David Sacerdote

@davidsacerdote.bsky.social did:plc:o4s55v3tsfph6whswxccpsia

Software engineer. Mostly talk climate and related politics.

En Bluesky desde el 23 agosto 2023

Seguidores: 8.463
Siguiendo: 1.109
Posts: 4.454
Días en rankings: 0

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David Sacerdote (@davidsacerdote.bsky.social) es un usuario de Bluesky que se unió el 23 agosto 2023. Tiene 8.463 seguidores, sigue a 1.109 cuentas y ha publicado 4.454 posts.

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Phil Plait@philplait.bsky.social03-11-2026 22:22
Today's job
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Kevin J. Kircher@kevinjkircher.com03-11-2026 22:13
In fact, I'd go so far as to argue that in the context of BAAJA modeling, where there is *SO MUCH UNCERTAINTY*, my probabilistic model makes more sense than the deterministic models that, AFAIK, everyone else has used. I specify distributions over uncertain parameters and evaluate impacts over the
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Kevin J. Kircher@kevinjkircher.com03-11-2026 22:13
Richard argues that because the RFF modelers make assumptions about transmission costs, where I make assumptions about BAAJA's overall effectiveness at accelerating clean electricity generation, my results are not trustworthy. I disagree.
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Kevin J. Kircher@kevinjkircher.com03-11-2026 22:13
For example, @rff.org modelers - who I respect and mention only because theirs is the most transparent study about assumptions (👏) - assume BAAJA's NEPA changes decrease the cost of interconnection and spur power lines on federal lands by 50%. Why 50%? Because the modelers said so.
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Kevin J. Kircher@kevinjkircher.com03-11-2026 22:13
As far as I know, all BAAJA studies so far used energy accounting models. Some just have higher spatial resolution. Higher-resolution models are no less assumption-driven than my low-resolution model. All energy modeling has the logical structure "If this, then that," even if presented otherwise.
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