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Econometrics
According to Douglas Harper, the word econometrics is derived from two Greek words: oikonomia, meaning the study of the management of a household or administration, and metriks, which means measurement. This decomposition shows that econometrics at its core involves “measuring” economic variables, like income, consumption, and so on, to discover relationships among them. In spite of this rather unambiguous role of econometrics, author Peter Kennedy laments about the fact that there is no universally agreed-on definition of econometrics. The lack of a general definition for econometrics may stem from the fact that the discipline of econometrics is an “amalgam of economic theory, mathematical economics, economic statistics and mathematical statistics” (Gujarati 2003, 2). In spite of this difficulty of not having an all-encompassing definition, a reasonable approximation that adequately captures the various facets of econometrics would be to define econometrics as “the application of mathematical statistics to economic data to lend empirical support to the models constructed by mathematical economics and to obtain numerical results” (Titner 1968, 74). This definition can be especially appreciated while considering the role that econometrics has played in consumer research. For almost a hundred years, statistical techniques like linear regression have been used on agricultural data to estimate demand and supply curves and to test certain hypotheses postulated by economic theory. Moreover, a lot of the contemporary research in the field of consumer behavior is quantitative in character and involves direct application of advanced econometric techniques that have been developed exclusively to address some of the issues arising from consumer research.
History of Econometrics
David C. Colander and Harry Landreth give a fascinating account of the development of econometrics starting from the early work of William Stanley Jevons. According to these scholars, the earliest contributions to econometrics were made by Jevons who proposed, in a first systematic, data-oriented or statistical (albeit unscientific) attempt to explain business cycles, that these cycles were actuated by sun spots. One of the earliest proponents of proper statistical research within economics was Henry L. Moore in the early 1900s. Using the methodology developed by statisticians like Francis Galton, Karl Pearson, and others, Moore tried to use statistical methods to decipher the relationship between wages and labor productivity. Moore also made the first (unsuccessful) attempt to calculate a demand curve and measure business cycles, thus making contributions to both macro-and microeconometrics. Moore's work was refined and developed by Henry Schultz who corrected Moore's method to accurately estimate a demand curve. Schultz also propounded the distinction between dependent and independent variables and noted that this distinction should be informed by theory.
There were fundamental contributions to the data collection and organization by Simon Kuznets and by Wassily Leontief during the 1920s and 1930s. These contributions led to fundamental advances in macroeconometrics during the 1920s and 1930s spearheaded by Norwegian economist Ragnar Frisch and by Jan Tinbergen. Importantly, Frisch coined the term econometrics and made several fundamental contributions to the field. Frisch contributed, among other things, to what is today known as production theory and also to the theory and techniques of the linear regression model. He also founded the Econometric Society, devoted to the advancement of economic theory and econometrics. Tinbergen, along with Frisch, developed the first comprehensive large-scale macro models that were used to successfully inform and direct public policy. Frisch was awarded the Nobel Prize for Economics in 1969 along with Tinbergen.
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