Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Bête noire des étudiants, les statistiques sont présentes dans tous les cursus et disciplines, aussi bien en sciences dites dures (mathématiques, physique, biologie, etc.) que commerciales (marketing, distribution, communication, etc.) ou qu’en sciences humaines (économie, sociologie, géographie, etc.). Or, la statistique est à la portée de tous, à condition d’être bien expliquée. Ce manuel a été mis au point en tenant compte des besoins et attentes des étudiants : toujours mis en contexte, les concepts sont abordés de manière progressive. Les définitions, les applications concrètes et les astuces techniques (Excel et Wolfram Alpha) sont systématiquement mises en avant. Cet ouvrage vous fournit toutes les bases nécessaires pour : remédier à vos difficultés et vous rappeler les fondamentaux ; analyser et décrire des phénomènes et tendances à l’aide de graphiques ; traiter des données bivariées ; utiliser les tables de probabilités les plus courantes (loi normale, loi de Poisson…) ; constituer un échantillon représentatif ; réaliser des estimations ponctuelles et par intervalle ; tester des hypothèses et comparer des populations ; réaliser des projections, etc.

Statistics --- Statistique. --- Texebooks.

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

How will the emergence of ChatGPT and other forms of artificial intelligence (AI) affect the skill premium? To address this question, we propose a nested constant elasticity of substitution production function that distinguishes among three types of capital: traditional physical capital (machines, assembly lines), industrial robots, and AI. Following the literature, we assume that industrial robots predominantly substitute for low-skill workers, whereas AI mainly helps to perform the tasks of high-skill workers. We show that AI reduces the skill premium as long as it is more substitutable for high-skill workers than low-skill workers are for high-skill workers.

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

We investigate the determinants of emerging markets performance during five U.S. Federal Reserve monetary tightening and easing cycles during 2004 - 2023. We study how macroeconomic and institutional conditions of an Emerging Market (EM) at the beginning of a cycle explain EM resilience during each cycle. More specifically, our baseline cross-sectional regressions examine how those conditions affect three measures of resilience, namely bilateral exchange rate against the USD, exchange rate market pressure, and country-specific Morgan Stanley Capital International index (MSCI). We then stack the five cross-sections to build a panel database to investigate potential asymmetry between tightening versus easing cycles. Our evidence indicates that macroeconomic and institutional variables are associated with EM performance, determinants of resilience differ during tightening versus easing cycles, and institutions matter more during difficult times. Our specific findings are largely consistent with economic intuition. For instance, we find that current account balance, international reserves, and inflation are all important determinants of EM resilience.