macroeconomic variables on residential property price: case study in Malaysia before and during COVID-19

PurposeThe purpose of this study is to analyse numerous aspects affecting residential property price in Malaysia against macroeconomics issues such as gross domestic product (GDP), exchange rate, unemployment and wage.Design/methodology/approachThe hedonic pricing model has been adopted as econometric model for this research to investigate the relationship between residential property price against macroeconomics indicator. The data for residential property price and macroeconomic variables were collected from 1991 to 2019. Multiple linear regression had been adopted to find the relationship between the dependent and independent variables.FindingsThe result shows that the GDP has a significant positive impact on residential property price, while exchange rate has no significant impact although it was positive. In addition, the unemployment rate has a significant impact on the residential property price and has a negative relationship. Similar to the wage that shows the negative relationship with residential property prices. Moreover, during the pandemic COVID-19 in Malaysia, this research shows a more transparent view of the relationship between residential property price and the macroeconomic issues of GDP, exchange rate, unemployment and wage.Originality/valueThe findings of this research found that macroeconomics issue cannot be eliminated due to Malaysia is a developing country, and there will always be an issue that will happen, but the issues can be reduced to maximise the advantages, e.g. during COVID-19, the solution to fight against COVID-19 were crucial and weaken the macroeconomics issues.

Residential Property Price Index in Nigeria: A Data Mining Approach

We employ the web-scraping technique and IMF residential property prices index methodology outlined in the latest RPPI practical compilation guide to compute the Nigeria’s Real Estate property Price Index (RPPI). The data was scraped from one of the largest real estate website in Nigeria hosting the largest real estate ads online. A total of 35,957 residential property sales ads comprising of 30,693 house and 5,264 flat/apartment listing from October 2021 to October 2022 was used for the study. A web scraping code was implemented in R-statistics to get the data. The asking price and other related information gotten from the website was used to compute the overall RPPI and its sub indices (for house and flats/apartments). The findings present the RPP national (total) index and sub-indices for the residential building (house) and residential flat/apartment. While the various data sources used in generating data for the RPPI computation have their advantages and disadvantages, the web scraping method provides a very timely approach, as data can be scraped almost immediately. This ensures timely policy decisions and implementation and also reduce the cost of survey tremendously if not totally. The study recommends the use of the web scraping technique in the generation of RPPI data to ensure timely policy decisions and internationally acceptable standard of RPPI compilation. With the web scraping approach to data collection, high frequency RPPI like monthly or weekly may be computed for the country.

Machine Learning of Usable Area of Gable-Roof Residential Buildings Based on Topographic Data

In real estate appraisal, especially of residential buildings, one of the primary evaluation parameters is the property’s usable area. When determining the property price, Polish appraisers use data from comparable transactions included in the Real Estate Price Register (REPR), which is highly incomplete, especially regarding properties’ usable areas. This incompleteness renders the identification of comparable transactions challenging and may lead to incorrect prediction of the property price. We address this challenge by applying machine learning methods to estimate the usable area of buildings with gable roofs based only on their topographic data, which is widely available in Poland in the Database of Topographic Objects (BDOT10k) of Light Detection and Ranging (LiDAR) origin. We show that three features are enough to make accurate predictions of the usable area: the covered area, the building’s height, and the number of stories optionally. A neural network trained on buildings from architectural bureaus reached a 4% median percentage error on the same source and 15% on the real buildings from the city of Koszalin, Poland. Therefore, the proposed method can be applied by appraisers to estimate the usable area of buildings with known transaction prices and solve the problem of finding comparable properties for appraisal.

Everyday scalar politics: navigating insecurity in the competitive city

ABSTRACT This contribution asks how urban inhabitants (trans)form their everyday practices in the face of insecurity in Neoliberal Urbanism. Based on the analysis of interviews conducted in the Southern Mexican city of Oaxaca, which has seen enormous rises in property prices, short-term rentals, and numbers of tourists, I argue that urban dwellers adapt to asymmetrical manifestations of insecurity through care networks and adapted mobilities, and such everyday practices sometimes turn into more collective, political practices. By combining feminist perspectives on everyday practices in austerity, relational geographies, and work on everyday responses to insecurity, I develop the notion of “everyday scalar politics’ to offer a relational reading of city-dwellers’ practices in the competitive city. The concept highlights that those not participating in formal governance decisions, do enact political agency, and reach beyond their neighbourhood and the local state, unsettling assumptions of passivity.

