Background | p. 1 |

Introduction | p. 1 |

What Is Econometrics? | p. 2 |

Basic Ingredients of an Empirical Study | p. 4 |

Empirical Project | p. 13 |

Summary | p. 14 |

Key Terms | p. 15 |

Exercises | p. 15 |

Review of Probability and Statistics | p. 16 |

Random Variables and Probability Distributions | p. 16 |

Mathematical Expectation, Mean, and Variance | p. 20 |

Joint Probabilities, Covariance, and Correlation | p. 26 |

Random Sampling and Sampling Distributions | p. 35 |

Procedures for the Estimation of Parameters | p. 38 |

Properties of Estimators | p. 42 |

The Chi-square, t-and F-distributions | p. 47 |

Testing Hypotheses | p. 50 |

Interval Estimation | p. 56 |

Key Terms | p. 58 |

References | p. 59 |

Exercises | p. 60 |

Miscellaneous Derivations | p. 63 |

Certain Useful Results on Summations | p. 63 |

Maximization and Minimization | p. 64 |

More on Estimation | p. 71 |

Basics | p. 75 |

The Simple Linear Regression Model | p. 76 |

The Basic Model | p. 76 |

Estimation of the Basic Model by the Method of Ordinary Least Squares (OLS) | p. 80 |

Properties of Estimators | p. 85 |

The Precision of the Estimators and the Goodness of Fit | p. 91 |

Tests of Hypotheses | p. 95 |

Scaling and Units of Measurement | p. 105 |

Application: Estimating an Engel Curve Relation between Expenditure on Health Care and Income | p. 106 |

Confidence Intervals | p. 110 |

Forecasting | p. 110 |

Causality in a Regression Model | p. 113 |

Application: Relation between Patents and the Expenditures on Research and Development (RandD) | p. 116 |

Summary | p. 119 |

Key Terms | p. 121 |

References | p. 122 |

Exercises | p. 122 |

Miscellaneous Derivations | p. 133 |

Three-Dimensional Representation of the Simple Linear Model | p. 133 |

More Results on Summations | p. 133 |

Derivation of the Normal Equations by Least Squares | p. 135 |

Best Linear Unbiased Estimator (BLUE) and the Gauss-Markov Theorem | p. 135 |

Maximum Likelihood Estimation | p. 137 |

Derivation of the Variances of the Estimators | p. 138 |

Unbiased Estimator of the Variance of the Error Term | p. 139 |

Derivation of Equation 3.26 | p. 140 |

Derivation of Equation 3.27a | p. 140 |

Proof That r[superscript 2 subscript xy]=R[superscript 2] for a Simple Regression Model | p. 141 |

Derivation of Equation 3.29 | p. 142 |

Derivation of Equation 3.30 | p. 143 |

Multiple Regression Models | p. 144 |

Normal Equations | p. 145 |

Goodness of Fit | p. 148 |

General Criteria for Model Selection | p. 151 |

Testing Hypotheses | p. 153 |

Specification Errors | p. 165 |

Application: The Determinants of the Number of Bus Travelers | p. 171 |

Application: Women's Labor Force Participation | p. 177 |

Empirical Example: Net Migration Rates and the Quality of Life | p. 183 |

Empirical Project | p. 185 |

Summary | p. 185 |

Key Terms | p. 187 |

References | p. 187 |

Exercises | p. 188 |

Miscellaneous Derivations | p. 205 |

The Three-Variable Regression Model | p. 205 |

Bias Due to the Omission of a Relevant Variable | p. 206 |

Proof of Property 4.4 | p. 208 |

Multicollinearity | p. 210 |

Examples of Multicollinearity | p. 210 |

Exact Multicollinearity | p. 213 |

Near Multicollinearity | p. 214 |

Applications | p. 220 |

Summary | p. 225 |

Key Terms | p. 226 |

References | p. 226 |

Exercises | p. 227 |

Derivation of Equations (5.4) through (5.6) | p. 229 |

Extensions | p. 231 |

Choosing Functional Forms and Testing for Model Specification | p. 232 |

Review of Exponential and Logarithmic Functions | p. 232 |

Linear-Log Relationship | p. 235 |

Reciprocal Transformation | p. 238 |

Polynomial Curve-Fitting | p. 238 |

Interaction Terms | p. 241 |

Lags in Behavior (Dynamic Models) | p. 243 |

Application: Relation between Patents and RandD Expenses Revisited | p. 244 |

Log-Linear Relationship (or Semilog Model) | p. 250 |

Comparison of R[superscript 2] Values between Models | p. 254 |

The Double-Log (or Log-Log) Model | p. 255 |

Application: Estimating Elasticities of Bus Travel | p. 257 |

Miscellaneous Other Models | p. 258 |

The Hendry/LSE Approach of Modeling from "General to Simple" | p. 261 |

"Simple to General" Modeling Using the Lagrange Multiplier Test | p. 262 |

Ramsey's RESET Procedure for Regression Specification Error | p. 270 |

Summary | p. 271 |

Key Terms | p. 272 |

References | p. 272 |

Exercises | p. 274 |

More Details on LR, Wald, and LM Tests | p. 284 |

Likelihood Ratio Test | p. 284 |

The Wald Test | p. 286 |

The Lagrange Multiplier Test | p. 287 |

Qualitative (or Dummy) Independent Variables | p. 290 |

Qualitative Variables with Two Categories Only | p. 290 |

Qualitative Variable with Many Categories | p. 298 |

The Effect of Qualitative Variables on the Slope Term (Analysis of Covariance) | p. 302 |

