Econometrics is the branch of economics concerned with the use of mathematics to describe, model, prove, and predict economic theory and systems.
This book can be considered to be three parts.
- Chapters 1-4
- An introduction and mathematical base needed to perform basic and more advanced econometrics.
- Chapters 5, 6
- The basics of bivariate and multivariate regression analysis.
- Chapters 7-16
- Applications of basic econometrics and advanced topics.
- Introduction to Econometric Theory
- Important Terms and Concepts of Regression Analysis
- Statistical Concepts
- Matrix Algebra
- Classical Normal Linear Regression Model (CNLRM)
- Multiple Regression Analysis
- Dummy Variables
- Problems with Heteroskedasticity and Autocorrelation
- The Nature of Multicollinearity
- Theoretical Consequences in case of Multicollinearity
- Practical Consequences in case of Multicollinearity
- Tests for Multicollinearity
- Solutions to Multicollinearity
- Serial Correlation - Autocorrelation
- Simultaneous-Equation Models
- Time-Series Analysis
- First-Order Autocorrelation
- An Autoregressive (AR) Process
- A Moving-Average (MA) Process
- ARIMA Models
- Box-Jenkins Methodology of identifying, estimating and checking ARIMA Models
- Vector Autoregression
- Model Specification and Diagnostic Testing
- Problems with Residuals: Robust Regression
- Heteroskedasticity-Consistent Estimators
- Microeconometrics: Qualitative Dependent Variable Models
- Linear Probability Model (LPM)
- Binary Choice Models
- Poisson Regression
- Study Aides and Equations
- Basic Statistics
- Hypothesis Testing
Ramanathan, Ramu. "Introductory Econometrics with Applications." South-western Thomson Learning, 2002.
- Gretl Gnu Regression, Econometrics and Time Series Library (open source and free software for econometric calculus)