Creating flashcards in Anki can be an extremely tedious process. Although there is no doubt that the process of putting together flashcards can be useful for revision, but is it really the best use of time? By leveraging ChatGPT and python, flashcards can quickly be generated (or re-generated) allowing you to start revising immediately.
The shipping sector has left a lot people scratching their heads – trying to figure out an equitable, cost-efficient, and efficient way to steer towards net-zero by 2050. Beyond the general complexities associated with decarbonising transportation, the shipping sector faces some further struggles. The combination of an uncertain policy landscape, competition effects, and questions surrounding technological maturity all contribute to making it one of the hardest sectors to abate.
How do we expect firms to react when faced with an increased cost of polluting? This post reflects on a recent Pluto.jl notebook I wrote, looking at how we can solve for a firm’s optimal CO2 abatement choices in light of different government policies.
The post is inspired by a long-lasting interest in understanding how to solve optimisation problems in economics programmatically. The question was then applied to a topic which I find interesting, namely, how environmental policy can affect firm choices.