This data visualization project from INET Oxford Complexity & Economics of Sustainability Programme researchers Joris Bücker, R. Maria del Rio-Chanona, Anton Pichler, Matthew Ives & Doyne Farmer aims to illuminate and explore the intricate dynamics of labor transitions in the face of a net-zero emissions power system, offering both a visual narrative and an interactive dashboard.

The underlying story and data derive from INET Oxford Working paper "Employment dynamics in a rapid decarbonization of the power sector", which analyses the employment dynamics of a fast transition scenario for the US electricity sector that reaches 95% decarbonization by 2035, using an input-output model coupled to an occupational mobility network.

In this research, the demand shock is determined by translating power sector decarbonization costs into annual changes in labor demand. Occupation data is sourced from the 2018 US data published by the Bureau of Labor Statistics. Using the 2018 data is to have an estimate of a relatively stable economic situation before the COVID pandemic. The ease of occupational transition is determined by the relatedness between occupations from O*NET’s data.

With thanks to Complexity Science Hub Vienna Data Visualisation Engineer Liuhuaying Yang.

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