Computer-Aided Introduction to Econometrics

1 Univariate Linear Regression Model.- 1.1 Probability and Data Generating Process.- 1.2 Estimators and Properties.- 1.3 Inference.- 1.4 Forecasting.- 2 Multivariate Linear Regression Model.- 2.1 Introduction.- 2.2 Classical Assumptions of the MLRM.- 2.3 Estimation Procedures.- 2.4 Properties of the Estimators.- 2.5 Interval Estimation.- 2.6 Goodness of Fit Measures.- 2.7 Linear Hypothesis Testing.- 2.8 Restricted and Unrestricted Regression.- 2.9 Three General Test Procedures.- 2.10 Dummy Variables.- 2.11 Forecasting.- 3 Dimension Reduction and Its Applications.- 3.1 Introduction.- 3.2 Average Outer Product of Gradients and its Estimation.- 3.3 A Unified Estimation Method.- 3.4 Number of E.D.R. Directions.- 3.5 The Algorithm.- 3.6 Simulation Results.- 3.7 Applications.- 3.8 Conclusions and Further Discussion.- 3.9 Appendix. Assumptions and Remarks.- 4 Univariate Time Series Modelling.- 4.1 Introduction.- 4.2 Linear Stationary Models for Time Series.- 4.3 Nonstationary Models for Time Series.- 4.4 Forecasting with ARIMA Models.- 4.5 ARIMA Model Building.- 4.6 Regression Models for Time Series.- 5 Multiplicative SARIMA models.- 5.1 Introduction.- 5.2 Modeling Seasonal Time Series.- 5.3 Identification of Multiplicative SARIMA Models.- 5.4 Estimation of Multiplicative SARIMA Models.- 6 Auto Regressive Conditional Heteroscedastic Models.- 6.1 Introduction.- 6.2 ARCH(1) Model.- 6.3 ARCH(q) Model.- 6.4 Testing Heteroscedasticity and ARCH(1) Disturbances.- 6.5 ARCH(1) Regression Model.- 6.6 GARCH(p,q) Model.- 6.7 Extensions of ARCH Models.- 6.8 Two Examples of Spanish Financial Markets.- 7 Numerical Optimization Methods in Econometrics.- 7.1 Introduction.- 7.2 Solving a Nonlinear Equation.- 7.3 Solving a System of Nonlinear Equations.- 7.4 Minimization of a Function: One-dimensional Case.- 7.5 Minimization of a Function: Multidimensional Case.- 7.6 Auxiliary Routines for Numerical Optimization.