Principles of Econometrics, 3 Edition

1 Principles of Econometrics, 3rd Edition R. Carter Hill, William E. Griffiths, Guay C. Lim Table of Contents Preface Chapter 1 An Introduction to Econometrics Why Study Econometrics? What is Econometrics About? Some Examples The Econometric Model How Do We Obtain Data? Experimental Data Nonexperimental Data Statistical Inference A Research Format Chapter 2 The Simple Linear Regression Model Learning Objectives and Keywords An Economic Model An Econometric Model Introducing the Error Term Estimating the Regression Parameters The Least Squares Principle Estimates for the Food Expenditure Function Interpreting the Estimates Elasticities Prediction Computer Output Other Economic Models Assessing the Least Squares Estimators The Estimator b2 The Expected Values of

2 B1 and b2 Repeated Sampling The Variances and Covariance of b1 and b2 The Gauss-Markov Theorem The Probability Distributions of the Least Squares Estimators Estimating the Variance of the Error Term Estimating the Variances and Covariances of the Least Squares Estimators Calculations for the Food Expenditure Data Exercises Problems Computer Exercises Appendix 2A Derivation of the Least Squares Estimates Appendix 2B Deviation from the Mean Form of b2 Appendix 2C b2 is a Linear Estimator Appendix 2D Derivation of Theoretical Expression for b2 Appendix 2E Deriving the Variance of b2 Appendix 2F Proof of the Gauss-Markov Theorem Chapter 3 Interval Estimation and Hypothesis Testing Learning Objectives and Keywords Interval Estimation The t-distribution Obtaining Interval Estimates An Illustration The Repeated Sampling Context Hypothesis Tests The Null Hypothesis The Alternative Hypothesis The Test Statistic The Rejection Region A Conclusion Rejection Regions for Specific Alternatives One-tail Tests with Alternative Greater Than (>) One-tail Tests with Alternative Less Than (<) Two-tail Tests with Alternative Not Equal To ( )

3 Examples of Hypothesis Tests Right-tail Tests One-Tail Test of Significance One-Tail Test of an Economic Hypothesis Left-Tail Tests Two-Tail Tests Two-Tail Test of an Economic Hypothesis Two-Tail Test of Significance The p-value p-value for a Right-Tail Test p-value for a Left-Tail Test p-value for a Two-Tail Test p-value for a Two-Tail Test of Significance Exercises Problems Computer Exercises Appendix 3A Derivation of the t-Distribution Appendix 3B Distribution of the t-Statistic Under H1 Chapter 4 Prediction, Goodness of Fit, and Modeling Issues Learning Objectives and Keywords Least Squares Prediction Prediction in the Food Expenditure Model Measuring Goodness of Fit Correlation Analysis Correlation Analysis and 2R The Food Expenditure Example Reporting the Results Modeling Issues The Effects of Scaling the Data Choosing a Functional Form The Food Expenditure Model Are the Regression Errors Normally Distributed?

4 Another Empirical Example Log-Linear Models A Growth Model A Wage Equation Prediction in the Log-Linear Model A Generalized 2R Measure Prediction Intervals in the Log-Linear Model Exercises Problems Computer Exercises Appendix 4A Development of a Prediction Interval Appendix 4B The Sum of Squares Decomposition Appendix 4C The Log-Normal Distribution Chapter 5 The Multiple Regression Model Learning Objectives and Keywords Model Specification and the Data The Economic Model The Econometric Model The General Model The Assumptions of the Model Estimating the Parameters of the Multiple Regression Model Least Squares Estimation Procedure Least Squares Estimates Using Hamburger Chain Data Estimation of the Error Variance 2 Sampling Properties of the Least Squares Estimator The Variances and Covariances of the Least Squares Estimators The Properties of the Least Squares Estimators Assuming Normally Distributed Errors Interval Estimation Hypothesis Testing for a Single Coefficient Testing the Significance of a Single Coefficient One-Tail Hypothesis Testing for a Single Coefficient Testing For Elastic Demand Testing Advertising Effectiveness Measuring Goodness of Fit Reporting the Regression Results Keywords Exercises

5 Problems Computer Exercises Appendix 5A Derivation of Least Squares Estimators Chapter 6 Further Inference in the Multiple Regression Model Learning Objectives and Keywords The F Test The Relationship Between t- and F-Tests the Significance of a Model An Extended Model Testing Some Economic Hypotheses The Significance of Advertising The Optimal Level of Advertising One-Tail Test with More than One Parameter Using Computer Software The Use of Nonsample Information Model Specification Omitted Variables Irrelevant Variables Choosing the Model The RESET Test Poor Data, Collinearity, and Insignificance The Consequences of Collinearity An Example Identifying and Mitigating Collinearity Prediction Exercises Problems Computer Exercises Appendix 6A Chi-Square and F-Tests: More Details Appendix 6B Omitted-Variable Bias: A Proof Chapter 7 Nonlinear Relationships Learning Objectives and Keywords Polynomials Cost and Product Curves A Wage Equation Dummy Variables Intercept Dummy Variables Choosing the Reference Group Slope Dummy Variables An Example.

