Índice

Bibliografía: p. [589]-592

Students often have difficulties recognizing which models are more suitable than others for analysis of data sets. This book addresses this issue by providing a hands-on practical guide rich in examples and using EViews to define and test statistical hypotheses. 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. Comments and conclusions allow the advantages and disadvantages of each model to be better understood. The many alternative time series models are based on a set of selected three or five variables, and serve as a good basic guide for defining and evaluating more advanced time series models (univariate or multivariate with a larger number of variables). 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.