Contents;
Preface;
Dedication;
1 Introduction;
What is Econometrics;
The Disturbance Term;
Estimates and Estimators;
Good and Preferred Estimators;
General Notes;
Technical Notes;
2 Criteria for Estimators;
Introduction;
Computational Cost;
Least Squares;
Highest R2;
Unbiasedness;
Efficiency;
Mean Square Error;
Asymptotic Properties;
Maximum Likelihood;
Monte Carlo Studies;
Adding Up;
General Notes;
Technical Notes;
The Classical Linear Regression Model 40;
3.1 Textbooks as Catalos 40;
3.2 The Five Assumptions 41;
3.3 The OLS Estimator in the CLR Model 43;
General Notes 44;
Technical Notes 47;
4 Interval Estimation and Hypothesis Testing 51;
4.1 Introduction 51;
4.2 Testing a Single Hypothesis: the t Test 51;
4.3 Testing a Joint Hypothesis: the F Test 52;
4.4 Interval Estimation for a Parameter Vector 54;
4.5 LR, W, and LM Statistics 56;
4.6 Bootstrapping 58;
General Notes 59;
Technical Notes 67;
5 Specification 71;
5.1 Introduction 71;
5.2 Three Methodologies ' 72;
5.3 General Principles for Specification 75;
5.4 Misspecification Tests/Diagnostics 76;
5.5 R2 Again 19;
General Notes 81;
Technical Notes 89;
6 Violating Assumption One: Wrong Repressors, Nonlinearities, and
Parameter Inconstancy 93;
6.1 Introduction 93;
6.2 Incorrect Set of Independent Variables 93;
6.3 Nonlinearity 95;
6.4 Changing Parameter Values 97;
General Notes 100;
Technical Notes 106;
7 Violating Assumption Two: Nonzero Expected Disturbance 109
General Notes 111;
8 Violating Assumption Three: Nonspherical Disturbances 112;
8.1 Introduction 112;
8.2 Consequences of Violation 113;
8.3 Heteroskedasticity 115;
8.4 Autocorrelated Disturbances 118;
8.5 Generalized Method of Moments 122;
General Notes 123;
Technical Notes 129;
9 Violating Assumption Four: Instrumental Variable Estimation 137;
9.1 Introduction 137;
9.2 The IV Estimator 141;
9.3 IV Issues 144;
General Notes 146;
Technical Notes 151;
10 Violating Assumption Four: Measurement Errors and Autoregression 157;
10.1 Errors in Variables 157;
10.2 Autoregression 160;
General Notes 163;
Technical Notes 167;
11 Violating Assumption Four: Simultaneous Equations 171;
11.1 Introduction 171;
11.2 Identification 173;
11.3 Single-Equation Methods 176;
11.4 Systems Methods 180;
General Notes 181;
Technical Notes 186
12 Violating Assumption Five: Multicollinearity 192;
12.1 Introduction 192;
12.2 Consequences 193;
12.3 Detecting Multicollinearity 194;
12.4 What To Do 196;
General Notes 198;
Technical Notes 202;
13 Incorporating Extraneous Information 203;
13.1 Introduction 203;
13.2 Exact Restrictions 203;
13.3 Stochastic Restrictions , 204;
13.4 Pre-Test Estimators 204;
13.5 Extraneous Information and MSE 206;
General Notes 207;
Technical Notes 211;
14 The Bayesian Approach 213;
14.1 Introduction 213;
14.2 What is a Bayesian Analysis? 213;
14.3 Advantages of the Bayesian Approach 216;
14.4 Overcoming Practitioners' Complaints 217;
General Notes 220;
Technical Notes – 226;
15 Dummy Variables 232;
15.1 Introduction 232;
15.2 Interpretation 233;
15.3 Adding another Qualitative Variable 234;
15.4 Interacting with Quantitative Variables 235;
15.5 Observation-Specific Dummies 236;
General Notes 237;
Technical Notes " 240;
16 Qualitative Dependent Variables 241;
16.1 Dichotomous Dependent Variables 241;
16.2 Polychotomous Dependent Variables 244;
16.3 Ordered Logit/Probit 245;
16.4 Count Data 246;
General Notes 246;
Technical Notes 254;
17 Limited Dependent Variables 262;
17.1 Introduction 262;
17.2 The Tobit Model 263;
17.3 Sample Selection 265;
17.4 Duration Models 267;
General Notes 269;
Technical Notes 273;
18 Panel Data 281;
18.1 Introduction, 281;
18.2 Allowing for Different Intercepts 282;
18.3 Fixed Versus Random Effects 284;
18.4 Short Run Versus Long Run 286;
18.5 Long, Narrow Panels 287;
General Notes 288;
Technical Notes 292;
19 Time Series Econometrics 296;
19.1 Introduction 296;
19.2 ARIMA Models 297;
19.3 VARs 298;
19.4 Error Correction Models 299;
19.5 Testing for Unit Roots 301;
19.6 Counteraction 302;
General Notes 304;
Technical Notes 314;
20 Forecasting 331;
20.1 Introduction 331;
20.2 Causal Forecasting/Econometric Models 332;
20.3 Time Series Analysis 333;
20.4 Forecasting Accuracy 334;
General Notes 335;;
Technical Notes 342;
21 Robust Estimation 345;
21.1 Introduction 345;
21.2 Outliers and Influential Observations 346;
21.3 Guarding Against Influential Observations 347;
21.4 Artificial Neural Networks 349;
21.5 Nonparametric Estimation 350;
General Notes 352;
Technical Notes 356;
22 Applied Econometrics 361;
22.1 Introduction 361;
22.2 The Ten Commandments of Applied Econometrics 362;
22.3 Getting the Wrong Sign 368;
22.4 Common Mistakes 372;
22.5 What do Practitioners Need to Know? 373;
General Notes 374;
Technical Notes 383;
23 Computational Considerations 385;
23.1 Introduction 385;
23.2 Optimizing via a Computer Search 386;
23.3 Estimating Integrals via Simulation 388;
23.4 Drawing Observations from Awkward Distributions 390;
General Notes 392;
Technical Notes 397;
Appendix A: Sampling Distributions, the Foundation of Statistics 403;
Appendix B: All about Variance 407;
Appendix C: A Primer on Asymptotics 412;
Appendix D: Exercises 417;
Appendix E: Answers to Even-Numbered Questions 479;
Glossary 503;
Bibliography 511;
Name Index 563;
Subject Index 573;