Financial, Macro and Micro Econometrics Using R, Volume 42, provides state-of-the-art information on important topics in econometrics, including multivariate GARCH, stochastic frontiers, fractional responses, specification testing and model selection, exogeneity testing, causal analysis and forecasting, GMM models, asset bubbles and crises, corporate investments, classification, forecasting, nonstandard problems, cointegration, financial market jumps and co-jumps, among other topics.
1. 1 Introduction - p. page_4 2. 2 Setup - p. page_6 3. 3 Realized measures of integrated volatility - p. page_8 4. 4 Jump testing - p. page_14 5. 5 Co-jump testing - p. page_19 6. 6 Empirical experiments - p. page_24 7. 7 Conclusion - p. page_48 8. Appendix R code - p. page_49 9. Chapter 2: Real time monitoring of asset markets: Bubbles and crises - p. page_59 10. Chapter 3: Component-wise AdaBoost algorithms for high-dimensional binary classification and class probability prediction - p. page_80 11. Part II: Macro Econometrics - p. page_114 12. Chapter 4: Mixed data sampling (MIDAS) regression models - p. page_114 13. Chapter 5: Encouraging private corporate investment in India - p. page_153 14. Chapter 6: High-mixed frequency forecasting methods in R—With applications to Philippine GDP and inflation - p. page_183 15. Chapter 7: Nonlinear time series in R: Threshold cointegration with tsDyn - p. page_227 16. Part III: Micro Econometrics - p. page_264 17. Chapter 8: Econometric analysis of productivity: Theory and implementation in R - p. page_264 18. Chapter 9: Stochastic frontier models using R - p. page_297 19. Index - p. page_327
Financial, Macro and Micro Econometrics Using R, Volume 42, provides state-of-the-art information on important topics in econometrics, including multivariate GARCH, stochastic frontiers, fractional responses, specification testing and model selection, exogeneity testing, causal analysis and forecasting, GMM models, asset bubbles and crises, corporate investments, classification, forecasting, nonstandard problems, cointegration, financial market jumps and co-jumps, among other topics.
1. 1 Introduction - p. page_4 2. 2 Setup - p. page_6 3. 3 Realized measures of integrated volatility - p. page_8 4. 4 Jump testing - p. page_14 5. 5 Co-jump testing - p. page_19 6. 6 Empirical experiments - p. page_24 7. 7 Conclusion - p. page_48 8. Appendix R code - p. page_49 9. Chapter 2: Real time monitoring of asset markets: Bubbles and crises - p. page_59 10. Chapter 3: Component-wise AdaBoost algorithms for high-dimensional binary classification and class probability prediction - p. page_80 11. Part II: Macro Econometrics - p. page_114 12. Chapter 4: Mixed data sampling (MIDAS) regression models - p. page_114 13. Chapter 5: Encouraging private corporate investment in India - p. page_153 14. Chapter 6: High-mixed frequency forecasting methods in R—With applications to Philippine GDP and inflation - p. page_183 15. Chapter 7: Nonlinear time series in R: Threshold cointegration with tsDyn - p. page_227 16. Part III: Micro Econometrics - p. page_264 17. Chapter 8: Econometric analysis of productivity: Theory and implementation in R - p. page_264 18. Chapter 9: Stochastic frontier models using R - p. page_297 19. Index - p. page_327