Capitalisation rates for commercial real estate investments: evidence from Australia

PurposeThe paper is motivated by the paucity of empirical research on the determinants of capitalisation rates/yield in the commercial property market. Compared to property price determinants, the capitalisation rate has received significantly less attention. This is somewhat surprising given that the capitalisation rate is a more insightful indicator for investors on commercial property market performance than merely price changes or trends. The capitalisation rate, measured as the ratio of net operating income to the property’s capital value, captures the asset’s overall ability to generate income which is crucial for investors who typically invest in property for their income-generating capacity. The purpose of this paper is to address these issues.Design/methodology/approachTo evaluate the determinants of capitalisation rates, time series analysis was used. The data capture performance in the Australian commercial property market between 2005 and 2018. All macroeconomic and financial data are freely available from official sources such as the Australian Bureau of Statistics and the nation’s central bank. Methodology wise, given the problematic nature of the data such as a mixed order of integration and the possibility of cointegration amongst some of the I (1) variables, the autoregressive distributed lag model was selected given its flexibility and relative lack of assumptions.FindingsBond rates, market risk premiums, stock market excess returns and other macroeconomic variables were found to drive capitalisation rates of Australian commercial properties. A 1% increase in the bond rate results in approximately 0.3–2.4% increase in capitalisation rates depending on the sub-market. Further, a 1% increase in excess market returns results in a 0.01–0.02% increase in capitalisation rates. Regarding risk premiums, a 100 basis point increase in the BBB spread results in approximately 0.92–1.27% reduction in cap rates in certain markets.Practical implicationsAsset managers will find these results useful in asset allocation strategies. Commercial properties offer attractive investment qualities such as yield stability in periods of economic uncertainty while allowing for the possibility of capital growth through appreciation of the underlying asset. By understanding the factors that affect the capitalisation rate, practitioners may predict emerging trends and identify threats to portfolio return and stability. This allows better integration of commercial property in the construction of portfolios that remain robust in a variety of market conditions.Originality/valueThe contribution to literature is significant given the lack of similar studies in the Australian market. The performance of real estate assets using cap rates as a comparative measure to equities and bonds influences decisions in asset allocation strategies. It provides crucial information for investors to estimate the performance of commercial property. This research supports the notion that both space and capital market indicators jointly affect capitalisation rates. The findings expand the knowledge base relating to commercial properties and validate the assessments of investors, developers and valuers who utilise yield as a performance benchmark for asset allocation strategies.

Parking not included: The effect of paid residential parking on housing prices and its relationship with public transport proximity

Under-priced street parking is widely considered to be a great urban policy failure and is partly what motivated Stockholm to expand its parking zones for both visitors and residents from 2016 onwards. In this paper we use a unique natural experiment to study the effect of priced parking on property prices in Stockholm suburbs. We find that apartment prices were negatively affected by the unexpected appeal and subsequent revocation of parking fees. This finding is interpreted to mean that the introduction of priced parking yielded benefits to apartment residents in the studied areas, which were capitalized in the price of housing. Based on our estimated results, we find that the implied benefits to residents amounted to the equivalent of approximately €2.5 per day. We investigate whether apartments were differentially impacted based on their distance to public transit but find no strong evidence to support this hypothesis. For single-family homes, no conclusions can be drawn as the standard errors are large in relation to the estimated effects.

The Price Premium in Green Buildings: A Spatial Autoregressive Model and a Multi-Criteria Optimization Approach

The energy issue has given rise to a prolific research field, which branches into several strands. One of these strands focuses on the role played by building energy features in shaping property prices. Indeed, market players are expected to show a higher willingness to pay for building units characterized by higher energy performance. The study of the so-called price premium for building energy efficiency has flourished in the last decade or so; plenty of evidence is now available concerning its occurrence, although its magnitude is still debated. The literature relies on the methodological frameworks of statistical modeling and multiple regression, primarily employing hedonic price models. Lately, spatial autoregressive models have also been adopted. Here, we propose to deal with estimation of the price premium by adopting an innovative perspective. In particular, we use a methodological framework in which regression models are complemented with a multi-criteria optimization approach. Using a spatial autoregressive model first, and with D as the reference energy rating band, we find the following price premiums: 55% for A4, 42% for A3 to A, 20% for B or C, −14% for F, and −29% for G. The multi-criteria optimization approach proves efficient in estimating the price premium. The estimates above are essentially confirmed: the results converge for all the energy rating bands except for G.

House price indexes: an empirical exercise using spatial data analysis.

The housing market occupies a central place within any society. Residential property represents the essential parts of most families’ wealth, as well as a substantial part of their monthly expenditure. It also represents a large fraction of private investment, generating significant earnings. However, and despite this importance, the compilation of reliable residential property price indexes (RPPI) is far from satisfactory in Portugal, revealing an important gap in the field of statistical information. The construction of a residential property price index (RPPI) poses particular problems arising from the inherent nature of the object concerned. Considering the gap in Portugal regarding the lack of a sufficiently enlarged database allowing the compilation of reliable RPPIs, this article seeks to contribute to this area, proposing a methodology applied to the urban area of Aveiro and Ílhavo by means of a spatial data analysis.

