6 resultados para proofofknowledge concurrent zero knowledge

em Scottish Institute for Research in Economics (SIRE) (SIRE), United Kingdom


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This paper develops stochastic search variable selection (SSVS) for zero-inflated count models which are commonly used in health economics. This allows for either model averaging or model selection in situations with many potential regressors. The proposed techniques are applied to a data set from Germany considering the demand for health care. A package for the free statistical software environment R is provided.

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This paper estimates whether both sourcing knowledge from and/or cooperating on innovation with HEIs (Higher Education Institutions)1 impacts on establishment-level total factor productivity (TFP) using a dataset created by merging the UK government’s Community Innovation Survey (CIS) with the Annual Respondents Database (ARD). It also considers whether higher graduate employment (as a measure of human capital) also impacts positively on TFP at the establishment-level. Many studies have investigated the relationship between university-firm knowledge links and innovation (see, for example, Mansfield, 1991; Becker, 2003; Thorn et al, 2007). Most of these studies find a positive impact. Fewer studies have investigated the impact of university-firm knowledge links on productivity. Belderbos et al. (2004), using the Dutch CIS, find that cooperation with universities has no statistically significant impact on the growth of labour productivity. Medda et al. (2005) find no statistically significant effect of collaborative research undertaken by Italian manufacturing firms and universities on the growth of TFP. Arvanitis et al. (2008), using Swiss data, show that university-firm knowledge and technology transfer has both a direct impact on labour productivity and an indirect impact through its positive impact on innovation. In sum, there is as yet no clear consensus as to the impact of university-firm knowledge links on productivity.

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In this paper we study a model where non-cooperative agents may exchange knowledge in a competitive environment. As a potential factor that could induce the knowledge disclosure between humans we consider the timing of the moves of players. We develop a simple model of a multistage game in which there are only three players and competition takes place only within two stages. Players can share their private knowledge with their opponents and the knowledge is modelled as in uencing their marginal cost of e¤ort. We identify two main mechanisms that work towards knowledge disclosure. One of them is that before the actual competition starts, the stronger player of the rst stage of a game may have desire to share his knowledge with the "observer", be- cause this reduces the valuation of the prize of the weaker player of that stage and as a result his e¤ort level and probability of winning in a ght. Another mechanism is that the "observer" may have sometimes desire to share knowledge with the weaker player of the rst stage, because in this way, by increasing his probability of winning in that stage, he decreases the probability of winning of the stronger player. As a result, in the second stage the "observer" may have greater chances to meet the weaker player rather than the stronger one. Keywords: knowledge sharing, strategic knowledge disclosure, multistage contest game, non-cooperative games

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In this paper, I look at the interaction between social learning and cooperative behavior. I model this using a social dilemma game with publicly observed sequential actions and asymmetric information about pay offs. I find that some informed agents in this model act, individually and without collusion, to conceal the privately optimal action. Because the privately optimal action is socially costly the behavior of informed agents can lead to a Pareto improvement in a social dilemma. In my model I show that it is possible to get cooperative behavior if information is restricted to a small but non-zero proportion of the population. Moreover, such cooperative behavior occurs in a finite setting where it is public knowledge which agent will act last. The proportion of cooperative agents within the population can be made arbitrarily close to 1 by increasing the finite number of agents playing the game. Finally, I show that under a broad set of conditions that it is a Pareto improvement on a corner value, in the ex-ante welfare sense, for an interior proportion of the population to be informed.

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This paper compares how increases in experience versus increases in knowledge about a public good affect willingness to pay (WTP) for its provision. This is challenging because while consumers are often certain about their previous experiences with a good, they may be uncertain about the accuracy of their knowledge. We therefore design and conduct a field experiment in which treated subjects receive a precise and objective signal regarding their knowledge about a public good before estimating their WTP for it. Using data for two different public goods, we show qualitative equivalence of the effect of knowledge and experience on valuation for a public good. Surprisingly, though, we find that the causal effect of objective signals about the accuracy of a subject’s knowledge for a public good can dramatically affect their valuation for it: treatment causes an increase of $150-$200 in WTP for well-informed individuals. We find no such effect for less informed subjects. Our results imply that WTP estimates for public goods are not only a function of true information states of the respondents but beliefs about those information states.

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In the context of the two-stage threshold model of decision making, with the agent’s choices determined by the interaction Of three “structural variables,” we study the restrictions on behavior that arise when one or more variables are xogenously known. Our results supply necessary and sufficient conditions for consistency with the model for all possible states of partial Knowledge, and for both single- and multivalued choice functions.