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Designing Nonlinear Electricity Pricing with Misperception: Evidence from Free Electricity Policy (with Ngawang Dendup)
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Abstract:In low- and middle-income country cities, poor households often reside in unattractive locations, including flood-prone areas. This can be due to poor information about flood risks or acceptance of these risks in the face of lower housing prices. Poor households are also more vulnerable to floods than richer households given the low-quality housing they occupy. Does information on flood risks help households make better location and housing choices? To what extent will these choices be revised with increased flood risks from climate change? To answer these questions, we develop a polycentric land use model with heterogeneous income groups, formal and informal housing, and flood risks. The model is calibrated to the city of Cape Town (South Africa) and simulations are run to assess the impact of flood risks on land values and income segregation within the city, distinguishing between the effects of three types of flooding (fluvial, pluvial, and coastal). Although total damages from floods are greater for rich households, they represent a larger relative share of poor households’ incomes. Better information encourages the adaptation of poor households up to a certain point, and this allows them to mitigate most of the adverse consequences from climate change. Considering the different nature of flood types is key to understanding their responses.
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