I posted yesterday about a recent piece attacking the Heritage Foundation's economic freedom index. Heritage's Marc Miles replies below the fold—though for my money, what you folks came up with in the discussion of yesterday's post constituted just as effective a reply.
Every year for the last decade, the Index of Economic Freedom, which we at The Heritage Foundation publish with The Wall Street Journal, has shown a strong link between economic freedom and economic growth. For readers with any acquaintance at all with how markets work, this conclusion probably seems obvious. Yet Doug Henwood of the Left Business Observer recently demonstrated how hard it is for some people to grasp it.
In a March 26 "special report" that's been circulating on the Web, Henwood condescendingly notes the truism that "correlation doesn't prove causation." We agree, and we have never claimed otherwise. The data show only that changes in the Index score and growth rates rise and fall together.
But there are other ideas embedded in this test, such as "wealth is created by people not governments" and "reducing the barriers in the path of individuals allow them to use better their natural abilities to achieve their goals in life." Statistics ultimately can be used only to disprove. The data, when correctly tested, fail to disprove any of these statements.
Those are the facts. Unfortunately, from here Henwood's analysis deteriorates into the realm of ad hoc conjecture.
For example, in his attempt to conjure up an alternative theory to explain the data results, he asserts, "Corruption lowers a country's score, but when times are good, outstretched palms are often hard to notice." Some consistency, please: Corruption is a tax, for it raises the cost of doing business. The truism he chooses to ignore here is that "it is a tax in bad times, it is a tax in good times."
Henwood then descends into an argument about "how countries' scores in a base year [are] correlated with subsequent growth." In other words, how the level of economic freedom as measured by the Index in a particular year is related to changes in income over time. Who claimed that to be true? Certainly we did not. This must be Henwood's theory, which he proceeds to test as if it were ours.
In the process, he raises some red herrings about the use of purchasing-power parity (PPP) data and per capita growth data. Sorry, Doug, but no matter which data are used, our results are essentially the same.
But when Henwood tests his theory, the data do not support his assertion. Alas, his view of the world can be disproved by the data. (For those who would like a sophisticated analysis of this point, see http://www.anderson.ucla.edu/documents/areas/adm/media/roll.pdf )
Most disturbing, however, is that this misrepresentation of our data is precisely the same as raised by Jeffrey Sachs in his new book "The End of Poverty." It is no more accurate when stated by Henwood as it is when written by Sachs. They proceed to test the level of the Index against the change in income, while our arguments have always been that the level of the Index is related to the level of income (see http://www.heritage.org/research/features/index/downloads/economicFreedomandPerCapita.gif), and changes in the Index are related to changes in income (See Figure 1 and explanation in http://www.heritage.org/research/features/index/chapters/Executive_Summary.pdf).
To paraphrase Henwood, anyone who lasted a week in basic statistics knows the difference between levels and changes in levels. Have those who have become ossified in 20th century economics forgotten the difference?
Sachs' and Henwood's screeds are not about good economics and good statistics. They are apparently about trying to hold on desperately to ideas of the past through misrepresentation and snide little potshots (e.g., "It's so much fun being on the right—you're liberated from the tyranny of having to make sense.") C'mon, boys, the public deserves better than that.