Adonis Yatchew provides simple and flexible (nonparametric) techniques for analyzing regression data. He includes a series of empirical examples with the estimation of Engel curves and equivalence scales, scale economies, household gasoline consumption, housing prices, option prices and state price density estimation. The book is of interest to a broad range of economists including those working in industrial organization, labor, development, and urban, energy and financial economics.

This text introduces students progressively to various aspects of qualitative models and assumes a knowledge of basic principles of statistics and econometrics. After the introduction, Chapters 2 through 6 present models with endogenous qualitative variables, examining dichotomous models, model specification, estimation methods, descriptive usage, and qualitative panel data. The final two chapters describe models that explain variables assumed by discrete or continuous positive variables.

This book systematically and thoroughly covers a vast literature on the nonparametric and semiparametric statistics and econometrics that has evolved over the past five decades. Within this framework, this is the first book to discuss the principles of the nonparametric approach to the topics covered in a first year graduate course in econometrics, e.g., regression function, heteroskedasticity, simultaneous equations models, logit-probit and censored models. Professors Pagan and Ullah provide intuitive explanations of difficult concepts, heuristic developments of theory, and empirical...

This two-volume work aims to present as completely as possible the methods of statistical inference with special reference to their economic applications. It is a well-integrated textbook presenting a wide diversity of models in a coherent and unified framework. The reader will find a description not only of the classical concepts and results of mathematical statistics, but also of concepts and methods recently developed for the specific needs of econometrics. Although the two volumes do not demand a high level of mathematical knowledge, they do draw on linear algebra and probability theory....

Concisely written and up-to-date, this book provides a unified and comprehensive analysis of the full range of topics that comprise modern time series econometrics. While it does demand a good quantitative grounding, it does not require a high mathematical rigor or a deep knowledge of economics. One of the book's most attractive features is the close attention it pays throughout to economic models and phenomena. The authors provide a sound analysis of the statistical origins of topics such as seasonal adjustment, causality, exogeneity, cointegration, prediction, and forecasting. Their...

Concisely written and up-to-date, this book provides a unified and comprehensive analysis of the full range of topics that comprise modern time series econometrics. While it does demand a good quantitative grounding, it does not require a high mathematical rigor or a deep knowledge of economics. One of the book's most attractive features is the close attention it pays throughout to economic models and phenomena. The authors provide a sound analysis of the statistical origins of topics such as seasonal adjustment, causality, exogeneity, cointegration, prediction, and forecasting. Their...

This two-volume work aims to present as completely as possible the methods of statistical inference with special reference to their economic applications. The reader will find a description not only of the classical concepts and results of mathematical statistics, but also of concepts and methods recently developed for the specific needs of econometrics. The authors have sought to avoid an overly technical presentation and go to some lengths to encourage an intuitive understanding of the results by providing numerous examples throughout. The breadth of approaches and the extensive coverage of...

This two-volume work aims to present as completely as possible the methods of statistical inference with special reference to their economic applications. It is a well-integrated textbook presenting a wide diversity of models in a coherent and unified framework. The reader will find a description not only of the classical concepts and results of mathematical statistics, but also of concepts and methods recently developed for the specific needs of econometrics. Although the two volumes do not demand a high level of mathematical knowledge, they do draw on linear algebra and probability theory....

This two-volume work aims to present as completely as possible the methods of statistical inference with special reference to their economic applications. The reader will find a description not only of the classical concepts and results of mathematical statistics, but also of concepts and methods recently developed for the specific needs of econometrics. The authors have sought to avoid an overly technical presentation and go to some lengths to encourage an intuitive understanding of the results by providing numerous examples throughout. The breadth of approaches and the extensive coverage of...

Time series econometrics is used for predicting future developments of variables of interest such as economic growth, stock market volatility or interest rates. A model has to be constructed, accordingly, to describe the data generation process and to estimate its parameters. Modern tools to accomplish these tasks are provided in this volume, which also demonstrates by example how the tools can be applied.