Introduction 1
Part I: Getting Started with Econometrics 5
Chapter 1: Econometrics: The Economist's Approach to Statistical Analysis 7
Chapter 2: Getting the Hang of Probability 21
Chapter 3: Making Inferences and Testing Hypotheses 39
Part II: Building the Classical Linear Regression Model 59
Chapter 4: Understanding the Objectives of Regression Analysis 61
Chapter 5: Going Beyond Ordinary with the Ordinary Least Squares Technique 75
Chapter 6: Assumptions of OLS Estimation and the Gauss-Markov Theorem 93
Chapter 7: The Normality Assumption and Inference with OLS 111
Part III: Working with the Classical Regression Model 135
Chapter 8: Functional Form, Specifi cation, and Structural Stability 137
Chapter 9: Regression with Dummy Explanatory Variables 153
Part IV: Violations of Classical Regression Model Assumptions 173
Chapter 10: Multicollinearity 175
Chapter 11: Heteroskedasticity 191
Chapter 12: Autocorrelation 209
Part V: Discrete and Restricted Dependent Variables in Econometrics 229
Chapter 13: Qualitative Dependent Variables 231
Chapter 14: Limited Dependent Variable Models 253
Part VI: Extending the Basic Econometric Model 265
Chapter 15: Static and Dynamic Models 267
Chapter 16: Diving into Pooled Cross-Section Analysis 281
Chapter 17: Panel Econometrics 291
Part VII: The Part of Tens 305
Chapter 18: Ten Components of a Good Econometrics Research Project 307
Chapter 19: Ten Common Mistakes in Applied Econometrics 315
Appendix: Statistical Tables 321
Index 327
