Shopping centres and house values: an empirical investigation

Rosiers, François Des; Laganá, Antonio; Thériault, Marius; Beaudoin, Marcel

doi:10.1108/14635789610153461

Cited by 129 publications

(103 citation statements)

References 20 publications

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“…In particular, for variations of the variable ∆R below 100%, i.e., for the situations where the unit housing rents are at most doubled from 2011 to 2015, the changes in unit housing prices appear rather modest (maximum increase equal to 14.38%), whereas the variable ∆Y exponentially grows (up to +276%) for variations of the variable ∆R between 100% and 180%. This functional relationship exalts the role of the variable unit housing rent as a proxy for infrastructure facilities and services that concern with the locational characteristics of the municipalities in the sample being investigated, factors that, as noted in the reference literature, are the main determinants of the unit housing prices [58][59][60][61][62][63].…”

Section: Interpretation Of the Resultsmentioning

confidence: 99%

An Analysis of the Influence of Property Tax on Housing Prices in the Apulia Region (Italy)

et al. 2017

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Abstract:In this research, the socio-economic determinants of housing market values have been examined, highlighting their respective contributions to the formation of the property prices and, in particular, verifying the property tax liability. The property tax is a factor that could determine, through modest fluctuations, the revival of the property demand, generating positive effects also on the construction sector, which has been currently affected by the negative real estate contingency. The functional correlations of housing prices with the main socio-economic variables considered (i.e., housing rents, household incomes, household consumptions, property taxes, population and mean population age) have been explained through an econometric analysis implemented with an innovative methodology that uses multi-objective genetic algorithms. The analysis is contextualized to the Apulia region in the South of Italy, and the population of the sample studied consists of 258 individuals, corresponding to the municipalities of the region. In particular, the data collected for each variable considered refer to two different moments, that is, the year 2011 and the year 2015, in order to take into account the fiscal tightening that has occurred in Italy in this period of time. The elaborations carried out have allowed us to enucleate interesting functional relationships between property prices and the explanatory variables considered.

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Section: Interpretation Of the Resultsmentioning

confidence: 99%

An Analysis of the Influence of Property Tax on Housing Prices in the Apulia Region (Italy)

et al. 2017

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“…Earlier studies show a significant positive correlation between the three major factors characterizing the residential area's socioeconomic level -income, education and employment -and the price of dwellings (Heikkila 1992;Potepan 1996;Goodman and Thibodeau 1998;Greenberg 1999;Des Rosiers et al 2002;Yates 2002). Income is considered the primary factor (Ozanne and Thibodeau 1983;Malpezzi et al 1998).…”

Section: Dwelling Price In Light Of Socioeconomic Level Characteristicsmentioning

confidence: 99%

Dwelling Price Ranking versus Socioeconomic Clustering: Possibility of Imputation

Fleishman¹,

Gubman²,

Tur‐Sinai³

2015

Journal of Official Statistics

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In order to characterize the socioeconomic profile of various geographic units, it is common practice to use aggregated indices. However, the process of calculating such indices requires a wide variety of variables from various data sources available concurrently. Using a number of administrative databases for 2001 and 2003, this study examines the question of whether dwelling prices in a given locality can serve as a proxy for its socioeconomic level. Based on statistical and geographic criteria, we developed a Dwelling Price Ranking (DPR) methodology. Our findings show that the DPR can serve as a good approximation for the socioeconomic cluster (SEC) calculated by the Israel Central Bureau of Statistics for years when the required data was available. As opposed to the SEC, the suggested DPR indicator can easily be calculated, thus ensuring a continuum of socioeconomic index series. Both parametric and nonparametric statistical analyses have been carried out in order to examine the additional social, demographic, location, crime and security effects that are exogenous to SEC. Complementary analysis on recently published SEC series for 2006 and 2008 show that our conclusions remain valid. The proposed methodology and the obtained findings may be applicable for different statistical purposes in other countries which possess dwelling transactions data.

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“…Attempts to model the impact of landscape quality on house prices are even less numerous (Li and Brown, 1980;Des Rosiers, Thérault, Kestens and Villeneuve, 2002). Bourassa, Hoesli and Sun (2003) introduced indicators to reflect the panoramic view over expanses of water for conurbations of the city of Auckland, New Zealand, as well as a series of variables measuring the average landscape and building quality in the neighbourhood.…”

Section: Landscape Quality and Hedonic Studiesmentioning

confidence: 99%

The Impact of Housing Market Segmentation between Tourists and Residents on the Hedonic Price for Landscape Quality

Soguel

Martin

Tangerini

2008

Swiss J Economics Statistics

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Summary Market segmentation is an important issue when estimating the implicit price for an environmental amenity from a surrogate market like property. This paper tests the hypothesis of a segmentation of the housing market between tourists and residents and computes the implicit price for natural landscape quality in Swiss alpine resorts. The results show a clear segmentation between both groups of consumers, although tests also show that the estimated coefficient for landscape is similar in the tourists’ model and in the residents’. However, since the functional form is non linear, the nominal — rather than relative — value of a change in natural landscape quality is higher in the tourist housing market than in the residents’. Hence, considering the segmentation of the market between tourists and residents is essential in order to provide valid estimates of the nominal implicit price of natural landscape quality.

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Shopping centres and house values: an empirical investigation

Cited by 129 publications

References 20 publications

An Analysis of the Influence of Property Tax on Housing Prices in the Apulia Region (Italy)

An Analysis of the Influence of Property Tax on Housing Prices in the Apulia Region (Italy)

Dwelling Price Ranking versus Socioeconomic Clustering: Possibility of Imputation

The Impact of Housing Market Segmentation between Tourists and Residents on the Hedonic Price for Landscape Quality

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