## 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 -by-doing approach to the study of econometrics. Rather than relying on complex theoretical discussions and complicated mathematics, this 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 concepts that underlie the material, making Econometrics by Example an ideally flexible and self-contained learning resource for studying econometrics for the first time.

The includes:
– a wide-ranging collection of examples, with data on mortgages, exchange rates, charitable giving, fashion sales and more
– a clear, step-by-step style that guides you from formulation, to 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 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
– companion website containing PowerPoint slides and a full solutions manual to all exercises for instructors, and downloadable data sets and chapter summaries for students.

View more

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 