This study tests distance weights based on the economic geography assumption of straight lines and the complex networks approach of empirical road segments in the Mexican system of cities to determine the best distance specification. We generated network graphs by using geospatial data and computed weights by measuring shortest paths, thereby characterizing their probability distributions and comparing them with spatial null models. Findings show that distributions are sufficiently different and are associated with asymmetrical beta distributions. Straight lines over- and underestimated distances compared to the empirical data, and they showed compatibility with random models. Therefore, accurate distance weights depend on the type of the network specification.
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