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Introduction to Econometrics (third edition) by Christopher Dougherty
Oxford University Press （2007）
Description
Introduction to Econometrics provides an introduction to econometrics using analytical and intuitive methods of the classical linear regression model. Mathematical notation is kept simple and step-by-step explanations of mathematical proofs are provided to facilitate learning. The text also provided to facilitate learning. The text also contains a large number of practical exercises, enabling students to practice what they have learned.
This new edition has been substantially updated and revised with the inclusion of new material on specification tests, binary choice models, tobit analysis, sample selection bias, nonstationary time series, and unit root tests and basic cointegration. The new edition is also accompanied by a website with Powerpoint slideshows giving a parallel graphical treatment of topics treated in the book, cross-section and time series data sets, manuals for practical exercises, and lecture note extending the text. Features
The text uses non-technical language helping students to understand this subject.
Taking a modern approach to econometrics this text coves cross sectional data followed by time series data.
Comprehensive Online Resource Centre with links to up-to-date author data sets and extensive author and student resources. Instructors manual, solutions to exercises in the text, exam questions, and a student guide.
table of contents
· Review: Random variables and sampling theory
· Chapter 1: Covariance, variance, and correlation
· Chapter 2: Simple regression analysis
· Chapter 3: Properties of the regression coefficients and hypothesis testing
· Chapter 4: Multiple regression analysis
· Chapter 5: Transformations of variables
· Chapter 6: Dummy variables
· Chapter 7: Specification of regression variables: A preliminary skirmish
· Chapter 8: Heteroscedasticity
· Chapter 9: Stochastic regressors and measurement errors
· Chapter 10: Simultaneous equations estimation
· Chapter 11: Binary choice and limited dependent models and maximum likelihood
estimation
· Chapter 12: Models using time series data
· Chapter 13: Autocorrelation
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