Sectoral wealth

SECTORAL WEALTH DENSITIES

This page is part of a wider tool development for physical risk assessment, aiming at providing country and sector specific estimations of the future financial effects caused by future natural disasters, such as tropical cyclones, under various climate change scenarios.

Please find below our proposition for constructing Sectoral Wealth Densities, granular geographic data representing repartition of the capacity (or equivalent) of a given sector on the whole world, based on Climate Trace data.



Global Wealth Density - LitPop

LitPop is a gridded asset exposure dataset obtained by spatial disaggregation of national total asset value, with a 30 arc-seconds (1 km) resolution. In our case, we used a 5-minutes aggregation to allow a faster computation process. There are 2 steps in the creation of LitPop database:
  • First, each grid cell is given a weight equal to the product of nightlight intensity and population.
  • Second, the total asset value of a country is disaggregated at the cell level proportionally to the weight of the cell. The LitPop database encompasses information from 224 countries that represent 99.9% of world GDP.
LitPop dataset (5-minutes)




Sectoral wealth Densities

We estimate sectoral densities using Climate Trace data on physical assets for a range of sectors in the following industries: Agriculture, Fossil fuel operations, Manufacturing, Mineral extraction, Power and Transportation.

A weighted kernel estimation (based on capacity, or an equivalent metric) is used to generate the densities at a country level. The densities generated can serve as a basis to estimate sector-specific damages caused by physical hazard such as tropical cyclones. Please contact us for any additional methodological details, as we are still in an experimental phase.

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