The use of sophisticated statistical techniques to estimate the parameters of carefully formulated economic models is today the standard practice in the attempt to learn about and from observed economic phenomena. Of course, this has not always been so. The present state of economic and econometric practice owes a very great deal of its rigor, coherence and elegance to the pioneering work of Frisch, Haavelmo, Tinbergen, Koopmans and Marschak, among others.

Of these pioneers, Haavelmo [1944] is responsible for providing the first comprehensive enunciation of the modern parametric approach to empirical economic analysis in his classic monograph The Probability Approach in Econometrics, which appeared as a supplement to Econometrica. There Haavelmo persuasively argued that the ad hoc correlation analyses and curve fitting techniques then prevalent should be replaced by modern statistical estimation and inference methods applied to carefully formulated probability models. Haavelmo showed how consideration of underlying economic principles, leading to mathematical relations embodying the economic model, together with consideration of difficulties of measurement and observation lead ultimately to a well-formulated parametric probability model. Haavelmo argued that appropriate statistical techniques, such as the method of maximum likelihood, should then be used for purposes of estimation, inference and prediction.