Knowledge that Transforms

This paper argues that precautionary savings due to uninsurable earnings uncertainty are likely to be an important source of aggregate wealth accumulation. The stylized model presented in this paper can easily generate levels of wealth above 60 percent of the observed net wealth in the United States, net of conventional life-cycle savings.

Contrary to the long-held notion of purchasing power parity (PPP), economists have found systematic evidence that the general level of prices across countries at a point in time varies dramatically. Irving B. Kravis, Alan W. Heston, and Robert Summers (1982), for example, report that some countries' national price levels are no more than one-third the U.S. price level. Extensions of this work show that such departures from PPP have persisted for decades. Recently, efforts have been made to explain systematically these persistent, or structural, departures from PPP. Pioneering work by Kravis and Robert E. Lipsey (1983, 1987, 1988) has demonstrated that a positive correlation between the price level and (real) per capita gross domestic product is robust across numerous cross-sectional specifications. For instance, using data from Kravis et al. (1982 table 6-12), 87 percent of the variation in national price levels (PL) of 21 countries' in 1975 is explained by per capita GDP (y) and a constant:

In this study we have developed an improved model of net migration that encompasses both equilibrium and disequilibrium components. Instrumental-variables fixed-effects estimates of the model with time-series data for 51 areas [in the United States] over the period 1971-1988 support the importance of both equilibrium and disequilibrium factors in migration. (EXCERPT)

Corporations - Finance; Bank investments; Financial leverage

When households are mobile among jurisdictions, income redistribution by individual jurisdictions creates fiscal externalities. A model of interjurisdictional migration is used to study the nature of this redistributive externality. Analysis of optimal redistribution and optimal corrective subsidies from higher-level governments shows that benefit levels for the recipients of income transfers and tax rates on mobile taxpayers should be equalized across jurisdictions. A system of jurisdictions with a common labor market can achieve welfare improvements through coordination of "domestic" redistributive policy or through the intervention of a higher-level government.

We examine a situation in which insurance is characterized by moral hazard. When market insurance is provided, supplementary mutual assistance between family and friends (unobservable to market insurers) will occur. When nonmarket insurers have no better information than market insurers, the mutual assistance not only crowds out market insurance but is also harmful and therefore dysfunctional Alternatively, when nonmarket insurers can observe each other's effort perfectly, mutual assistance is beneficial These results point to the potential importance of peer-monitoring mechanisms in mitigating moral hazard.

Economists are often puzzled as to why profit-maximizing firms buy professional forecasts when statistics such as the root-mean-squared error or the mean absolute error often indicate that a naive model will forecast about as well. This paper argues that the reason is that these traditional summary statistics may not be closely related to a forecast's profits. Using profit measures, the authors find only very weak relationships between such summary error statistics and forecast value. If these results are robust, then least-squares regression analysis may not be appropriate for many studies of economic behavior.

Economic analysis has largely avoided questions about the way in which economic agents make choices when confronted by a perpetually novel and evolving world. As a result, there are outstanding questions of great interest to economics in areas ranging from technological innovation to strategic learning in games. This is so, despite the importance of the questions, because standard tools and formal models are ill-tuned for answering such questions. However, recent advances in computer-based modeling techniques, and in the subdiscipline of artificial intelligence called machine learning, offer new possibilities. Artificial adaptive agents (AAA) can be defined and can be tested in a wide variety of artificial worlds that evolve over extended periods of time. The resulting complex adaptive systems can be examined both computationally and analytically, offering new ways of experimenting with and theorizing about adaptive economic agents. Many economic systems can be classified as complex adaptive systems. Such a system is complex in a special sense: (i) It consists of a network of interacting agents (processes, elements); (ii) it exhibits a dynamic, aggregate behavior that emerges from the individual activities of the agents; and (iii) its aggregate behavior can be described without a detailed knowledge of the behavior of the individual agents. An agent in such a system is adaptive if it satisfies an additional pair of criteria: the actions of the agent in its environment can be assigned a value (performance, utility, payoff, fitness, or the like); and the agent behaves so as to increase this value over time. A complex adaptive system, then, is a complex system containing adaptive agents, networked so that the environment of each adaptive agent includes other agents in the system. Complex adaptive systems usually operate far from a global optimum or attractor. Such systems exhibit many levels of aggregation, organization, and interaction, each level having its own time scale and characteristic behavior. Any given level can usually be described in terms of local niches that can be exploited by particular adaptations. The niches are various, so it is rare that any given agent can exploit all of them, as rare as finding a universal competitor in a tropical forest. Moreover, niches are continually created by new adaptations. It is because of this ongoing evolution of the niches, and the perpetual novelty that results, that the system operates far from any global attractor. Improvements are always possible and, indeed, occur regularly. The everexpanding range of technologies and products in an economy, or the everimproving strategies in a game like chess, provide familiar examples. Adaptive systems may settle down temporarily at a local optimum, where performance is good in a comparative sense, but they are usually uninteresting if they remain at that optimum for an extended period. A theory of complex adaptive systems based on AAA makes possible the development of well-defined, yet flexible, models that exhibit emergent behavior. Such models can capture a wide range of economic phenomena precisely, even though the development of a general mathematical theory of complex adaptive systems is still in its early stages.' The AAA models complement current theoretical directions; they are