Author Name Variants
Fields of Specialization
Economics of Development, Environment, and Climate
Externally Hosted Work
Last updated May 3, 2023
Jun Rentschler is a Senior Economist at the Office of the Chief Economist for Sustainable Development, working at the intersection of climate change and sustainable resilient development. Prior to joining The World Bank in 2012, he served as an Economic Adviser at the German Foreign Ministry. He also spent two years at the European Bank for Reconstruction and Development (EBRD) working on private sector investment projects in resource efficiency and climate change. Before that he worked on projects with Grameen Microfinance Bank in Bangladesh and the Partners for Financial Stability Program by USAID in Poland. He is a Visiting Fellow at the Payne Institute for Public Policy, following previous affiliations with the Oxford Institute for Energy Studies and the Graduate Institute for Policy Studies in Tokyo. Jun holds a PhD in Economics from University College London (UCL), specializing in development, climate, and energy.
Publication Search Results
Now showing 1 - 7 of 7
Publication(World Bank, Washington, DC, 2022-04) Rentschler, Jun ; Leonova, NadiaAir pollution is one of the leading causes of death worldwide, especially affecting poorer people who tend to be more exposed and vulnerable. This study contributes (i) updated global exposure estimates for the World Health Organizations's 2021 revised fine particulate matter (PM2.5) thresholds, and (ii) estimates of the number of poor people exposed to unsafe PM2.5 concentrations. It shows that 7.28 billion people, or 94 percent of the world population, are directly exposed to unsafe average annual PM2.5 concentrations. Low- and middle-income countries account for 80 percent of people exposed to unsafe PM2.5 levels. Moreover, 716 million poor people (living on less than $1.90 per day) live in areas with unsafe air pollution. Around half of them are located in just three countries: India, Nigeria, and the Democratic Republic of Congo. Air pollution levels are particularly high in lower-middle-income countries, where economies tend to rely more heavily on polluting industries and technologies. The findings are based on high-resolution air pollution and population maps with global coverage, as well as subnational poverty estimates based on harmonized household surveys.
Publication(World Bank, Washington, DC, 2020-12) He, Yiyi ; Thies, Stephan ; Avner, Paolo ; Rentschler, JunTransportation networks underpin socioeconomic development by enabling the movement of goods and people. However, little is known about how flooding disrupts transportation systems in urban areas in developing country cities, despite these natural disasters occurring frequently. This study documents the channels through which regular flooding in Kinshasa, the Democratic Republic of Congo, impacts transport services, commuters' ability to reach their jobs, and the associated economic opportunity costs from travel delays. This assessment is based on transit feed specification data sets collected specifically for this analysis under normal and flooded conditions. These data sets were combined with travel survey data containing travelers' socioeconomic attributes and trip parameters, as well as a high-resolution flood maps. The results show that (1) flood disruptions cause increases in public transit headways and transit re-routing, decreases in travel speeds, and thus travel time delays, which translate into substantial economic costs to local commuters; (2) accessibility to jobs decreases under flooded conditions, hindering the establishment of an integrated citywide labor market; (3) there are spatial clusters where some of the poorest commuters experience among the highest travel delays, highlighting socio-spatial equity aspects of floods; (4) certain road segments are critical for the transport network and should be prioritized for resilience measures; and (5) the estimated daily cost of flood disruption to commuters’ trips in Kinshasa is $1,166,000. The findings of this assessment provide disaster mitigation guidance to the Office des Voiries et Drainage under the Ministry of Infrastructure, as well as strategic investment recommendations to the Ministry of Housing and Planning.
Publication(World Bank, Washington, DC, 2020-10-20) Rentschler, Jun ; de Vries Robbé, Sophie ; Braese, Johannes ; Nguyen, Dzung Huy ; van Ledden, Mathijs ; Pozueta Mayo, BeatrizIn a country that is among the most exposed to natural hazards, Vietnam’s coastline often bears the brunt. Typhoons, storm surges, riverine flooding, coastal erosion, droughts, or saline intrusion are all-too-familiar threats to most people living along the coast. Yet despite these risks, coastal regions host thriving economic sectors, providing livelihoods for a growing and rapidly urbanizing population. The coastal regions could be a powerful engine for Vietnam’s continued socioeconomic development, but rapid urbanization, economic growth, and climate change mean that disaster risks are bound to increase in the future. Although the government of Vietnam has made impressive progress in reducing and managing natural risks, current trends show that the work is far from complete. To guide effective action, this report provides an in-depth and multi-sectoral analysis of natural risks in coastal Vietnam and reviews current efforts in risk management, proposing a concrete action plan to balance the risks and opportunities of coastal development. These actions, if taken decisively, are an opportunity to strengthen the resilience of coastal communities and hence the prosperity of coming generations.
