Randomized control trials and economic models: friends or foes?

Randomized control trial (RTC) studies are getting more and more attention among policymakers in the last few decades. In addition, the RCT is one of the core experimental methodologies used by the recent nobel prize laureates in economics Duflo, Kremer and Banerjee

Given the excitement around these methods, Chicago University has recently run the IGM Economic Experts Panel asking economic experts on whether the “ Randomized control trials are a valuable tool for making significant progress in poverty reduction”. The results of the poll are summarized in the graph below. 

The chart above highlights respondents’ agreement distribution. What struck me most from the results was Angus Deaton’s strong disagreement with the statement – especially given that he is an expert in the field.

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GDP in three different charts

Flipchart Rick has a post up about Andy Haldane’s speech the other day and, like all Haldane’s work, it’s witty and engaging so you should definitely read it. The subject is the recent slowdown in growth in the developed world and it illustrates how different views of the same data can lead to very different conclusions.

Haldane plots the last 3000 years of GDP to show what a recent phenomenon exponential growth is:

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The Economist’s misguided lecture to macroeconomists

In a bizarre leader article The Economist praises microeconomists for their use of data to better predict people’s behaviour and recommend macroeconomists do the same:

Macroeconomists are puritans, creating theoretical models before testing them against data. The new breed [of microeconomists] ignore the whiteboard, chucking numbers together and letting computers spot the patterns. And macroeconomists should get out more. The success of micro is its magpie approach, stealing ideas from psychology to artificial intelligence. If macroeconomists mimic some of this they might get some cool back. They might even make better predictions.

I’m tempted to label this as obvious baiting but the misunderstanding is deeper than that. Read more

Merry Christmas from TVHE

Have a great Christmas and we’ll be back in the New Year. If you’re feeling starved of economics over the next ten days The Atlantic has a selection of beautiful Christmas cards to send to your loved ones:

If you need something a little more stimulating then you can catch up on some of the debates you missed on the blogs over the past week. Read more

In support of dynamic scoring

Estimating the impact of tax cuts is a tricky business. You can fairly easily calculate how the revenue from current income and spending will change, but that’s just the beginning. The problem is that people don’t stand still: they change their earning and spending habits in response to your tax changes, which changes the revenues from the taxes. The UK government is pretty good at estimating that but economists have long known that there are a couple more stages before you have a full picture of what’s going on. That’s why HM Treasury has begun to use a dynamic, computable, general-equilibrium (CGE) model to estimate the effect of tax changes.

CGE models bring us closer to reality…

The CGE model accounts for the long-term effect on the economy of changing behaviour. In the case of cuts in the fuel duty it accounts for the growth in production caused by a reduction in transport costs. Increasing production generates more road traffic, which yields more fuel duty revenues and partially offsets the cost of the cut. Using the CGE model to ‘dynamically score’ (as the jargon goes) the cost of the tax cut incorporates effects these effects that are not a part of the traditional approach. Read more

Economics, theory, and data

This post was titled “Why data alone is not enough for economic inference”.  I was all prepared to write a post on the fact we need data and theory in order to do economic inference and create knowledge. I had links (*,*,*,*,*).  Then Noah Smith wrote this like really good post on the issue, so I’d suggest reading that.

On the other side there are those who are “too in love” with theory without any reference to data, or prior literature (which is a way of building a case for inference between theory and data).  A clear example of that comes from some of the comments that specific physicists moving into economics make – and Chris House has expressed that here.

I’d note that Read more