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Innovations in CoEfAs (e.g., GiveWell)
  • Cost-Effect-Analysis: Quant. uncertainty, transparent, customize
  • Organization and introduction
    • Using this resource
    • Key writings and resources
    • Who is involved?
    • Opportunities to contribute to this project
  • Innovations and issues
    • Limitations of GiveWell
      • (Possible errors and misunderstandings: examples from GW and beyond)
    • Incorporating uncertainty
    • (User-input, sensitivity checks)
    • (Type checking and code)
  • Tools and examples
    • Givewell models in explained maths
    • Squiggle
    • Causal.app
      • Causal/Givewell -- working examples (in progress)
    • Guesstimate
    • Pedant
    • hesim and other R package
    • cole_haus modeling
    • Other examples (MC/Fermi)
  • GiveWell model (and extensions)
    • Code representations of GW models
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On this page
  • Tanae Rao's work, focusing on AMF
  • Froolow's discussion & ex. 'refactoring'
  • Sam Nolan's (Quri) work, focusing on GiveDirectly
  • Cole_haus (earlier) work
  • Adjacent: Pedant/Hazelfire
  • Further Background and explanations
  • The general case
  1. Organization and introduction

Key writings and resources

PreviousUsing this resourceNextWho is involved?

Last updated 2 years ago

Sept-Nov. 2022: GiveWell 'change our mind' contest

Perhaps motivated by critiques, suggestions, and further analysis like those in this gitbook and the writings below... In Sept. 2022 GiveWell announced a , with $35k in total prize.

A great deal of additional writing and work has been posted in response to this, much of which engages the issues discussed here, including Incorporating uncertainty, transparent and organized data and calculation 'pipelines', and user input of moral and other parameters. We plan to outline this work below (to do).

Tanae Rao's work, focusing on AMF

Squiggle notebook:

Froolow's discussion & ex. 'refactoring'

Discussion of the approaches to uncertainty and GiveWell's processes

Sam Nolan's (Quri) work, focusing on GiveDirectly

Cole_haus (earlier) work

Adjacent: Pedant/Hazelfire

Further Background and explanations

I think this 'explainer' is a step in the right direction in some ways.

The general case

Douglas Hubbard, strong 'business/layman' arguments for explicitly stating modeling uncertainty and better calibrating one's own beliefs

EA Forum brief on this

See also Froolow's more general discussion/critique of GiveWell's processes

... by cole_haus using Python code (full model on Github

here
here
Uncertainty and sensitivity analyses of GiveWell's cost-effectiveness analyses
here
'change our mind' contest
Adding Quantified Uncertainty to GiveWell's Cost Effectiveness Analysis of the Against Malaria FoundationObservable
E
Methods for improving uncertainty analysis in EA cost-effectiveness models - EA Forum
Refactored GiveWell model v9.xlsmDropbox
Excel-based model, multiple charities
GiveWell's GiveDirectly Cost Effectiveness Analysis
First-pass implementation on 'observable'
Quantifying Uncertainty in GiveWell's GiveDirectly Cost-Effectiveness Analysis - EA Forum
Uncertainty and sensitivity analyses of GiveWell's cost-effectiveness analyses - EA Forum
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Pedant, a type checker for Cost Effectiveness Analysis - EA Forum
Why Is It So Expensive to Save Lives?GiveWell
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How to Measure Anything: Finding the Value of Intangibles in Business
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