Nonparametric Frontier Estimation from Noisy Data

A new nonparametric estimator of production a frontier is defined and studied when the data set of production units is contaminated by measurement error. The measurement error is assumed to be an additive normal random variable on the input variable, but its variance is unknown. The estimator is a modification of the m-frontier, which necessitates the computation of a consistent estimator of the conditional survival function of the input variable given the output variable. In this paper, the identification and the consistency of a new estimator of the survival function is proved in the presence of additive noise with unknown variance. The performance of the estimator is also studied through simulated data.

Effets des pratiques agroécologiques sur l’efficacité du système productif des producteurs maraîchers au sud du Bénin

La production maraîchère au Bénin est associée à l’usage des intrants chimiques pour améliorer les rendements. Mais face aux risques environnementaux qui pèsent sur le milieu de production, il est nécessaire de produire plus écologique. L’objectif de cette étude est d’évaluer l’effet des pratiques agroécologiques sur l’efficience du système productif des maraîchers. A cet effet, une base de données du Centre VaLDERA renseignant sur les pratiques agricoles, comptes et résultats d‘exploitation de 197 producteurs des villes de Cotonou, Sèmè-kpodji et Ouidah en 2014 a été analysée. Une analyse en composante principale (ACP) a permis d’identifier des méta-variables : niveau d’utilisation d’engrais, pratiques agroécologiques et caractéristiques sociodémographiques. Ensuite une regression linéaire multiple log-log a permis d’identifier les variables : quantité de fientes, quantité de NPK utilisées, comme les principaux déterminants de l’efficience des producteurs. Les variables diversité écologique, association culturale, rotation sont faiblement corrélées à l’efficience. Il urge de former les producteurs sur les types de rotation qui puissent améliorer leur niveau de productivité et la qualité de leur production, mais aussi de les sensibiliser à l’usage des engrais organiques pour assurer la durabilité de la production.   Vegetable production in Benin is associated with the use of chemical inputs to improve yields. However, given the environmental risks that weigh on the environment, it is necessary to produce in a more ecological way. The objective of this study is to evaluate the effect of agroecological practices on the efficiency of the market gardeners' production system. To this end, a database from the VaLDERA Centre providing information on the agricultural practices, accounts and operating results of 197 producers in the cities of Cotonou, Sèmè-kpodji and Ouidah in 2014 was analysed. A principal component analysis (PCA) identified meta-variables: level of fertiliser use, agroecological practices and socio-demographic characteristics. Then a multiple log-log linear regression identified variables: amount of manure, amount of NPK used, as the main determinants of producer efficiency. The variables ecological diversity, crop association and rotation are weakly correlated with efficiency. There is an urgent need to train producers on the types of rotation that can improve their level of productivity and the quality of their production, but also to make them aware of the use of organic fertilisers to ensure the sustainability of production

Forecasting international stock market correlations: does anything beat a CCC?

It is well known that the correlation between financial series varies over time. Here, the forecasting performance of different time-varying correlation models is compared for cross-country correlations of weekly G5 and daily European stock market indices. In contrast to previous studies only the correlation and not the entire covariance matrix is forecasted and multi-step forecasts are considered. The forecast comparison is done by considering statistical and economic criteria. The results suggest that under a statistical criterion time-varying correlation models perform quite well for weekly data, but cannot outperform the constant correlation model for daily data. Considering economic criteria it is hard to beat a constant correlation model. --dynamic conditional correlation,regime switching,stochastic correlation,smooth correlations,indirect model comparison,portfolio construction

A Kolmogorov-Smirnov type test for shortfall dominance against parametric alternatives

This paper proposes a Kolmogorov-type test for the shortfall order (also known in the literature as the right-spread or excess-wealth order) against parametric alternatives. In the case of the null hypothesis corresponding to the Negative Exponential distribution, this provides a test for the new better than used in expectation (NBUE) property. Such a test is particularly useful in reliability applications as well as duration and income distribution analysis. The theoretical properties of the testing procedure are established. Simulation studies reveal that the test proposed in this paper performs well, even with moderate sample sizes. Applications to real data, namely chief executive officer (CEO) compensation data and flight delay data, illustrate the empirical relevance of the techniques described in this paper.Right-spread order; Excess-wealth order; New better than used in expectation; Bootstrap; Reliability; CEO compensation; Flight delay

