Non-Parametric Econometrics

Ibrahim Ahamada is Assistant Professor of Economics at the University Paris 1 Panthéon-Sorbonne and a member of the Paris School of Economics. Between 2002 and 2004, he held position at the Université de la Réunion. He obtained his PhD in Economics from the Université de la Méditerranée in 2002. ; Emmanuel Flachaire is Professor of Economics at Aix-Marseille University and a member of the GREQAM (Groupement de Recherche en Economie Quantitative d'Aix Marseille). Between 2001 and 2008, he taught at the University Paris 1 Panthéon-Sorbonnne, and at the Paris School of Economics. After obtaining his PhD in Economics from the Université de la Méditerranée in 1998, he has held short research positions at CORE, Université Catholique de Louvain, and the London School of Economics.

• 1. Kernel Density Estimation ; 2. Kernel Regression ; 3. Spline Regression ; 4. Wavelet Regression ; 5. Semi-Parametric Regression Models ; 6. Mixture Models ; Appendix: Implementation in R

Overall, this is a great book and provides a well-conceived overview of the main techniques that econometricians use to deal with situations where the parametric form of the model is unknown. Non-parametric techniques are increasingly used in mainstream econometrics and this book will be useful for those who wish to get caught up on these exciting developments.