Prior to Haavelmo's thesis, researchers lacked a common conceptual system for formulating, analyzing and solving econometric problems. At the time, few econometric methods were based on probability theory and therefore could not utilize statistical inference to draw conclusions from data. To the extent that calculations contained any random variations at all, they usually referred to measurement errors in the variables. During this period, most prominent economists including Keynes - rejected more extensive use of probability theory in empirical research on the grounds that, e.g. , economic processes were irreversible. In his dissertation, Haavelmo refuted these various objections and showed that in order for economic theories to be testable, probability theory formulation is not only a prerequisite, but also extremely reasonable.
Economists analyze results of millions of decisions made by individuals and firms.
Decisions are in fact affected by individual characteristics and numerous temporary conditions which change over time. As economic theories in general do not refer to individual decisions but are concerned with relations which comprise long sequences of decisions and a multitude of decision-makers, there are frequent opportunities to make relatively simple assumptions about the probability distribution of these aggregate relations. Haavelmo also demonstrated that by formulating theories in probability theory terms, statistical inference methods could be applied to estimate and test economic theories and use them in forecasting. Most of the problems he dealt with and analyzed are associated with interdependence in economic relations. In economic life, every individual decision may be regarded as affecting all other decisions through a chain of market relations.