First course in Econometrics in Economics Departments at better schools, also Economic/Business Forecasting. Statistics prerequisite but no calculus. Slightly higher level and more comprehensive than Gujarati (M-H, 1996) . P-R covers more time series and forecasting. P-R coverage is notch below Johnston-DiNardo (M-H, 97) and requires no matrix algebra. Includes data disk.
"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
This is a first course in Econometrics in Economics Departments at better schools, and also includes Economic/Business Forecasting. Statistics are a prerequisite, but not calculus. This is at a slightly higher level and more comprehensive than Gujarati (M-H, 1996) . P-R covers more time series and forecasting. P-R coverage is a notch below Johnston-DiNardo (M-H, 97) and requires no matrix algebra. It also includes a data disk.
"About this title" may belong to another edition of this title.
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