The drug war takes another hit

Lots of media coverage about the new report out from the London School of Economics. Check out Time to rethink the war on drugs by Kasia Malinowska-Sempruch at CNN, for example.

How bad is it? The London School of Economics this week publishes a report that attempts to quantify some of these consequences of the war on drugs.

The report has been endorsed by five Nobel Prize-winning economists who write, “It is time to end the ‘war on drugs’ and massively redirect resources towards effective evidence-based policies underpinned by rigorous economic analysis. The pursuit of a militarized and enforcement-led global ‘war on drugs’ strategy has produced enormous negative outcomes and collateral damage.”

This report is an opening salvo for a battle that will take place in the U.N.

There’s a reason why these calls are being directed at the United Nations. In 2016, at the request of several Latin American presidents, the U.N. General Assembly will hold a special session to review the functioning of the drug control system. The London School of Economics report is being delivered to a representative of the Guatemalan government – Guatemalan President Otto Pérez Molina inspired the 2016 session and has said he will use it in negotiations with other governments.

The coverage is good new, and the overall thrust of the report is good news. However, the report itself is a mixed bag.

Probably the worst is the incoherent and bizarre chapter by Jonathan Caulkins, where he admits that the drug war is bad and should be eliminated, but still claims that by pulling completely invented future statistics out of his ass, he can prove economically that there are benefits to keeping prohibition.

But… why should I critique it when Jacob Sullum has already done a thorough job? Can We End the War on Drugs Without Repealing Prohibition?

The main impression left by Caulkins’ discussion is that you can make calculations like this demonstrate anything you want about prohibition, depending on which costs and benefits you decide to include, the way you measure them, and the weights you assign to them.

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