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In his excellent book The Mismeasure of Man Stephen Jay Gould provides a great historical critique of intelligence testing. His focus is not so much on the tests themselves but on the fallacious conclusions which early 20th century scientists all too eagerly drew from them. Again and again he shows that supposedly objective proofs for the inequality of races were based on nothing more than prejudiced interpretations of statistical data. Some scientists resorted to direct falsification, but it is striking how many acted in good faith without any particular political agendas on their minds, yet still ended up concocting results which were clearly influenced by racist prejudice.

The generally accepted preconceptions of the times predisposed people to interpret the data in a certain way. Since most Africans lived in huts and utilized only primitive technology it was clearly unthinkable that they could be endowed with mental capacities comparable to the white man. An immediate consequence was that any given study of intelligence had to be defective if it didn’t show a clear difference between white and black. The properly scientific thing to do was then to revise the testing procedure or the results until the differences – objectively true as they were, by virtue of common sense – could be discerned.

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In my first essay Things that grow I argued that the GDP aggregate is an artificial construct with no clear correspondence to the real world. When GDP is calculated, goods and services sold on a market are aggregated with goods and services produced outside of any markets. This aggregation is supposedly justified by the assumption that their values are commensurable. I attempted to show what a specious assumption that is.

The definition of GDP was my main concern in that essay because it’s pointless to speculate on the value or true meaning of the GDP measure if it isn’t an accurate measure of anything at all. But since GDP is nevertheless often interpreted as a happiness or welfare metric by misinformed economists, it might be worthwhile to take a closer look at that misinterpretation. I still don’t see GDP as a well-defined statistical quantity, but in this essay I want to focus on the usage of statistical aggregates, not on their theoretical justifications. And as I wrote in Things that grow, justifications are often dictated by usage, not the other way around. That’s what makes GDP such an incongruous quantity in the first place.

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National accounts are a means for connecting public policy to empirical information. No other set of statistical data is referred to more often in political rhetoric. The most ubiquitous indicator in the national accounts, the Gross Domestic Product, usually holds center stage. The word growth has become practically synonymous with a positive change in GDP. A recent book published by the OECD states that

“The most important use made of national accounts is to forecast the following year in order to provide the macroeconomic framework for the government budget. The prime aim is to evaluate the volume growth in GDP for the following year (…).” (OECD p.308)

and

“All the main public finance indicators are expressed as percentages of GDP (…).” (OECD p.248)

Clearly then, the political importance of the GDP aggregate can hardly be exaggerated. However, I will argue in this essay that national accounting is a problematic enterprise. It is by no means clear what features of the economy the aggregates like GDP truly reflect.

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