Econometrics by example

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Econometrics by example

Damodar Gujarati

Palgrave Macmillan, 2011

  • : pbk

Available at  / 26 libraries

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Includes index

Description and Table of Contents

Description

Damodar Gujarati is the author of bestselling econometrics textbooks used around the world. In his latest book, Econometrics by Example, Gujarati presents a unique learning-by-doing approach to the study of econometrics. Rather than relying on complex theoretical discussions and complicated mathematics, this book explains econometrics from a practical point of view, with each chapter anchored in one or two extended real-life examples. The basic theory underlying each topic is covered and an appendix is included on the basic statistical concepts that underlie the material, making Econometrics by Example an ideally flexible and self-contained learning resource for students studying econometrics for the first time. The book includes: - a wide-ranging collection of examples, with data on mortgages, exchange rates, charitable giving, fashion sales and more - a clear, step-by-step writing style that guides you from model formulation, to estimation and hypothesis-testing, through to post-estimation diagnostics - coverage of modern topics such as instrumental variables and panel data - extensive use of Stata and EViews statistical packages with reproductions of the outputs from these packages - an appendix discussing the basic concepts of statistics - end-of-chapter summaries, conclusions and exercises to reinforce your learning - a companion website containing PowerPoint slides and a full solutions manual to all exercises for instructors, and downloadable data sets and chapter summaries for students.

Table of Contents

PART I: THE LINEAR REGRESSION MODEL CHAPTER 1: The Linear Regression Model: An Overview CHAPTER 2: Functional Forms of Regression Models CHAPTER 3: Qualitative Explanatory Variables Regression Models PART II: CRITICAL EVALUATION OF THE CLASSICAL LINEAR REGRESSION MODEL CHAPTER 4: Regression Diagnostic I: Multicollinearity CHAPTER 5: Regression Diagnostic II: Heteroscedasticity CHAPTER 6: Regression Diagnostic III: Autocorrelation CHAPTER 7: Regression Diagnostic IV: Model Specification Errors PART III: REGRESSION MODELS WITH CROSS-SECTIONAL DATA CHAPTER 8: The Logit And Probit Models CHAPTER 9: Multinomial Regression Models CHAPTER 10: Oridinal Regression Models CHAPTER 11: Limited Dependent Variable Regression Models CHAPTER 12: Modeling Count Data: The Poisson and Negative Binomial Regression Models PART IV: TOPICS IN TIME SERIES ECONOMETRICS CHAPTER 13: Stationary and Nonstationary Time Series CHAPTER 14: Cointegration and Error Correction Models CHAPTER 15: Asset Price Volatility: The ARCH and GARCH Models CHAPTER 16: Economic Forecasting CHAPTER 17: Panel Data Regression Models CHAPTER 18: Survival Analysis CHAPTER 19: Stochastic Regressors and the Method of Instrumental Variables

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