Kernel deconvolution estimation for random fields

In this work, we establish the asymptotic normality of the deconvolution kernel density estimator in the context of strongly mixing random fields. Only minimal conditions on the bandwidth parameter are required and a simple criterion on the strong mixing coefficients is provided. Our approach is based on the Lindeberg's method rather than on Bernstein's technique and coupling arguments widely used in previous works on nonparametric estimation for spatial processes. We deal also with nonmixing random fields which can be written as a (nonlinear) functional of i.i.d. random fields by considering the physical dependence measure coefficients introduced by Wu (2005).Comment: 28 pages. arXiv admin note: text overlap with arXiv:1109.269

The Transmission of Global Commodity Prices to Consumer Prices in a Commodity Import-Dependent Country: Evidence from Morocco

This paper uses the Breitung and Candelon (2006) causality test to examine the effect of global oil and food price changes on the inflation in Morocco over the period from 1998Q1 to 2018Q1. The results show significant transmission from oil and food prices to domestic inflation. Specifically, the food prices are shown more important than oil prices in explaining inflation in the short-run, which reflects the high weight of food in the consumption basket. However, the effect of oil prices on inflation is much more persistent than the effect of food prices. Furthermore, the impact of commodity price shocks on inflation exhibits asymmetries. The oil price hikes affect more weakly the inflation than oil price decreases, whereas the food price increases are more transmitted to inflation than food price decreases. Our findings may provide useful information to researchers and policymakers in formulating more appropriate monetary policy.JEL Codes - C32; E31; Q0

Return and Volatility Spillovers in the Moroccan Stock Market During The Financial Crisis

The aim of this paper is to investigate the return and volatility linkages among Moroccan stock market with that of U.S. and three European countries (France, Germany and U.K.) before and during the financial crisis. More specifically, we use stock returns in MASI, CAC, DAX, FTSE and NASDAQ as representatives of Moroccan, French, German, British and U.S. markets respectively. The data sample frequency is daily and spans from January 2002 to December 2012 excluding holidays. Using the estimation results of bivariate VAR-BEKK GARCH model, we analyze the return and volatility spillover effects between the Moroccan market and the other considered markets. Moreover, the identification of break point due to the subprime crisis is made by Lee-Strazicich (2003,2004) and Bai-Perron (1998, 2003) structural break tests. The empirical findings provide clear evidence of stronger linkages between the Moroccan market and the four other considered stock markets have been created during the subprime financial crisis period

Financial Market Contagion During the Global Financial Crisis: Evidence from the Moroccan Stock Market

In this paper, we aim at the study of the contagion of the global financial crisis (2007-2009) on Moroccan stock market. Our study focuses to examine whether contagion effects exist on Moroccan stock market, during the current financial crisis. Following Forbes and Rigobon (2002), we define contagion as a positive shift in the degree of comovement between asset returns. We use stock returns in MASI, CAC, DAX, FTSE and NASDAQ as representatives of Moroccan, French, German, British and U.S. markets respectively. To measure the degree of volatility comovement, time-varying correlation coefficients are estimated by flexible multivariate dynamic conditional correlation (DCC). We investigate empirical studies using the DCC-GARCH model to test the contagion hypothesis from U.S. and European markets to the Moroccan one

Return and Volatility Spillovers in the Moroccan Stock Market During The Financial Crisis

The aim of this paper is to investigate the return and volatility linkages among the Moroccan stock market and that of the US and three European countries (France, Germany and UK) before and during the financial crisis. More specifically, we use stock returns in MASI, CAC, DAX, FTSE and NASDAQ as representatives of Moroccan, French, German, British and US markets respectively. The data sample frequency is daily and spans from January 2002 to December 2012 excluding holidays. Using the estimation results of a bivariate VAR-BEKK GARCH model, we analyze the return and volatility spillover effects between the Moroccan market and the other considered markets. Moreover, the identification of break point due to the subprime crisis is made by Lee and Strazicich (2003, 2013), Papell and Prodan (2006) and Prodan (2008) structural break tests. The empirical results indicate varying degrees of interdependence and spillover effects between the four considered major stock markets and the Moroccan emerging stock market before and after the global financial crisis

Soil organisms in organic and conventional cropping systems.

Apesar do crescente interesse pela agricultura orgânica, são poucas as informações de pesquisa disponíveis sobre o assunto. Assim, num Argissolo Vermelho-Amarelo distrófico foram comparados os efeitos de sistemas de cultivo orgânico e convencional, para as culturas do tomate (Lycopersicum esculentum) e do milho (Zea mays), sobre a comunidade de organismos do solo e suas atividades. As populações de fungos,bactérias e actinomicetos, determinadas pela contagem de colônias em meio de cultura, foram semelhantes para os dois sistemas de produção. A atividade microbiana, avaliada pela evolução de CO2, manteve-se superior no sistema orgânico, sendo que em determinadas avaliações foi o dobro da evolução verificada no sistema convencional. O número de espécimes de minhoca foi praticamente dez vezes maior no sistema orgânico. Não foi observada diferença na taxa de decomposição de matéria orgânica entre os dois sistemas. De modo geral, o número de indivíduos de microartrópodos foi superior no sistema orgânico do que no sistema convencional, refletindo no maior índice de diversidade de Shannon. As maiores populações de insetos foram as da ordem Collembola, enquanto para os ácaros a maior população foi a da superfamília Oribatuloidea. Indivíduos dos grupos Aranae, Chilopoda, Dyplopoda, Pauropoda, Protura e Symphyla foram ocasionalmente coletados e de forma similar entre os sistemas

