4.7 Testing for Conditional Homoskedasticity 4.8 Empirical Applications 4.9 Conclusion Chapter 5 Linear Regression Models with Dependent Observations 5.1 Introduction to Time Series Analysis 5.2 Framework and Assumptions 5.3 Consistency of OLS 5.4 Asymptotic Normality of OLS 5.5 Asymptotic Variance Estimator for OLS 5.6 Hypothesis Testing 5.7 Testing for Conditional Heteroskedasticity and Autoregressive Conditional Heteroskedas- ticity 5.8 Testing for Serial Correlation 5.9 Conclusion Chapter 6 Linear Regression Models under Conditional Heteroskedasticity and Autocorrelation 6.1 Framework and Assumptions 6.2 Long-run Variance Estimation 6.3 Consistency of OLS 6.4 Asymptotic Normality of OLS 6.5 Hypothesis Testing 6.6 Testing Whether Long-run Variance Estimation Is Needed 6.7 A Classical Ornut-Cochrane Procedure 6.8 Empirical Applications 6.9 Conclusion Chapter 7 Instrumental Variables Regression 7.1 Framework and Assumptions 7.2 Two-Stage Least Squares (2SLS)Estimation 7.3 Consistency of 2SLS 7.4 Asymptotic Normality of 2SLS 7.5 Interpretation and Estimation of the 2SLS Asymptotic Variance 7.6 Hypothesis Testing 7.7 Hausman's Test 7.8 Empirical Applications 7.9 Conclusion 54.7 Testing for Conditional Homoskedasticity 4.8 Empirical Applications 4.9 Conclusion Chapter 5 Linear Regression Models with Dependent Observations 5.1 Introduction to Time Series Analysis 5.2 Framework and Assumptions 5.3 Consistency of OLS 5.4 Asymptotic Normality of OLS 5.5 Asymptotic Variance Estimator for OLS 5.6 Hypothesis Testing 5.7 Testing for Conditional Heteroskedasticity and Autoregressive Conditional Heteroskedas￾ticity 5.8 Testing for Serial Correlation 5.9 Conclusion Chapter 6 Linear Regression Models under Conditional Heteroskedasticity and Autocorrelation 6.1 Framework and Assumptions 6.2 Long-run Variance Estimation 6.3 Consistency of OLS 6.4 Asymptotic Normality of OLS 6.5 Hypothesis Testing 6.6 Testing Whether Long-run Variance Estimation Is Needed 6.7 A Classical Ornut-Cochrane Procedure 6.8 Empirical Applications 6.9 Conclusion Chapter 7 Instrumental Variables Regression 7.1 Framework and Assumptions 7.2 Two-Stage Least Squares (2SLS) Estimation 7.3 Consistency of 2SLS 7.4 Asymptotic Normality of 2SLS 7.5 Interpretation and Estimation of the 2SLS Asymptotic Variance 7.6 Hypothesis Testing 7.7 Hausmanís Test 7.8 Empirical Applications 7.9 Conclusion 5