Predicting Urban Employment Distributions

Cities are intricately interconnected socioeconomic systems, with transport networks connecting people to their jobs, health, and education facilities, and ensuring the smooth functioning of supply chains. When floods happen, they isolate people and firms from these vital networks, causing cascading disruptions and losses. Such floods are not limited to rare and extreme events. Especially in developing country cities, the lack of resilient infrastructure systems means that even regular rainfall events, for example, during rainy seasons, can cause havoc. Attention is often biased towards direct asset losses from floods, rather than the wider economic costs of disrupted networks. This is due primarily to the complex dynamics of economic and infrastructure networks. But public transport and road usage data are also often limited, especially when the predominant modes of transport are informal and walking. So how can we identify and prioritize cost-effective measures for urban resilience This note describes an analytical approach that can help prioritize investments in urban transport resilience and public transport, while also strengthening the economic case for such investments.

Bibliographic Details

Main Authors:	Avner, Paolo, Maruyama Rentschler, Jun Erik, Barzin, Samira, O’Clery, Neave
Format:	Brief biblioteca
Language:	English
Published:	Washington, DC 2022-06
Subjects:	EMPLOYMENT PREDICTION, EMPLOYMENT DENSITY MAP, SPACIAL DISTRIBUTION OF JOBS, TARGETING PRODUCTIVITY IMPROVEMENT, OPEN-SOURCE DATA, RESILIENCE, URBAN INVESTMENT PLANNING,
Online Access:	http://documents.worldbank.org/curated/en/099140104282225258/P172672014f4020b00b0100a7bbebba39a2 https://hdl.handle.net/10986/37577
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