Download or read book Dynamic Factor Models written by Siem Jan Koopman and published by Emerald Group Publishing. This book was released on 2016-01-08 with total page 685 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume explores dynamic factor model specification, asymptotic and finite-sample behavior of parameter estimators, identification, frequentist and Bayesian estimation of the corresponding state space models, and applications.
Download or read book The Oxford Handbook of Economic Forecasting written by Michael P. Clements and published by OUP USA. This book was released on 2011-07-08 with total page 732 pages. Available in PDF, EPUB and Kindle. Book excerpt: Greater data availability has been coupled with developments in statistical theory and economic theory to allow more elaborate and complicated models to be entertained. These include factor models, DSGE models, restricted vector autoregressions, and non-linear models.
Download or read book Dynamic Factor Models written by Jörg Breitung and published by . This book was released on 2005 with total page 29 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Structural Vector Autoregressive Analysis written by Lutz Kilian and published by Cambridge University Press. This book was released on 2017-11-23 with total page 757 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the econometric foundations of structural vector autoregressive modeling, as used in empirical macroeconomics, finance, and related fields.
Download or read book Econometrics of Structural Change written by Walter Krämer and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: Econometric models are made up of assumptions which never exactly match reality. Among the most contested ones is the requirement that the coefficients of an econometric model remain stable over time. Recent years have therefore seen numerous attempts to test for it or to model possible structural change when it can no longer be ignored. This collection of papers from Empirical Economics mirrors part of this development. The point of departure of most studies in this volume is the standard linear regression model Yt = x;fJt + U (t = I, ... , 1), t where notation is obvious and where the index t emphasises the fact that structural change is mostly discussed and encountered in a time series context. It is much less of a problem for cross section data, although many tests apply there as well. The null hypothesis of most tests for structural change is that fJt = fJo for all t, i.e. that the same regression applies to all time periods in the sample and that the disturbances u are well behaved. The well known Chow test for instance assumes t that there is a single structural shift at a known point in time, i.e. that fJt = fJo (t
Download or read book Partial Identification in Econometrics and Related Topics written by Nguyen Ngoc Thach and published by Springer Nature. This book was released on with total page 724 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Real Sectoral Spillovers A Dynamic Factor Analysis of the Great Recession written by MissNan Li and published by International Monetary Fund. This book was released on 2018-05-09 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper studies changes in the transmission of common versus sectoral idiosyncratic shocks across different U.S. nonfarm business sectors during the Great Recession, and evaluates the cross-sectoral spillovers. Shocks are identified by dynamic factor methods. We find that the Great Recession is largely a time of heightened impact of common shocks— which accounts for 3/4 of aggregate volatility—and large spillovers of negative financerelated shocks. Moreover, in contrast with the earlier literature that failed to find a significant role of sectoral shocks (propagated through the input-output linkages across sectors) in driving variability in aggregate industry output, this study allows spillovers of shocks to operate through other mechanisms intertemporally. We find that prior to the recession the majority of aggregate fluctuations is explained by sector-specific shocks.
Download or read book Large dimensional Panel Data Econometrics Testing Estimation And Structural Changes written by Feng Qu and published by World Scientific. This book was released on 2020-08-24 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to fill the gap between panel data econometrics textbooks, and the latest development on 'big data', especially large-dimensional panel data econometrics. It introduces important research questions in large panels, including testing for cross-sectional dependence, estimation of factor-augmented panel data models, structural breaks in panels and group patterns in panels. To tackle these high dimensional issues, some techniques used in Machine Learning approaches are also illustrated. Moreover, the Monte Carlo experiments, and empirical examples are also utilised to show how to implement these new inference methods. Large-Dimensional Panel Data Econometrics: Testing, Estimation and Structural Changes also introduces new research questions and results in recent literature in this field.
