Hierarchical Organization and Inequality in an Economy with an Implicit Market for Productive Time

This paper proposes an equilibrium theory of the organization of work in an economy with an implicit market for productive time. In this economy, agents have limited productive time and can choose to produce in autarky, buy productive time from helpers to increase own production or, sell their productive time to a leader and thereby give up own production. This implicit market gives rise to the formation of teams, organized in hierarchies with one leader at the top and helpers below. We show that relative to autarky, hierarchical organization leads to higher within and between team payoffs/productivity inequality. We investigate this link empirically in the context of road cycling. We show that the rise in performance inequality in the peloton since the 1970s is merely due to a rise in within team performance inequality and consistent with a change in the hierarchical organization of teams and an increase in the helping intensity within team.hierarchical organization, productive time, helping time, inequality, professional cycling

Off-line detection of multiple change points with the Filtered Derivative with p-Value method

This paper deals with off-line detection of change points for time series of independent observations, when the number of change points is unknown. We propose a sequential analysis like method with linear time and memory complexity. Our method is based at first step, on Filtered Derivative method which detects the right change points but also false ones. We improve Filtered Derivative method by adding a second step in which we compute the p-values associated to each potential change points. Then we eliminate as false alarms the points which have p-value smaller than a given critical level. Next, our method is compared with the Penalized Least Square Criterion procedure on simulated data sets. Eventually, we apply Filtered Derivative with p-Value method to segmentation of heartbeat time series, and detection of change points in the average daily volume of financial time series

Fast change point analysis on the Hurst index of piecewise fractional Brownian motion

In this presentation, we introduce a new method for change point analysis on the Hurst index for a piecewise fractional Brownian motion. We first set the model and the statistical problem. The proposed method is a transposition of the FDpV (Filtered Derivative with p-value) method introduced for the detection of change points on the mean in Bertrand et al. (2011) to the case of changes on the Hurst index. The underlying statistics of the FDpV technology is a new statistic estimator for Hurst index, so-called Increment Bernoulli Statistic (IBS). Both FDpV and IBS are methods with linear time and memory complexity, with respect to the size of the series. Thus the resulting method for change point analysis on Hurst index reaches also a linear complexity

The Nature of Occupational Unemployment Rates in the United States: Hysteresis or Structural?

This paper provides new evidence on the nature of occupational differences in unemployment dynamics, which is relevant for the debate between the structural or hysteresis hypotheses. We develop a procedure that permits us to test for the presence of a structural break at unknown date. Our approach allows the investigation of a broader range of persistence than the 0/1 paradigm about the order of integration, usually implemented for testing the hypothesis of hysteresis in occupational unemployment. In almost all occupations, we find support for both the structuralist and the hysteresis hypotheses, but stress the importance of estimating the degree of persistence of seasonal shocks along with the degree of long-run persistence on raw data without applying seasonal filters. Indeed hysteresis appears to be underestimated when data are initially adjusted using traditional seasonal filters.fractional integration, structural break, occupational unemployment, structuralist, hysteresis

Management des contradictions et santé au travail : exploration en pays de lean management

Atteindre des performances durables est un enjeu majeur dans un monde confronté à une complexité croissante et à des risques multiples. Dans ce contexte, la santé des travailleurs est régulièrement pointée comme étant le symptôme du caractère non durable ou non tenable de certains modèles productifs regroupés en particulier sous le terme de lean management (management au plus juste). En étudiant trois entreprises ayant adopté ce type d'organisation mais présentant des différences notables en termes de santé au travail notre propos est de comprendre en quoi certains aspects du management peuvent contribuer à corriger les effets prétendument délétères du lean management et expliquer les différences observées. Plus précisément, cette étude se focalise sur la manière dont les trois entreprises managent les problèmes et contradictions potentiellement générateurs de stress auxquels doivent faire face leurs membres. Deux angles d'étude sont privilégiés : l'équipement de l'organisation en termes d'espaces de discussion d'une part, le positionnement et les caractéristiques du management intermédiaire d'autre part.Santé ; lean management ; performance ; management intermédiaire

Acoustic Observation of Living Organisms Reveals the Upper Limit of the Oxygen Minimum Zone

Background: Oxygen minimum zones (OMZs) are expanding in the World Ocean as a result of climate change and direct anthropogenic influence. OMZ expansion greatly affects biogeochemical processes and marine life, especially by constraining the vertical habitat of most marine organisms. Currently, monitoring the variability of the upper limit of the OMZs relies on time intensive sampling protocols, causing poor spatial resolution. Methodology/Principal Findings: Using routine underwater acoustic observations of the vertical distribution of marine organisms, we propose a new method that allows determination of the upper limit of the OMZ with a high precision. Applied in the eastern South-Pacific, this original sampling technique provides high-resolution information on the depth of the upper OMZ allowing documentation of mesoscale and submesoscale features (e.g., eddies and filaments) that structure the upper ocean and the marine ecosystems. We also use this information to estimate the habitable volume for the world’s most exploited fish, the Peruvian anchovy (Engraulis ringens). Conclusions/Significance: This opportunistic method could be implemented on any vessel geared with multi-frequency echosounders to perform comprehensive high-resolution monitoring of the upper limit of the OMZ. Our approach is a novel way of studying the impact of physical processes on marine life and extracting valid information about the pelagic habitat an

Continuous Cold-atom Inertial Sensor with 1 nrad.s−11\ \text{nrad.s}^{-1} Rotation Stability

We report the operation of a cold-atom inertial sensor which continuously captures the rotation signal. Using a joint interrogation scheme, where we simultaneously prepare a cold-atom source and operate an atom interferometer (AI) enables us to eliminate the dead times. We show that such continuous operation improves the short-term sensitivity of AIs, and demonstrate a rotation sensitivity of $100\ \text{nrad.s}^{-1}.\text{Hz}^{-1/2}$ in a cold-atom gyroscope of $11 \ \text{cm}^2$ Sagnac area. We also demonstrate a rotation stability of $1 \ \text{nrad.s}^{-1}$ at $10^4$ s of integration time, which establishes the record for atomic gyroscopes. The continuous operation of cold-atom inertial sensors will enable to benefit from the full sensitivity potential of large area AIs, determined by the quantum noise limit.Comment: 4 pages, 3 figure

Density modification based reliability sensitivity analysis

Sensitivity analysis of a numerical model, for instance simulating physical phenomena, is useful to quantify the influence of the inputs on the model responses. This paper proposes a new sensitivity index, based upon the modification of the probability density function (pdf) of the random inputs, when the quantity of interest is a failure probability (probability that a model output exceeds a given threshold). An input is considered influential if the input pdf modification leads to a broad change in the failure probability. These sensitivity indices can be computed using the sole set of simulations that has already been used to estimate the failure probability, thus limiting the number of calls to the numerical model. In the case of a Monte Carlo sample, asymptotical properties of the indices are derived. Based on Kullback-Leibler divergence, several types of input perturbations are introduced. The relevance of this new sensitivity analysis method is analysed through three case studies