Detection of Pesticides in Active and Depopulated Beehives in Uruguay

The influence of insecticides commonly used for agricultural purposes on beehive depopulation in Uruguay was investigated. Honeycombs, bees, honey and propolis from depopulated hives were analyzed for pesticide residues, whereas from active beehives only honey and propolis were evaluated. A total of 37 samples were analyzed, representing 14,800 beehives. In depopulated beehives only imidacloprid and fipronil were detected and in active beehives endosulfan, coumaphos, cypermethrin, ethion and chlorpyrifos were found. Coumaphos was present in the highest concentrations, around 1,000 μg/kg, in all the propolis samples from active beehives. Regarding depopulated beehives, the mean levels of imidacloprid found in honeycomb (377 μg/kg, Standard Deviation: 118) and propolis (60 μg/kg, Standard Deviation: 57) are higher than those described to produce bee disorientation and fipronil levels detected in bees (150 and 170 μg/kg) are toxic per se. The other insecticides found can affect the global fitness of the bees causing weakness and a decrease in their overall productivity. These preliminary results suggest that bees exposed to pesticides or its residues can lead them in different ways to the beehive

Impacts of climate change on plant diseases – opinions and trends

There has been a remarkable scientific output on the topic of how climate change is likely to affect plant diseases in the coming decades. This review addresses the need for review of this burgeoning literature by summarizing opinions of previous reviews and trends in recent studies on the impacts of climate change on plant health. Sudden Oak Death is used as an introductory case study: Californian forests could become even more susceptible to this emerging plant disease, if spring precipitations will be accompanied by warmer temperatures, although climate shifts may also affect the current synchronicity between host cambium activity and pathogen colonization rate. A summary of observed and predicted climate changes, as well as of direct effects of climate change on pathosystems, is provided. Prediction and management of climate change effects on plant health are complicated by indirect effects and the interactions with global change drivers. Uncertainty in models of plant disease development under climate change calls for a diversity of management strategies, from more participatory approaches to interdisciplinary science. Involvement of stakeholders and scientists from outside plant pathology shows the importance of trade-offs, for example in the land-sharing vs. sparing debate. Further research is needed on climate change and plant health in mountain, boreal, Mediterranean and tropical regions, with multiple climate change factors and scenarios (including our responses to it, e.g. the assisted migration of plants), in relation to endophytes, viruses and mycorrhiza, using long-term and large-scale datasets and considering various plant disease control methods

Contribution à l'identification de modèles de séries temporelles

Cette thèse de doctorat comporte deux parties traitant des problèmes d'identification et de sélection en économétrie. Nous étudions les sujets suivants : (1) le problème d'identification de modèles de séries temporelles à l'aide des fonctions d'autocorrélation, d'autocorrélation partielle, d'autocorrélation inverse et d'autocorrélation partielle inverse ; (2) l'estimation de la fonction d'autocorrélation inverse dans le cadre des séries temporelles non linéaires. Dans une première partie, nous considérons le problème d'identification de modèles de séries temporelles à l'aide des fonctions d'autocorrélation susmentionnées. Nous construisons des tests statistiques basés sur des estimateurs empiriques de ces fonctions puis nous étudions leur distribution asymptotique. En utilisant l'approche de Bahadur et de Pitman, nous comparons la performance de ces fonctions d'autocorrélation dans la détection de l'ordre d'une moyenne mobile et d'un modèle autorégressif. Par la suite, nous nous intéressons à l'identification du processus inverse d'un modèle ARMA et à l'étude des ses propriétés probabilistes. Enfin, nous caractérisons la réversibilité temporelle à l'aide des processus dual et inverse. La deuxième partie est consacrée à l'estimation de la fonction d'autocorrélation inverse dans le cadre des processus non linéaires. Sous certaines conditions de régularité, nous étudions les propriétés asymptotiques des autocorrélations inverses empiriques pour un processus stationnaire et fortement mélangeant. Nous obtenons la convergence et la normalité asymptotique des estimateurs. par la suite, nous considérons le cas d'un processus linéaire généré par un bruit blanc de type GARCH. Nous obtenons une formule explicite pour la matrice d'autocovariance asymptotique. A l'aide d'exemples, nous montrons que la formule standard de cette matrice n'est pas valable lorsque le processus générateur des données est non linéaire. Enfin, nous appliquons les résultats précédents pour montrer la normalité asymptotique des estimateurs des paramètres d'une moyenne mobile faible. Nos résultats sont illustrés par des expériencesThis PhD dissertation consists of two parts dealing with the probelms of identification and selection in econometrics. Two mains topics are considered : (1) time series model identification by using (inverse) autocorrelation and (inverse) partial autocorrelation functions ; (2) estimation of inverse autocorrelation function in the framework of nonlinear tima series. The two parts are summarized below. In the first part of this work, we consider time series model identification y using (inverse) autocorrelation and (inverse) partial autocorrelation functions. We construct statistical tests based on estimators of these functions and establish their asymptotic distribution. Using Bahadur and Pitman approaches, we compare the performance of (inverse) autocorelations and (inverse) partial autocorrelations in detecting the order of moving average and autoregressive model. Next, we study the identification of the inverse process of an ARMA model and their probalistic properties. Finally, we characterize the time reversibility by means of the dual and inverse processes. The second part is devoted to estimation of the inverse autocorrelation function in the framework of nonlinear time series. Undes some regularity conditions, we study the asymptotic properties of empirical inverse autocorrelations for stationary and strongly mixing process. We establish the consistency and the asymptotic normality of the estimators. Next, we consider the case of linear process with GARCH errors and obtain means of some examples that the standard formula can be misleading if the generating process is non linear. Finally, we apply our previous results to prove the asymptotic normality of the parameter estimates of weak moving average. Our results are illustrated by Monte Carlo experiments and real data experiencesLILLE3-BU (590092101) / SudocSudocFranceF