This study proposes an alternative, fully probabilistic approach to combining model-based forecasts with surveys or other judgmental forecasts. This approach allows data to determine how informative survey forecasts are regarding the data-generating process by probabilistically exploiting...

New products are highly valued by manufacturers and retailers due to their vital role in revenue generation. Product life cycle curves often vary by their shapes and are complicated by promotional activities that induce spiky and irregular behaviors. We collaborate with JD.com to develop a...

Quantile regression has become widely used in empirical macroeconomics, in particular for estimating and forecasting tail risks to macroeconomic indicators. In this paper we examine various choices in the specification of quantile regressions for macro applications, for example, choices related...

This study firstly applied a Bayesian symbolic regression (BSR) to the forecasting of numerous commodities' prices (spot-based ones). Moreover, some features and an initial specification of the parameters of the BSR were analysed. The conventional approach to symbolic regression, based on...

In this paper, we study the empirical relationship between credit funding sources and the financial vulnerability of the Colombian banking system. We propose a statistical model to measure and predict banking-fragility episodes associated with credit funding sources classified into retail...