City subcenter as a regional development policy: Impact on the property market

AbstractThe aim of this study is to perform a locally specific investigation of a polycentric development policy through the lens of the property market. The capital city of China, Beijing, adopted a subcenter program for the purpose of developing a new economic growth pole in the suburbs through the redistribution of administrative and economic resources. Herein, we exploit spatial and temporal differencing in microproperty transaction data to address the issue of nonrandom selection of the site for developing the subcenter. The results show that in the first year after announcing the subcenter program, property prices in the subcenter rose by 10.5%, stabilizing at approximately 20% after 2 years of continuous increase. Moreover, property price growth decreases sharply with increased distance from the new administrative center in the subcenter, which will host tens of thousands of civil servants under the subcenter program. In response to the subcenter‐induced demand shock, locations with elastically supplied housing have experienced greater population growth and weaker appreciation in property prices. Although strict purchase restrictions have helped stabilize the subcenter's property market to some extent, the fever has spread to adjacent markets. The specific geography of property market dynamics provides an important channel to evaluate the impact of the subcenter program and offers insight regarding the development of tactics to optimize subcenter outcomes.

Examining key macroeconomic determinants of serviced apartments price index: the case of Kuala Lumpur, Malaysia

PurposeIncreasing overhang of serviced apartments poses a serious concern to the national property market. This study aims to examine the impacts of macroeconomic determinants, namely, gross domestic product (GDP), consumer confidence index (CF), existing stocks (ES), incoming supply (IS) and completed project (CP) on serviced apartment price changes.Design/methodology/approachTo achieve more accurate, quality price changes, a serviced apartment price index (SAPI) was constructed through a self-developed hedonic price index model. This study has collected 1,567 transaction data in Kuala Lumpur, covering 2009Q1–2018Q4 for price index construction and data were analysed using the vector autoregressive model, the vector error correction model and the fully modified ordinary least squares (OLS) (FMOLS).FindingsResults of the regression model show that only GDP, ES and IS were significantly associated with SAPI, with an R2 of 0.7, where both ES and IS have inverse relationships with SAPI. More precisely, it is predicted that the price of serviced apartments will be reduced by 0.56% and 0.21% for every 1% increase in ES and IS, respectively.Practical implicationsTherefore, government monitoring of serviced apartments’ future supply is crucial by enforcing land use-planning regulations via stricter development approval of serviced apartments to safeguard and achieve more stable property prices.Originality/valueBy adopting an innovative approach to estimating the response of price change to supply and demand in a situation where there is no price indicator for serviced apartments, the study addresses the knowledge gap, especially in terms of understanding what are the key determinants of, and to what extent they influence, the SAPI.

The local socio-economic impact of improved waterborne public transportation. The case of the New York City ferry service

This paper looks into the recent actions of the New York City government to connect its five boroughs over water and the consequential impact on the socio-economic conditions of local coastal neighborhoods. The predictions from the Comprehensive Citywide Ferry Study (CFS2013) are contrasted with actual data and observations of the transformations that have taken place in the direct surroundings of a selection of ferry terminals, both in terms of spatial changes, as well as economic growth or decline.The paper starts with an illustration of how different modes of waterborne transportation steered urban transformation processes and coastal land uses over time. Next, the paper explains the rise of the NYC ferry network as a contemporary answer to a growing demand for public transportation that connects coastal neighborhoods. A comparative analysis between a selection of ferry landings reflects upon the impact that improved accessibility has on neighborhoods’ spatial, social, economic, and environmental conditions. The paper studies several parameters, including the neighborhoods’ property prices, employment rates, daily commutes, development interest, demographics, and tourism.What distinguishes this paper from other studies is the direct link between the quantitative data and the social, economic and environmental characteristics of the surroundings of the ferry landings. Instead of providing a mere technical analysis, the paper studies the transformation of neighborhoods in proximity to the ferry stops and reflects upon hypothetical future impact of new ferry stops. A link is made between the quantitative results of existing studies to a case analysis of the concerned neighborhoods. Whereas the methodology used in this paper is a combination of both a theoretical and an empirical analysis of New York City's waterfront, the main goal is to provide a theoretical contribution by notion of a case study approach.

The effect of Movida on residential property prices: up or down?

ABSTRACT Hedonic regression technique has often been used to study the effect of road, railway and airport noise on property prices. However, European cities are experiencing a particular type of noise pollution originated by night-time recreational activities mainly located in the city centres, the so-called ‘Movida’, which has not been properly investigated yet. The aim of this paper is to examine the effect of recreational noise on residential property prices. We used an original highly detailed housing transactions dataset from the City of Turin covering the period 2017 to 2018 and built an indicator of recreational noise based on the proximity of dwellings to the night recreational activities. The results obtained employing hedonic modelling show that the adverse environment for an apartment located in a ‘Movida’ district will result in a lower market value as compared to an apartment with similar characteristics, except for recreational noise. This occurs because potential buyers reduce their demand, as they discount the present value of the costs of annoyance, loss of tranquillity and health effects due to sleep deprivation.