Purpose: Lockdown and movement restrictions that imposed by governments have significantly changed customers behavior, making the planning and decision-making processes more challenging. Providing accurate estimation of the demand, enable managers to take more successful decisions and allow...

Factor modelling extracts common information from a high-dimensional data set into few common components, where the latent factors usually explain a large share of data variation. Exploratory factor estimation induces sparsity into the loading matrix to associate units or series with those...

The study aims to demonstrate gender differences in financial health indicators, assessed through perceptions, lived experiences, and actions to deal with financial crises. The scale used is a composite instrument that includes the eight financial health indicators from BBVA and the Center for...

Throughout history, governments and investors have relied on predictions of prices for a broad spectrum of commodities. Using time-series data covering 08/23/2013-04/15/2021, this study investigates the challenging problem of predicting scrap steel prices, which are issued daily for the...

This paper introduces a Bayesian Quantile Factor Augmented VAR (BQFAVAR) to examine the asymmetric effects of monetary policy throughout the business cycle. Monte Carlo experiments demonstrate that the model effectively captures non-linearities in impulse responses. Analysis of aggregate...

We study the application of approximate mean field variational inference algorithms to Bayesian panel VAR models in which an exchangeable prior is placed on the dynamic parameters and the residuals follow either a Gaussian or a Student-t distribution. This reduces the estimation time of possibly...