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Spatial statistical modeling of housing price in Yangtze River Delta (Comparing with Pearl River Delta and BTH Coordinated Development)

Liu, Yunsong LU (2024) In Master’s Theses in Mathematical Sciences MASM02 20241
Mathematical Statistics
Abstract
This paper aims to explore the spatial statistical model of housing prices in the Yangtze River Delta (YRD) and compare it with prices in the Pearl River Delta (PRD) and the Beijing-Tianjin-Hebei Cooperative Development Area (BTH). By collecting the relevant data such as population structure, economic development level, and education level, and using a spatial statistical method, the paper constructs a spatial statistical model of the housing prices in these three regions. It is found that the housing prices in the YRD region show unique spatial distribution characteristics that are mainly affected by geography. In contrast, housing prices in the PRD and BTH regions also
have their own characteristics, showing spatial agglomeration... (More)
This paper aims to explore the spatial statistical model of housing prices in the Yangtze River Delta (YRD) and compare it with prices in the Pearl River Delta (PRD) and the Beijing-Tianjin-Hebei Cooperative Development Area (BTH). By collecting the relevant data such as population structure, economic development level, and education level, and using a spatial statistical method, the paper constructs a spatial statistical model of the housing prices in these three regions. It is found that the housing prices in the YRD region show unique spatial distribution characteristics that are mainly affected by geography. In contrast, housing prices in the PRD and BTH regions also
have their own characteristics, showing spatial agglomeration centered on a certain city. The models are based on a Bayesian approach, and inference is made using Integrated Nested Laplace Approximation (INLA). (Less)
Popular Abstract
The theoretical discussion on spatial analysis in the real estate industry dates back to the early 1960s. However, it's only in the past two decades that empirical studies have gained momentum, driven largely by geographers, while contributions from the real estate sector have remained relatively modest. Despite the pivotal role of location in real estate, spatial analysis has yet to become mainstream in research. Notably, growing theoretical and empirical foundations support the practical integration of spatial statistical models into real estate analysis, showing significant potential.

Have you ever wondered what influences housing prices in China's vibrant economic centers? This study delves into how economic development, demographic... (More)
The theoretical discussion on spatial analysis in the real estate industry dates back to the early 1960s. However, it's only in the past two decades that empirical studies have gained momentum, driven largely by geographers, while contributions from the real estate sector have remained relatively modest. Despite the pivotal role of location in real estate, spatial analysis has yet to become mainstream in research. Notably, growing theoretical and empirical foundations support the practical integration of spatial statistical models into real estate analysis, showing significant potential.

Have you ever wondered what influences housing prices in China's vibrant economic centers? This study delves into how economic development, demographic structure, and educational levels uniquely impact housing prices in the Yangtze River Delta, Pearl River Delta, and Beijing-Tianjin-Hebei Coordinated Development area.

In the Yangtze River Delta, exemplified by Shanghai's economic dynamism, we explore how rapid economic growth affects real estate values. Similar patterns driven by population density and economic development are observed in the emerging economic zones of the Pearl River Delta. Meanwhile, in the Beijing-Tianjin-Hebei Coordinated Development area, including Beijing and its surroundings, governmental regulations and concentrated educational resources play pivotal roles in shaping housing market dynamics.

Using spatial statistical models, this study reveals clear and reliable spatial patterns in housing price distributions across these regions. These insights are valuable for local planning authorities and real estate professionals, helping them formulate targeted policies to optimize housing market regulations effectively. (Less)
Please use this url to cite or link to this publication:
author
Liu, Yunsong LU
supervisor
organization
course
MASM02 20241
year
type
H2 - Master's Degree (Two Years)
subject
keywords
Housing price, Spatial statistical model, Temporal component, Bayesian inference
publication/series
Master’s Theses in Mathematical Sciences
report number
LUNFMS-3127-2024
ISSN
1404-6342
other publication id
2024:E24
language
English
id
9168562
date added to LUP
2024-06-26 13:48:37
date last changed
2024-06-26 13:48:37
@misc{9168562,
  abstract     = {{This paper aims to explore the spatial statistical model of housing prices in the Yangtze River Delta (YRD) and compare it with prices in the Pearl River Delta (PRD) and the Beijing-Tianjin-Hebei Cooperative Development Area (BTH). By collecting the relevant data such as population structure, economic development level, and education level, and using a spatial statistical method, the paper constructs a spatial statistical model of the housing prices in these three regions. It is found that the housing prices in the YRD region show unique spatial distribution characteristics that are mainly affected by geography. In contrast, housing prices in the PRD and BTH regions also
have their own characteristics, showing spatial agglomeration centered on a certain city. The models are based on a Bayesian approach, and inference is made using Integrated Nested Laplace Approximation (INLA).}},
  author       = {{Liu, Yunsong}},
  issn         = {{1404-6342}},
  language     = {{eng}},
  note         = {{Student Paper}},
  series       = {{Master’s Theses in Mathematical Sciences}},
  title        = {{Spatial statistical modeling of housing price in Yangtze River Delta (Comparing with Pearl River Delta and BTH Coordinated Development)}},
  year         = {{2024}},
}