# **1. Introduction**

Urban areas around the world are attractive places for people looking for opportunities for a better life. About 55 percent of the world’s population lived in urban areas in 2018 and that number is likely to grow by 68 percent by 2050 (United Nations 2019). Urban agglomerations spur economic growth through productivity gains within economic sectors and structural transformation (Duranton and Puga 2004; Glaeser et al. 1992; Glaeser and Gottlieb 2009; Michaels, Rauch, and Redding 2012). At the same time, urban residents tend to be vulnerable to climatic and environmental shocks triggered by the increase in economic activities and are often pushed back to or remain trapped in poverty (Hallegatte et al. 2017). Without proper mitigation and adaptation measures against climate change, the benefits of urbanization could be negated (Mukim and Roberts 2022).

In this context, this paper attempts to test the following two hypotheses. The first is that people are more likely to become or stay nonpoor in larger or denser cities, compared to smaller or less densely populated towns. The second hypothesis is that large or dense cities that are more exposed to climatic and environmental shocks offer residents a lower chance to become or stay nonpoor, compared to cities of similar size but not exposed to such shocks. By empirically testing those hypotheses, we investigate the following key question: _Do climatic and environmental shocks hamper the key function of urban agglomerations as the escalator out of poverty in the developing world?_ Confirming this question is critically important as it underscores the need for policy interventions to help achieve inclusive and green growth through urban development.

We develop an analytical approach to addressing the questions with and without panel datasets by combining panel (or synthetic panel) household surveys with climatic datasets. The synthetic panel method is a useful approach to analyzing poverty dynamics when panel household survey datasets are not available. We develop synthetic panel datasets out of repeated cross-sectional household surveys in Chile between 2011 and 2015 and Colombia between 2008 and 2010. We then examine the association between poverty changes over time and city population size as well as the heterogeneity of the association by flood risks. We also analyze another country, Indonesia, to apply a similar analytical framework. Instead of developing a synthetic panel, however, we estimate twoway fixed-effect (FE) regressions on the five waves of the Indonesia Family and Life Surveys (IFLS) to analyze the variation of probabilities of poor households escaping from poverty by urban agglomeration classifications and climatic shocks/risks. The IFLS spans from 1993 to 2014 over 298 districts and tracks the same households over time. We focus on flood as the climatic factor, by measuring the rainfall anomaly and heavy rain measured by the Standardized Precipitation Evapotranspiration Index (SPEI).

The results of our analysis support the hypothesis that climatic risks could undermine the upward mobility facilitated by urban agglomerations. The synthetic panels in Chile between 2011 and 2015 and Colombia between 2008 and 2010 indicate a reduction in urban poverty rates measured by the upper-middle-income international poverty line (US$5.5 per day in 2011 purchasing power parity [PPP]). In those countries, 7.4 percent and 4.1 percent of the urban poor escaped from poverty during the periods, respectively. The analysis finds that the probabilities of households’ transition from poor to nonpoor status were positively correlated with the city population size in both countries. More importantly, such upward mobility was observed only in larger cities with low flood risk. The empirical analysis of Indonesia finds that compared to rural areas, the chance of getting out of vulnerability is higher by 7.0 percentage points in metropolitan cores based on the results with household FEs. However, heavy rainfall and high flood risk decrease the chance of upward mobility in the cores and urban peripheries of metropolitan areas.

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