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New Perspectives in Econometric Theory
New Perspectives in Econometric Theory comprises specially selected papers by Halbert White which reflect his research in a variety of related areas in econometrics: heteroskedasticity of unknown form; nonlinear and nonparametric regression; instrumental variables and generalized method of moments estimation; and measurability and limit theory. In many instances, results from one paper provide the foundation for, or suggest new directions for, research taken up by others in the collection. The intent of collecting these papers together in the present volume, with new commentaries by the author, is to provide access both to a modern unified perspective for econometric theory and to a set of concepts and tools that will be useful to practitioners in the field. As a companion to the first volume entitled Advances in Econometric Theory, this latest selection of Halbert White's work will appeal to academics and researchers in econometrics and economic theory.
Advances in Econometric Theory
Halbert White has made a major contribution to key areas of econometrics including specification analysis, specification testing, encompassing and Cox tests and model selection. This book presents his most important published work supplemented with new material setting his work in context. Together with new introductions to each of the chapters, the articles cover work from the early 1980s to 1996 and provide an excellent overview of the breadth of Professor White's work and the evolution of his ideas. Using rigorous mathematical techniques Halbert White develops many of the central themes in econometrics concerning models, data generating processes and estimation procedures. Throughout the book the unifying vision is that econometric models are only imperfect approximations to the processes generating economic data and that this has implications for the interpretation of estimates, inference and selection of econometric models. This unique collection of some of Halbert White's important work, not otherwise readily accessible, will be welcomed by researchers, graduates and academics in econometrics and statistics.
Asymptotic Theory for Econometricians
This book is intended to provide a somewhat more comprehensive and unified treatment of large sample theory than has been available previously and to relate the fundamental tools of asymptotic theory directly to many of the estimators of interest to econometricians. In addition, because economic data are generated in a variety of different contexts (time series, cross sections, time series--cross sections), we pay particular attention to the similarities and differences in the techniques appropriate to each of these contexts.
Artificial Neural Networks
The recent re-emergence of network-based approaches to artificial intelligence has been accomplished by a virtual explosion of research. This research spans a range of disciplines - cognitive science, computer science, biology, neuroscience, electrical engineering, psychology, econometrics, philosophy, etc. - which is, perhaps, wider than any other contemporary endeavor. Of all the contributing disciplines the relatively universal language of mathematics provides some of the most powerful tools for answering fundamental questions about the capabilities and limitations of these 'artificial neural networks'. In this collection, Halbert White and his colleagues present a rigorous mathematical analysis of the approximation and learning capabilities of the leading class of single hidden layer feedforward networks. Drawing together work previously scattered in space and time, the book gives a unified view of network learning not available in any other single location, and forges fundamental links between network learning and modern mathematical statistics.
Estimation, Inference and Specification Analysis
This book examines the consequences of misspecifications for the interpretation of likelihood-based methods of statistical estimation and interference. The analysis concludes with an examination of methods by which the possibility of misspecification can be empirically investigated.
Cointegration, Causality, and Forecasting
A collection of essays in honour of Clive Granger. The chapters are by some of the world's leading econometricians, all of whom have collaborated with and/or studied with both) Clive Granger. Central themes of Granger's work are reflected in the book with attention to tests for unit roots and cointegration, tests of misspecification, forecasting models and forecast evaluation, non-linear and non-parametric econometric techniques, and overall, a careful blend of practical empirical work and strong theory. The book shows the scope of Granger's research and the range of the profession that has been influenced by his work.
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