Knowledge that Transforms

The Administrative Foundations of Self-Enforcing Constitutions by Yadira Gonzalez de Lara, Avner Greif and Saumitra Jha. Published in volume 98, issue 2, pages 105-09 of American Economic Review, May 2008

A serious difficulty in determining the importance of credit constraints in education arises because standard data sources do not provide a direct way of identifying which students are credit constrained. This paper differentiates itself from previous work by taking a direct approach, made possible by unique longitudinal data from the Berea Panel Study. The results from our study of Berea College students suggest that, while credit constraints likely play an important role in the drop-out decisions of some students, the large majority of attrition of students from low-income families should be primarily attributed to reasons other than credit constraints.

Using panel data for a large set of high-income, emerging market, developing, and transition countries, we find robust evidence that the large output loss from financial crises and some types of political crises is highly persistent. The results on financial crises are also highly robust to the assumption on exogeneity. Moreover, we find strong evidence of growth over optimism before financial crises. We also find a distinction between the output impact of civil wars versus other crises, in that there is a partial output rebound for civil wars but no significant rebound for financial crises or the other political crises.

In this paper I review evidence on the long-run relation between height and economic development in Italy. I ask three questions: What are the long-run trends of mean height and real incomes in Italy? What do we know about height dispersion? What other aspects of the distribution of height changed with economic development?

Assessment Practices and Trends in Undergraduate Economics Courses by Georg Schaur, Michael Watts and William E. Becker. Published in volume 98, issue 2, pages 552-56 of American Economic Review, May 2008

Most economists and neuroeconomists believe that individuals make choices first by assigning values to objects and then by selecting the option with the highest value, perhaps with some noise (Rangel, Colin Camerer, and Read Montague 2007). This raises a question with important implications for economics: How does the brain compute the values that guide decisions (henceforth called decision values) and what are the properties of those processes? Important and more concrete examples of these questions include the following: Does the brain always assign values to objects that are commensurate with the benefits that they generate, or does it make mistakes sometimes? Does the amount of time spent computing the value matter? Are there incidental variables, such as the way an object is displayed at the time of sale, that affect the value that is assigned to it? The properties of the brain’s value computation processes should be of interest to economists since those properties determine the extent to which individuals are able to make quality choices. In addition, the properties of these processes could have important implications for the behavioral and welfare effects of practices such as in-store marketing. In this paper we explore these questions theoretically and experimentally. We propose a simple model of how computation time and experience can affect the value that is assigned to items. The model makes several stark predictions that we test using behavioral experiments.

The onset of Medicare eligibility at age 65 leads to sharp changes in the health insurance coverage of the U.S. population. These changes lead to increases in the use of medical services, with a pattern of gains across socioeconomic groups that varies by type of service. While routine doctor visits increase more for groups that previously lacked insurance, hospital admissions for relatively expensive procedures like bypass surgery and joint replacement increase more for previously insured groups that are more likely to have supplementary coverage after 65, reflecting the relative generosity of their combined insurance package under Medicare.

“All models are wrong, but some are useful. ” G.E.P. Box (1979, p. 202) Macroeconomists seek to understand the structure and performance of economies at a national or regional level and the manner in which government policy makers attempt to influence this structure and performance over time. Such understanding would seem to require a systematic exploration of the intricate feedback loops connecting micro behaviors, interaction patterns, and macro regularities as observed in real-world economies. In fact, however, mainstream macroeconomic theory remains firmly rooted in general equilibrium microfoundations (David Colander, 2006). Emphasis is on the isolated optimal choice behaviors of utility-maximizing households and profit-maximizing firms subject to budget and technological feasibility constraints, and on the equilibrium states attained through external imposition of conditions requiring fulfilled expectations and market clearing. Potentially important real-world factors such as subsistence needs, incomplete markets, imperfect competition, inside money, strategic behavioral interactions, and open-ended learning that tremendously complicate analytical formulations are typically not incorporated. Starting around the mid-1980s, various researchers have sought to develop agent-based computational economics tools able to capture in useful terms the complexity of real-world

Economists have long been interested in the idea that there is a direct circular relation between poverty and low productivity, and not just one that is mediated by market failures, usually in asset markets. The nutrition-based efficiency wage model (Partha Dasgupta and Debraj Ray, 1987) is the canonical example of models where this happens: However it has been variously suggested (see for example T. N. Srinivasan, 1994) that the link from nutrition to productivity and especially the link from productivity to nutrition is too weak to be any more than a small part of the story. Partha Dasgupta himself acknowledges this when he writes nutrition-productivity construct provides a metaphor,..., for ... an economic environment harboring poverty traps (Partha Dasgupta, 1997, page 5). We propose an alternative approach to this question based on the idea that attention is a scarce resource that is important for productivity. Specifically, people may not be able to fully attend to their jobs if they are also worrying about problems at home and being distracted in this way reduces productivity. But not paying attention at home is also costly: early symptoms of a child's sickness may go unnoticed; water may run out at the end of the day; kerosene for lighting lamps at home might run out and make it hard to do homework; etc. Finally, the extent to which home life distracts depends on the nature of home life. Specifically, certain goods (e.g. a good baby sitter, a 24-hour piped water supply, a connection to a power supply grid) can reduce the extent of home life distraction. These three assumptions generate an interesting relation between income and productivity that is at the core of our model. The non-poor in this model, by virtue of owning distraction-saving goods and services at home, are able to focus more on their work. Hence they will be more productive at work and will be able to afford more distraction-saving goods. This simple two-way relationship between in(This abstract was borrowed from another version of this item.)