This article argues that economics is currently undergoing a fundamental shift in its method, away from neoclassical economics and into something new. Although that something new has not been fully developed, it is beginning to take form and is centered on dynamics, recursive methods and complexity theory. The foundation of this change is coming from economists who are doing cutting edge work and influencing mainstream economics. These economists are defining and laying the theoretical groundwork for the fundamental shift that is occurring in the economics profession.

Economists not only failed to anticipate the financial crisis; they may have contributed to it-with risk and derivatives models that, through spurious precision and untested theoretical assumptions, encouraged policy makers and market participants to see more stability and risk sharing than was actually present. Moreover, once the crisis occurred, it was met with incomprehension by most economists because of models that, on the one hand, downplay the possibility that economic actors may exhibit highly interactive behavior; and, on the other, assume that any homogeneity will involve economic actors sharing the economist's own putatively correct model of the economy, so that error can stem only from an

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This paper argues that macro models should be as simple as possible, but not more so. Existing models are "more so" by far. It is time for the science of macro to step beyond representative agent, DSGE models and focus more on alternative heterogeneous agent macro models that take agent interaction, complexity, coordination problems and endogenous learning seriously. It further argues that as analytic work on these scientific models continues, policy-relevant models should be more empirically based; policy researchers should not approach the data with theoretical blinders on; instead, they should follow an engineering approach to policy analysis and let the data guide their choice of the relevant theory to apply.

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Abstract:The economics profession appears to have been unaware of the long build-up to the current worldwide financial crisis and to have significantly underestimated its dimensions once it started to unfold. In our view, this lack of understanding is due to a misallocation of research efforts in economics. We trace the deeper roots of this failure to the profession's insistence on constructing models that, by design, disregard the key elements driving outcomes in real-world markets. The economics profession has failed in communicating the limitations, weaknesses, and even dangers of its preferred models to the public. This state of affairs makes clear the need for a major reorientation of focus in the research economists undertake, as well as for the establishment of an ethical code that would ask economists to understand and communicate the limitations and potential misuses of their models.

As economists, we have an interest in and individual knowledge of the initiation process that turns students into professional economists. However, other than anecdotal evidence, very little in the way of data exists. This paper is a step toward providing insight into that process. We obtained our data from questionnaires distributed to graduate students at six top-ranking graduate economic programs -- University of Chicago, Columbia University, Harvard University, Massachusetts Institute of Technology, Stanford University, and Yale University -- exploring who current graduate students are and what they think about economics, the economy, and graduate school. The 212 respondents were relatively equally divided by year of study. We followed up our survey with a series of interviews. Certain results seem unambiguous and worth repeating. Specifically, there is a significant variety of opinions among graduate economics students and among the schools in the survey, and there definitely seems to be a Chicago school of economics. There are also tensions between the emphasis on techniques and the desire to do policy-oriented work. Students believe that what leads to success in graduate school is techniques; that success has little to do with understanding the economy, nor does it have much to do with economic literature. We hope that this information leads to discussion within the profession of whether this focus is good or bad.

In this article, I discuss some earlier debates about the foundations of utility and its measurement, focusing on the contributions of Francis Y. Edgeworth (1845-1926), a famous British economist who was a leader in the development of a more mathematically structured economics in the late 1800s, and Irving Fisher (1867-1947), one of the first quantitative U.S. economists, best-known today for his work on the quantity theory and interest rate theory. Edgeworth argued that utility was directly measurable and that new developments in "physio-psychology" would make it possible to develop a "hedonimeter" that would allow economists to develop a firm physiological underpinning of utility. Fisher, while agreeing with Edgeworth that it was important to have a workable measure of utility, disagreed with Edgeworth about the possibility of doing so with a hedonimeter and, hence, of having any physiological underpinnings of utility. He argued that instead of searching for physiological underpinnings of utility, economists should instead rely upon backward induction from observed behavior to measured utility. Neither of these views about the possibility of utility measurement carried through, and attempts to measure utility were abandoned in the 1930s, when utility measurement and happiness considerations were determined to be outside the purview of economics. Both Edgeworth and Fisher knew that their approaches to utility measurement opened up a Pandora's box of problems; they opened that box, nonetheless, because they felt that theoretical economics had to be relevant to policy, and, to be relevant, it had to face the problems.