Recent Advances and Future Directions in Causality, Prediction, and Specification Analysis

Chapter 1 Improving U.S. GDP Measurement: A Forecast Combination Perspective

Chapter 2 Identification Without Exogeneity Under Equiconfounding in Linear Recursive Structural Systems

Chapter 3 Optimizing Robust Conditional Moment Tests: An Estimating Function Approach

Chapter 4 Asymptotic Properties of Penalized M Estimators with Time Series Observations

Chapter 5 A Survey of Recent Advances in Forecast Accuracy Comparison Testing, with an Extension to Stochastic Dominance

Chapter 6 New Directions in Information Matrix Testing: Eigenspectrum Tests

Chapter 7 Recent Advances and Future Directions in Causality, Prediction, and Specification Analysis

Chapter 8 Hal White: Time at MIT and Early Days of Research

Chapter 9 Open-Model Forecast-Error Taxonomies

Chapter 10 Heavy-Tail and Plug-In Robust Consistent Conditional Moment Tests of Functional Form

Chapter 11 Nonparametric Identification in Dynamic Nonseparable Panel Data Models

Chapter 12 Consistent Model Selection: Over Rolling Windows

Chapter 13 Estimating Misspecified Moment Inequality Models

Chapter 14 Model Adequacy Checks for Discrete Choice Dynamic Models

Chapter 15 On Long-Run Covariance Matrix Estimation with the Truncated Flat Kernel

Chapter 16 Predictability and Specification in Models of Exchange Rate Determination

Chapter 17 Thirty Years of Heteroskedasticity-Robust Inference

Chapter 18 Smooth Constrained Frontier Analysis

Chapter 19 NoVaS Transformations: Flexible Inference for Volatility Forecasting

Chapter 20 Regression Efficacy and the Curse of Dimensionality