Wisconsin National Data Consortium

This will be the last MPSGE Monthly for the foreseeable future. I will be taking a reduced appointed in order to preserve funding and will be scaling back certain activities. I will continue to develop MPSGE and plan to continue posting occasional updates on the blog. With that being said, I think it will be pertinent to discuss the backend of MPSGE, my future goals with MPSGE, and what the community would like to see implemented. I plan to spend some time in the new year refactoring the code base. I'll be looking for optimizations to improve performance and user experience.

What is the total value of soybeans grown in Wisconsin that is sold to China? This question is not directly answerable using data provided by the US Census. However, this number is going to be an important metric as global trade gets disrupted by tariffs. I am currently working on estimating this using a gravity model implemented in MPSGE with an iceberg trade assumption. This talk will use a simple example to demonstrate the process of estimating bilateral trade flows using MPSGE and Julia.

This month I would like to demonstrate a few examples for calibrating dynamic models in MPSGE. We'll discuss the data, models and an interesting application with non-constant growth rates.

The standard NLP dynamic Ramsey model hides the price of labor and capital returns. Converting this into a CGE model exposes these prices, allowing for the introduction of taxes. We will convert this model into MPSGE format then perform some analysis.

During this meeting we will introduce the basic concepts of MPSGE and then dive into a large model, the GTAP9 model, which is a global computable general equilibrium model. We will use the Julia package gtap9_in_julia.jl to explore the model and its data. The meeting will cover how to set up MPSGE models in Julia, interpret the GTAP data, and run simulations.