Time Series Data Analysis Using EViews

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Do you want to recognize the most suitable models for analysis of statistical data sets? This book provides a hands-on practical guide to using the most suitable models for analysis of statistical data sets using EViews - an interactive Windows-based computer software program for sophisticated data analysis, regression, and forecasting - to define and test statistical hypotheses. Rich in examples and with an emphasis on how to develop acceptable statistical models, Time Series Data Analysis Using EViews is a perfect complement to theoretical books presenting statistical or econometric models for time series data. The procedures introduced are easily extendible to cross-section data sets. The author: * Provides step-by-step directions on how to apply EViews software to time series data analysis * Offers guidance on how to develop and evaluate alternative empirical models, permitting the most appropriate to be selected without the need for computational formulae * Examines a variety of times series models, including continuous growth, discontinuous growth, seemingly causal, regression, ARCH, and GARCH as well as a general form of nonlinear time series and nonparametric models * Gives over 250 illustrative examples and notes based on the author's own empirical findings, allowing the advantages and limitations of each model to be understood * Describes the theory behind the models in comprehensive appendices * Provides supplementary information and data sets An essential tool for advanced undergraduate and graduate students taking finance or econometrics courses. Statistics, life sciences, and social science students, as well as applied researchers, will also find this book an invaluable resource.
This book is a practical guide to selecting and applying the most appropriate time series model and analysis of data sets using EViews. After introducing EViews workfiles and how to carry out descriptive data analysis, the book goes on to describe various models in detail (continuous growth, discontinuous growth, seemingly causal models, special cases of regression models, ARCH and GARCH models), all illustrated with a rich variety of examples and accompanied by helpful notes. Additional testing hypotheses are also explored and finally extension to a general form of nonlinear time series model is examined. Designed as a special guide for students and less experienced researchers it is a perfect complement to more theoretical books presenting statistical or econometric models for time series data.

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Econometrics Economics Finanz- u. Wirtschaftsstatistik Ökonometrie Statistics Statistics for Finance, Business & Economics Statistik Time Series Volkswirtschaftslehre Zeitreihen Zeitreihenanalyse

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