This important book consists of surveys of high-frequency financial data analysis and econometric forecasting, written by pioneers in these areas including Nobel laureate Lawrence Klein. Some of the chapters were presented as tutorials to an audience in the Econometric Forecasting and High-Frequency Data Analysis Workshop at the Institute for Mathematical Science, National University of Singapore in May 2006. They will be of interest to researchers working in macroeconometrics as well as financial econometrics. Moreover, readers will find these chapters useful as a guide to the literature as well as suggestions for future research. Sample Chapter(s). Foreword (32 KB). Chapter 1: Forecast Uncertainty, Its Representation and Evaluation* (97 KB). Contents: Forecasting Uncertainty, Its Representation and Evaluation (K F Wallis); The University of Pennsylvania Models for High-Frequency Macroeconomic Modeling (L R Klein & S Ozmucur); Forecasting Seasonal Time Series (P H Franses); Car and Affine Processes (C Gourieroux); Multivariate Time Series Analysis and Forecasting (M Deistler). Readership: Professionals and researchers in econometric forecasting and financial data analysis.
Zusammenfassung: This book, set out over four-volumes, provides a comprehensive history of economic thought in the 20th century. Special attention is given to the cultural and historical background behind the development of economic theories, the leading or the peripheral research communities and their interactions, and a critical appreciation and assessment of economic theories throughout these times. Volume III addresses economic theory in the period of the new golden age of capitalism, between the years from the end of the Second World War to the mid1970s, which saw the establishment of the new mainstream, in particular in its Harvard-MIT-Cowles version. It was the period of the pre-eminence of the Neoclassical Keynesian Synthesis--the theoretical core of the period's dominant school of thought. This work provides a significant and original contribution to the history of economic thought and gives insight to the thinking of some of the major international figures in economics. It will appeal to students, scholars and the more informed reader wishing to further their understanding of the history of the discipline. Roberto Marchionatti is Professor Emeritus of Economics at the University of Torino, Fellow of the Accademia delle Scienze di Torino, and a Life Member of Clare Hall College, Cambridge. He has previously been a Visiting Scholar at the University of New York and the University of Cambridge. He is the editor of Annals of Fondazione Luigi Einaudi: An Interdisciplinary Journal of Economics, History and Political Science and he has been co-editor of History of Economic Ideas. He has published almost 50 journal articles and more than 15 books as well as a great number of contributions in edited volumes
This substantial volume has two principal objectives. First it provides an overview of the statistical foundations of Simulation-based inference. This includes the summary and synthesis of the many concepts and results extant in the theoretical literature, the different classes of problems and estimators, the asymptotic properties of these estimators, as well as descriptions of the different simulators in use. Second, the volume provides empirical and operational examples of SBI methods. Often what is missing, even in existing applied papers, are operational issues. Which simulator works best for which problem and why? This volume will explicitly address the important numerical and computational issues in SBI which are not covered comprehensively in the existing literature. Examples of such issues are: comparisons with existing tractable methods, number of replications needed for robust results, choice of instruments, simulation noise and bias as well as efficiency loss in practice.
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