HaukeHillebrandt's Shortform

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"RCTs in the Field of Development - A Critical Perspective" is a book that was recently published. Description below.

We cite one the chapters extensively in our "Growth and the case against randomista development" piece. 

The individual chapters seem all available for free in preprint version (e.g. http://ftp.iza.org/dp12882.pdf ).

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In October 2019, Abhijit Banerjee, Esther Duflo, and Michael Kremer jointly won the 51st Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel "for their experimental approach to alleviating global poverty." But what is the exact scope of their experimental method, known as randomized control trials (RCTs)? Which sorts of questions are RCTs able to address and which do they fail to answer? The first of its kind, Randomized Control Trials in the Field of Development: A Critical Perspective provides answers to these questions, explaining how RCTs work, what they can achieve, why they sometimes fail, how they can be improved and why other methods are both useful and necessary. Bringing together leading specialists in the field from a range of backgrounds and disciplines (economics, econometrics, mathematics, statistics, political economy, socioeconomics, anthropology, philosophy, global health, epidemiology, and medicine), it presents a full and coherent picture of the main strengths and weaknesses of RCTs in the field of development. Looking beyond the epistemological, political, and ethical differences underlying many of the disagreements surrounding RCTs, it explores the implementation of RCTs on the ground, outside of their ideal theoretical conditions and reveals some unsuspected uses and effects, their disruptive potential, but also their political uses. The contributions uncover the implicit worldview that many RCTs draw on and disseminate, and probe the gap between the method's narrow scope and its success, while also proposing improvements and alternatives.

Without disputing the contribution of RCTs to scientific knowledge, Randomized Control Trials in the Field of Development warns against the potential dangers of their excessive use, arguing that the best use for RCTs is not necessarily that which immediately springs to mind. Written in plain language, this book offers experts and laypeople alike a unique opportunity to come to an informed and reasoned judgement on RCTs and what they can bring to development.

Table of Contents

General Introduction, Florent Bédécarrats, Isabelle Guérin, and François Roubaud
0:Randomization in the Tropics Revisited: A Theme and Eleven Variations, Sir Angus Deaton
1:Should the Randomistas (Continue to) Rule?, Martin Ravallion
2:Randomizing Development: Method or Madness?, Lant Pritchett
3:The Disruptive Power of RCTs, Jonathan Morduch
4:RCTs in Development Economics, Their Critics, and Their Evolution, Timothy Ogden
5:Reducing the Knowledge Gap in Global Health Delivery: Contributions and Limitations of Randomized Controlled trials, Andres Garchitorena, Megan Murray, Bethany Hedt-Gauthier, Paul Farmer, and Matthew Bonds
6:Trials and Tribulations: The Rise and Fall of the RCT in the WASH Sector, Dean Spears, Radu Ban, and Oliver Cumming
7:Microfinance RCTs in Development: Miracle or Mirage?, Florent Bédécarrats, Isabelle Guérin, and François Roubaud
8:The Rhetorical Superiority of Poor Economics, Agnès Labrousse
9:Are the 'Randomistas' Evaluators?, Robert Picciotto
10:Ethics of RCTs: Should Economists Care about Equipoise?, Michel Abramowicz and Ariane Szafarz
11:Using Priors in Experimental Design: How Much Are We Leaving on the Table?, Eva Vivalt
12:Epilogue: Randomization and Social Policy Evaluation Revisited, James J. Heckman
Interviews
 


 

[Years of life lost due to C19]

A recent meta-analysis looks at C-19-related mortality by age groups in Europe and finds the following age distribution:

< 40: 0.1%

40-69: 12.8%

≥ 70: 84.8%

In this spreadsheet model I combine this data with Metaculus predictions to get at the years of life lost (YLLs) due to C19.

I find C19 might cause 6m - 87m YYLs (highly dependending on # of deaths). For comparison, substance abuse causes 13m, diarrhea causes 85m YYLs.

Countries often spend 1-3x GDP per capita to avert a DALY, and so the world might want to spend $2-8trn to avert C19 YYLs (could also be a rough proxy for the cost of C19).

One of the many simplifying assumptions of this model is that excludes disability caused by C19 - which might be severe.

Are the diarrhea and substance abuse numbers annualized? (does diarrhea cost 85 m YLL/yr)

My brain dump "Potential priority areas within cognitive sciences (psychology, neuroscience, and philosophy of mind)"

https://docs.google.com/document/d/12m_KDzKWfwQebrHGN4G4XCVIYPUHrm05Z6SB_loZr5w/edit

Feel free to contribute by making suggested edits!