Two Essays on Econometric Forecasting with an Econometric Model PDF Download

Author: A. C. Fenwick
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 40

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Author: Lawrence Robert Klein
Publisher: Chicago : Markham Publishing Company
ISBN:
Category : Business & Economics
Languages : en
Pages : 150

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Author: Hyun Hak Kim
Publisher:
ISBN:
Category : Macroeconomics
Languages : en
Pages : 106

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Book Description
This dissertation comprises two essays in macroeconomic forecasting. The first essay empirically examines approaches to combining factor models and robust estimation, and presents the results of a "horse-race" in which mean-square-forecast-error (MSFE) "best" models are selected, in the context of a variety of forecast horizons, estimation window schemes and sample periods. For the majority of the target variables that we forecast, it is found that various of these shrinkage methods, when combined with simple factors formed using principal component analysis (e.g. component-wise boosting), perform better than all other models. It is also found that model averaging methods perform surprisingly poorly, given our prior that they would "win" in most cases. The second essays outlines and discusses a number of interesting new forecasting methods that have recently been developed in the statistics and econometrics literature. It focuses in particular on the examination of a variety of factor modeling methods, including principal components, independent component analysis (ICA) and sparse principal component analysis (SPCA). Further, it outlines a number of approaches for creating hybrid forecasting models that use these factor modeling approaches in conjunction with various type of shrinkage methods. The results show that pure factor modeling approaches alone are not enough to lead to our overall finding that simple linear econometric models as well as models based on various forecast combination strategies are dominated by more complicated (factor/shrinkage) type models.

Author: R.A.L. Carter
Publisher: Springer Science & Business Media
ISBN: 1461390168
Category : Business & Economics
Languages : en
Pages : 378

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The purpose of this volume is to honour a pioneer in the field of econometrics, A. L. Nagar, on the occasion of his sixtieth birthday. Fourteen econometricians from six countries on four continents have contributed to this project. One of us was his teacher, some of us were his students, many of us were his colleagues, all of us are his friends. Our volume opens with a paper by L. R. Klein which discusses the meaning and role of exogenous variables in struc tural and vector-autoregressive econometric models. Several examples from recent macroeconomic history are presented and the notion of Granger-causality is discussed. This is followed by two papers dealing with an issue of considerable relevance to developing countries, such as India; the measurement of the inequality in the distribution of income. The paper by C. T. West and H. Theil deals with the problem of measuring inequality of all components of total income vvithin a region, rather than just labour income. It applies its results to the regions of the United States. The second paper in this group, by N. Kakwani, derives the large-sample distributions of several popular inequality measures, thus providing a method for drawing large-sample inferences about the differences in inequality between regions. The techniques are applied to the regions of Cote d'Ivoire. The next group of papers is devoted to econometric theory in the context of the dynamic, simultaneous, linear equations model. The first, by P. J.

Author: L.R. Klein
Publisher: Springer Science & Business Media
ISBN: 9400904630
Category : Business & Economics
Languages : en
Pages : 274

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Lawrence Klein, University of Pennsylvania Jaime Marquez, Federal Reserve BoarrI* All examination of the economics literature over the last twenty years reveals a marked tendency towards polarisation. On the one hand, there has been a propensity to develop theoretical models which have little connection with either empirical verification or problems requiring immediate attention. On the other iland, empirical analyses are generally typified by testing for its own sake, with limited examination of the implications of the results. As a result, the number of papers confronting theory with facts towards the solution of economic problems has been on the decline for years. To fill this growing gap in the literature, we have invited a number of authors to write papers using both theoretical and empirical techniques to address current issues of interest to the profession at large: the US trade deficit and the global implications of policies that attempt to reduce it, the international ramifications of the debt crisis, the international oil market and its implications for the US oil industry, and the development of new econometric techniques. In addressing these issues, each author has approached the subject matter from an eclectic standpoint - that is, avoiding strict adherence to a given doctrine.

Author: Qing Tian
Publisher:
ISBN:
Category :
Languages : en
Pages : 234

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This thesis contributes towards the improvement of model-based econometric forecast performance under realistic forecast environments, such as when information about in-sample structural breaks is unknown or when the forecast users' loss function is not based on squared-errors.

Author: Clive W. J. Granger
Publisher: Cambridge University Press
ISBN: 9780521772976
Category : Business & Economics
Languages : en
Pages : 544

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Book Description
This book, and its companion volume, present a collection of papers by Clive W.J. Granger. His contributions to economics and econometrics, many of them seminal, span more than four decades and touch on all aspects of time series analysis. The papers assembled in this volume explore topics in spectral analysis, seasonality, nonlinearity, methodology, and forecasting. Those in the companion volume investigate themes in causality, integration and cointegration, and long memory. The two volumes contain the original articles as well as an introduction written by the editors.

Author: Donald W. K. Andrews
Publisher: Cambridge University Press
ISBN: 1139444603
Category : Business & Economics
Languages : en
Pages : 589

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Book Description
This 2005 volume contains the papers presented in honor of the lifelong achievements of Thomas J. Rothenberg on the occasion of his retirement. The authors of the chapters include many of the leading econometricians of our day, and the chapters address topics of current research significance in econometric theory. The chapters cover four themes: identification and efficient estimation in econometrics, asymptotic approximations to the distributions of econometric estimators and tests, inference involving potentially nonstationary time series, such as processes that might have a unit autoregressive root, and nonparametric and semiparametric inference. Several of the chapters provide overviews and treatments of basic conceptual issues, while others advance our understanding of the properties of existing econometric procedures and/or propose others. Specific topics include identification in nonlinear models, inference with weak instruments, tests for nonstationary in time series and panel data, generalized empirical likelihood estimation, and the bootstrap.

Author: Xiaohong Chen
Publisher: Springer Science & Business Media
ISBN: 1461416531
Category : Business & Economics
Languages : en
Pages : 582

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Book Description
This book is a collection of articles that present the most recent cutting edge results on specification and estimation of economic models written by a number of the world’s foremost leaders in the fields of theoretical and methodological econometrics. Recent advances in asymptotic approximation theory, including the use of higher order asymptotics for things like estimator bias correction, and the use of various expansion and other theoretical tools for the development of bootstrap techniques designed for implementation when carrying out inference are at the forefront of theoretical development in the field of econometrics. One important feature of these advances in the theory of econometrics is that they are being seamlessly and almost immediately incorporated into the “empirical toolbox” that applied practitioners use when actually constructing models using data, for the purposes of both prediction and policy analysis and the more theoretically targeted chapters in the book will discuss these developments. Turning now to empirical methodology, chapters on prediction methodology will focus on macroeconomic and financial applications, such as the construction of diffusion index models for forecasting with very large numbers of variables, and the construction of data samples that result in optimal predictive accuracy tests when comparing alternative prediction models. Chapters carefully outline how applied practitioners can correctly implement the latest theoretical refinements in model specification in order to “build” the best models using large-scale and traditional datasets, making the book of interest to a broad readership of economists from theoretical econometricians to applied economic practitioners.

Author: Roberto S. Mariano
Publisher: World Scientific
ISBN: 9812778969
Category : Business & Economics
Languages : en
Pages : 200

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Book Description
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.