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In this paper, we propose three new predictive models: the multi-step nonparametric predictive regression model and the … multi-step additive predictive regression model, in which the predictive variables are locally stationary time series; and … the multi-step time-varying coefficient predictive regression model, in which the predictive variables are stochastically …
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The understanding of co-movements, dependence, and influence between variables of interest is key in many applications. Broadly speaking such understanding can lead to better predictions and decision making in many settings. We propose Quantile Graphical Models (QGMs) to characterize prediction...
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Quantile regression has become widely used in empirical macroeconomics, in particular for estimating and forecasting … Bayesian quantile regression dominating frequentist quantile regression. …
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