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.
DAMODAR GUJARATI has over 40 years of teaching and writing experience.
As well as his bestselling textbooks he has published many articles in leading economics
and statistics journals. He has Visiting Professorships at leading universities in the UK,
Australia, Singapore and India.
Table of Contents
PART I: THE LINEAR REGRESSION MODEL
CHAPTER 1: The Linear Regression Model: An Introduction
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 with ARIMA and VAR Models
CHAPTER 17: Panel Data Regression Models
CHAPTER 18: Survival Analysis
CHAPTER 19: Stochastic Regressors and the Method of Instrumental Variables
400 pages, Paperback
