Understanding City Size Distributions
Author Information
Author(s): Chen Yanguang
Primary Institution: Peking University, Beijing, China
Hypothesis
The study proposes a dual competition hypothesis of city development to explain the scaling relation between city rank and size.
Conclusion
The study concludes that city size distributions can be explained by the interplay of two effects: the Pareto effect indicating city number increase and the Zipf effect indicating city size growth.
Supporting Evidence
- The study shows that city size distributions follow Zipf's law.
- Mathematical experiments support the dual competition hypothesis.
- Empirical analysis of U.S. cities reveals two trends in city size growth.
Takeaway
This study looks at how cities grow in size and number, showing that they compete in two ways: some cities get bigger while others increase in number.
Methodology
The study uses mathematical experiments and scaling analysis to derive the parameters of city size distributions.
Potential Biases
Different algorithms may yield different results, potentially leading to biased conclusions.
Limitations
The study's findings may vary based on the algorithms used for data analysis and the definitions of cities.
Participant Demographics
The study analyzes 513 cities in the United States with urbanized area populations over 40,000.
Digital Object Identifier (DOI)
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