This text aims to help students understand the art of model building, what type of model to build, building the appropriate model, testing it statistically and applying the model to practical problems in forecasting and analysis. Although statistics is a prerequisite to use the text effectively, calculus is not required. This edition includes new material on descriptive statistics, a new chapter on non-linear and maximum likelihood estimation with a section on ARCH and GARCH models and a new test for heterosedasticity and use of panel data.
"synopsis" may belong to another edition of this title.
Book restructured into four (previously three) parts.
Part One now introduces the multiple regression model and chapter 2 has new material on descriptive statistics.
Part Two now covers single-equation regression models
New chapter (10) on nonlinear and maximum-likelihood estimation with a section on ARCH and GARCH models. New tests for heteroscedasticity (ch.6) and use of panel data (ch.9).
Part Three has revised exposition and a small macroeconomic model in an Appendix.
Four Four includes a revised treatment of time-series analysis. Chapter 18 combines two chapters from the 3/e on estimation and forecasting with time-series models.
Data for examples included in text or in IM. Now data also provided in a diskette which comes with the book.
Reviewers acclaim student accessibility, comprehensiveness, and appropriate and extensive examples.
Book helps the student understand the art of model building. The book aids understanding what type of model to build, building the appropriate model, testing it statistically, and applying the model to practical problems in forecasting and analysis
"About this title" may belong to another edition of this title.
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