Unlocking neighborhood density
Bibliographic Data
| ID | 11079926 |
|---|---|
| Authors | Melanie Krause (0000-0001-9299-2366, Leipzig University of Applied Sciences), André Seidel (0000-0002-9170-4833, Western Norway University of Applied Sciences, corresponding author) |
| Year | 2024 |
| Volume | 144 |
| Pages | 103708 |
| Publication date | 2024-11-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Urban Economics (JOURNAL) |
| Journal identifiers | ISSN: 0094-1190 • E-ISSN: 1095-9068 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.jue.2024.103708 |
| OpenAlex | W4403286102 |
| Language | EN |
| Citations received | 4 |
| References cited | 30 |
Studying the components of neighborhood population density reveals a complex picture that little is known about. Hidden under the same level of population density, neighborhoods can vastly differ in crowding, if residential coverage or building heights are moving in opposite directions. We study this heterogeneity in density components and how it is linked to the variation in neighborhood socio-economic characteristics that define modern cities. To do so, we use novel high-resolution (10 m × 10 m) geo-spatial data on building height and footprints in combination with Norwegian register data. This data allows us to decompose the variation of density into its components, as well as along various margins. We identify urban spatial structures with a latent profile analysis. These data-driven density profiles turn out to be strongly associated with the sorting of people by socio-economic characteristics, such as income and demographic variables. Our results show that below the surface of density, there is the so-far unknown potential to learn about the prevalence and geography of socio-economic groups in the absence of micro-level data
Has Consumption Inequality Mirrored Income Inequality?
Why is central Paris rich and downtown Detroit poor?
Spreading of Covid-19
McLust 5
Unhappy Cities
Medieval cities through the lens of urban economics
Tall Buildings and Land Values
Testing the monocentric standard urban model in a global sample of cities
Housing estates in Europe
Motives for Tenure Choice during the Life Cycle
Air pollution in an urban world
Applied Latent Class Analysis
Life Cycle and Environmental Factors in Selecting Residential and Job Locations
Driving to opportunity
What is different about urbanization in rich and poor countries? Cities in Brazil, China, India and the United States
Accounting for central neighborhood change, 1980–2010
JUE Insight
Recreation Demand and Residential Location
The economic effects of density
The economics of urban yard space
Urban form and driving
The economics of skyscrapers
The vertical city
East-Side Story
| Citations per year | 4 |
|---|---|
| Citation span | 2025 - 2026 (2) |
| Highly cited | No |