We present a general framework for Bayesian estimation and causality assessment in epidemiological models. The key to … distribution. We show how to use the posterior simulation outputs as inputs for exercises in causality assessment. We apply our …

Testing for Granger non-causality over varying quantile levels could be used to measure and infer dynamic linkages …, enabling the identification of quantiles for which causality is relevant, or not. However, dynamic quantiles in financial … quantile regression and the skewed-Laplace distribution, is designed for estimation and inference of the quantile causal …

This paper considers estimation of the treatment effect where the researcher has data from a large number of related …

constrained estimation produces a quantitative model with both reasonable asset-pricing as well as business-cycle implications. …