A Monthly Indicator of the French Business Climate

In France, the business tendency surveys conducted in all the important sectors of the economy are key components in diagnosing the economic outlook. Over the years, INSEE has gradually introduced business climate indicators for each business sector. Such indicators summarise the data contained in the many balances of opinion supplied by the surveys and enable to measure the economic situation each month. An indicator of this kind has been lacking, however, for the economy as the whole. To fill this gap and enrich the existing panel of business climate indicators we provide in this paper the first composite indicator based on French business surveys covering all the important economic sectors of the French economy. We chose the dynamic factor analysis to deal with mixed and changing frequencies and time availability of the data. Parameters are estimated by maximum likelihood based on the Kalman filter. Several indicators can be estimated according to the type (sector-based business climate indicators or elementary components) and the number of variables included in the model. To validate our results and choose the best indicator, we defined three criteria : real-time stability, predictive accuracy to forecast GDP growth and ability to reproduce French business cycles. The new monthly synthetic indicator which passed the tests best allows a clear and simple interpretation of all the business surveys and can deliver each month an early and accurate quantitative message concerning the current business climate in France. This indicator can also be used to improve GDP growth forecast.business survey, dynamic factor analysis, unobserved components model, Kalman filter

Forecasting interest rates: A Comparative assessment of some second generation non-linear model

Modelling and forecasting of interest rates has traditionally proceeded in the framework of linear stationary models such as ARMA and VAR, but only with moderate success. We examine here four models which account for several specific features of real world asset prices such as non-stationarity and non-linearity. Our four candidate models are based respectively on wavelet analysis, mixed spectrum analysis, non-linear ARMA models with Fourier coefficients, and the Kalman filter. These models are applied to weekly data on interest rates in India, and their forecasting performance is evaluated vis-…-vis three GARCH models (GARCH (1,1), GARCH-M (1,1) and EGARCH (1,1)) as well as the random walk model. The Kalman filter model emerges at the top, with wavelet and mixed spectrum models also showing considerable promise.Interest rates, wavelets, mixed spectra, non-linear ARMA, Kalman filter, GARCH, Forecast encompassing

FORECASTING INTEREST RATES - A COMPARATIVE ASSESSMENT OF SOME SECOND GENERATION NON-LINEAR MODELS

Modelling and forecasting of interest rates has traditionally proceeded in the framework of linear stationary models such as ARMA and VAR, but only with moderate success. We examine here four models which account for several specific features of real world asset prices such as non-stationarity and non-linearity. Our four candidate models are based respectively on wavelet analysis, mixed spectrum analysis, non-linear ARMA models with Fourier coefficients, and the Kalman filter. These models are applied to weekly data on interest rates in India, and their forecasting performance is evaluated vis--vis three GARCH models (GARCH (1,1), GARCH-M (1,1) and EGARCH (1,1)) as well as the random walk model. The Kalman filter model emerges at the top, with wavelet and mixed spectrum models also showing considerable promise.interest rates, wavelets, mixed spectra, non-linear ARMA, Kalman filter, GARCH, Forecast encompassing.

Biotechnologies et arachide

Research on groundnut biotechnology is mainly carried out in the United States and also through international collaborative programs involving Icrisat and Cirad. However, despite its high phenotypic variation, cultivated groundnut shows little molecular polymorphism. The only known application to DNA marker-assisted selection has been the use of genes from wild species in crosses with cultivated species. Until quite recent years, the main results published concerned the development of efficient plant regeneration and gene transfer techniques. Groundnut is an important food and cash crop in the semi-arid tropics but drought and subsequent seeds pre-harvest aflatoxin contamination are the main constraints to crop productivity and quality. Since genetic engineering techniques are available and genetic mapping proves unfruitful, research is now focused on functional genomics. The objective is to provide new molecular tools to assist breeding programmes for the resistance to these two complex traits. (Résumé d'auteur

Amélioration de la culture de l'arachide dans le Yunnan : rapport de mission en Chine du 23 octobre au 4 novembre 1999

A la demande de l'Académie des Sciences Agricoles du Yunnan (Yaas) et dans le cadre des relations existant depuis 1992 entre le Cirad et le Yaas, j'ai réalisé, en tant un sélectionneur arachide du Cirad-Ca, une mission auprès de l'Ocri (Oil Crop Research lnstitute), un des instituts constituant le Yaas, à Kunming (Yunnan), du 25 au 30 octobre 1999. Le financement du voyage a été obtenu auprès du Mae 1 /France, le Yaas et le Cirad ont pris en charge les frais de séjour. L'objectif de la mission était d'évaluer les capacités scientifiques de l'Ocri-Yaas en matière de recherche sur l'arachide afin de proposer un programme de coopération dans le cadre d'un Pra (Programme de recherche avancée) sur financement du Service de coopération et d'action culturelle de !'Ambassade de France à Pékin. L'arachide est une culture marginale au Yunnan (30 000 ha) mais représente un complément de revenu très apprécié par les petits cultivateurs, largement majoritaires, du Yunnan. Il semble établi que la sécheresse constitue le facteur limitant principal de la production car l'irrigation est rarement réalisable. Il s'ensuit que la demande des paysans est clairement orientée sur la recherche de variétés mieux adaptées à la sécheresse que celles qui sont actuellement utilisées. Par ailleurs afin d'accroître la valeur ajouté sur le produit, l'Ocri-Yaas est également intéressé par les aspects liés à la qualité et à la transformation de l'arachide pour l'utilisation directe et en confiserie, hors huilerie car la filière n'est pas organisée pour ce type de transformation. Les objectifs scientifiques définis lors de la mission sont les suivants • évaluer de nouvelles variétés d'arachide introduites en vue d'une meilleure adaptation aux conditions climatiques du Yunnan (sécheresse); • améliorer l'itinéraire technique de la culture notamment au niveau de la densité de peuplement; • améliorer la qualité de l'arachide produite et développer de nouvelles utilisations (première transformation) de l'arachide au Yunnan