Price Stability and the ECB'S monetary policy strategy

This paper focuses on the price stability objective within the framework of the single monetary policy strategy. It starts by reviewing what this objective, which is common to all central banks, means. Second, this paper focuses exclusively on the anchoring of short- to medium-term inflation expectations (Part 2). Several measures show that this anchoring is effective. A 'two-pillar' small structural macro-economic model framework is used to analyze the impact that this anchoring of expectations has on the determination of the short- to medium-term inflation rate. From this point of view, observed inflation in the euro area seems to be in line with the theory and the ECB's action seems to be very effective. Third, we focus on the other aspect of monetary stability: the degree of price-level uncertainty and the anchoring of inflation expectations in the medium to long term. Even though this assessment is more difficult than it is in the short to medium term, since we only have a track record covering 6 years, various indicators from the theoretical analysis paint a fairly reassuring picture of the effectiveness of the device used by the ECB.European Central Bank • Inflation • Monetary policy

Semiparametric estimation of a two-component mixture model

Suppose that univariate data are drawn from a mixture of two distributions that are equal up to a shift parameter. Such a model is known to be nonidentifiable from a nonparametric viewpoint. However, if we assume that the unknown mixed distribution is symmetric, we obtain the identifiability of this model, which is then defined by four unknown parameters: the mixing proportion, two location parameters and the cumulative distribution function of the symmetric mixed distribution. We propose estimators for these four parameters when no training data is available. Our estimators are shown to be strongly consistent under mild regularity assumptions and their convergence rates are studied. Their finite-sample properties are illustrated by a Monte Carlo study and our method is applied to real data.Comment: Published at http://dx.doi.org/10.1214/009053606000000353 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Extended geometric processes: Semiparametric estimation and application to reliability

International audienceLam (2007) introduces a generalization of renewal processes named Geometric processes, where inter-arrival times are independent and identically distributed up to a multiplicative scale parameter, in a geometric fashion. We here envision a more general scaling, not necessarily geometric. The corresponding counting process is named Extended Geometric Process (EGP). Semiparametric estimates are provided and studied for an EGP, which includes consistency results and convergence rates. In a reliability context, arrivals of an EGP may stand for successive failure times of a system submitted to imperfect repairs. In this context, we study: 1) the mean number of failures on some finite horizon time; 2) a replacement policy assessed through a cost function on an infinite horizon time

Semiparametric estimate of the efficiency of imperfect maintenance actions for a gamma deteriorating system

International audienceA system is considered, which is deteriorating over time according to a non homogeneous gamma process with unknown parameters. The system is subject to periodic and instantaneous imperfect maintenance actions (repairs). Each imperfect repair removes a proportion ρ of the accumulated degradation since the previous repair. The parameter ρ hence appears as a measure for the maintenance efficiency. This model is called arithmetic reduction of degradation of order 1. The system is inspected right before each maintenance action, thus providing some multivariate measurement of the successively observed deterioration levels. Based on these data, a semiparametric estimator of ρ is proposed, considering the parameters of the underlying gamma process as nuisance parameters. This estimator is mainly based on the range of admissible ρ's, which depends on the data. Under technical assumptions, consistency results are obtained, with surprisingly high convergence rates (up to exponential). The case where several i.i.d. systems are observed is next envisioned. Consistency results are obtained for the efficiency estimator, as the number of systems tends to infinity, with a convergence rate that can be higher or lower than the classical square root rate. Finally, the performances of the estimators are illustrated on a few numerical examples

Semi- and non-parametric competing risks analysis of right censored data and failure cause missing completely at random

We consider a nonparametric and a semiparametric (in presence of covariates) additive hazards rate competing risks model with censoring and failure cause possibly missing completely at random. Estimators of the unknown parameters are proposed in order to satisfy some optimality criteria. Large ample results are given for all the estimators. Our nonparametric method is applied to a real data set and the behavior of the semiparametric estimators are analyzed through a Monte Carlo study

Semiparametric inference of competing risks data with additive hazards and missing cause of failure under MCAR or MAR assumptions

International audienceIn this paper, we consider a semiparametric model for lifetime data with competing risks and missing causes of death. We assume that an additive hazards model holds for each cause-specific hazard rate function and that a random right censoring occurs. Our goal is to estimate the regression parameters as well as the functional parameters such as the baseline and cause-specific cumulative hazard rate functions / cumulative incidence functions. We first introduce preliminary estimators of the unknown (Euclidean and functional) parameters when cause of death indicators are missing completely at random (MCAR). These estimators are obtained using the observations with known cause of failure. The advantage of considering the MCAR model is that the information given by the observed lifetimes with unknown failure cause can be used to improve the preliminary estimates in order to attain an asymptotic optimality criterion. This is the main purpose of our work. However, since it is often more realistic to consider a missing at random (MAR) mechanism, we also derive estimators of the regression and functional parameters under the MAR model. We study the large sample properties of our estimators through martingales and empirical process techniques. We also provide a simulation study to compare the behavior of our three types of estimators under the different mechanisms of missingness. It is shown that our improved estimators under MCAR assumption are quite robust if only the MAR assumption holds. Finally, three illustrations on real datasets are also given

DOI 10.1007/s10463-008-0170-8 Proportional hazards regression under progressive Type-II censoring

Abstract This paper proposes an inferential method for the semiparametric proportional hazards model for progressively Type-II censored data. We establish martingale properties of counting processes based on progressively Type-II censored data that allow to derive the asymptotic behavior of estimators of the regression parameter, the conditional cumulative hazard rate functions, and the conditional reliability functions. A Monte Carlo study and an example are provided to illustrate the behavior of our estimators and to compare progressive Type-II censoring sampling plans with classical Type-II right censoring sampling plan

Feeding pigs in organic farming

The technical booklet "Feeding pigs in organic farming" is intended for farmers and advisors. It is based on the results of four research projects and provides a synthesis of information on e.g. the regulations concerning the feeding of organic pigs, feeding management and the needs of animals according to their physiological stage. Furthermore, it includes information on the nutritive value of organic raw materials, examples of diet formulation and expected performances, the use of feedstuff and its manufacturing on the farm. This document has been produced specifically for organic farming but may be useful for all pig farmers. It can be used regardless of a farm's location