Advances in Applied Econometrics

Advances in Applied Econometrics

Celebrating Peter Schmidt's Legacy

Sickles, Robin; Kumbhakar, Subal C; Wang, Hung-Jen

Springer International Publishing AG

06/2024

833

Dura

Inglês

9783031483844

Pré-lançamento - envio 15 a 20 dias após a sua edição

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Chapter 1. Introduction.- Chapter 2. Robust Dynamic Space-time Panel Data Models Using ??-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.
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Panel data;Time series;Limited dependent variables;Nonparametric methods;Machine learning;Copulas;Stochastic frontiers;Econometrics;Productivity;Efficiency;Treatment effects