The types of knowledge, skills, and proficiencies that should be imparted to students in graduate economics programs are a matter of long-standing controversy. A 1953 American Economic Association (AEA) report cataloged major shortcomings in graduate economic education and recommended changes to enhance the quality and effectiveness of economics Ph.D. programs (Howard R. Bowen, 1953). By the 1980’s, the perception grew that economics Ph.D. programs devoted excessive attention to theoretical work at the expense of real-world application (Wassily Leontief, 1982). This development triggered David Colander and Arjo Klamer (1987) to conduct an independent study based on interviews with graduate students at elite Ph.D. programs. Their study reinforced the views of many, including leaders in the AEA, the National Science Foundation, and several private foundations, that something was amiss. In 1988, the AEA established the Commission on Graduate Education in Economics (COGEE) to undertake a thorough study of graduate training. The Commission’s major concern, based on extensive surveys and interviews of graduate students, faculty, and employers, was that graduate education in economics had removed itself from real-world economic problems (Anne O. Krueger et al., 1991). The COGEE study is distinguished by its attempt to determine the emphasis given to cultivating a set of economic proficiencies in graduate school and the importance of an array of skills for success in graduate school and later on the job (Hansen, 1991). The proficiencies included in the COGEE study were: providing rigorous training in economic theory, providing training in econometrics and measurement, applying theory to real-world problems, using economic theory in empirical applications, and conducting independent economic research. For this study, we added three proficiencies to the COGEE list: understanding economic institutions and history and understanding the history of economic ideas, to capture concerns about curriculum changes that eliminated or scaled back training in these two fields, and developing teaching skills, to reflect recent emphasis on improving the quality of instruction (William E. Becker, 2003). The skills included in the COGEE study were: critical judgment (analyzing ideas, reviewing literature, formulating pertinent comments), analytics (understanding and solving problems, making and analyzing logical arguments), application (seeing practical implications of abstract ideas, analyzing real-world policies and processes), mathematics (constructing and analyzing proofs, manipulating mathematical abstractions), computation (effectively and quickly finding and manipulating relevant data, estimating economic relationships using statistical software), communication (speaking and writing effectively, quickly understanding spoken and written ideas of others, explaining ideas clearly), and creativity (conceiving interesting questions, finding new means of analysis). We added instruction (being an effective classroom teacher) to the skills list for the same reason mentioned above.

Geophysicists examine and document the repercussions for the earth’s climate induced by alternative emission scenarios and model specifications. Using simplified approximations, they produce tractable characterizations of the associated uncertainty. Meanwhile, economists write highly stylized damage functions to speculate about how climate change alters macroeconomic and growth opportunities. How can we assess both climate and emissions impacts, as well as uncertainty in the broadest sense, in social decision-making? We provide a framework for answering this question by embracing recent decision theory and tools from asset pricing, and we apply this structure with its interacting components to a revealing quantitative illustration.

We demonstrate the asymptotic equivalence between commonly used test statistics for out-of-sample forecasting performance and conventional Wald statistics. This equivalence greatly simplifies the computational burden of calculating recursive out-of-sample test statistics and their critical values. For the case with nested models, we show that the limit distribution, which has previously been expressed through stochastic integrals, has a simple representation in terms of -distributed random variables and we derive its density. We also generalize the limit theory to cover local alternatives and characterize the power properties of the test.

We examine the value relevance of a comprehensive set of summary performance measures including sales, earnings, comprehensive income, and operating cash flows. We find that, while value relevance peaks for measures “above the line,” no single measure dominates around the world. Instead, a measure is more relevant when it captures, directly and quickly, information about firms’ cash flows. Specifically, for each performance measure by country, we estimate eight attributes commonly used to assess earnings quality. We find these attributes highly correlated—most of their variance is explained by only two principal factors. A factor capturing articulation with cash flows is positively associated with a measure’s value relevance; a factor reflecting the measure’s persistence, predictability, smoothness, and conservatism is negatively associated. Our results suggest that, when it comes to equity valuation, accounting researchers and standard-setters should focus not on what performance measure is “best” at a given point in time, but on the underlying attributes that investors find most relevant.

When raising new equity capital managers have historically rejected the direct offer method favoring instead the seemingly more expensive underwritten public issue. This paper provides a resolution for this equity financing paradox by demonstrating empirically that firms which engage in direct offers enjoy a comparative cost advantage that is more than sufficient to account for the absolute reported cost differences between the two methods of equity financing.