Download or read book Macroeconomic Forecasting in the Era of Big Data written by Peter Fuleky and published by Springer Nature. This book was released on 2019-11-28 with total page 716 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book surveys big data tools used in macroeconomic forecasting and addresses related econometric issues, including how to capture dynamic relationships among variables; how to select parsimonious models; how to deal with model uncertainty, instability, non-stationarity, and mixed frequency data; and how to evaluate forecasts, among others. Each chapter is self-contained with references, and provides solid background information, while also reviewing the latest advances in the field. Accordingly, the book offers a valuable resource for researchers, professional forecasters, and students of quantitative economics.
Download or read book Macroeconometrics and Time Series Analysis written by Steven Durlauf and published by Springer. This book was released on 2016-04-30 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: Specially selected from The New Palgrave Dictionary of Economics 2nd edition, each article within this compendium covers the fundamental themes within the discipline and is written by a leading practitioner in the field. A handy reference tool.
Download or read book Handbook of Macroeconomics written by John B. Taylor and published by Elsevier. This book was released on 2016-12-01 with total page 1376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Macroeconomics surveys all major advances in macroeconomic scholarship since the publication of Volume 1 (1999), carefully distinguishing between empirical, theoretical, methodological, and policy issues. It courageously examines why existing models failed during the financial crisis, and also addresses well-deserved criticism head on. With contributions from the world's chief macroeconomists, its reevaluation of macroeconomic scholarship and speculation on its future constitute an investment worth making. - Serves a double role as a textbook for macroeconomics courses and as a gateway for students to the latest research - Acts as a one-of-a-kind resource as no major collections of macroeconomic essays have been published in the last decade
Download or read book Forecasting in the Presence of Structural Breaks and Model Uncertainty written by David E. Rapach and published by Emerald Group Publishing. This book was released on 2008-02-29 with total page 691 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting in the presence of structural breaks and model uncertainty are active areas of research with implications for practical problems in forecasting. This book addresses forecasting variables from both Macroeconomics and Finance, and considers various methods of dealing with model instability and model uncertainty when forming forecasts.
Download or read book Statistical Learning for Big Dependent Data written by Daniel Peña and published by John Wiley & Sons. This book was released on 2021-03-02 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master advanced topics in the analysis of large, dynamically dependent datasets with this insightful resource Statistical Learning with Big Dependent Data delivers a comprehensive presentation of the statistical and machine learning methods useful for analyzing and forecasting large and dynamically dependent data sets. The book presents automatic procedures for modelling and forecasting large sets of time series data. Beginning with some visualization tools, the book discusses procedures and methods for finding outliers, clusters, and other types of heterogeneity in big dependent data. It then introduces various dimension reduction methods, including regularization and factor models such as regularized Lasso in the presence of dynamical dependence and dynamic factor models. The book also covers other forecasting procedures, including index models, partial least squares, boosting, and now-casting. It further presents machine-learning methods, including neural network, deep learning, classification and regression trees and random forests. Finally, procedures for modelling and forecasting spatio-temporal dependent data are also presented. Throughout the book, the advantages and disadvantages of the methods discussed are given. The book uses real-world examples to demonstrate applications, including use of many R packages. Finally, an R package associated with the book is available to assist readers in reproducing the analyses of examples and to facilitate real applications. Analysis of Big Dependent Data includes a wide variety of topics for modeling and understanding big dependent data, like: New ways to plot large sets of time series An automatic procedure to build univariate ARMA models for individual components of a large data set Powerful outlier detection procedures for large sets of related time series New methods for finding the number of clusters of time series and discrimination methods , including vector support machines, for time series Broad coverage of dynamic factor models including new representations and estimation methods for generalized dynamic factor models Discussion on the usefulness of lasso with time series and an evaluation of several machine learning procedure for forecasting large sets of time series Forecasting large sets of time series with exogenous variables, including discussions of index models, partial least squares, and boosting. Introduction of modern procedures for modeling and forecasting spatio-temporal data Perfect for PhD students and researchers in business, economics, engineering, and science: Statistical Learning with Big Dependent Data also belongs to the bookshelves of practitioners in these fields who hope to improve their understanding of statistical and machine learning methods for analyzing and forecasting big dependent data.
