geographic coordinates of surveyed firms. These were provided with a random shift of up to 2 kilometers to mask firms’ true locations and allow firms to be matched with natural cities as described below.

# **2.2. Data on Natural Cities Based on Nighttime Lights Satellite Imagery**

A novel dataset of more than 1,500 “natural” cities across Asia and the Pacific developed recently (Jiang, 2021) is utilized for capturing cities. The dataset is based on nighttime lights (NTL) satellite imagery data available since 1992 from the National Oceanic and Atmospheric Administration website. Human settlements were delineated with the deblurred NTL data as contiguously illuminated areas. Those meeting certain criteria, such as covering units captured by the Global Rural Urban Mapping Project database with population greater than 100,000 in year 2000 or having a land area greater than 100 km<sup>2</sup> in 2000 are classified as urban agglomerations. These urban agglomerations are referred to as natural cities to distinguish them from administratively defined cities.

The population of natural cities is estimated using grid population data from LandScan. Other city characteristics including weather (precipitation and annual maximum and minimum temperature), distance to the nearest seaport, and citywide ruggedness are added to the dataset. Jiang (2021) provides additional details on the development of the natural city dataset.

The advantages of using natural cities are many. First, natural cities are uniformly defined and their characteristics are measured consistently across countries and over time. In contrast, official statistics on cities rely heavily on administrative designations, for example, defining cities as areas administered by municipal councils, or combining administrative designations with economic ones, for example, requiring a city to meet some country-specific thresholds on population size and density and even share of agricultural employment (ADB 2019). As may be expected, the boundaries of administratively designated cities differ substantially in their size, institutional status and governance structure across different countries. Second, natural cities offer a better representation of the urban agglomerations in which firms operate. This is because many administratively defined cities contain both dense urban areas and sparsely populated rural areas; additionally, economic activity invariably expands beyond the administrative boundaries of cities and spreads over multiple administrative units (urban and/or rural). These areas are economically integrated and should be considered as part of an urban agglomerations.<sup>12</sup> To illustrate these points, Figure 1 shows two examples of natural cities and their corresponding administratively defined units. In India, officially designated cities are described as “statutory towns”—i.e., administrative units with a municipal corporation, municipality, cantonment board, notified town area committee, or town council. However, the boundaries of these cities are widely acknowledged as too restrictive, given the complex and time-consuming process of redrawing municipal boundaries as cities expand (Colmer 2016). Thus, the Indian

> 12 The literature increasingly recognizes the advantage of defining urban agglomerations through economically integrated areas via remote sensing technologies instead of administrative boundaries. For applications to the developing world, see Dingel, Miscio, and Davis (2019), Galdo, Li, and Rama (2019), and Bosker, Park and Roberts (2020).

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