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Unemployment and Unemployment Insurance

There are 20,000 members of the American Economic Association, the profession’s premier professional association. There are many PhD economists in the US who are not members, particularly at smaller universities. Many – likely most – economists in other countries are not members. So … 40,000 PhD economists globally? What that means is that if a journalist or political hack puts forth a little effort, they can find a certified economist claiming to find anything imaginable. They also can find much beyond imagination – and my imagination is vivid.

So what is the impact of the end of unemployment insurance in the US on unemployment? One trope on the right (maybe not common) is that our high unemployment is due to excessively generous benefits that keep people at home. Strike #1: in Europe, where some countries offer munificent benefits, unemployment is up from low levels, suddenly and without changes in their benefit systems. Strike #2: in the US benefits are low relative to pre-unemployment wages, particularly for middle-class type jobs. Tempting? – I don’t find that likely. Strike #3: there was no shift in 2008-9 that would lead over 10 million workers in the US to suddenly decide staying at home was better.  (The total is 11.75 million if we go from when employment began falling in early 2007 through July 2011, after which we see steady increases, and that’s net of the increases in a few months in 2007 and scattered months in 2010 and 2011.) So by my reckoning it’s not worth going further.

However, there are economists claiming otherwise, and for obvious reasons this gets picked up by the media. One example is a paper by Marcus Hagedorn, Iourii Manovskii and Kurt Mitman, which is now out in an updated version from the NBER [note: W&L has a subscription]. They’re not total hacks, either. So economists are in fact reading their paper to see what’s up, how they can actually claim this. To give an example of the good end of blogging, Mike Konczal (among others) provides a careful analysis of where their results come from and whether we should believe them.