Publication(World Bank, Washington, DC, 2020-10) Rentschler, Jun ; Salhab, MeldaFlooding is among the most prevalent natural hazards affecting people around the world. This study provides a global estimate of the number of people who face the risk of intense fluvial, pluvial, or coastal flooding. The findings suggest that 1.47 billion people, or 19 percent of the world population, are directly exposed to substantial risks during 1-in-100 year flood events. The majority of flood exposed people, about 1.36 billion, are located in South and East Asia; China (329 million) and India (225 million) account for over a third of global exposure. Of the 1.47 billion people who are exposed to flood risk, 89 percent live in low- and middle-income countries. Of the 132 million people who are estimated to live in both extreme poverty (under $1.9 per day) and in high flood risk areas, 55 percent are in Sub-Saharan Africa. About 587 million people face high flood risk, while living on less than $5.5 per day. These findings are based on high-resolution flood hazard and population maps that enable global coverage, as well as poverty estimates from the World Bank's Global Monitoring Database of harmonized household surveys.
Publication(World Bank, Washington, DC, 2022-04) Rentschler, Jun ; Avner, Paolo ; Marconcini, Mattia ; Su, Rui ; Strano, Emanuele ; Hallegatte, Stephane ; Bernard, Louise ; Riom, CapucineAs countries rapidly urbanize, settlements are expanding into hazardous flood zones. This study provides a global analysis of spatial urbanization patterns and the evolution of flood exposure between 1985 and 2015. Using high-resolution annual data, it shows that settlements across the world grew by 85 percent to over 1.28 million square kilometers. In the same period, settlements exposed to the highest flood hazard level increased by 122 percent. In many regions, risky growth is outpacing safe growth, particularly in East Asia, where high-risk settlements have expanded 60 percent faster than safe ones. Developing countries are driving the recent growth of flood exposure: 36,500 square kilometers of settlements were built in the world’s highest-risk zones since 1985–82 percent of which are in low- and middle-income countries. In comparison, recent growth in high-income countries has been relatively slow and safe. These results document a divergence in countries’ exposure to flood hazards. Rather than adapting their exposure to climatic hazards, many countries are actively increasing their exposure.
Publication(World Bank, Washington, DC, 2021-09) Rentschler, Jun ; Kim, Ella ; Thies, Stephan ; De Vries Robbe, Sophie ; Erman, Alvina ; Hallegatte, StéphaneThis study explores how businesses in Tanzania are impacted by floods, and which strategies they use to cope and adapt. These insights are based on firm survey data collected in 2018 using a tailored questionnaire, covering a sample of more than 800 firms. To assess the impact of disasters on businesses, the study considers direct damages and indirect effects through infrastructure systems, supply chains, and workers. While direct on-site damages from flooding can be substantial, they tend to affect a relatively small share of firms. Indirect impacts of floods are more prevalent and sizable. Flood-induced infrastructure disruptions—especially electricity and transport—obstruct the operations of firms even when they are not directly located in flood zones. The effects of such disruptions are further propagated and multiplied along supply chains. The study estimates that supply chain multipliers are responsible for 30 to 50 percent of all flood-related delivery delays. To cope with these impacts, firms apply a variety of strategies. Firms mitigate supply disruptions by adjusting the size and geographical reach of their supply networks, and by adjusting inventory holdings. By investing in costly backup capacity (such as water tanks and electricity generators), firms mitigate the impact of infrastructure disruptions. The study estimates that only 13 percent of firms receive government support in the aftermath of floods.
Where Are All the Jobs ?: A Machine Learning Approach for High Resolution Urban Employment Prediction in Developing Countries(World Bank, Washington, DC, 2022-03) Barzin, Samira ; Avner, Paolo ; Rentschler, Jun ; O’Clery, NeaveGlobally, both people and economic activity are increasingly concentrated in urban areas. Yet, for the vast majority of developing country cities, little is known about the granular spatial organization of such activity despite its key importance to policy and urban planning. This paper adapts a machine learning based algorithm to predict the spatial distribution of employment using input data from open access sources such as Open Street Map and Google Earth Engine. The algorithm is trained on 14 test cities, ranging from Buenos Aires in Argentina to Dakar in Senegal. A spatial adaptation of the random forest algorithm is used to predict within-city cells in the 14 test cities with extremely high accuracy (R- squared greater than 95 percent), and cells in out-of-sample ”unseen” cities with high accuracy (mean R-squared of 63 percent). This approach uses open data to produce high resolution estimates of the distribution of urban employment for cities where such information does not exist, making evidence-based planning more accessible than ever before.