پارسی   English   العربیه

Econometrics For Dummies


Learn to:

  • Grasp the techniques and applications of econometrics
  • Make sense of complex concepts and material
  • Use specialized software to apply your acquired econometrics skills

Understand econometric theory and apply econometric techniques

Econometrics can prove challenging for many students. Thankfully, Econometrics For Dummies eliminates that confusion with easy-to-understand explanations of important topics in the study of econometrics. This hands-on, friendly guide breaks down the complex subject of econometrics and provides you with an easy-to-follow course supplement to further refine your understanding of how econometrics works and how it can be applied in real-world situations.

  • The nuts and bolts — get familiar with the various characteristics of the classical linear regression model (CLRM), which is the foundation of traditional econometric analysis
  • Form and function — discover how econometric analysis is able to accommodate a considerable amount of flexibility with different mathematical functions and types of data
  • Don't assume — find out how econometricians use some bizarre titles to identify problems that violate CLRM assumptions
  • Be discrete — get to know how discrete and restricted dependent variables can create problems for traditional regression analysis and discover the techniques econometricians have developed to modify traditional regression analysis
  • Make special note — delve deeper into a few specialized areas of econometrics, namely time-series analysis, pooled cross sections, and panel econometrics

Open the book and find:

  • Plain-English explanations of complex material
  • Computer outputs from STATA for many of the examples
  • The economist's approach to statistical analysis
  • The various characteristics of the classical linear regression model
  • The most common problems encountered when performing regression analysis
  • Lots of helpful figures
  • Common mistakes in applied econometrics

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