The Economics of Scientific Research Coalitions: Collaborative Network Formation in the Presence of Multiple Funding Agencies

The paper develops a formal model of coalition-building (“network” formation) among research units that seek competitive funding from a supra-regional program, while also drawing support from their respective regional funding agencies. This approach enables one to ask whether there are stable (equilibrium) outcomes in the interactions among the several funding entities, and to investigate what those outcomes would imply for the evolving distribution of scientific performance within the entire region and its national sub-regions. This analysis is motivated by the absence of frameworks of analysis applicable to problems of design of public R&D funding arrangements in the European Union, and in other regional systems were independent programs of “federal and state” support for research co-exists First, a model is developed to analyze how collaborations are formed under different sets of funding rules of an international funding institution, starting with a fixed finite population of research units and an associated distribution of reputed quality, or scientific reputation.. Collaborations are formed in the expectation of attracting supra-national funding, following a specific ordering procedure; this gives rise to a repeated non-cooperative game of coalition (or collaboration) formation with the distribution of payoffs within the collaboration following to a fixed rule. Non- cooperative games of coalition formation developed by Bloch (1995), and Ray and Vohra (1999), provides a useful framework single-period framework. Following Keely (1999), this type of game is applied to a multi-period setting in which a distribution of coalitions is tracked, along with the levels of funding received. The latter are determined according to a rule comparing the distribution of reputations within and across collaborations. Alternative possible external funding rules are analyzed to determine how they impact upon collaboration formation, and the resulting evolution of the reputation distribution (as that will be affected by the allocation of funding). In the second part of the analysis, various combinations of national and supra-national funding regimes are examined, but all the rules considered stipulate that collaborations are funded as a whole, regardless of the number of members; and that their funding is determined by the absolute level of average reputation, or of the variance in reputation, rather than just the rankings of the proposed networks. The Nash equilibria associated with each of the stipulated funding regimes can be compared, and to characterize the outcomes, the paper examines these two moments of the endogenously determined distributions research “competence” (signaled by the reputation measures) within the entire ensemble of research units and its national partitions. A numerical simulation helps illustrate the nature of the conclusions for policy design that can be drawn from this style of analysis.

Understanding Preferences For Income Redestribution

Recent research suggests that income redistribution preferences vary across identity groups. We employ a new pattern recognition technology, tree regression analysis, to uncover what these groups are. Using data from the General Social Survey, we present a new stylized fact that preferences for governmental provision of income redistribution vary systematically with race, gender, and class background. We explore the extent to which existing theories of income redistribution can explain our results, but conclude that current approaches do not fully explain the findings.

Understanding Divergent Views on Redistribution Policy in the United States

Particular demographic groups are often associated with distinct points of view across various dimensions of redistribution policy. In this paper, we investigate which demographic groups account for heterogeneity in views on welfare policy and views on appropriate levels of overall redistribution. Using data from the General Social Survey and classification tools, we find evidence that classifications of the population by race, socioeconomic status, and age have some predictive power. However, much heterogeneity in views on redistribution policy persists even within these demographic groupings and remains unexplained. Our results suggest that identity-based explanations for variations in these views have to be interpreted with caution.Data mining, classification and regression trees, random forests, redistribution preferences, welfare, identity

Understanding preferences for income redistribution

Recent research suggests that income redistribution preferences vary across identity groups. We employ a new pattern recognition technology to uncover what these groups are. Using data from the General Social Survey, we present a new stylized fact that preferences for governmental provision of income redistribution vary systematically with race, gender, and class background. We explore the extent to which existing theories of income redistribution can explain our results, but conclude that current approaches do not fully explain the findingsIncome redistribution, social interactions

Pathway from poverty?: intellectual property and developing countries

This new report, published in association with the IPI is the first wide-ranging analysis of the economic studies done on intellectual property laws. It concludes that there are some benefits from intellectual property protection; but that strengthening such protection may not always boost economic welfare and might even reduce it, even in developed countries

Technology in growth

We review the role of R&D in endogenous growth theory, and describe extant empirical research macro and micro bearing on R&D as an engine of growth. Taking R&D to be key while recognizing the significance of economic incentives emphasizes knowledge as an economic object and, more generally, the economics of intellectual property rights. This paper argues that property rights matter, but in subtle counterintuitive ways not yet fully investigated in research on endogenous growth

Understanding preferences for income redistribution

Recent research suggests that income redistribution preferences vary across identity groups. We employ statistical learning methods that emphasize pattern recognition; classification and regression trees (CART(TM)) and random forests (RandomForests(TM)), to uncover what these groups are. Using data from the General Social Survey, we find that, out of a large set of identity markers, only race, gender, age, and socioeconomic class are important classifiers for income redistribution preferences. Further, the uncovered identity groupings are characterized by complex patterns of interaction amongst these salient classifiers. We explore the extent to which existing theories of income redistribution can explain our results, but conclude that current approaches do not fully explain the findings.

Pathway from poverty? Intellectual property and developing countries

Includes bibliographical referencesAvailable from British Library Document Supply Centre- DSC:02/42425 / BLDSC - British Library Document Supply CentreSIGLEGBUnited Kingdo