Old but worth commenting on...

I've just come across some interesting views on macroeconomics and macroeconomics.  The most recent thing is some comments by Lawrence Meyer picked up by a number of bloggers.  One blogger in particular, a staunch Austrian who sees everything in economics having originated in one person (Hayek), points readers back to Arnold Kling's thoughts on empirical macroeconomics, posted back in February 2009.

What gets me most, and I think this is common for all economists who sit back and criticise another field, is that this guy hasn't got a clue what macroeconometricians do these days.  This is why I've stopped making such rash statements about DSGE models.  I have a feeling that they are progressing along certain lines I don't like and so I make general statements which one of my co-authors will constantly tell me are way off the mark.  So until I can make a proper assessment I've stopped.

Arnold Kling talks about how the empirical macroeconomist goes about his work.  He looks at data, and because of serial correlation, he takes differences - Kling goes as far as to say that to do otherwise "would be utterly unsound practice".  Thankfully Robert Bell in the comments takes him to task on this - as does any sensible Econometrics textbook, as Bell says.  Differencing destroys massive amounts of information on the levels of data series of interest, and economic theories consider the levels of variables (inflation, nominal GDP, consumption, etc).

The modern macroeconometrician looks into whether cointegrating relationships exist in the levels of the data.  Kling has concerns about imposing priors on the analysis.  Until recently I thought the Pesaran et al approach to cointegration (bounds testing etc) was no different essentially to the Johansen/Hendry et al approach - but now I realise there is a fundamental difference.  Pesaran et al assert you must have strong theoretical priors about the cointegrating relationships before you even begin - the Johansen school is instead more agnostic about it.

Basically, if stationary relationships exist in the data, you can look at them.  You can see whether they make economic sense, and if they do (and even if they don't) you can start to make economic inference about them - and of course only then in a qualified sense - this was a particular country in a particular time period.  But it doesn't render this kind of information useless, as a lot of economists (Austrians and theoretical macroeconomists - from very different starting principles).  It gives us some idea about the size of effects.  We get some rough bound on how big an effect is - and if we want to apply it elsewhere we have to consider whether or not that application is appropriate - critically so.  Probably the most harm is done to econometrics by its proponents claiming much too much for it.