Labor market dynamics when effort depends on wage growth comparisons

We present an efficiency wage model in which workers'' effort depends on the level and on the growth rate of their wage relative to an alternative wage. Using data for four countries (US, UK, FR, GY), the implications of the model are examined and are found to be in accordance with the information in the non-stationary data. The restrictions implied by the model dynamics are not rejected by the data. Moreover the structural parameters are found to be constant through time, indicating that, although very simple, the model is likely to be robust to the Lucas critique. One interesting result is that the workers'' effort depends less on relative wages growth and more on relative wage levels in the US than in the three European countries analyzed.mathematical economics and econometrics ;

Intertemporal Substitution in Import Demand and Habit Formation

To study non-durable import demand, we extend previous work done by Clarida (1994) and Ceglowski (1991) by considering a two-good version of the life cycle model in which we introduce time-nonseparability in the households' preferences. The model is estimated using quarterly data for US and France. Using the information contained in the observed stochastic and deterministic trends, we derive a cointegration restriction used to estimate curvature parameters of the instantaneous utility function. The remaining parameters are estimated in a second step by GMM. The constancy of the different parameters is investigated, both in the long and the short-run. Habit formation turns out to be an important factor of import demand.Imports; Habit formation; Inter-temporal Substitution; cointegration; GMM

Le programme économique de Vivant : entre utopie et réalisme

Vivant propose de remplacer les allocations sociales par un revenu de base inconditionnel, de détaxer le travail et d’instaurer une taxe sociale sur la consommation de 50 %. Ce programme est-il utopique ? Le cas échéant, certaines adaptations le rendent-elles applicable ? Toutes les générations gagnent-elles à l’application de ce programme ? Qu’en est-il de la croissance économique à long terme ?

Intertemporal substitution in import demand and habit formation *

To study non-durable import demand, we extend previous work done by Clarida (1994) and Ceglowski (1991) by considering a two-good version of the life cycle model in which we introduce time-nonseparability in the households'' preferences. The model is estimated using quarterly data for US and France. Using the infor- mation contained in the observed stochastic and deterministic trends, we derive a cointegration restriction used to estimate curvature parameters of the instantaneous utility function. The remaining parameters are estimated in a second step by GMM. The constancy of the different parameters is investigated, both in the long and the short-run. Habit formation turns out to be an important factor of import demand.mathematical applications;

Labor market dynamics when effort depends on wage growth comparisons

We present an efficiency wage model in which workers' effort depends on the level and on the growth rate of their wage relative to an alternative wage. Using data for four countries (US, UK, FR, GY), the implications of the model are examined and are found to be in accordance with the information in the non-stationary data. The restrictions implied by the model dynamics are not rejected by the data. Moreover the structural parameters are found to be constant through time, indicating that, although very simple, the model is likely to be robust to the Lucas critique. One interesting result is that the workers' effort depends less on relative wages growth and more on relative wage levels in the US than in the three European countries analyzed.efficiency wages; effort function; cointegration; GMM

Group-Size Selection for a Parameterized Class of Predator-Prey Models

Presented at the 21st International Symposium on Mathematical Theory of Networks and Systems (MTNS 2014), July 7-11, 2014, Groningen, The Netherlands.In this paper, we investigate whether we can qualitatively recover the appropriate group sizes for a team of predators by varying environmental and operational conditions. The result is a combination of biologically inspired analytical and algorithmic tools that not only establish guaranteed capture conditions, but also identify the number of predators needed for a successful capture. We implement the parameterized model on a team of mobile robots to validate that it is possible to generate a cooperative strategy that achieves capture with this model and these tools

Pancakes: A Software Framework for Distributed Robot and Sensor Network Applications

Presented at the 10th International Symposium on Distributed Autonomous Systems, Nov. 2010.The development of control applications for multi-agent robot and sensor networks is complicated by the heterogeneous nature of the systems involved, as well as their physical capabilities (or limitations). We propose a software framework that unifies these networked systems, thus facilitating the development of multi-agent control across multiple platforms and application domains. This framework addresses the need for these systems to dynamically adjust their actuating, sensing, and networking capabilities based on physical constraints, such as power levels. Furthermore, it allows for sensing and control algorithms to migrate to different platforms, which gives multi-agent control application designers the ability to adjust sensing and control as the network evolves. This paper describes the design and implementation of our software system and demonstrates its successful application on robots and sensor nodes, which dynamically modify their operational components

Distributed Fast Motion Planning for Spacecraft Swarms in Cluttered Environments Using Spherical Expansions and Sequence of Convex Optimization Problems

This paper presents a novel guidance algorithm for spacecraft swarms in an environment cluttered with many obstacles like a debris field or the asteroid belt. The objective of this algorithm is to reconfigure the swarm to a desired formation in a distributed manner while minimizing fuel and avoiding collisions among themselves and with the obstacles. The agents first use a spherical-expansion-based sampling algorithm to cooperatively explore the workspace and find paths to the desired terminal positions. Using a distributed assignment algorithm, the agents converge on an optimal assignment of the target locations in the desired formation. Then each agent generates a locally optimal trajectory from its current location to its terminal position by solving a sequence of convex optimization problems. As the agent moves along this trajectory, it receives the position of other agents and updates its trajectory to avoid collisions with other agents and the obstacles. Thus the swarm achieves the desired formation in a distributed manner while avoiding collisions. Moreover, this algorithm is computationally efficient, therefore it can be implemented onboard resource-constrained spacecraft. Simulations results show that the proposed distributed algorithm can be used by a spacecraft swarm to reconfigure a desired formation around an asteroid in a collision-free manner

Distributed Spatiotemporal Motion Planning for Spacecraft Swarms in Cluttered Environments

This paper focuses on trajectory planning for spacecraft swarms in cluttered environments, like debris fields or the asteroid belt. Our objective is to reconfigure the spacecraft swarm to a desired formation in a distributed manner while minimizing fuel and avoiding collisions among themselves and with the obstacles. In our prior work we proposed a novel distributed guidance algorithm for spacecraft swarms in static environments. In this paper, we present the Multi-Agent Moving-Obstacles Spherical Expansion and Sequential Convex Programming (MAMO SE-SCP) algorithm that extends our prior work to include spatiotemporal constraints such as time-varying, moving obstacles and desired time-varying terminal positions. In the MAMO SE-SCP algorithm, each agent uses a spherical-expansion-based sampling algorithm to cooperatively explore the time-varying environment, a distributed assignment algorithm to agree on the terminal position for each agent, and a sequential-convex-programming-based optimization step to compute the locally-optimal trajectories from the current location to the assigned time-varying terminal position while avoiding collision with other agent and the moving obstacles. Simulations results demonstrate that the proposed distributed algorithm can be used by a spacecraft swarm to achieve a time-varying, desired formation around an object of interest in a dynamic environment with many moving and tumbling obstacles