Correlated risks, bivariate utility and optimal choices

In this paper, we consider a décision-maker facing a financial risk flanked by a background risk, possibly non-financial, such as health or environmental risk. A decision has to be made about the amount of an investment (in the financial dimension) resulting in a future benefit either in the same dimension (savings) or in the order dimension (environmental quality or health improvement). In the first case, we show that the optimal amount of savings decreases as the pair of risks increases in the bivariate increasing concave dominance rules of higher degrees which express the common preferences of all the decision-makers whose two-argument utility function possesses direct and cross derivatives fulfilling some specific requirements. Roughly speaking, the optimal amount of savings decreases as the two risks become "less positively correlated" or marginally improve in univariate stochastic dominance. In the second case, a similar conclusion on optimal investment is reached under alternative conditions on the derivatives of the utility function.bivariate higher order increasing concave stochastic dominance, precautionary savings, background risk, dependence

Solvabilité II

Selon l’Autorité Européenne des Assurances et des Pensions Professionnelles (AEAPP) (European Insurance and Occupational Pensions Authority (EIOPA), en anglais), “Solvabilité II est un projet qu’a comme objectif réviser le régime de surveillance des entreprises d’assurance et réassurance dans l’Union Européenne. Le premier pas a été l’adoption en Novembre de 2009 de la Directive Solvabilité II.” Ce document présente les concepts clés et les principales formules de calcul quantitatif inclus dans Solvabilité II. Ce document est le résultat de la préparation et l’enseignement du point 4 du cours «Solvabilité» du Master en Sciences Actuarielles et Financières de l’Université de Barcelone. Cette version en français est le résultat de la participation dans la “Formation des formateurs” en collaboration avec l’ISFA de l’Université de Lyon-I

Econometric analysis of volatile art markets

A new heteroskedastic hedonic regression model is suggested which takes into account time-varying volatility and is applied to a blue chips art market. A nonparametric local likelihood estimator is proposed, and this is more precise than the often used dummy variables method. The empirical analysis reveals that errors are considerably non-Gaussian, and that a student distribution with time-varying scale and degrees of freedom does well in explaining deviations of prices from their expectation. The art price index is a smooth function of time and has a variability that is comparable to the volatility of stock indices.Volatility, art markets, hedonic regression, semiparametric estimation

Forecasting Mortality Rate Using a Neural Network with Fuzzy Inference System

Various methods have been developed to improve mortality forecasts. The authors proposed a neuro-fuzzy model to forecast the mortality. The forecasting of mortality is curried out by an ANFIS model which uses a first order Sugeno-type FIS. The model predicts the yearly mortality in a one step ahead prediction scheme. The method of trial and error was used in order to decide the type of membership function that describe better the model and provides the minimum error. The output of the models is the next year�s mortality. The results were presented and compared based on three different kinds of errors: RMSE, MAE, and MAPE. The ANFIS model gives good results for the case of two gbell membership functions and 500 epochs. Finally, the ANFIS model gives better results than the AR and ARMA model.ANFIS, Forecasting, Mortality, Modeling.

A One Line Derivation of DCC: Application of a Vector Random Coefficient Moving Average Process

One of the most widely-used multivariate conditional volatility models is the dynamic conditional correlation (or DCC) specification. However, the underlying stochastic process to derive DCC has not yet been established, which has made problematic the derivation of asymptotic properties of the Quasi-Maximum Likelihood Estimators. The paper shows that the DCC model can be obtained from a vector random coefficient moving average process, and derives the stationarity and invertibility conditions. The derivation of DCC from a vector random coefficient moving average process raises three important issues: (i) demonstrates that DCC is, in fact, a dynamic conditional covariance model of the returns shocks rather than a dynamic conditional correlation model; (ii) provides the motivation, which is presently missing, for standardization of the conditional covariance model to obtain the conditional correlation model; and (iii) shows that the appropriate ARCH or GARCH model for DCC is based on the standardized shocks rather than the returns shocks. The derivation of the regularity conditions should subsequently lead to a solid statistical foundation for the estimates of the DCC parameters