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Computer-Aided Econometrics

David E. A. Giles

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CRC Press
30 June 2020
Econometrics; Computer science
Emphasizing the impact of computer software and computational technology on econometric theory and development, this text presents recent advances in the application of computerized tools to econometric techniques and practicesaEURO focusing on current innovations in Monte Carlo simulation, computer-aided testing, model selection, and Bayesian methodology for improved econometric analyses.
Edited by:   David E. A. Giles
Imprint:   CRC Press
Country of Publication:   United Kingdom
Dimensions:   Height: 229mm,  Width: 152mm, 
Weight:   1.002kg
ISBN:   9780367578497
ISBN 10:   0367578492
Pages:   520
Publication Date:   30 June 2020
Audience:   College/higher education ,  Primary
Format:   Paperback
Publisher's Status:   Active
1. Some Methodological Questions Arising from Large Data Sets 2. Finite-Sample Simulation-Based Tests in Seemingly Unrelated Regressions 3. Finding Optimal Penalties for Model Selection in the Linear Regression Model 4. On Bootstrap Coverage Probability with Dependent Data 5. A Comparison of Alternative Causality and Predictive Accuracy Tests in the Presence of Integrated and Cointegrated Economic Variables 6. Finite Sample Performance of the Empirical Likelihood Estimator Under Endogeneity 7. Testing for Unit Roots in Semiannual Data 8. Using Simulation Methods for Bayesian Econometric Models 9. Bayesian Inference in the Seemingly Unrelated Regressions Model 10. Computationally Intensive Methods for Deriving Optimal Trimming Parameters 11. Estimating and Testing Fundamental Stock Prices: Evidence from Simulated Economies 12. Neural Networks: An Econometric Tool 13. Real-Time Forecasting with Vector Autoregressions: Spurious Drift, Structural Change, and Intercept Correction 14. Econometric Modeling Based on Pattern Recognition via the Fuzzy C-Means Clustering Algorithm 15. Nonparametric Bootstrap Specification Testing in Econometric Models 16. The Effect of Economic Growth on Standard of Living: A Semiparametric Analysis

Giles\, David E. A.

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