6 The University Effect on House Prices Applying Dummy Variables Interactions Among Qualitative Factors Qualitative Factors with Several Categories Testing the Equivalence of Two Regressions Controlling for Time Seasonal Dummies Annual Dummies Regime Effects Interactions Between Two Continuous Variables Log-Linear Models Dummy Variables A Rough Calculation An Exact Calculation Interaction and Quadratic Terms Exercises Problems Computer Exercises Appendix 7A Details of Log-Linear Model Interpretation Chapter 8 Heteroskedasticity Learning Objectives The Nature of Heteroskedasticity Using the Least Squares Estimator The Generalized Least Squares Estimator Transforming The Model Estimating the Variance Function A Heteroskedastic Partition Detecting Heteroskedasticity Residual Plots The Goldfeld-Quandt Test Testing the Variance Function The White Test Testing the Food Expenditure Example Exercises Problems Computer Exercises Appendix 8A Properties of the Least Squares Estimator Appendix 8B Variance Function Tests for Heteroskedasticity Chapter 9 Dynamic Models.

7 Autocorrelation and Forecasting Learning Objectives and Keywords Introduction Lags in the Error Term: Autocorrelation Area Response Model for Sugar Cane First Order Autoregressive Errors Estimating an AR(1) Error Model Least Squares Estimation Nonlinear Least Squares Estimation Generalized Least Squares Estimation Estimating a More General Model Testing for Autocorrelation Residual Correlogram A Lagrange Multiplier Test Recapping and Looking Forward An Introduction to Forecasting: Autoregressive Models Finite Distributed Lags Autoregressive Distributed Lag Models Exercises Problems Computer Exercises Appendix 9A Generalized Least Squares Estimation Appendix 9B The Durbin Watson Test The Durbin-Watson Bounds Test Appendix 9C Deriving ARDL Lag Weights The Geometric Lag Lag Weights for More General ARDL Models Appendix 9D Forecasting:Exponential Smoothing Chapter 10 Random Regressors and Moment Based Estimation Learning Objectives and Keywords Linear Regression with Random x s The Small Sample Properties of the Least Squares Estimator Asymptotic Properties of the Least Squares Estimator.

8 X Not Random Asymptotic Properties of the Least Squares Estimator: x Random Why Least Squares Fails Cases in Which x and e are Correlated Measurement Error Omitted Variables Simultaneous Equations Bias Lagged Dependent Variable Models with Serial Correlation Estimators Based on the Method of Moments Method of Moments Estimation of a Population Mean and Variance Method of Moments Estimation in the Simple Linear Regression Model Instrumental Variables Estimation in the Simple Linear Regression Model The Importance of Using Strong Instruments An Illustration Using Simulated Data An Illustration Using a Wage Equation Instrumental Variables Estimation with Surplus Instruments An Illustration Using Simulated Data An Illustration Using a Wage Equation Instrumental Variables Estimation in a General Model Hypothesis Testing with Instrumental

9 Variables Estimates Goodness of Fit with Instrumental Variables Estimates Specification Tests The Hausman Test for Endogeneity Testing for Weak Instruments Testing Instrument Validity Numerical Examples Using Simulated Data The Hausman Test Test for Weak Instruments Testing Surplus Moment Conditions Specification Tests for the Wage Equation Exercises Problems Computer Exercises Appendix 10A Conditional and Iterated Expectations Conditional Expectations Iterated Expectations Regression Model Applications Appendix 10B The Inconsistency of Least Squares Appendix 10C The Consistency of the Instrumental Variables Estimator Appendix 10D The Logic of the Hausman Test Chapter 11 Simultaneous Equations Models Learning Objectives and Keywords A Supply and Demand Model The Reduced Form Equations The Failure of Least Squares The Identification Problem Two-Stage Least Squares Estimation The General Two-Stage Least Squares Estimation Procedure The Properties of the Two-Stage Least Squares Estimator An Example of Two-Stage Least Squares Estimation Identification The Reduced Form Equations The Structural Equations Supply and Demand at the Fulton Fish Market Identification The Reduced Form Equations Two Stage Least Squares Estimation of Fish Demand Exercises