Analysis of causal effects between continuous-valued variables typically uses either autoregressive models or structural equation models with instantaneous effects. Estimation of Gaussian, linear structural equation models poses serious identifiability problems, which is why it was recently proposed to use non-Gaussian models. Here, we show how to combine the non-Gaussian instantaneous model wi...

Within the approaches that have been applied to assess the impact of public capital on economic growth, this paper estimates the dynamic effects of public infrastructures using a structural vector autoregressive (SVAR) methodology for the Spanish regions. From a methodological point of view, our work contains different innovative features with respect to the previous studies using VAR models. T...

In conventional causal discovery, structural equation models (SEM) are directly applied to the observed variables, meaning that the causal effect can be represented as a function of the direct causes themselves. However, in many real world problems, there are significant dependencies in the variances or energies, which indicates that causality may possibly take place at the level of variances o...

This paper investigates the impact of uncertainty shocks on REITs returns over a monthly period from 1972:01 to 2015:12, and sub-samples 2009:06, 2009:07 accommodate for possible effects Global Financial Crisis (GFC) unconventional monetary policy decisions. We use recently-proposed variations in price gold, around events associated with unexpected changes as an instrument identify proxy Struct...