Advances in Applied Econometrics

Chapter 1. Introduction.- Chapter 2. Robust Dynamic Space–time Panel Data Models Using εε-contamination: An Application to Crop Yields and Climate Change.- Chapter 3. Unbiased Estimation of the OLS Covariance Matrix When the Errors are Clustered.- Chapter 4. Refined GMM Estimators for Simultaneous Equations Models with Network Interactions.- Chapter 5. Identification and Estimation of Categorical Random Coefficient Models.- Chapter 6. Dynamic Panel GMM Estimators with Improved Finite Sample Properties using Parametric Restrictions for Dimension Reduction.- Chapter 7. Testing for Correlation Between the Regressors and Factor Loadings in Heterogeneous Panels with Interactive Effects.- Chapter 8. Assessing the Impacts of Pandemic and the Increase in Minimum Down Payment Rate on Shanghai Housing Prices.- Chapter 9. A Simple, Robust Test for Choosing the Level of Fixed Effects in Linear Panel Data Models.- Chapter 10. Internal Adjustment Costs of Firm-specific Factors and the Neoclassical Theory of the Firm.- Chapter 11. Proportional Incremental Cost Probability Functions and Their Frontiers.- Chapter 12. Hotelling Tubes, Confidence Bands and Conformal Inference.- Chapter 13. Indirect Inference Estimation of Stochastic Production Frontier Models With Skew-normal Noise.- Chapter 14. The Noise Error Component in Stochastic Frontier Analysis.- Chapter 15. An Alternative Corrected Ordinary Least Squares Estimator for the Stochastic Frontier Model.- Chapter 16. Likelihood-based Inference for Dynamic Panel Data Models.- Chapter 17. Approximating Long-memory Processes With Low-order Autoregressions: Implications for Modeling Realized Volatility.- Chapter 18. Does Climate Change Affect Economic Data?.- Chapter 19. Information Loss in Volatility Measurement With Flat Price Trading.- Chapter 20. Forecasting in the Presence of in-sample and Out-of-sample Breaks.- Chapter 21. Multivariate Models of Commodity Futures Markets: A Dynamic Copula Approach.- Chapter 22. Generalized Kernel Regularized Least Squares Estimator With Parametric Error Covariance.- Chapter 23. Predicting Binary Outcomes Based on the Pair-copula Construction.- Chapter 24. Public Subsidies and Innovation: a Doubly Robust Machine Learning Approach Leveraging Deep Neural Networks.- Chapter 25. DS-HECK: Double-lasso Estimation of Heckman Selection Model.- Chapter 26. Simultaneity in Binary Outcome Models with an Application to Employment for Couples.

• Erscheinungsdatum: 08.01.2025
• Autor/Autorin: Subal C. Kumbhakar
• Reihe: Economics and Finance (R0)
• Format: E-Book
• Dateiformat: PDF
• Kopierschutz: Wasserzeichen
• Dateigröße: 31.4 MB
• Verlag: SPRINGER
• Sprache: Englisch
• Umfang: 777 Seiten
• ISBN: 9783031483851
• Lieferung: Sofort per Download
• Hinweis: Sofort per Download lieferbar. Kein physischer Versand.
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