Introduction to Econometrics

Description

Brief Contents......Page 3 Contents......Page 4 Key Concepts......Page 20 General Interest Boxes......Page 23 New to the third edition......Page 24 Features of this Book......Page 26 Contents & Organization......Page 30 Sample Courses......Page 32 Supplements......Page 34 Website......Page 35 Economic Questions We Examine......Page 39 Causal Effects and Idealized Experiments......Page 43 Data: Sources and Types......Page 45 Review of Probability......Page 52 Random Variables and Probability Distributions......Page 53 Expected Values, Mean, and Variance......Page 57 Two Random Variables......Page 64 Distributions......Page 74 Random Sampling and the Distribution of the Sample Average......Page 81 Large-Sample Approximations to Sampling Distributions......Page 85 Derivation of Results in Key Concept 2.3......Page 101 Review of Statistics......Page 103 Estimation of the Population Mean......Page 104 Hypothesis Tests Concerning the Population Mean......Page 109 Confidence Intervals for the Population Mean......Page 118 Comparing Means from Different Populations......Page 120 Differences-of-Means Estimation of Causal Effects Using Experimental Data......Page 122 -Statistic When the Sample Size Is Small......Page 125 Scatterplots, the Sample Covariance, and the Sample Correlation......Page 129 The U.S. Current Population Survey......Page 144 Is the Least Squares Estimator of......Page 145 A Proof That the Sample Variance Is Consistent......Page 146 The Linear Regression Model......Page 147 Estimating the Coefficients of the Linear Regression Model......Page 152 Measures of Fit......Page 159 The Least Squares Assumptions......Page 162 Sampling Distribution of the OLS Estimators......Page 167 Conclusion......Page 171 Derivation of the OLS Estimators......Page 179 Sampling Distribution of the OLS Estimator......Page 180 Testing Hypotheses About One of the Regression Coefficients......Page 184 Confidence Intervals for a Regression Coefficient......Page 191 Is a Binary Variable......Page 193 Heteroskedasticity and Homoskedasticity......Page 195 The Theoretical Foundations of Ordinary Least Squares......Page 201 -Statistic in Regression When the Sample Size Is Small......Page 204 Conclusion......Page 206 Formulas for OLS Standard Errors......Page 215 The Gauss–Markov Conditions and a Proof of the Gauss–Markov Theorem......Page 216 Linear Regression with Multiple Regressors......Page 220 Distribution of the OLS Estimators When There Are Two Regressors and Homoskedastic Errors......Page 252 The Frisch–Waugh Theorem......Page 253 Hypothesis Tests and Confidence Intervals for a Single Coefficient......Page 255 Tests of Joint Hypotheses......Page 260 Testing Single Restrictions Involving Multiple Coefficients......Page 267 Confidence Sets for Multiple Coefficients......Page 269 Model Specification for Multiple Regression......Page 270 Analysis of the Test Score Data Set......Page 276 Conclusion......Page 281 The Bonferroni Test of a Joint Hypothesis......Page 289 Conditional Mean Independence......Page 291 Nonlinear Regression Functions......Page 294 A General Strategy for Modeling Nonlinear Regression Functions......Page 296 Nonlinear Functions of a Single Independent Variable......Page 304 Interactions Between Independent Variables......Page 316 Nonlinear Effects on Test Scores of the Student–Teacher Ratio......Page 331 Conclusion......Page 336 Regression Functions That Are Nonlinear in the Parameters......Page 347 Slopes and Elasticities for Nonlinear Regression Functions......Page 351 Assessing Studies based on Multiple Regression......Page 353 The Massachusetts Elementary School Testing Data......Page 387 Regression with Panel Data......Page 388 Standard Errors for Fixed Effects Regression......Page 418 Regression with Binary dependent Variable......Page 423 Binary Dependent Variables and the Linear Probability Model......Page 424 Probit and Logit Regression......Page 429 Estimation and Inference in the Logit and Probit Models......Page 436 Application to the Boston HMDA Data......Page 440 Conclusion......Page 447 Maximum Likelihood Estimation......Page 456 Other Limited Dependent Variable Models......Page 459 Instrumental Variables Regression......Page 462 Derivation of the Formula for the TSLS Estimator in Equation (12.4)......Page 505 Large-Sample Distribution of the TSLS Estimator......Page 506 Large-Sample Distribution of the TSLS Estimator When the Instrument Is Not Valid......Page 507 Instrumental Variables Analysis with Weak Instruments......Page 509 TSLS with Control Variables......Page 511 Experiments & Quasi-Experiments......Page 513 IV Estimation When the Causal Effect Varies Across Individuals......Page 556 The Potential Outcomes Framework for Analyzing Data from Experiments......Page 558 Intro to Time Series Regression & Forecasting......Page 560 Using Regression Models for Forecasting......Page 561 Introduction to Time Series Data and Serial Correlation......Page 562 Autoregressions......Page 569 Time Series Regression with Additional Predictors and the Autoregressive Distributed Lag Model......Page 575 Lag Length Selection Using Information Criteria......Page 585 Nonstationarity I: Trends......Page 589 Nonstationarity II: Breaks......Page 599 Conclusion......Page 611 Time Series Data Used in Chapter 14......Page 621 Stationarity in the AR(1) Model......Page 622 Lag Operator Notation......Page 623 ARMA Models......Page 624 Consistency of the BIC Lag Length Estimator......Page 625 Estimation of Dynamic Causal Effects......Page 627 The ADL Model and Generalized Least Squares in Lag Operator Notation......Page 672 Vector Autoregressions......Page 676 Multiperiod Forecasts......Page 681 Orders of Integration and the DF-GLS Unit Root Test......Page 687 Cointegration......Page 694 Volatility Clustering and Autoregressive Conditional Heteroskedasticity......Page 702 Conclusion......Page 708 Theory of Linear Regression with 1 Regressor......Page 714 The Normal and Related Distributions and Moments of Continuous Random Variables......Page 738 Two Inequalities......Page 741 Theory of Multiple Regression......Page 743 The Linear Multiple Regression Model and OLS Estimator in Matrix Form......Page 744 -Statistic......Page 748 Tests of Joint Hypotheses......Page 751 Distribution of Regression Statistics with Normal Errors......Page 754 Efficiency of the OLS Estimator with Homoskedastic Errors......Page 758 Generalized Least Squares......Page 760 Instrumental Variables and Generalized Method of Moments Estimation......Page 766 Summary of Matrix Algebra......Page 784 Multivariate Distributions......Page 787 Derivation of the Asymptotic Distribution of......Page 789 Derivations of Exact Distributions of OLS Test Statistics with Normal Errors......Page 790 Proof of the Gauss–Markov Theorem for Multiple Regression......Page 791 Proof of Selected Results for IV and GMM Estimation......Page 792 Appendix......Page 795 Refs......Page 803 Glossary......Page 808 Index......Page 816