Search results for "Elastic"
showing 10 items of 2162 documents
A kink that makes you sick : The effect of sick pay on absence
2018
We exploit a regression kink design to estimate the elasticity of the duration of sickness absence with respect to replacement rate. Elasticity is a central parameter in defining the optimal social insurance scheme compensating for lost earnings due to sickness. We use comprehensive administrative data and a kink in the policy rule near the median earnings. We find a statistically significant estimate of the elasticity of the order of one. peerReviewed
THE STOCHASTIC VOLATILITY MODEL OF BARNDORFF-NIELSEN AND SHEPHARD IN COMMODITY MARKETS
2010
We consider the non-Gaussian stochastic volatility model of Barndorff-Nielsen and Shephard for the exponential mean-reversion model of Schwartz proposed for commodity spot prices. We analyze the properties of the stochastic dynamics, and show in particular that the log-spot prices possess a stationary distribution defined as a normal variance-mixture model. Furthermore, the stochastic volatility model allows for explicit forward prices, which may produce a hump structure inherited from the mean-reversion of the stochastic volatility. Although the spot price dynamics has continuous paths, the forward prices will have a jump dynamics, where jumps occur according to changes in the volatility p…
Trade Associations: Why Not Cartels?
2021
First published: 30 September 2020 The relevance of special interests lobbying in modern democracies can hardly be questioned. But if large trade associations can overcome the free riding problem and form effective lobbies, why do they not also threaten market competition by forming equally effective cartels? We argue that the key to understanding the difference lies in supply elasticity. The group discipline which works in the case of lobbying can be effective in sustaining a cartel only if increasing output is sufficiently costly ‐ otherwise the incentive to deviate is too great. The theory helps organizing a number of stylized facts within a common framework. This article has been accept…
How does fiscal policy react to wealth composition and asset prices?
2012
Prova tipográfica
Analysis of different geometrical features to achieve close-to-bone stiffness material properties in medical device: A feasibility numerical study
2021
Background and objective: In orthopedic medical devices, elasto-plastic behavior differences between bone and metallic materials could lead to mechanical issues at the bone-implant interface, as stress shielding. Those issue are mainly related to knee and hip arthroplasty, and they could be responsible for implant failure. To reduce mismatching-related adverse events between bone and prosthesis mechanical properties, modifying the implant's internal geometry varying the bulk stiffness and density could be the right approach. Therefore, this feasibility study aims to assess which in-body gap geometry improves, by reducing, the bulk stiffness. Methods: Using five finite element models, a unia…
Analysis and optimization against buckling of beams interacting with elastic foundation
2017
We consider an infinite continuous elastic beam that interacts with linearly elastic foundation and is under compression. The problem of the beam buckling is formulated and analyzed. Then the optimization of beam against buckling is investigated. As a design variable (control function) we take the parameters of cross-section distribution of the beam from the set of periodic functions and transform the original problem of optimization of infinite beam to the corresponding problem defined at the finite interval. All investigations are on the whole founded on the analytical variational approaches and the optimal solutions are studied as a function of problems parameters. peerReviewed
Vibrations of a continuous web on elastic supports
2017
We consider an infinite, homogenous linearly elastic beam resting on a system of linearly elastic supports, as an idealized model for a paper web in the middle of a cylinder-based dryer section. We obtain closed-form analytical expressions for the eigenfrequencies and the eigenmodes. The frequencies increase as the support rigidity is increased. Each frequency is bounded from above by the solution with absolutely rigid supports, and from below by the solution in the limit of vanishing support rigidity. Thus in a real system, the natural frequencies will be lower than predicted by commonly used models with rigid supports. peerReviewed
Regularized extreme learning machine for regression problems
2011
Extreme learning machine (ELM) is a new learning algorithm for single-hidden layer feedforward networks (SLFNs) proposed by Huang et al. [1]. Its main advantage is the lower computational cost, which is especially relevant when dealing with many patterns defined in a high-dimensional space. This paper proposes an algorithm for pruning ELM networks by using regularized regression methods, thus obtaining a suitable number of the hidden nodes in the network architecture. Beginning from an initial large number of hidden nodes, irrelevant nodes are then pruned using ridge regression, elastic net and lasso methods; hence, the architectural design of ELM network can be automated. Empirical studies…
Prediction of type 2 diabetes mellitus based on nutrition data
2021
Abstract Numerous predictive models for the risk of type 2 diabetes mellitus (T2DM) exist, but a minority of them has implemented nutrition data so far, even though the significant effect of nutrition on the pathogenesis, prevention and management of T2DM has been established. Thus, in the present study, we aimed to build a predictive model for the risk of T2DM that incorporates nutrition data and calculates its predictive performance. We analysed cross-sectional data from 1591 individuals from the population-based Cooperative Health Research in the Region of Augsburg (KORA) FF4 study (2013–14) and used a bootstrap enhanced elastic net penalised multivariate regression method in order to bu…
An entropy-based machine learning algorithm for combining macroeconomic forecasts
2019
This paper applies a Machine Learning approach with the aim of providing a single aggregated prediction from a set of individual predictions. Departing from the well-known maximum-entropy inference methodology, a new factor capturing the distance between the true and the estimated aggregated predictions presents a new problem. Algorithms such as ridge, lasso or elastic net help in finding a new methodology to tackle this issue. We carry out a simulation study to evaluate the performance of such a procedure and apply it in order to forecast and measure predictive ability using a dataset of predictions on Spanish gross domestic product.