There has always been one strand of thought which claims that the past is strewn with so much of ignorance—especially in scientific pursuits—that it is fruitless to go back to it. But that approach would deny us the many insights into the present position of any discipline because there is no present that did not have a past. There is a particular danger that this type of myopic approach is adopted in the case of recently developed academic disciplines like econometrics because people assume that, as they are of recent origin, they are free from historical puzzles.
Econometrics, if looked at etymologically, is a combination of familiar words, namely economics and metrics (from the Greek word metron), meaning “theory of measurement”. Joseph Schumpeter, one of the early supporters of this budding discipline, thought that the term was “exposed to objection on philological grounds” and that it should have been either ecometrics or economometrics (Schumpeter 1954:209n. ). Just as a rose is a rose by whatever name you choose to call it, econometrics is all about measurement and analysis of economic phenomena. Though in the present time all economists use mathematics and statistics in greater or lesser measure, in the 1930s it was thought necessary to adopt a distinctive name embodying a research programme in the manner of biometrics, as statistical biology is known.
The year 1930 is a particularly important year because it was only in that year that Ragnar Frisch christened this new discipline with this name. Hashem Pesaran informs us through the New Palgrove that one Pawel Ciompa used the phrase many decades earlier, but we do not have any other details about the context in which the word was used. 1 It was only after the foundation of the Econometric Society in 1930 that the subject acquired a separate discipline (at least a subdiscipline) status. Professor Irving Fisher—a student of the mathematician Willard Gibbs at Yale University—had tried as early as 1912 to organize a group to “stimulate the development of economic theory in its relation to statistics and mathematics” under the auspices of the