Criticism of assumptions

Economics has been subject to criticism that it relies on unrealistic, unverifiable, or highly simplified assumptions, in some cases because these assumptions lend themselves to elegant mathematics. Examples include perfect information, profit maximization and rational choices.^{[153] [154][155]} Some contemporary economic theory has focused on addressing these problems through the emerging subdisciplines of information economics, behavioral economics, and complexity economics, with Geoffrey Hodgson forecasting a major shift in the mainstream approach to economics.^[156] Nevertheless, prominent mainstream economists such as Keynes^[157] and Joskow, along with heterodox economists, have observed that much of economics is conceptual rather than quantitative, and difficult to model and formalize quantitatively. In a discussion on oligopoly research, Paul Joskow pointed out in 1975 that in practice, serious students of actual economies tended to use "informal models" based upon qualitative factors specific to particular industries. Joskow had a strong feeling that the important work in oligopoly was done through informal observations while formal models were "trotted out ex post". He argued that formal models were largely not important in the empirical work, either, and that the fundamental factor behind the theory of the firm, behavior, was neglected.^[158]

Despite these concerns, mainstream graduate programs have become increasingly technical and mathematical.^[159] Although much of the most groundbreaking economic research in history involved concepts rather than math, today it is nearly impossible to publish a non-mathematical paper in top economic journals.^[160] Disillusionment on the part of some students with the abstract and technical focus of economics led to the post-autistic economics movement, which began in France in 2000.

David Colander, an advocate of complexity economics, has also commented critically on the mathematical methods of economics, which he associates with the MIT approach to economics, as opposed to the Chicago approach (although he also states that the Chicago school can no longer be called intuitive). He believes that the policy recommendations following from Chicago's intuitive approach had something to do with the decline of intuitive economics. He notes that he has encountered colleagues who have outright refused to discuss interesting economics without a formal model, and he believes that the models can sometimes restrict intuition.^[161] More recently, however, he has written that heterodox economics, which generally takes a more intuitive approach, needs to ally with mathematicians and become more mathematical.^[102] "Mainstream economics is a formal modeling field", he writes, and what is needed is not less math but higher levels of math. He notes that some of the topics highlighted by heterodox economists, such as the importance of institutions or uncertainty, are now being studied in the mainstream through mathematical models without mention of the work done by the heterodox economists. New institutional economics, for example, examines institutions mathematically without much relation to the largely heterodox field of institutional economics.

In his 1974 Nobel Prize lecture, Friedrich Hayek, known for his close association to the heterodox school of Austrian economics, attributed policy failures in economic advising to an uncritical and unscientific propensity to imitate mathematical procedures used in the physical sciences. He argued that even much-studied economic phenomena, such as labor-market unemployment, are inherently more complex than their counterparts in the physical sciences where such methods were earlier formed. Similarly, theory and data are often very imprecise and lend themselves only to the direction of a change needed, not its size.^[162] In part because of criticism, economics has undergone a thorough cumulative formalization and elaboration of concepts and methods since the 1940s, some of which have been toward application of the hypothetico-deductive method to explain real-world phenomena