Correlation and Causality

We've now got through the course content for econ101b in lectures, so enjoy the vacation! I thought I'd link up an article by John B Taylor, who has recently become a staunch proponent of government austerity. He's supported/encouraged by Greg Mankiw, who is another Republican poster child.

For those more averse to all things US, the Republicans are much more right wing than any of the mainstream UK political parties, although their closest equivalent would be the Conservative Party.

John B. Taylor is the man who proposed the Taylor Rule, a rule that monetary policymakers should follow when setting monetary policy. He strongly believes the sole cause of the Financial Crisis was that monetary policy was too loose, according to his model (scroll through old posts on his blog and you'll get a sense of this, I can't find the original article).

In the main linked article though, Taylor takes us through some scatter plots. Now these are interesting scatter plots - they show that government purchases are positively correlated with unemployment, and that investment is negatively correlated. From this, Taylor draws the conclusion that austerity is fine and should be encouraged (since it means lower government purchases) while at the same time investment should be encouraged.

This is all well and good, but a scatter plot shows correlation and not causality. Why does this matter? Well, Taylor proposes austerity (cutting back government purchases drastically) because in his mind it will cause lower unemployment. But what if the causality is the other way? What if high unemployment causes higher government purchases? Now this is hardly controversial really, since if people become unemployed, the government will have more to do: Higher benefits, likely higher other costs too, and naturally we might see some attempt by government to stimulate the economy by increasing purchases (data is 1990 on). If this happens, the purchases happen at the same time as the unemployment exists, hence we get a correlation like in the plot.

So does Taylor's plot really tell us much? Even if the government purchases worked, this plot wouldn't tell us that since it's a dynamic picture - i.e. the reduction in unemployment wouldn't necessarily come instantaneously! So the plot has ignored causality and also the dynamic nature of cause and effect in the macroeconomy.

It's another example of why it's very hard to know who to trust when doing economics. Blogs are great - they contain the opinions of top economists who can comment on real world events as they are happening. But they are not what we call peer reviewed. For a paper to get into a journal, it must be read by a number of referees who decide on its quality. Shoddy data work like that shown in this blog post, would not get past the referees and editors at a top journal.

The conclusion to draw - be careful, and in particular if you do read blogs (and I'd recommend it!) try to read a balanced selection of them - something like the list given on the right-hand side of this blog.

Classic Economists and Mistakes

In the UK, the Bank of England has a mono mandate, so to speak: It is charged with keeping inflation low and stable - around 2%. In the US however, the Federal Reserve (the central bank system) has a dual mandate: To also achieve maximum employment via its monetary policy decisions.

It's fair to say some people disagree with this while others agree. John B Taylor is a prominent figure in monetary policy theory in economics, as you'll learn next term. He devised what is called the Taylor Rule: That the interest rate should be set taking into account both inflation and the output gap (the difference between actual and potential GDP).

However, despite this, Taylor is now a fierce critic of the Federal Reserve and commonly makes statements like: "The Fed's decision to hold interest rates too low for too long from 2002 to 2004 exacerbated the formation of the housing bubble." He states this based on a very simple equation called the Taylor Rule: It's not even estimated. It's a very theory-orientated construction and from his he asserts monetary policy was too loose in 2002-4 and this caused the housing bubble and subsequent crash.

Now Taylor, along with a Republican politician, is suggesting that this dual mandate should be removed and replaced with a single-mandate, just price stability.

Greg Mankiw isn't convinced about this, suggesting that even if the mandate was simply price stability some of the same policies (notably quantitative easing) would have still taken place.

Furthermore, Taylor is making a really fundamentally basic error of judgement that a lot of economics (and people more generally) often make: Comparing apples and oranges.

Taylor says: QE1 (quantitative easing last year) didn't work: The economy is still in a mess. Yet how on earth does he know this? He's comparing the pre-QE1 economy with the post-QE1 economy yet these are two fundamentally different things.

He wants to compare the post-QE1 (or today's) economy with another US economy run up to today without QE1, so a without-QE1 post-QE1 economy. But he can't and the next best thing is to compare where we are now with where we were back then.

But how does John B Taylor know that the without-QE1 economy today wouldn't be in a much worse situation? The answer is: He doesn't. He asserts it would be, based on no evidence.

Next term, we'll try and cover why this kind of analysis is very dangerous indeed because it often leads to policymakers changing policy - changing policy based on little or no evidence, but simple assertions, however strongly put.