Public houses and house prices in Great Britain: a panel analysis

Cabras, Ignazio; Sohns, Franziska; Canduela, Jesus; Toms, Steven

doi:10.1080/09654313.2020.1726294

Cited by 10 publications

(10 citation statements)

References 38 publications

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“…The real estate prices of Wuhan are increasing at an alarming rate, associated with rapid industrialization and urbanization and consequent demands for various categories of real estate. A spatial heterogeneity analysis of real estate prices is considered crucial for revealing major issues in real estate market development, understanding effective strategies of economic macro control, and promoting the high-quality development of internal economics [46][47][48][49]. This paper uses the listed residential sale prices of Wuhan City, Hubei Province, China as characteristic price data, constructs a characteristic price model [30,[50][51][52][53][54], and conducts an experimental analysis.…”

Section: Study Area and Datamentioning

confidence: 99%

Simulating the Spatial Heterogeneity of Housing Prices in Wuhan, China, by Regionally Geographically Weighted Regression

Wang

Zhao

Zhang

2022

IJGI

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Geographically weighted regression (GWR) is an effective method for detecting spatial non-stationary features based on the hypothesis of proximity correlation. In reality, especially in the social and economic fields, research objects not only have spatial non-stationary characteristics, but also spatial discrete heterogeneity characteristics. Therefore, how to improve the accuracy of GWR estimation in this case is worth studying. In this paper, a regionally geographically weighted regression (RGWR) is proposed. Using incoming dummy variables, the zoning discrimination is added to the spatial kernel function of GWR, the spatial kernel function is modified, the spatial weight is optimized, and the influence of “near heterogeneous” observation points is reduced. In this paper, the residential sale price in Wuhan City is taken as an example in the analysis of three aspects: model performance, fitting effect and influencing factors. The results show that the introduction of a zoning dummy variables can significantly improve the model accuracy of a fixed bandwidth and adaptive bandwidth. Under a fixed bandwidth, compared with the GWR model, RGWR increases R2 and R2adj from 0.6776 and 0.6732 to 0.777 and 0.7746, respectively, and the Akaike information criterion, corrected (AICc) standard decreases by 37.4006 compared with GWR, which proves the effectiveness of the method.

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Section: Study Area and Datamentioning

confidence: 99%

Simulating the Spatial Heterogeneity of Housing Prices in Wuhan, China, by Regionally Geographically Weighted Regression

Wang

Zhao

Zhang

2022

IJGI

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“…The expansion of craft breweries has increased the variety of different craft beers available to British consumers, who now have a wide range of flavours from which to choose (Cabras, 2020). Several studies in literature analyse the demand for beer and its price elasticity in relation to brand and type (Tegene,1990; Lee and Tremblay, 1992; Hausman et al , 1994; Freeman, 2001), although there is still a paucity of research addressing cross-price elasticity among different types of beer.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In the the UK, several studies have focused on public houses or pubs and their importance in terms of economic development, social aggregation and the communities’ well-being (Maye et al , 2005; Muir, 2009; Cabras and Mount, 2017; Cabras and Lau, 2019). Many of these studies illustrated the positive impact generated by pubs in terms of employment opportunities, community cohesion and social engagement, reporting a progressing decline in their number and highlighting the potential negative implications for local communities and economies (Cabras et al , 2020).…”

Section: Introductionmentioning

confidence: 99%

How do beer prices vary across different pubs? An empirical study

Shakina

Cabras

2022

IJCHM

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Purpose This paper aims to investigate the impact of pubs and breweries’ attributes on beer prices by exploring and examining the variation of beer prices across pubs in York, UK. Design/methodology/approach Data gathered from five surveys of pubs conducted between 2012 and 2020 are used to test six research hypotheses analysing how factors such as location, type of ownership and management of pubs, beers’ characteristics and breweries’ attributes affect beer prices in the on-licence market. Findings Beer packaging, type of brewery, pubs’ ownership and management all have a significant impact on beer prices, with beer on average cheaper in premises owned by pub companies and breweries compared to independently owned pubs. Research limitations/implications Findings can have implications in the first instance, on current fiscal policies affecting beer prices and, on a broader scale, regulating alcohol consumption. Practical implications Understanding beer price mechanisms in the pub sector offers valuable insights to practitioners and policymakers about designing and delivering policies and actions aimed at halting the decline of pubs in the UK. Social implications Findings provide original information relevant for developing initiatives aimed at preventing excessive alcohol consumption in private premises, an issue commonly associated with problems such as alcohol-related diseases, loneliness and antisocial behaviour. Originality/value To the best of the authors’ knowledge, this study is the first, providing an empirical analysis of beer price mechanisms within the pub sector at such a granular level; findings have important implications for pubs and on-licence businesses and for local communities and economies.

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“…It has been confirmed that the Coronavirus Disease 2019 (COVID- 19) pandemic has posed significant impacts on the global economy [4], which has led to varying degrees of stagnation or even recession in the development of the global economy [5][6][7][8]. As the real estate market is one of the most active markets in China and plays a vital role in the Chinese economy, exploring the spatial heterogeneity of housing prices is Land 2023, 12, 167 2 of 24 considered to be crucial for revealing major issues in real estate market development, understanding effective strategies of economic macro-control, and promoting the highquality development of internal economics in the post-COVID-19 pandemic era [9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Exploring the Spatial Discrete Heterogeneity of Housing Prices in Beijing, China, Based on Regionally Geographically Weighted Regression Affected by Education

Wang

Zhang

Zhao

2023

Land

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Spatial heterogeneity analysis of housing prices, in general, is crucial for maintaining high-quality economic development in China, especially in the post-COVID-19 pandemic context. Previous studies have attempted to explain the associated geographical evolution by studying the spatial non-stationary continuous heterogeneity; however, they ignored the spatial discrete heterogeneity caused by natural or policy factors, such as education, economy, and population. Therefore, in this study, we take Beijing as an example and consider educational factors in order to propose an improved local regression algorithm called the regionally geographically weighted regression affected by education (E-RGWR), which can effectively address spatial non-stationary discrete heterogeneity caused by education factors. Our empirical study indicates that the R2 and R2adj values of E-RGWR are 0.8644 and 0.8642, which are 10.98% and 11.01% higher than those of GWR, and 3.26% and 3.27% higher than those of RGWR, respectively. In addition, through an analysis of related variables, the quantitative impacts of greening rate, distance to market, distance to hospitals. and construction time on housing prices in Beijing are found to present significant spatial discrete heterogeneity, and a positive relationship between school districts and housing prices was also observed. The obtained evaluation results indicate that E-RGWR can explain the spatial instability of housing prices in Beijing and the spatial discrete heterogeneity caused by education factors. Finally, based on the estimation results of the E-RGWR model, regarding housing prices in Beijing, we analyze the relationships between enrollment policy, real estate sales policy, and housing prices, E-RGWR can provide policy makers with more refined evidence to understand the nature of the centralized change relationship of Beijing’s housing price data in a well-defined manner. The government should not only carry out macro-control, but also implement precise policies for different regions, refine social governance, promote education equity, and boost the economy.

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Public houses and house prices in Great Britain: a panel analysis

Cited by 10 publications

References 38 publications

Simulating the Spatial Heterogeneity of Housing Prices in Wuhan, China, by Regionally Geographically Weighted Regression

Simulating the Spatial Heterogeneity of Housing Prices in Wuhan, China, by Regionally Geographically Weighted Regression

How do beer prices vary across different pubs? An empirical study

Exploring the Spatial Discrete Heterogeneity of Housing Prices in Beijing, China, Based on Regionally Geographically Weighted Regression Affected by Education

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