Modelling economic series
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Modelling economic series readings in econometric methodology by

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Published by Clarendon Press, Oxford University Press in Oxford [England], New York .
Written in English

Subjects:

  • Econometrics

Book details:

Edition Notes

Includes bibliographical references.

Statementedited by C.W.J. Granger.
ContributionsGranger, C. W. J. 1934-
Classifications
LC ClassificationsHB139 .M624 1990
The Physical Object
Paginationvi, 419 p. :
Number of Pages419
ID Numbers
Open LibraryOL2196559M
ISBN 100198286899
LC Control Number89016203

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This third edition, co-authored with Raphael Markellos, contains a wealth of material reflecting the developments of the last decade. Particular attention is paid to the wide range of nonlinear models that are used to analyse financial data observed at high frequencies and to the long memory characteristics found in financial time by: Chapters examine the key features of economic time series, univariate time series analysis, trends, seasonality, aberrant observations, conditional heteroskedasticity and ARCH models, non-linearity and multivariate time series, making this a complete practical by: In the section on "Modelling Business Organization," a model of a Japanese organization is presented. Furthermore, a model suitable for an efficient budget management of a health service unit by applying goal programming method is analyzed, taking into account various socio-economic by: 4. Econometric Models and Economic Forecasts 4th Edition by Robert Pindyck (Author), Daniel Rubinfeld (Author), Robert S. Pindyck (Author), Daniel L. Rubinfeld (Author) & 1 more/5(11).

Book Description. This book provides a general framework for specifying, estimating, and testing time series econometric models. Special emphasis is given to estimation by maximum likelihood, but other methods are also discussed, including quasi-maximum likelihood estimation, generalized method of moments estimation, nonparametric estimation, and estimation by by: This book is an excellent "how-to" for building economic cost-effectiveness models for healthcare. The bulk of it focuses on what I would describe as intermediately complex situations such as Monte Carlo simulation of decision trees and how to build Markov by: Developed by economists, the Eviews statistical software package is used most commonly for time-series oriented econometric analysis. It allows users to quickly develop statistical relations from data and then use those relations to forecast future values of the data. Economic Modelling fills a major gap in the economics literature, providing a single source of both theoretical and applied papers on economic Economic Modelling fills a major gap in the economics literature, providing a single source of both theoretical and applied papers on economic modelling.

Developed by economists, the Eviews statistical software package is used most commonly for time series-oriented econometric analysis. It allows users to quickly develop statistical relations from data and then use those relations to forecast future values of the data. Description This book contains an extensive up-to-date overview of nonlinear time series models and their application to modelling economic relationships. It considers nonlinear models in stationary and nonstationary frameworks, and both parametric and nonparametric models are discussed. A - maybe slightly more modern - book on general methodology in the same area as Blaug’s. Granger, C.W.J. (Ed.): \Modeling Economic Series", Oxford: Oxford University Press, A book af readings in methodology from the perspective of econometricians. Some of . Publisher Summary. This chapter discusses the formulation and analysis of unobserved-components models. It discusses how unobserved-components models, which capture much of the flavor of those used by economic statisticians of the 19th and early 20th centuries, may be formulated by superimposing simple mixed moving-average autoregressive models with independent white noise .