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Preface | p. x |
Dedication | p. xii |
Introduction | p. 1 |
What is Econometrics? | p. 1 |
The Disturbance Term | p. 2 |
Estimates and Estimators | p. 4 |
Good and Preferred Estimators | p. 5 |
General Notes | p. 6 |
Technical Notes | p. 10 |
Criteria for Estimators | p. 11 |
Introduction | p. 11 |
Computational Cost | p. 11 |
Least Squares | p. 12 |
Highest R[superscript 2] | p. 13 |
Unbiasedness | p. 14 |
Efficiency | p. 16 |
Mean Square Error | p. 17 |
Asymptotic Properties | p. 18 |
Maximum Likelihood | p. 21 |
Monte Carlo Studies | p. 22 |
Adding Up | p. 25 |
General Notes | p. 26 |
Technical Notes | p. 32 |
The Classical Linear Regression Model | p. 40 |
Textbooks as Catalogs | p. 40 |
The Five Assumptions | p. 41 |
The OLS Estimator in the CLR Model | p. 43 |
General Notes | p. 44 |
Technical Notes | p. 47 |
Interval Estimation and Hypothesis Testing | p. 51 |
Introduction | p. 51 |
Testing a Single Hypothesis: the t Test | p. 51 |
Testing a Joint Hypothesis: the F Test | p. 52 |
Interval Estimation for a Parameter Vector | p. 54 |
LR, W, and LM Statistics | p. 56 |
Bootstrapping | p. 58 |
General Notes | p. 59 |
Technical Notes | p. 67 |
Specification | p. 71 |
Introduction | p. 71 |
Three Methodologies | p. 72 |
General Principles for Specification | p. 75 |
Misspecification Tests/Diagnostics | p. 76 |
R[superscript 2] Again | p. 79 |
General Notes | p. 81 |
Technical Notes | p. 89 |
Violating Assumption One: Wrong Regressors, Nonlinearities, and Parameter Inconstancy | p. 93 |
Introduction | p. 93 |
Incorrect Set of Independent Variables | p. 93 |
Nonlinearity | p. 95 |
Changing Parameter Values | p. 97 |
General Notes | p. 100 |
Technical Notes | p. 106 |
Violating Assumption Two: Nonzero Expected Disturbance | p. 109 |
General Notes | p. 111 |
Violating Assumption Three: Nonspherical Disturbances | p. 112 |
Introduction | p. 112 |
Consequences of Violation | p. 113 |
Heteroskedasticity | p. 115 |
Autocorrelated Disturbances | p. 118 |
Generalized Method of Moments | p. 122 |
General Notes | p. 123 |
Technical Notes | p. 129 |
Violating Assumption Four: Instrumental Variable Estimation | p. 137 |
Introduction | p. 137 |
The IV Estimator | p. 141 |
IV Issues | p. 144 |
General Notes | p. 146 |
Technical Notes | p. 151 |
Violating Assumption Four: Measurement Errors and Autoregression | p. 157 |
Errors in Variables | p. 157 |
Autoregression | p. 160 |
General Notes | p. 163 |
Technical Notes | p. 167 |
Violating Assumption Four: Simultaneous Equations | p. 171 |
Introduction | p. 171 |
Identification | p. 173 |
Single-Equation Methods | p. 176 |
Systems Methods | p. 180 |
General Notes | p. 181 |
Technical Notes | p. 186 |
Violating Assumption Five: Multicollinearity | p. 192 |
Introduction | p. 192 |
Consequences | p. 193 |
Detecting Multicollinearity | p. 194 |
What To Do | p. 196 |
General Notes | p. 198 |
Technical Notes | p. 202 |
Incorporating Extraneous Information | p. 203 |
Introduction | p. 203 |
Exact Restrictions | p. 203 |
Stochastic Restrictions | p. 204 |
Pre-Test Estimators | p. 204 |
Extraneous Information and MSE | p. 206 |
General Notes | p. 207 |
Technical Notes | p. 211 |
The Bayesian Approach | p. 213 |
Introduction | p. 213 |
What is a Bayesian Analysis? | p. 213 |
Advantages of the Bayesian Approach | p. 216 |
Overcoming Practitioners' Complaints | p. 217 |
General Notes | p. 220 |
Technical Notes | p. 226 |
Dummy Variables | p. 232 |
Introduction | p. 232 |
Interpretation | p. 233 |
Adding Another Qualitative Variable | p. 234 |
Interacting with Quantitative Variables | p. 235 |
Observation-Specific Dummies | p. 236 |
General Notes | p. 237 |
Technical Notes | p. 240 |
Qualitative Dependent Variables | p. 241 |
Dichotomous Dependent Variables | p. 241 |
Polychotomous Dependent Variables | p. 244 |
Ordered Logit/Probit | p. 245 |
Count Data | p. 246 |
General Notes | p. 246 |
Technical Notes | p. 254 |
Limited Dependent Variables | p. 262 |
Introduction | p. 262 |
The Tobit Model | p. 263 |
Sample Selection | p. 265 |
Duration Models | p. 267 |
General Notes | p. 269 |
Technical Notes | p. 273 |
Panel Data | p. 281 |
Introduction | p. 281 |
Allowing for Different Intercepts | p. 282 |
Fixed Versus Random Effects | p. 284 |
Short Run Versus Long Run | p. 286 |
Long, Narrow Panels | p. 287 |
General Notes | p. 288 |
Technical Notes | p. 292 |
Time Series Econometrics | p. 296 |
Introduction | p. 296 |
ARIMA Models | p. 297 |
VARs | p. 298 |
Error Correction Models | p. 299 |
Testing for Unit Roots | p. 301 |
Cointegration | p. 302 |
General Notes | p. 304 |
Technical Notes | p. 314 |
Forecasting | p. 331 |
Introduction | p. 331 |
Causal Forecasting/Econometric Models | p. 332 |
Time Series Analysis | p. 333 |
Forecasting Accuracy | p. 334 |
General Notes | p. 335 |
Technical Notes | p. 342 |
Robust Estimation | p. 345 |
Introduction | p. 345 |
Outliers and Influential Observations | p. 346 |
Guarding Against Influential Observations | p. 347 |
Artificial Neural Networks | p. 349 |
Nonparametric Estimation | p. 350 |
General Notes | p. 352 |
Technical Notes | p. 356 |
Applied Econometrics | p. 361 |
Introduction | p. 361 |
The Ten Commandments of Applied Econometrics | p. 362 |
Getting the Wrong Sign | p. 368 |
Common Mistakes | p. 372 |
What do Practitioners Need to Know? | p. 373 |
General Notes | p. 374 |
Technical Notes | p. 383 |
Computational Considerations | p. 385 |
Introduction | p. 385 |
Optimizing via a Computer Search | p. 386 |
Estimating Integrals via Simulation | p. 388 |
Drawing Observations from Awkward Distributions | p. 390 |
General Notes | p. 392 |
Technical Notes | p. 397 |
Sampling Distributions, The Foundation of Statistics | p. 403 |
All About Variance | p. 407 |
A Primer on Asymptotics | p. 412 |
Exercises | p. 417 |
Answers to Even-Numbered Questions | p. 479 |
Glossary | p. 503 |
Bibliography | p. 511 |
Name Index | p. 563 |
Subject Index | p. 573 |
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