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Roberto Pedace, PhD, is an associate professor in the Department of Economics at Scripps College. His published work has appeared in Economic Inquiry, Industrial Relations, the Southern Economic Journal, Contemporary Economic Policy, the Journal of Sports Economics, and other outlets.
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
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