I don't see why Andrew's analysis is construed as showing that the =
correlation between industry prices and values is spurious.
As I understand it, this would only apply if the third variable he =
introduced, industry costs, could be shown to cause both prices and =
values.
Let's look at Andrew's charming example of a spurious correlation, the =
Dog-Ownership Theory of Employment. Dogs owned by country correlates =
spuriously with employment by country. In fact there is another (more =
independent) variable, population by country, that explains this =
correlation.=20
But the spurious character of the correlation is not derived from the =
deflated correlation itself. It comes from the causal theories attached. =
The DOTE does not fail because there is no correlation between dog =
ownership and employment once population is corrected for. The DOTE =
fails because there is a far tidier PTEDO - a Population Theory of =
Employment and Dog Ownership which has plausible mechanisms wherein =
population is an independent, and dog ownership and employment are =
dependent, variables.
Imagine it was a fact that dog ownership caused population (rather than =
the other way round). This different causal situation could be =
consistent with the same correlation data exactly. The DOTE would be =
true, and country population would play the role of intermediate link in =
a causal chain from dogs to employment.
When I apply this analysis to the price/value correlation I see no =
evidence that the correlation is spurious. There is no mechanism =
proposed whereby industry costs would determine values. Until we have a =
theory presented of how costs and/or prices determine values, no =
corrected correlations can dethrone value as independent and hence =
causal variable.
What Andrew's reinterpretation suggests to me is the notion that values =
determine prices via costs, and that the variations in industry markups =
are determined otherwise.=20
Imagine that industry prices are largely determined by values, but that =
there is an industry-specific "monopoly factor" that allows a particular =
industry to gain (or lose) an extra profit by raising (or being forced =
to lower) their prices.
This would produce a component of price variation by industry not =
determined by value. But the costs per industry would correlate more =
closely to the values because=20
1. They do not include the gross profit of that industry.
2. As well as wages, they contain shares of the prices of all industries =
(who supply a particular industry) and hence the "non-value" variations =
in the industry price component of costs would tend to be averaged out.
What I'd like to see is some correlations between industry costs and =
values. Perhaps they are higher than those between prices and values.
Brendan
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