Application: Covariance Analysis of the Wage Model | p. 305 |

Estimating Seasonal Effects | p. 312 |

Testing for Structural Change | p. 314 |

Empirical Example: Motor Carrier Deregulation | p. 320 |

Application: The Demand for a Sealant Used in Construction | p. 320 |

Empirical Project | p. 324 |

Summary | p. 325 |

Key Terms | p. 325 |

References | p. 325 |

Exercises | p. 326 |

Some Special Issues with Cross-Section and Time Series Data | p. 343 |

Heteroscedasticity | p. 344 |

Consequences of Ignoring Heteroscedasticity | p. 346 |

Testing for Heteroscedasticity | p. 347 |

Estimation Procedures | p. 355 |

Application: A Model of the Expenditure on Health Care in the United States | p. 363 |

Empirical Project | p. 365 |

Summary | p. 366 |

Key Terms | p. 367 |

References | p. 367 |

Exercises | p. 368 |

Properties of OLS Estimators in the Presence of Heteroscedasticity | p. 378 |

Serial Correlation | p. 380 |

Serial Correlation of the First Order | p. 382 |

Consequences of Ignoring Serial Correlation | p. 383 |

Testing for First-Order Serial Correlation | p. 386 |

Treatment of Serial Correlation | p. 389 |

Higher-Order Serial Correlation | p. 398 |

Engle's ARCH Test | p. 401 |

Application: Demand for Electricity | p. 406 |

Summary | p. 416 |

Key Terms | p. 417 |

References | p. 417 |

Exercises | p. 419 |

Miscellaneous Derivations | p. 431 |

Proof That the DW d is Approximately 2(1-[rho]) | p. 431 |

Properties of u[subscript t] When It Is AR(1) | p. 431 |

Treatment of the First Observation under AR(1) | p. 432 |

Distributed Lag Models | p. 434 |

Lagged Independent Variables | p. 434 |

Lagged Dependent Variables | p. 442 |

Lagged Dependent Variables and Serial Correlation | p. 446 |

Estimation of Models with Lagged Dependent Variables | p. 449 |

Application: A Dynamic Model of Consumption Expenditures in the United Kingdom | p. 453 |

Application: Hourly Electricity Load Model Revisited | p. 454 |

Unit Roots and the Dickey-Fuller Tests | p. 455 |

Error Correction Models (ECM) | p. 461 |

Application: An Error Correction Model of U.S. Defense Expenditures | p. 464 |

Cointegration | p. 472 |

Causality | p. 475 |

Pooling Cross-Sectional and Time Series Data (or Panel Data) | p. 478 |

Empirical Project | p. 481 |

Summary | p. 482 |

Key Terms | p. 484 |

References | p. 484 |

Exercises | p. 487 |

Special Topics | p. 493 |

Forecasting | p. 494 |

Fitted Values Ex-post, and Ex-ante Forecasts | p. 495 |

Evaluation of Models | p. 496 |

Conditional and Unconditional Forecasts | p. 497 |

Forecasting from Time Trends | p. 498 |

Combining Forecasts | p. 504 |

Forecasting from Econometric Models | p. 510 |

Forecasting from Time Series Models | p. 514 |

Summary | p. 524 |

Key Terms | p. 525 |

References | p. 526 |

Exercises | p. 527 |

Qualitative and Limited Dependent Variables | p. 528 |

Linear Probability (or Binary Choice) Models | p. 529 |

The Probit Model | p. 530 |

The Logit Model | p. 532 |

Limited Dependent Variables | p. 534 |

Summary | p. 538 |

Key Terms | p. 539 |

References | p. 539 |

Exercises | p. 539 |

Simultaneous Equation Models | p. 542 |

Structure and Reduced Forms of Simultaneous Equation Models | p. 542 |

Consequences of Ignoring Simultaneity | p. 544 |

The Identification Problem | p. 546 |

Estimation Procedures | p. 551 |

Empirical Example: Regulation in the Contact Lens Industry | p. 556 |

Application: A Simple Keynesian Model | p. 558 |

Summary | p. 561 |

Key Terms | p. 561 |

References | p. 562 |

Exercises | p. 562 |

Derivation of the Limits for OLS Estimates | p. 565 |

Practice | p. 567 |

Carrying Out an Empirical Project | p. 568 |

Selecting a Topic | p. 568 |

Review of Literature | p. 573 |

Formulating a General Model | p. 574 |

Collecting the Data | p. 574 |

Empirical Analysis | p. 579 |

Key Terms | p. 582 |

References | p. 583 |

Statistical Tables | p. 585 |

Answers to Selected Problems | p. 607 |

Practice Computer Sessions | p. 635 |

Descriptions of the Data and Practice Computer Sessions | p. 639 |

Copyrights and Acknowledgments | p. 675 |

Name Index | p. 677 |

Subject Index | p. 679 |

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