Meanwhile, Ferré et al. (2012) conducted a study that focuses on the relationship between poverty and city size in eight low- and middle-income countries.<sup>11</sup> They employed a small area estimation method to estimate poverty for specific geographic units. The study revealed that poverty incidence tends to be higher in smaller towns, and a significant concentration of poverty is observed in these areas. While the study provides valuable insights, it also has some limitations. For instance, it used each country’s national poverty line instead of global poverty lines, which may limit the comparability of the results across countries. Additionally, the study did not consider the distinction in the cost of living based on city size, and similar to Ravallion et al. (2007), it did not apply a consistent urban definition across countries.

These studies contribute to our understanding of the spatial dynamics of poverty, but they also highlight the need for further research improvements in methodology to address the challenges associated with defining urban areas, measuring poverty consistently across countries, and accounting for variations in the cost of living.

# **2.2 Urban delineation**

Accurately and consistently defining urban areas is a crucial step in obtaining accurate and consistent estimates of urban (and rural) poverty across countries. Historically, there has been little attention in urban economics towards establishing consistent definitions for urban areas across different countries (Combes et al., 2023; Duranton, 2021; Roberts et al., 2017). These definitions vary significantly across countries, but most of them incorporate at least one of four essential criteria for defining urban areas. The most commonly used criterion is population size, with the majority of countries employing a minimum population threshold as part of their urban area definition. Additionally, some countries take into account factors such as the availability of urban infrastructure and services, the structure of the local economy, and/or population density (Roberts et al., 2017). However, it is worth noting that many countries do not utilize explicit criteria for delineating cities (Dijkstra et al., 2021; Roberts et al., 2017). This lack of a consistent definition of urban areas can lead to statistical artifacts, ultimately impeding policy recommendations and potentially reducing their effectiveness.<sup>12</sup> In response to the challenges posed by inaccurate and inconsistent urban delineation, recent research has highlighted the significance of developing new methodologies to accurately and consistently define urban areas across countries.<sup>13</sup> This is made possible by the increasing availability of high-resolution global gridded population datasets and satellite imagery. According to Combes et al. (2023), two leading methodologies have emerged for achieving consistent urban delineation. The first is the Degree of Urbanization (DOU) method, initially introduced by Dijkstra and Poelman (2014) and later extended globally by Dijkstra et al. (2021). The DOU method defines cities based on two primary absolute thresholds: population size and population density. This method is straightforward to implement and has been widely applied by a coalition of international organizations led by the European Commission. In fact, it was endorsed by the United Nations Statistical Commission in March 2020 as a recommended method for international comparisons of urban areas (Dijkstra et al., 2021). In contrast, the second approach, known as

> 11Albania, Brazil, Kazakhstan, Kenya, Mexico, Morocco, Thailand, and Sri Lanka.

> 12As an example, Latin American countries have significantly lower GDP per capita than expected based on their urbanization levels and are also “over-urbanized” relative to the size of their agriculture sectors. Roberts et al. (2017) demonstrate that these patterns are an illusion resulting from systematic biases in the measurement of urbanization levels, and disappear when adopting a consistent definition of urban areas across countries.

> 13These new methods tend to adopt either a functional or, more commonly, a morphological approach to delineating urban areas (Duranton, 2021). Functional approaches identify a city’s geographical extent based on the strength of spatial economic interactions with the typical focus being on delineating cities based on the strength of commuting flows. By contrast, morphological approaches identify a city’s geographical extent based on its physical extent. Examples of more functional based approaches to the globally consistent definition of urban areas include Uchida and Nelson (2009; see also World Bank, 2009) and Moreno-Monroy et al. (2021). Meanwhile, examples of morphological approaches include those that identify a city’s physical extent using built-up area data (Heinrigs, 2020; OECD/SWAC, 2020; OECD/UN ECA/AfDB, 2022), gridded population data (Dijkstra and Poelman, 2014; Dijkstra et al., 2021), and nighttime lights data (Balk et al., 2006; Brecht et al., 2013; Ch et al., 2021; Dingel et al., 2021; Ellis and Roberts, 2016; Zhang and Seto, 2011; Zhou et al., 2015).

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