2024公共卫生危机下的都市区划定和韧性：来自菲律宾的证据

Metabolic Area Delineation and Resilience Under a Public Health Crisis: Evidence from the Philippines

Abstract

This paper uses cellphone user flow data to delineate metropolitan areas (MAs) in the Philippines, identifying several large MAs that are not officially recognized and different spatial extents for the three officially designated MAs. Urban systems align more closely with Zipf's Law when considering the delineated MAs. MAs with a population exceeding 1 million have grown faster than officially defined urban areas and the country as a whole. Mobility restrictions during the coronavirus disease (COVID-19) pandemic led to fragmentation and contraction of MAs initially, but they rapidly rebounded as restrictions eased. Proximity, administrative boundaries, accessibility, and labor market complementarity are key factors driving MA formation.

Introduction

Metropolitan areas transcending administrative boundaries arise as urbanization progresses. They serve as vital engines for economic growth by operating as functionally autonomous spatial entities and generating significant agglomeration benefits. However, official recognition, planning, and management of MAs are rare in developing countries. The Philippines has formally recognized only three MAs—Metro Manila, Metro Cebu, and Metro Davao—since the 1970s, consisting of only 45 cities and municipalities out of over 1,600 nationwide. Given that economic connectivity and urban expansion are rarely confined within administrative boundaries, it is essential to delineate appropriate urban agglomerations for both research and practical purposes.

Methodology

The study employs the commute-based algorithm introduced by Duranton (2015) to delineate MAs within the Philippines. Hourly cellphone user flow data at the municipal level from January to September 2020 were used to construct average daily flows approximating commuting patterns by week. The analysis shows a high correlation between cellphone-based proxies and commuting flows estimated from Census microdata. Cellphone data allow for examining the dynamics of MAs on a weekly basis, unlike the decade-long intervals required by census data.

Findings

1. Urban Landscape Before the Pandemic: The delineated MAs reveal a different urban landscape compared to administrative boundaries, highlighting the importance of functional urban agglomerations.
2. Role of Metropolitan Areas: MAs play crucial roles in the urbanization process.
3. Comparison with Administrative Definitions: The delineation by pre-pandemic commuting flows differs from the administrative definitions of officially recognized MAs.
4. Impact of Quarantine Policies: Initial mobility restrictions led to fragmentation and contraction of MAs, but rapid recovery occurred as restrictions eased.
5. Key Factors Driving MA Formation: Proximity, administrative boundaries, accessibility, and labor market complementarity are important factors.

Conclusion

The delineation of MAs based on cellphone user flow data provides valuable insights into the urban landscape and dynamics of MAs in the Philippines. These insights are crucial for effective urban planning and management, especially in the context of public health crises.