Download or read book The Oxford Handbook of Economic Forecasting written by Michael P. Clements and published by Oxford University Press. This book was released on 2011-06-29 with total page 732 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Handbook provides up-to-date coverage of both new and well-established fields in the sphere of economic forecasting. The chapters are written by world experts in their respective fields, and provide authoritative yet accessible accounts of the key concepts, subject matter, and techniques in a number of diverse but related areas. It covers the ways in which the availability of ever more plentiful data and computational power have been used in forecasting, in terms of the frequency of observations, the number of variables, and the use of multiple data vintages. Greater data availability has been coupled with developments in statistical theory and economic analysis to allow more elaborate and complicated models to be entertained; the volume provides explanations and critiques of these developments. These include factor models, DSGE models, restricted vector autoregressions, and non-linear models, as well as models for handling data observed at mixed frequencies, high-frequency data, multiple data vintages, methods for forecasting when there are structural breaks, and how breaks might be forecast. Also covered are areas which are less commonly associated with economic forecasting, such as climate change, health economics, long-horizon growth forecasting, and political elections. Econometric forecasting has important contributions to make in these areas along with how their developments inform the mainstream.
Download or read book Large Dimensional Factor Analysis written by Jushan Bai and published by Now Publishers Inc. This book was released on 2008 with total page 90 pages. Available in PDF, EPUB and Kindle. Book excerpt: Large Dimensional Factor Analysis provides a survey of the main theoretical results for large dimensional factor models, emphasizing results that have implications for empirical work. The authors focus on the development of the static factor models and on the use of estimated factors in subsequent estimation and inference. Large Dimensional Factor Analysis discusses how to determine the number of factors, how to conduct inference when estimated factors are used in regressions, how to assess the adequacy pf observed variables as proxies for latent factors, how to exploit the estimated factors to test unit root tests and common trends, and how to estimate panel cointegration models.
Download or read book Handbook of Econometrics written by and published by Elsevier. This book was released on 2020-11-25 with total page 594 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Econometrics, Volume 7A, examines recent advances in foundational issues and "hot" topics within econometrics, such as inference for moment inequalities and estimation of high dimensional models. With its world-class editors and contributors, it succeeds in unifying leading studies of economic models, mathematical statistics and economic data. Our flourishing ability to address empirical problems in economics by using economic theory and statistical methods has driven the field of econometrics to unimaginable places. By designing methods of inference from data based on models of human choice behavior and social interactions, econometricians have created new subfields now sufficiently mature to require sophisticated literature summaries. - Presents a broader and more comprehensive view of this expanding field than any other handbook - Emphasizes the connection between econometrics and economics - Highlights current topics for which no good summaries exist
Download or read book Multivariate scaling methods and the reconstruction of social spaces written by Alice Barth and published by Verlag Barbara Budrich. This book was released on 2023-10-02 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: Der Sammelband vereint Beiträge von führenden Forscherinnen und Forschern im Bereich statistischer Methoden und deren Anwendung in den Sozialwissenschaften mit einem besonderen Fokus auf sozialen Räumen. Multivariate Skalierungsmethoden für kategoriale Daten, speziell Korrespondenzanalyse, werden verwendet um die wichtigsten Dimensionen aus komplexen Kreuztabellen mit vielen Variablen zu extrahieren und Zusammenhänge in den Daten bildlich darzustellen. In diesem Band werden statistische Weiterentwicklungen, grundsätzliche methodologische Überlegungen und empirische Anwendungen multivariater Analysemethoden diskutiert. Mehrere Anwendungsbeispiele thematisieren verschiedene Aspekte des Raumes und deren soziologische Bedeutung: die Rekonstruktion „sozialer Räume“ mit statistischen Methoden, die Illustration räumlicher Beziehungen zwischen Nähe, Distanz und Ungleichheit, aber auch konkrete Interaktionen in urbanen Räumen. Der Band erscheint zur Würdigung der wissenschaftlichen Leistungen von Prof. Jörg Blasius.
