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| Author | : Johannes Degn |
| Publisher | : |
| Total Pages | : 154 |
| Release | : 2014 |
| Genre | : |
| ISBN | : |
| Author | : Michael P. Clements |
| Publisher | : OUP USA |
| Total Pages | : 732 |
| Release | : 2011-07-08 |
| Genre | : Business & Economics |
| ISBN | : 0195398645 |
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.
| Author | : Michael P. Clements |
| Publisher | : Oxford University Press |
| Total Pages | : 732 |
| Release | : 2011-06-29 |
| Genre | : Business & Economics |
| ISBN | : 0199875510 |
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.
| Author | : Marc Hallin |
| Publisher | : World Scientific Publishing Company |
| Total Pages | : 764 |
| Release | : 2020-03-30 |
| Genre | : Business & Economics |
| ISBN | : 9789813278004 |
Factor models have become the most successful tool in the analysis and forecasting of high-dimensional time series. This monograph provides an extensive account of the so-called General Dynamic Factor Model methods. The topics covered include: asymptotic representation problems, estimation, forecasting, identification of the number of factors, identification of structural shocks, volatility analysis, and applications to macroeconomic and financial data.
| Author | : Michael Clements |
| Publisher | : Cambridge University Press |
| Total Pages | : 402 |
| Release | : 1998-10-08 |
| Genre | : Business & Economics |
| ISBN | : 9780521634809 |
This book provides a formal analysis of the models, procedures, and measures of economic forecasting with a view to improving forecasting practice. David Hendry and Michael Clements base the analyses on assumptions pertinent to the economies to be forecast, viz. a non-constant, evolving economic system, and econometric models whose form and structure are unknown a priori. The authors find that conclusions which can be established formally for constant-parameter stationary processes and correctly-specified models often do not hold when unrealistic assumptions are relaxed. Despite the difficulty of proceeding formally when models are mis-specified in unknown ways for non-stationary processes that are subject to structural breaks, Hendry and Clements show that significant insights can be gleaned. For example, a formal taxonomy of forecasting errors can be developed, the role of causal information clarified, intercept corrections re-established as a method for achieving robustness against forms of structural change, and measures of forecast accuracy re-interpreted.
| Author | : Jörg Breitung |
| Publisher | : |
| Total Pages | : 40 |
| Release | : 2016 |
| Genre | : |
| ISBN | : |
Factor models can cope with many variables without running into scarce degrees of freedom.
| Author | : Jiahan Li |
| Publisher | : |
| Total Pages | : 43 |
| Release | : 2014 |
| Genre | : |
| ISBN | : |
In a data-rich environment, forecasting economic variables amounts to extracting and organizing useful information out of a large number of predictors. So far dynamic factor model and its variants have been the most successful models for such exercises. In this paper, we investigate a category of LASSO-based approaches and evaluate their predictive abilities in forecasting twenty important macroeconomic variables. These alternative models could handle hundreds of data series simultaneously, and extract useful information for forecasting. We also show analytically and empirically that combing forecasts from LASSO-based models and those from dynamic factor models could further reduce the mean square forecast error (MSFE). Our three main findings can be summarized as follows. First, for most of the variables under investigation, all LASSO-based models outperform dynamic factor models in the out-of-sample forecast evaluations. Second, by extracting information and formulating predictors at the economically meaningful block levels, new methods greatly enhance model interpretabilities. Third, once forecasts from a LASSO-based approach and those from a dynamic factor model are combined by forecasts combination techniques, the combined forecasts are significantly better than dynamic factor model forecasts and the naïve random walk benchmark.
| Author | : C. W. J. Granger |
| Publisher | : Academic Press |
| Total Pages | : 353 |
| Release | : 2014-05-10 |
| Genre | : Business & Economics |
| ISBN | : 1483273245 |
Economic Theory, Econometrics, and Mathematical Economics, Second Edition: Forecasting Economic Time Series presents the developments in time series analysis and forecasting theory and practice. This book discusses the application of time series procedures in mainstream economic theory and econometric model building. Organized into 10 chapters, this edition begins with an overview of the problem of dealing with time series possessing a deterministic seasonal component. This text then provides a description of time series in terms of models known as the time-domain approach. Other chapters consider an alternative approach, known as spectral or frequency-domain analysis, that often provides useful insights into the properties of a series. This book discusses as well a unified approach to the fitting of linear models to a given time series. The final chapter deals with the main advantage of having a Gaussian series wherein the optimal single series, least-squares forecast will be a linear forecast. This book is a valuable resource for economists.
| Author | : Michael P. Clements |
| Publisher | : MIT Press |
| Total Pages | : 398 |
| Release | : 1999 |
| Genre | : Business & Economics |
| ISBN | : 9780262531894 |
This text on economic forecasting asks why some practices seem to work empirically despite a lack of formal support from theory. After reviewing the conventional approach to forecasting, it looks at the implications for causal modelling, presents forecast errors and delineates sources of failure.
| Author | : Terence C. Mills |
| Publisher | : Cambridge University Press |
| Total Pages | : 392 |
| Release | : 1990 |
| Genre | : Business & Economics |
| ISBN | : 9780521405744 |
The application of time series techniques in economics has become increasingly important, both for forecasting purposes and in the empirical analysis of time series in general. In this book, Terence Mills not only brings together recent research at the frontiers of the subject, but also analyses the areas of most importance to applied economics. It is an up-to-date text which extends the basic techniques of analysis to cover the development of methods that can be used to analyse a wide range of economic problems. The book analyses three basic areas of time series analysis: univariate models, multivariate models, and non-linear models. In each case the basic theory is outlined and then extended to cover recent developments. Particular emphasis is placed on applications of the theory to important areas of applied economics and on the computer software and programs needed to implement the techniques. This book clearly distinguishes itself from its competitors by emphasising the techniques of time series modelling rather than technical aspects such as estimation, and by the breadth of the models considered. It features many detailed real-world examples using a wide range of actual time series. It will be useful to econometricians and specialists in forecasting and finance and accessible to most practitioners in economics and the allied professions.
