The purpose of this research is to study empirically the dynamics of obesity in Finland and provide empirical evidence of temporal causality between obesity, health expenditure, unemployment, urbanization, alcohol consumption and calorie intake. The paper employs bounds testing cointegration procedure and augmented causality tests. The empirical results suggest the existence of cointegration am...

Previous studies on causality estimation mainly aquire causal event pairs from a large corpus based on lexico-syntactic patterns and coreference relations, and estimate causality by a statistical method. However, most of the previous studies assume event pairs can be represented by a pair of single words, therefore they cannot estimate multiword causality correctly (e.g.“tired”-“give up”) . In ...

We investigate the instability of the Cauchy horizon caused by causality violation in the compact vacuum universe with the topology B × S × R, which Moncrief and Isenberg considered. We show that if the occurrence of curvature singularities are restricted to the boundary of causality violating region, the whole segments of the boundary become curvature singularities. This implies that the stron...

We provide a structural approach to disentangle Granger versus instantaneous causality effects from transaction durations to transaction prices. So far, in the literature, instantaneous causality effects have either been excluded or cannot be identified separately from Granger type causality effects. By giving explicit moment conditions for observed returns over (random) transaction duration in...

Causal markers, syntactic structures and connectives have been the sole identifying features for automatically extracting causal relations in natural language discourse. However, various connectives such as “and”, prepositions such as “as”, and other syntactic structures are highly ambiguous in nature, as they have multiple meanings besides causality. As a result, one cannot solely rely on lexi...

1 Nonlinear Causality, with Applications to Liquidity and Stochastic Volatility Abstract The conditional Laplace transform is often easier to use in financial data analysis than the conditional density. This paper characterizes nonlinear causality hypotheses for models based on the conditional Laplace transform and provides interpretations of the linear and quadratic causality in this framework...

An understanding of relations between causes and effects is essential for making sense of the dynamic physical world. It has been argued that this understanding of causality depends on both perceptual and inferential components. To investigate whether causal perception and causal inference rely on common or on distinct processes, the authors tested 2 callosotomy (split-brain) patients and a gro...