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稀疏趋势估计AI 解读

Abstract The low-frequency movements of economic variables play a prominent role in policy analysis and decision-making. We develop a robust estimation approach for these slow-moving trend processes which is guided by a judicious choice of priors and is characterized by sparsity. We present novel stylized facts from longer-run survey expectations that inform the structure of the estimation procedure. The general version of the proposed Bayesian estimator with a…

评论AI 解读

Conducting valid inference in a time series setting often requires the use of a heteroscedasticity and autocorrelation (HAC) robust variance estimator. Under mild dependence structures, the theory ...