Multilevel approach to the analysis of housing submarkets
Bibliographic Data
| ID | 7366647 |
|---|---|
| Authors | Berna Keskin (corresponding author) |
| Year | 2022 |
| Volume | 9 |
| Issue | 1 |
| Pages | 264-279 |
| Publication date | 2022-05-27 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Regional Studies Regional Science (JOURNAL) |
| Journal identifiers | ISSN: 2168-1376 • E-ISSN: 2168-1376 |
| Publisher | Taylor & Francis (PUBLISHER • GB) |
| DOI | 10.1080/21681376.2022.2067005 |
| OpenAlex | W4281664037 |
| Language | EN |
| Citations received | 2 |
| References cited | 43 |
There is a vast literature that seeks to define and identify spatial submarkets in metropolitan housing systems. These tend to use one of three methods to delineate submarkets: a priori geographies, ad hoc subdivision and data-driven approaches to grouping units. Recently, analysts have increasingly used multilevel modelling strategies to analyse spatial segmentation in the housing market. Despite the increasing prevalence of multilevel approaches, there is no existing systematic analysis of which of these three main approaches to submarket definition has the greatest effectiveness when employed in a multilevel modelling framework. This paper addresses the gap in the literature by comparing the utility of these main approaches to submarket definition. It develops and evaluates three separate, distinct multilevel models of submarkets to a data set comprising 2175 transactions in the Istanbul housing market of Turkey, an emergent market context. The results show that multilevel models with a priori submarket dummy variable can predict price more accurately than the models with ad hoc subdivision or data-driven stratified submarkets. Similarly, test results indicate that multilevel models with neighbourhood submarket dummy variables (a priori) perform better than other models. These test results show that granular definition of submarkets tend to perform better in terms of predictive accuracy than less spatially granular models. The paper also suggests that real estate agents’ views of submarket structures might be particularly useful as inputs into micro-modelling processes in contexts where datasets are thin
Economic geography · Geography · Housing Market and Economics · Housing, Finance, and Neoliberalism · Urbanization and City Planning
Housing Markets and Public Policy
Hedonic modelling, housing submarkets and residential valuation
Housing market segmentation and hedonic prediction accuracy
Do housing submarkets really matter?
Housing Market Segmentation
Defining Housing Submarkets
A multilevel analysis of housing submarkets defined by the municipal boundaries and by the street connections in the metropolitan area
Emergence, formation and outcomes of flexibility in Turkish planning practice
Under examination
Spatial Change and the Structure of Urban Housing Sub-markets
Technological change and estate agents’ practices in the changing nature of housing transactions
Economic perspectives on the structure of local housing systems
Online Housing Search and the Geography of Submarkets
Defining neighborhood boundaries
The Predictive Performance of Multilevel Models of Housing Sub-markets
The Definition of Housing Market Areas and Strategic Planning
The Property Market
A Multi-level Analysis of the Variations in Domestic Property Prices
Modelling Spatial Structures in Local Housing Market Dynamics
A Unified Framework for Measuring Preferences for Schools and Neighborhoods
Modelling Complexity
The Great Failure
Drivers of spatial change in urban housing submarkets
The Definition and Identification of Housing Submarkets
The Spatial Context of Social Integration
| Unique citing works | 2 |
|---|---|
| Citations per year | 1 |
| Citation span | 2024 - 2025 (2) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 2 |