@ibanaressanchez @robinslburgess & any others interested in this topic

Following from last week's discussion let me share these two documents:

• van Gevelt (2014) - Rural electrification and development in South Korea.pdf
• Korea - Rural Electrification Project.pdf

The first provides an overview of Korea's electrification experience while the second is a much more detailed overview of how the policy was rolled out (prepared by the government).

I suggest we review these documents in detail and then convene a separate call to discuss how we might look at this more closely. As Robin indicated the goal would be to try to pull together as much historical data as possible on the build out of the grid and then combine this with secondary data on firms etc. The above documents might be helpful for us to think about identification; the Burlig & Preonas paper on India being perhaps the best example of using quasi-experimental variation in the roll of out electrification to get at treatment effects.

People: Robin @robinslburgess , Azhar @azharhsain , Nikita @NikitaSharma30 , Tim

Strand I: examining how flood events impact economic outcomes and modelling how flood exposure may change over time
Task 1: establish a relationship between historical flood events and economic outcomes

• Compile list of datasets that document historical flood events across India (variables, geographic scope, precision/resolution, and time period)
• Compile list of economic datasets that measure outcome variables of interest (agricultural yields, employment, sector shares, capital, etc).
  • Indicate lowest geographic unit we can measure these outcomes on (e.g. district, village, individual, GPS)
  • Also add in satellite data (e.g. night lights)
• Begin merging datasets to start simple event-study analysis to see if we are picking up any meaningful effects on economic outcomes

Task 2: use hydrological models to forecast how planned precipitation changes, glacial melt, etc. influence river flow and subsequently flood exposure in the future

• Determine main inputs (variables like river flow) for core hydrological models to assess data requirements for forecasts
• Use historical data to test the first stage: does the model well predict flood events which we have seen in the past?
• Apply to a standard climate model which includes changes in precipitation etc

Strand II: examining how surface water availability is expected to change over time and what the economic impacts of this will be
Task 3: closely linked to Task 2, list the main hydrological models used for determining water availability for a given cell in a grid

• List the data inputs that go into these models (e.g. river flow, precipitation, land use, terrain, etc)
• Using similar economic data as in Task 1, explore whether the second stage is interesting: can we show how changes in surface water availability lead to meaningful changes in economic outcomes?

Task 4: forecast how climate change will lead to changes in water availability

This is a space for us to learn about the measurement of AFOLU emissions together.