If the income elasticity of demand for “manufactured goods” were one and the price elasticity of demand were zero, then we would have expected the decline in relative price to 40% of its initial value to be associated with stability in relative quantities, and for the nominal share of manufactures in GDP to fall on the same track as the price–as it has.
…For our demand for manufactured goods to have a price elasticity of zero seems to me to make little sense: Manufactured stuff is useful. When the price of manufactures drops relative to the price of other stuff, we ought to buy more manufactures
Pointer from Mark Thoma. DeLong is looking at the changes in reported price of manufactured goods relative to the rest of GDP and the reported nominal quantities over the past 70 years. A few of my thoughts:
1. We did increase our purchase of manufactured goods over the past 70 years, but we imported more and exported less. The price of foreign manufactures (including the cost of shipping them here) fell by more than did our cost of producing them. I doubt that this resolves the entire puzzle, but it must resolve some of it.
2. My guess is that the same sort of arithmetic applies to food. That is, the relative price of food has fallen, and the nominal share of food production in GDP has fallen by about the same amount. Even though food also is useful.
3. Robert Fogel told us that the income elasticity of food and manufactured goods is 0.6, not one.
“The price of foreign manufactures (including the cost of shipping them here) fell by more than did our cost of producing them.”
Consider automobiles. The import share has not increased for many decades, and real prices (when considering quality improvements) have fallen. But annual quantities sold have not increased. Why? Improved durability. The change in average length of ownership has been quite dramatic even in the past 10 years:
http://goo.gl/CAedQl
The same applies, in a different way, to electronics. Unlike cars, they don’t really wear out — instead, people discard perfectly functional electronics because of obsolescence. But recently, many technologies have plateaued and sales of laptops, tablets, and smart phones have started declining. Devices have become more ‘durable’ because they’re no longer being rendered obsolete at the same pace as before.
And then there’s the slowing in the pace of household formation — young adults living with parents or roommates don’t need their own appliances. furniture, etc.
Also, spending has been shifting away from durable manufactured goods and toward services and experiences. More stuff requires more storage space — but there’s no such problem with dining out or trips to Italy.
1. When I worked for an industrial controls supplier, manufacturing had a annual objective of driving costs down by 7% for our major product line. They generally succeeded. Other manufacturers probably have similar objectives.
2. Look at penetration rates. We have more registered vehicles than licensed drivers. Lots of manufactured goods are really selling into a replacement market rather than new users.
Put those together and you get a decrease in manufacturing as a % of total output.
Numbers like elasticity are only useful to a point.
One other point, the quality of manufactured goods has improved and hard to detect. Since the early 1980s (almost the early 1970s) the US has had average of 15M new vehicles sold to consumers despite more drivers and more vehicles. Why because the average length on road is now over 10 years when it around 7 in the 1980s.
I have a question about the weighting system of the Fed in calculating their index of industrial production. I suspect we may be understating the growth of industrial production.
For year industrial production of information technology ( IT ) has been significantly faster than all other industrial production. This would lead you to think that IT’s weight in industrial production would increase over time. But it hasn’t, rather it has fallen almost every year. The reason is that the Fed recalculates the weights every year using nominal values. So If IT real output jumps 15% and IT prices fall 20%
the nominal value will fall 5%. So with nominal output falling the Fed reduces the weight of IT in the index. I understand why they do it way. But I can not help put believe it is causing the Fed’s estimate of IT and industrial production is biased downward by this methodology.