Wisconsin National Data Consortium

I'm working on the household disaggregation. During this process I am working to identify common disaggregation procedures with the goal to provide some methods to assist with future disaggregations. One example is disaggregating by shares which is much simpler in Julia than other languages. Today I'll show off the preliminary household disaggregation and give some Julia DataFrame pro-tips.

The state disaggregation is "complete", in the sense that all the data is disaggregated and satisfies the balance conditions. I am currently working on documenting each disaggregation step, improving code readability, improving speed, and making the data easier to load and maintain. Today I'll show off the state data and talk a little about WiNDContainer, the backbone of the data.

I've been working on the State disaggregation in Julia. I have the data close and am working to reconcile differences between the Julia and GAMS versions. Let's talk about the disaggregation process today.

Canadian IO tables are much more complete than the US, they provide bilateral trade between each province. Today I am writing a package to load this data. My ultimate goal is to aggregate the interprovincial trade data, then disaggregate using the iceberg-gravity model. Seems like a good litmus test on the effectiveness of the iceberg model. During the meeting today I will show off my progress. I will also set up Documenter and write some documentation using Literate.jl.

Today we'll discuss converting an NLP CGE model into MPSGE. I've found the paper referenced by the document shared by Siwa, it has a full derivation of the model but is missing the SAM.