Urbanization encompasses both population growth and land-use change, yet the relationship between urban population growth and urban land expansion (ULE) remains poorly understood. This study addresses this gap by investigating the relative contributions of population and economic growth (measured by GDP) to ULE across diverse geographic regions, economic development levels, and governance types. Understanding these drivers is crucial due to the projected 2.5 billion increase in global urban population by 2050. Uncontrolled urban expansion has significant negative consequences: increased greenhouse gas emissions, habitat fragmentation, biodiversity loss, inefficient resource use, and agricultural land loss. Conversely, compact growth is associated with improved health outcomes, economic growth, and resource efficiency. Existing research often focuses on single cities, countries, or regions, making it difficult to generalize findings. Furthermore, past studies frequently analyze multiple factors affecting ULE, without focusing specifically on the relative importance of population and economic growth across different contexts. This study specifically addresses this limitation by focusing solely on the relative impacts of population and economic growth on ULE and examining how these impacts are moderated by geographic region, economic development level, and governance quality. The central research question is: what matters more for ULE under different contexts: population or GDP growth?

The literature points to urban population growth, economic development, governance, and institutions as key factors shaping urban expansion. However, most studies are case-specific, hindering generalization. Existing global studies typically focus on a single year or time period and use country-level GDP data. This research distinguishes itself by explicitly testing the relative roles of population and GDP growth in shaping ULE across 300 cities over 45 years, considering two periods (1970–2000 and 2000–2014) and incorporating the mediating role of governance. The theoretical framework is rooted in urban scaling theory and a derivative urban expansion accounting framework, which breaks down urban land growth into components attributable to population and GDP growth.

The study uses data from various sources to analyze ULE, population growth, and economic growth (GDP per capita) from 1970 to 2014. Data on ULE for the pre-2000 period (1970-2000) came from a meta-analysis of city-based studies, while data for the post-2000 period (2000-2014) utilized a top-down approach using the Global Human Settlement Layer (GHSL) dataset. Population data for the pre-2000 period came from the World Cities Database, and for the post-2000 period from the Oxford Economics database. GDP data were city-level for China, India, and the U.S., and country-level for other countries. The analysis included 251 cities for the pre-2000 period and 363 cities (population exceeding 1 million) for the post-2000 period. Cities were categorized into regions (Africa, East and Southeast Asia, Europe, etc.) and income groups (low, lower middle, upper middle, high) based on World Bank data. Governance quality was assessed using Worldwide Governance Indicators (WGI), specifically the Rule of Law and Government Effectiveness indicators. Descriptive statistics were calculated, and linear regression models were employed to assess the influence of population growth, GDP per capita growth, and governance on ULE in both time periods. The models included various combinations of independent variables to account for region, income level, and governance. A specific method was employed to calculate the proportion of ULE attributed to population and GDP growth based on the fitted values of the regression models. The analysis was conducted using the R programming language.

The study reveals significant variability in the annual growth rates of ULE, population, and GDP per capita across cities and regions. On average, urban land expands at a slower rate than population or GDP growth, particularly in cities with over one million people. Geographic patterns show that cities with higher ULE growth rates than population growth are concentrated in China and East and Southeast Asia, while the opposite is true for Africa, the Middle East, India, Central and South America, and North America. Regression analysis consistently shows that population growth rate is a stronger driver of ULE than economic growth rate in both pre-2000 and post-2000 periods. In the post-2000 period, a one-unit increase in the population growth rate is associated with a 23% increase in the ULE rate, compared to a 12.4% increase with a one-unit increase in the GDP per capita growth rate. This finding remains robust after controlling for region, income level, and institutional factors. The analysis reveals an inverted U-shaped relationship between GDP per capita growth rate and ULE across income groups. The contribution of economic growth to ULE is low in low-income countries but increases significantly in middle-income countries before decreasing again in high-income countries. A similar trend is observed across regions, with the largest increase in the contribution of GDP per capita to ULE occurring in China, followed by India, Central and South America, and Africa. Although urbanization levels are strongly correlated with national income, urban land percentage shows little correlation with national income, especially in low-income countries such as those in Africa, highlighting the inefficient use of urban land and the lack of benefit from agglomeration economies. The analysis of governance indicators reveals that strong governance enables economic growth to contribute more to ULE than population growth. For countries with improving governance, a significant portion of ULE can be attributed to GDP per capita growth, especially in the post-2000 period. This suggests that effective governance creates conditions conducive to economic development, thus reducing the relative influence of population growth on ULE. The study also noted a tendency for more outward, low-rise urban expansion globally, except in countries with strong governance like China, South Korea, and several Middle Eastern countries where high-rise construction is more prevalent.

The study's findings demonstrate that population growth, more than economic growth, consistently drives ULE across diverse contexts. This has significant implications for sustainability and environmental change, especially in developing countries. The decoupling of ULE and economic growth in low-income regions, particularly in South Asia and Africa, suggests a need for targeted interventions. The inverted U-shaped relationship between GDP per capita growth and ULE indicates that the influence of economic growth on ULE increases during early economic development, but then decreases as a country reaches higher income levels, likely due to shifts in drivers of migration. Strong governance plays a critical role in facilitating the link between economic growth and ULE. The study emphasizes the simultaneous consideration of land supply and demand forces when understanding ULE. Demand is influenced by population and employment, preferences, and policy, while supply is impacted by planning, zoning, geography, and market forces. The quality of governance shapes how these market forces function. The authors acknowledge potential influences of external shocks like pandemics and climate change that may alter the projected trends.

The research concludes that population growth is a consistently significant driver of ULE, while the role of economic growth is contingent on governance and economic development. High ULE rates in low-income regions with limited economic growth highlight sustainability concerns. Effective governance is crucial for harnessing the positive effects of economic growth on urban development while mitigating the negative impacts of rapid population growth. Further research should explore the impact of external shocks and technological advancements on ULE patterns.

The study's reliance on existing datasets may limit the availability of detailed, city-level data for all variables in all time periods. The use of aggregate measures for population, GDP, and governance indicators could mask variations within cities. The analysis focuses on cities with populations over one million, potentially neglecting the dynamics of smaller urban areas. Future studies could incorporate additional factors such as land-use policies, technological innovations, and climate change impacts to provide a more comprehensive understanding of ULE.