Scope of Innovations, Knowledge Spillovers and Growth

This paper exploits the formalization of a circular product differentiation model of Salop (1979) to propose an endogenous growth quality ladder model in which the knowledge inherent in a given sector can spread variously across the sectors of the economy, ranging from local to global influence. Accordingly, this affects the size of the pool of knowledge in which innovations draw themselves on in order to be produced. Therefore, the law of knowledge accumulation, and thus the growth rate of the economy, depend positively on the expected scope of diffusion of innovations, i.e. on the intensity of knowledge spillovers. This approach generalizes the endogenous growth theory as developed in the seminal models of Grossman & Helpman (1991) and Aghion & Howitt (1992), extending their analysis to the possibility of considering stochastic and partial knowledge spillovers. This framework allows us to mitigate the positive externality of knowledge and thus to apprehend the issue of the funding of research with more parsimony. We characterize the set of steady-state Schumpeterian equilibria as a function of the public tools. We provide an explanation for the fact that research effort can either be suboptimal or over-optimal, depending on the expected scope of knowledge. Accordingly, we find that the optimal public tool dedicated to foster R&D activity depends positively on it.Schumpeterian growth, scope of diffusion of innovations, knowledge spillovers

Likelihood-Free Parallel Tempering

Approximate Bayesian Computational (ABC) methods (or likelihood-free methods) have appeared in the past fifteen years as useful methods to perform Bayesian analyses when the likelihood is analytically or computationally intractable. Several ABC methods have been proposed: Monte Carlo Markov Chains (MCMC) methods have been developped by Marjoramet al. (2003) and by Bortotet al. (2007) for instance, and sequential methods have been proposed among others by Sissonet al. (2007), Beaumont et al. (2009) and Del Moral et al. (2009). Until now, while ABC-MCMC methods remain the reference, sequential ABC methods have appeared to outperforms them (see for example McKinley et al. (2009) or Sisson et al. (2007)). In this paper a new algorithm combining population-based MCMC methods with ABC requirements is proposed, using an analogy with the Parallel Tempering algorithm (Geyer, 1991). Performances are compared with existing ABC algorithms on simulations and on a real example

Dynamic adverse selection and debt

This paper argues that the strategic use of debt favours the revelation of information in dynamic adverse selection problems. Our argument is based on the idea that debt is a credible commitment to end long term relationships. Consequently, debt encourages a privately informed party to disclose its information at early stages of a relationship. We illustrate our point with the financing decision of a monopolist selling a good to a buyer whose valuation is private information. A high level of (renegotiable) debt, by increasing the scope for liquidation, may induce the high valuation buyer to buy early at a high price and thus increase the monopolist's expected payoff. By affecting the buyer's strategy, it may reduce the probability of excessive liquidation. We investigate the consequences of good durability and we examine the way debt may alleviate the ratchet effect.Dynamic adverse selection, durable good, ratchet effect, renegotiation, financial constraint, debt