Demographic Differentials in Facebook Usage Around the World

We use data from the Facebook Advertisement Platform to study patterns of demographic disparities in usage of Facebook across countries. We address three main questions: (1) How does Facebook usage differ by age and by gender around the world? (2) How does the size of friendship networks vary by age and by gender? (3) What are the demographic characteristics of specific subgroups of Facebook users? We find that in countries in North America and northern Europe, patterns of Facebook usage differ little between older people and younger adults. In Asian countries, which have high levels of gender inequality, differences in Facebook adoption by gender disappear at older ages, possibly as a result of selectivity. We also observe that across countries, women tend to have larger networks of close friends than men, and that female users who are living away from their hometown are more likely to engage in Facebook use than their male counterparts, regardless of their region and age group. Our findings contextualize recent research on gender gaps in online usage, and offer new insights into some of the nuances of demographic differentials in the adoption and the use of digital technologies.Comment: Accepted at a poster at ICWSM 2019. Please cite the ICWSM versio

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