For a neo-paleo-Keynesian like me, the first week of an undergraduate macroeconomics lecture is taken up with accounting: Tedious but necessary. What is GDP? How is it different from GNP? National Income? How do we measure it? Does it matter? I've always struggled with outside readings to fill this material out and make it interesting. Now I have one. Diane Coyle has written a timely and very readable little tome about her love affair with national income accounting. It's very short, and you will be able to gobble it down in an afternoon. I did, while whiling away a few hours on a flight.
Why? You say! How could this be interesting? It's interesting because it has a lot to say about the current controversy over productivity. Unemployment is almost back to normal in the UK and the USA. But Real GDP is lagging well behind trend. How could this be?
We have been drinking the index-number cool-aid for so long that we have forgotten how difficult and ambiguous it is to construct a measure of aggregate product in a world where more than 60% of GDP is intangible: as Diane would say, it is weightless.
It is tempting to give up entirely on measuring real GDP and implicitly on economic growth. One might argue that we should be far more concerned about resource utilization than about the number we attach to an increasingly diverse bundle of differentiated commodities. Unemployment matters. What we produce, in a modern market oriented economy, arguably, matters less.
If we are interested primarily in resource utilization, the stuff of business cycles, there is an alternative to standard measures of real GDP. We can divide nominal GDP by a wage index, instead of a price index. Labor has a least a semblance of homogeneity and aggregating the time input of doctors with that of burger flippers is surely easier that adding plum puddings to computer chips. I showed how to do this, in a recent book, by using national income accounting data to estimate the money wage: My wage index data is available here.
I do not want to suggest that we should stop trying to measure growth. Economic progress is an important idea as 1.5 billion Chinese can attest to. If we must be metaphorical bean counters, and there are few alternatives to counting progress, there is no alternative but to bite the bullet and produce the best measures of an aggregate price index that we can. But as Diane reminds us, small revisions to our measurement methods can cause very large revisions of our estimates. Let's not be too concerned when our index numbers temporarily misbehave.
We have been drinking the index-number cool-aid for so long that we have forgotten how difficult and ambiguous it is to construct a measure of aggregate product in a world where more than 60% of GDP is intangible: as Diane would say, it is weightless.
It is tempting to give up entirely on measuring real GDP and implicitly on economic growth. One might argue that we should be far more concerned about resource utilization than about the number we attach to an increasingly diverse bundle of differentiated commodities. Unemployment matters. What we produce, in a modern market oriented economy, arguably, matters less.
If we are interested primarily in resource utilization, the stuff of business cycles, there is an alternative to standard measures of real GDP. We can divide nominal GDP by a wage index, instead of a price index. Labor has a least a semblance of homogeneity and aggregating the time input of doctors with that of burger flippers is surely easier that adding plum puddings to computer chips. I showed how to do this, in a recent book, by using national income accounting data to estimate the money wage: My wage index data is available here.
I do not want to suggest that we should stop trying to measure growth. Economic progress is an important idea as 1.5 billion Chinese can attest to. If we must be metaphorical bean counters, and there are few alternatives to counting progress, there is no alternative but to bite the bullet and produce the best measures of an aggregate price index that we can. But as Diane reminds us, small revisions to our measurement methods can cause very large revisions of our estimates. Let's not be too concerned when our index numbers temporarily misbehave.