This repository captures the ideas and notes that come out of our weekly EEE Hour.
A live version of all discussion notes can be found below:
Ideas and notes from our weekly EEE Hour
This repository captures the ideas and notes that come out of our weekly EEE Hour.
A live version of all discussion notes can be found below:
@ibanaressanchez @robinslburgess & any others interested in this topic
Following from last week's discussion let me share these two documents:
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
Task 2: use hydrological models to forecast how planned precipitation changes, glacial melt, etc. influence river flow and subsequently flood exposure in the future
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
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.
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TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. ๐๐๐
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google โค๏ธ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.