Rentschler, Jun

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Economics of Development, Environment, and Climate
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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.
Citations 72 Scopus

Publication Search Results

Now showing 1 - 4 of 4
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    Carbon Price Efficiency : Lock-in and Path Dependence in Urban Forms and Transport Infrastructure
    (World Bank, Washington, DC, 2014-06) Avner, Paolo ; Rentschler, Jun ; Hallegatte, Stéphane
    This paper investigates the effect of carbon or gasoline taxes on commuting-related CO2 emissions in an urban context. To assess the impact of public transport on the efficiency of the tax, the paper investigates two exogenous scenarios using a dynamic urban model (NEDUM-2D) calibrated for the urban area of Paris: (i) a scenario with the current dense public transport infrastructure, and (ii) a scenario without. It is shown that the price elasticity of CO2 emissions is twice as high in the short run if public transport options exist. Reducing commuting-related emissions thus requires lower (and more acceptable) tax levels in the presence of dense public transportation. If the goal of a carbon or gasoline tax is to change behaviors and reduce energy consumption and CO2 emissions (not to raise revenues), then there is an incentive to increase the price elasticity through complementary policies such as public transport development. The emission elasticity also depends on the baseline scenario and is larger when population growth and income growth are high. In the longer run, elasticities are higher and similar in the scenarios with and without public transport, because of larger urban reconfiguration in the latter scenario. These results are policy relevant, especially for fast-growing cities in developing countries. Even for cities where emission reductions are not a priority today, there is an option value attached to a dense public transport network, since it makes it possible to reduce emissions at a lower cost in the future.
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    The Impact of Flooding on Urban Transit and Accessibility: A Case Study of Kinshasa
    (World Bank, Washington, DC, 2020-12) He, Yiyi ; Thies, Stephan ; Avner, Paolo ; Rentschler, Jun
    Transportation 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.
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    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, Neave
    Globally, 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.
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    Three Feet Under: The Impact of Floods on Urban Jobs, Connectivity, and Infrastructure
    (World Bank, Washington, DC, 2019-06) Rentschler, Jun ; Braese, Johannes ; Jones, Nick ; Avner, Paolo
    This paper analyses the degree to which infrastructure reliability and urban economic activity in several African cities is impacted by flooding. It combines firm-level micro data, flood maps, and several spatial data layers across cities through a harmonized geospatial network analysis. The analysis shows that a significant share of jobs in cities is directly affected by floods. It further details how transport infrastructure is subjected to significant flood risk that disproportionally affects main roads in many cities. While direct flood effects are revealed to be significant, this work further shows how knock-on implications for the entire urban economy might be even larger. Regardless of the direct flood exposure of firms, flooded transport networks mean that disruptions propagate across the city and drastically reduce the connectivity between firms. Access to hospitals is also found to be reduced significantly -- even during relatively light flooding events: From a third of locations in Kampala, floods mean that people would no longer be able to reach hospitals within the "golden hour" -- a rule of thumb referring to the window of time that maximizes the likelihood of survival after a severe medical incident. Overall, this study showcases the use of high-detail city-level analyses to better understand the localized impacts of natural hazards on urban infrastructure networks.