Carl Menger and Friedrich von Wieser on the Role of Knowledge and Beliefs in the Emergence and Evolution of Institutions

In this article we start from the well-known contribution of the Austrian school with respect to the problem of knowledge and its role in inter- individual coordination. Focusing on two authors of this school - his founding father Carl Menger and Friedrich von Wieser, we show that the y both appreciate the role of knowledge in the emergence of economic and social institutions. However, their divergences regarding methodological individualism and subjectivism lead them to provide two different perspectives concerning the emergence and dynamics of institutions. This is exemplified by Menger and Wieser’s way of dealing with the emergence of money: on one hand, Menger takes for granted the involuntary formation of shared knowledge about the validity of social institutions such as money; on the other hand, Wieser favours an explanation whereby collective beliefs are more than shared knowledge since they do have some autonomy vis-à-vis individuals.

Statistics for the Luria-Delbr\"uck distribution

The Luria-Delbr\"uck distribution is a classical model of mutations in cell kinetics. It is obtained as a limit when the probability of mutation tends to zero and the number of divisions to infinity. It can be interpreted as a compound Poisson distribution (for the number of mutations) of exponential mixtures (for the developing time of mutant clones) of geometric distributions (for the number of cells produced by a mutant clone in a given time). The probabilistic interpretation, and a rigourous proof of convergence in the general case, are deduced from classical results on Bellman-Harris branching processes. The two parameters of the Luria-Delbr\"uck distribution are the expected number of mutations, which is the parameter of interest, and the relative fitness of normal cells compared to mutants, which is the heavy tail exponent. Both can be simultaneously estimated by the maximum likehood method. However, the computation becomes numerically unstable as soon as the maximal value of the sample is large, which occurs frequently due to the heavy tail property. Based on the empirical generating function, robust estimators are proposed and their asymptotic variance is given. They are comparable in precision to maximum likelihood estimators, with a much broader range of calculability, a better numerical stability, and a negligible computing time

Crossings of smooth shot noise processes

In this paper, we consider smooth shot noise processes and their expected number of level crossings. When the kernel response function is sufficiently smooth, the mean number of crossings function is obtained through an integral formula. Moreover, as the intensity increases, or equivalently, as the number of shots becomes larger, a normal convergence to the classical Rice's formula for Gaussian processes is obtained. The Gaussian kernel function, that corresponds to many applications in physics, is studied in detail and two different regimes are exhibited.Comment: Published in at http://dx.doi.org/10.1214/11-AAP807 the Annals of Applied Probability ( http://www.imstat.org/aap/ ) by the Institute of Mathematical Statistics (http://www.imstat.org

Money, Banking and Dynamics: Schumpeter vs. Hayek

In the first section we discuss the Wicksellian origins of Schumpeter's and Hayek's approaches to money and banking in the context of dynamic economic analysis. The second section compares the role played by banks and credit in Schumpeter's and Hayek's explanation of economic fluctuations. We conclude by contrasting both authors' perception of economic dynamics.Banking ; credit theory ; business cycles

Dynamic robust duality in utility maximization

A celebrated financial application of convex duality theory gives an explicit relation between the following two quantities: (i) The optimal terminal wealth $X^*(T) : = X_{\varphi^*}(T)$ of the problem to maximize the expected $U$-utility of the terminal wealth $X_{\varphi}(T)$ generated by admissible portfolios $\varphi(t), 0 \leq t \leq T$ in a market with the risky asset price process modeled as a semimartingale; (ii) The optimal scenario $\frac{dQ^*}{dP}$ of the dual problem to minimize the expected $V$-value of $\frac{dQ}{dP}$ over a family of equivalent local martingale measures $Q$, where $V$ is the convex conjugate function of the concave function $U$. In this paper we consider markets modeled by It\^o-L\'evy processes. In the first part we use the maximum principle in stochastic control theory to extend the above relation to a \emph{dynamic} relation, valid for all $t \in [0,T]$. We prove in particular that the optimal adjoint process for the primal problem coincides with the optimal density process, and that the optimal adjoint process for the dual problem coincides with the optimal wealth process, $0 \leq t \leq T$. In the terminal time case $t=T$ we recover the classical duality connection above. We get moreover an explicit relation between the optimal portfolio $\varphi^*$ and the optimal measure $Q^*$. We also obtain that the existence of an optimal scenario is equivalent to the replicability of a related $T$-claim. In the second part we present robust (model uncertainty) versions of the optimization problems in (i) and (ii), and we prove a similar dynamic relation between them. In particular, we show how to get from the solution of one of the problems to the other. We illustrate the results with explicit examples

A Parameterized Algebra for Event Notification Services

Event notification services are used in various applications such as digital libraries, stock tickers, traffic control, or facility management. However, to our knowledge, a common semantics of events in event notification services has not been defined so far. In this paper, we propose a parameterized event algebra which describes the semantics of composite events for event notification systems. The parameters serve as a basis for flexible handling of duplicates in both primitive and composite events

Knowledge and beliefs in economics: the case of the Austrian tradition

The contribution focuses on the problem of the influence of individual knowledge and beliefs on the working of economic activity, within the Austrian tradition of economic thought. More specifically, the contributions of von Mises, Hayek and Schumpeter are investigated. These contributions show a large variety of answers concerning the relation between individual and social beliefs. This variety is not exhaustive but it substantially contributes to a better understanding of contemporary theoretical debates.Individual/social beliefs, shared Knowledge, subjectivism, social rules

Why Global Integration May Lead to Terrorism: An Evolutionary Theory of Mimetic Rivalry

We study the emergence of the recent form of terrorism using evolutionary game theory. The model is an economic interpretation of René Girard's theory of mimetic rivalry. This theory presents terrorism as the result of competition between countries, when the desire to imitate the leading country is frustrated by the impossibility of doing so. We define a multi-country setup where interaction takes place in an international trade game, which is a coordination game. Countries follow a simple behavioral rule trying to reduce the gap between the maximal payoff obtained and their own payoff. In a coordination game, this may lead to mimetic rivalry behavior, that is the deliberate choice of a strategy degrading the situation of the leading country. Paradoxically, we find that the desire of convergence may lead to a more partitioned world economy.Terrorism Evolutionary game theory Mimetic Rivalry Risk-dominance

Societal Comparison and Social Change of the Family Division of Labour

In the case of the comparative societal analysis, the methodological problems are not simple methodological questions but of real theoretical questions. One will take the example of an international comparison relating to the division of the paid work and unpaid, to show how should have been worked out a specific methodology. This one lies nevertheless within a preliminary theoretical scope; it is partly the fruit of a "specific" theory. And, more basically still, it leads to a "general" theory; in fact a theory of the social change. This way, one studies the conditions of passage of a theory specific to a general theory by transfer of the paradigm of the societal regulations.paid and un paid work; family; international comparison; societal regulations; methodology/theory; task share; social change

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