This Volume of "Advances in Econometrics" contains a selection of papers presented initially at the 7th Annual Advances in Econometrics Conference held on the LSU campus in Baton Rouge, Louisiana during November 14-16, 2008. The theme of the conference was 'Nonparametric Econometric Methods', and the papers selected for inclusion in this Volume span a range of nonparametric techniques including kernel smoothing, empirical copulas, series estimators, and smoothing splines along with a variety of semiparametric methods. The papers in this Volume cover topics of interest to those who wish to familiarize themselves with current nonparametric methodology. Many papers also identify areas deserving of future attention. There exist survey papers devoted to recent developments in nonparametric nance, constrained nonparametric regression, miparametric/nonparametric environmental econometrics and nonparametric models with non-stationary data. There exist theoretical papers dealing with novel approaches for partial identification of the distribution of treatment effects, xed effects semiparametric panel data models, functional coefficient models with time series data, exponential series estimators of empirical copulas, estimation of multivariate CDFs and bias-reduction methods for density estimation. There also exist a number of applications that analyze returns to education, the evolution of income and life expectancy, the role of governance in growth, farm production, city size and unemployment rates, derivative pricing, and environmental pollution and economic growth. In short, this Volume contains a range of theoretical developments, surveys, and applications that would be of interest to those who wish to keep abreast of some of the most important current developments in the field of nonparametric estimation.

""Nonparametric Econometrics" by Li and Racine is a must for any serious econometrician or statistician who is working on cutting-edge problems. The theoretical treatment of nonparametric methods is remarkably complete in its coverage of mainstream and relatively arcane topics. I particularly like Li and Racine's general treatment of continuous and discrete regressors and of specification testing, topics that I have not seen handled in such a comprehensive fashion. I will certainly use this in my graduate econometrics courses and in conducting my own research."--Robin Sickles, Rice University

"Very few studies have tried to apply the nonparametric techniques to analyze real data. The lack of applications of those techniques is perhaps attributable to the lack of a good textbook that explains intuitively how and why those techniques work. This book by Li and Racine serves both applied researchers and graduate students. It is written in plain language so that it can be understood by anyone with basic econometrics but zero knowledge of nonparametric methods. And it contains enough specifics that clearly spell out steps to implement those methods."--Chunrong Ai, University of Florida

"This book represents a very significant contribution to the field of econometrics. It provides an extremely thorough coverage of our knowledge in the area of nonparametric and semiparametric methods as they apply to economic models and economic data. And it makes accessible, for the first time, a body of relatively new material relating to discrete and 'mixed' data. There is a good balance of theoretical material and applications. Apart from serving as a superb teaching text in graduate-level courseswhere the students have a strong econometrics/statistics preparation, I believe this book will become a must-have reference resource for many researchers."--David E. Giles, University of Victoria