Political competition in a model of economic growth: Some theoretical results

Summary We analyze the role of political competition on the type of economic policies that are selected in a one sector model of economic growth. We identify conditions under which neoclassical optimal growth plans occur, and conditions in which political business cycles occur. We find that the ability commit to multiperiod economic policy leads to less political stability of economic plans.Support for this research was provided in part by NSF grant #SES-9022932 to the California Institute of Technology. We are grateful to a referee for pointing out that our results could be extended to supra majority rules, as in Proposition 1.     

A multistage game representation of sophisticated voting for binary procedures

Farquharson [5] was instrumental in creating the concept of sophisticated voting, in which voters are assumed to successively eliminate dominated strategies. However, his “matrix reduction” procedure is so cumbersome that little use has been made of his insights. Here we define, for binary procedures, a multistage method of sophisticated voting which is easy to apply and intuitively understandable. Our approach allows us to prove that if a majority alternative exists, sophisticated voting leads to an outcome at least as good as and sometimes preferred to the outcome of sincere voting. Our approach yields different sophisticated strategies than Farquharson's method, but we conjecture that both approaches always yield the same outcome.     

Designing an electronic auction market for complex ‘smart parts’ logistics: Options based on LeBaron's computational stock market

Modern technologies, such as RFID, offer never-before seen learning abilities to parts moving in supply chains. Logistics systems may be understood as complex adaptive logistics systems (CALS). They also may be conceived as electronic auction markets as ‘smart parts’ bid for the best routing and pricing from transportation firms. To ensure the world-wide functionality and efficiency of CALS transportation markets, we suggest the utility of an agent-based computational market design based on Blake LeBaron's stock-market model. Given that parts may be more or less smart, markets more or less complex, and self-organizing CALS systems probabilistically subject to the bullwhip effect, we suggest nine different computational CALS market-design options, offering more adaptivity to unexpected environmental contingencies.     

Intransitivities in multidimensional voting models and some implications for agenda control

This note examines critically two welfare theorems proved by Gary Becker in his “Economics of Discrimination.” Becker demonstrated that discrimination diminishes the welfare of a discriminating group. He also derived a necessary condition for a group which is the victim of discrimination to be made relatively worse off. These results are shown to depend critically on the assumption that disciminators incur psychic costs which nondiscriminators do not. When the same market equilibrium results from psychic benefits, “discriminators” are shown to gain from having a taste for favoritism and the group discriminated against is shown always to be made worse off.     

Knowledge,entrepreneurship and regional transformation: contributing to the Schumpeterian and evolutionary perspective on the relationships between them

Small Business Economics -     

Restoration of a Depleted Transboundary Fishery Subject to Climate Change: A Dynamic Investment Under Uncertainty with Information Updates

Environmental and Resource Economics - We model the evolution of a trans-boundary marine fishery, which is based on the harvesting of a single “highly-migratory” stock and is beginning...     

Learning in experimental games

Summary Experimental games typically involve subjects playing the same game a number of times. In the absence of perfect rationality by all players, the subjects may use the behavior of their opponents in early rounds to learn about the extent of irrationality in the population they face. This makes the problem of finding the Bayes-Nash equilibrium of the experimental game much more complicated than finding the game-theoretic solution to the ideal game without irrationality. We propose and implement a computationally intensive algorithm for finding the equilibria of complicated games with irrationality via the minimization of an appropriate multi-variate function. We propose two hypotheses about how agents learn when playing experimental games. The first posits that they tend to learn about each opponent as they play it repeatedly, but do not learn about the population parameters through their observations of random opponents (myopic learning). The second posits that both types of learning take place (sequential learning). We introduce a computationally intensive sequential procedure to decide on the informational value of conducting additional experiments. With the help of that procedure, we decided after 12 experiments that our original model of irrationality was unsatisfactory for the purpose of discriminating between our two hypotheses. We changed our models, allowing for two different types of irrationality, reanalyzed the old data, and conducted 7 more experiments. The new model successfully discriminated between our two hypotheses about learning. After only 7 more experiments, our approximately optimal stopping rule led us to stop sampling and accept the model where both types of learning occur.We acknowledge the financial support from NSF grant #SES9011828 to the California Institute of Technology. We also acknowledge the able research assistance of Mark Fey, Lynell Jackson and Jeffrey Prisbrey in setting up the experiments, recruiting subjects and running the experiments. We acknowledge the help of the Jet Propulsion Laboratory and its staff members for giving us access to their Cray XMP/18, and subsequently their Cray YMP2E/116.     

How public policy can stimulate the capabilities of firms to innovate in a traditional industry through academic engagement: the case of the Swedish food industry

This paper shows how public policy can stimulate innovation in low- and medium-technology industries, by connecting firms and universities through collaborative scientific research. A conceptual framework proposes that collaborative research between universities and firms may result in tangible innovative outcomes, such as new or improved products or processes, and intangible outcomes that strengthen firms’ internal capabilities and thereby indirectly increase their innovativeness. Findings are presented from a case study of a Swedish public policy stimulating the development of firm capabilities for innovation, through collaborative research projects connecting universities and firms in the food industry between 1998 and 2006. In line with the conceptual framework, the analysis distinguishes between (i) direct outcomes, such as new products; and (ii) indirect outcomes in the form of the development of firms’ capabilities to innovate. Based on this analysis, the initial conceptual framework is expanded to indicate how policy can stimulate the development of firms’ capabilities.