Applied Econometrics: A Practical Guide
In: Routledge Advanced Texts in Economics and Finance Ser.
Cover -- Half Title -- Series -- Title -- Copyright -- Contents -- List of figures -- List of tables -- Preface -- Acknowledgments -- 1 Review of estimation and hypothesis tests -- 1.1 The problem -- 1.2 Population and sample -- 1.3 Hypotheses -- 1.4 Test statistic and its sampling distribution -- 1.5 Type I and Type II errors -- 1.6 Significance level -- 1.7 p-value -- 1.8 Powerful tests -- 1.9 Properties of estimators -- 1.10 Summary -- Review questions -- 2 Simple linear regression models -- 2.1 Introduction -- 2.1.1 A hypothetical example -- 2.1.2 Population regression line -- 2.1.3 Stochastic specification for individuals -- 2.2 Ordinary least squares estimation -- 2.3 Coefficient of determination (R2) -- 2.3.1 Definition and interpretation of R2 -- 2.3.2 Application of R2: Morck, Yeung and Yu (2000) -- 2.3.3 Application of R2: Dechow (1994) -- 2.4 Hypothesis test -- 2.4.1 Testing H0 : β1 = 0 vs. H1 : β1 ≠ 0 -- 2.4.2 Testing H0 : β1 = c vs. H1 : β1 ≠ c (c is a constant) -- 2.5 The model -- 2.5.1 Key assumptions -- 2.5.2 Gauss-Markov Theorem -- 2.5.3 Consistency of the OLS estimators -- 2.5.4 Remarks on model specification -- 2.6 Functional forms -- 2.6.1 Log-log linear models -- 2.6.2 Log-linear models -- 2.7 Effects of changing measurement units and levels -- 2.7.1 Changes of measurement units -- 2.7.2 Changes in the levels -- 2.8 Summary -- Review questions -- References -- Appendix 2 How to use EViews, SAS and R -- 3 Multiple linear regression models -- 3.1 The basic model -- 3.2 Ordinary least squares estimation -- 3.2.1 Obtaining the OLS estimates -- 3.2.2 Interpretation of regression coefficients -- 3.3 Estimation bias due to correlated-omitted variables -- 3.4 R2 and the adjusted R2 -- 3.4.1 Definition and interpretation of R2 -- 3.4.2 Adjusted R2 -- 3.5 Hypothesis test -- 3.6 Model selection -- 3.6.1 General-to-simple approach.
