Alternative tests for correct specification of conditional predictive densities
提出一种新框架来评估预测密度，在零假设下保留参数估计误差，联合检验模型设定和估计方法，蒙特卡洛模拟显示检验效果良好，并应用于专业预测者调查的密度预测。
We propose a new framework for evaluating predictive densities in an environment where the estimation error of the parameters used to construct the densities is preserved asymptotically under the null hypothesis. The tests offer a simple way to evaluate the correct specification of predictive densities, where both the model specification and its estimation technique are evaluated jointly. Monte Carlo simulation results indicate that our tests are well sized and have good power in detecting misspecification. An empirical application to density forecasts of the Survey of Professional Forecasters shows the usefulness of our methodology.