Econometrics and Data Science: Apply Data Science Techniques to Model Complex Problems and Implement Solutions for Economic Problems
Intro -- Table of Contents -- About the Author -- About the Technical Reviewer -- Acknowledgments -- Introduction -- Chapter 1: Introduction to Econometrics -- Econometrics -- Economic Design -- Understanding Statistics -- Machine Learning Modeling -- Deep Learning Modeling -- Structural Equation Modeling -- Macroeconomic Data Sources -- Context of the Book -- Practical Implications -- Chapter 2: Univariate Consumption Study Applying Regression -- Context of This Chapter -- Theoretical Framework -- Lending Interest Rate -- Final Consumption Expenditure (in Current U.S. Dollars) -- The Normality Assumption -- Normality Detection -- Descriptive Statistics -- Covariance Analysis -- Correlation Analysis -- Ordinary Least-Squares Regression Model Development Using Statsmodels -- Ordinary Least-Squares Regression Model Development Using Scikit-Learn -- Cross-Validation -- Predictions -- Estimating Intercept and Coefficients -- Residual Analysis -- Other Ordinary Least-Squares Regression Model Performance Metrics -- Ordinary Least-Squares Regression Model Learning Curve -- Conclusion -- Chapter 3: Multivariate Consumption Study Applying Regression -- Context of This Chapter -- Social Contributions (Current LCU) -- Lending Interest Rate -- GDP Growth (Annual Percentage) -- Final Consumption Expenditure -- Theoretical Framework -- Descriptive Statistics -- Covariance Analysis -- Correlation Analysis -- Correlation Severity Detection -- Dimension Reduction -- Ordinary Least-Squares Regression Model Development Using Statsmodels -- Residual Analysis -- Residual Autocorrelation -- Ordinary Least-Squares Regression Model Development Using Scikit-Learn -- Cross-Validation -- Hyperparameter Optimization -- Residual Analysis -- Ordinary Least-Squares Regression Model Learning Curve -- Conclusion -- Chapter 4: Forecasting Growth -- Descriptive Statistics.