Can LAW be justified to prevent financial instability? A cost-benefit analysis of leaning against the wind (LAW) in Norway : Evidence from a Bayesian VAR model

Since the 2008 Global Financial Crisis, there has been an ongoing debate about how central banks can prevent future financial crises by mitigating the build-up of financial imbalances. We analyse the effect of incorporating financial stability considerations through monetary policy by "leaning against the wind" (LAW), which involves keeping a slightly tighter monetary policy for the purpose of mitigating financial instability. The benefits of LAW are lower probability and severity of a financial crisis in the future, while the cost is higher unemployment. We model LAW as a one-time monetary policy shock using a structural Bayesian VAR model on Norwegian data, inspired by Robstad (2018). Then, we analyse the cost-benefit trade-off of LAW in Norway using a modified version of the framework in Svensson (2017a), and contribute to the literature by including house price growth as an indicator explaining the probability of a crisis. We find that LAW is clearly unjustified when using household credit growth as an indicator of financial instability. This conclusion also is robust to any reasonable changes in the underlying estimates and assumptions. When using house price growth, we actually find that LAW is justified in the benchmark model, although only by a very small margin. However, this conclusion is not at all robust, as reasonable changes to the underlying estimates and assumptions easily change the conclusion, making LAW unjustified. Hence, we cannot use this result to conclude that LAW is an advisable policy in Norway. In sum, the numerical results do not find evidence that LAW is justified in Norway. Furthermore, Norway has a well-equipped macroprudential policy toolkit to counteract financial imbalances, arguably reducing the effect of and need for LAW. We therefore recommend that Norges Bank should not "lean against the wind", unless the Norwegian economy experiences extraordinary circumstances where the macroprudential policy tools clearly are insufficient to secure financial stability.nhhma

The age of violence: Mapping brain age in psychosis and psychopathy

Young chronological age is one of the strongest predictors for antisocial behaviour in the general population and for violent offending in individuals with psychotic disorders. An individual's age can be predicted with high accuracy using neuroimaging and machine-learning. The deviation between predicted and chronological age, i.e., brain age gap (BAG) has been suggested to reflect brain health, likely relating partly to neurodevelopmental and aging-related processes and specific disease mechanisms. Higher BAG has been demonstrated in patients with psychotic disorders. However, little is known about the brain-age in violent offenders with psychosis and the possible associations with psychopathy traits. We estimated brain-age in 782 male individuals using T1-weighted MRI scans. Three machine learning models (random forest, extreme gradient boosting with and without hyper parameter tuning) were first trained and tested on healthy controls (HC, n = 586). The obtained BAGs were compared between HC and age matched violent offenders with psychosis (PSY-V, n = 38), violent offenders without psychosis (NPV, n = 20) and non-violent psychosis patients (PSY-NV, n = 138). We ran additional comparisons between BAG of PSY-V and PSY-NV and associations with Positive and Negative Syndrome Scale (PANSS) total score as a measure of psychosis symptoms. Psychopathy traits in the violence groups were assessed with Psychopathy Checklist-revised (PCL-R) and investigated for associations with BAG. We found significantly higher BAG in PSY-V compared with HC (4.9 years, Cohen's d = 0.87) and in PSY-NV compared with HC (2.7 years, d = 0.41). Total PCL-R scores were negatively associated with BAG in the violence groups (d = 1.17, p < 0.05). Additionally, there was a positive association between psychosis symptoms and BAG in the psychosis groups (d = 1.12, p < 0.05). While the significant BAG differences related to psychosis and not violence suggest larger BAG for psychosis, the negative associations between BAG and psychopathy suggest a complex interplay with psychopathy traits. This proof-of-concept application of brain age prediction in severe mental disorders with a history of violence and psychopathy traits should be tested and replicated in larger samples

The age of violence: Mapping brain age in psychosis and psychopathy

Young chronological age is one of the strongest predictors for antisocial behaviour in the general population and for violent offending in individuals with psychotic disorders. An individual's age can be predicted with high accuracy using neuroimaging and machine-learning. The deviation between predicted and chronological age, i.e., brain age gap (BAG) has been suggested to reflect brain health, likely relating partly to neurodevelopmental and aging-related processes and specific disease mechanisms. Higher BAG has been demonstrated in patients with psychotic disorders. However, little is known about the brain-age in violent offenders with psychosis and the possible associations with psychopathy traits. We estimated brain-age in 782 male individuals using T1-weighted MRI scans. Three machine learning models (random forest, extreme gradient boosting with and without hyper parameter tuning) were first trained and tested on healthy controls (HC, n = 586). The obtained BAGs were compared between HC and age matched violent offenders with psychosis (PSY-V, n = 38), violent offenders without psychosis (NPV, n = 20) and non-violent psychosis patients (PSY-NV, n = 138). We ran additional comparisons between BAG of PSY-V and PSY-NV and associations with Positive and Negative Syndrome Scale (PANSS) total score as a measure of psychosis symptoms. Psychopathy traits in the violence groups were assessed with Psychopathy Checklist-revised (PCL-R) and investigated for associations with BAG. We found significantly higher BAG in PSY-V compared with HC (4.9 years, Cohen's d = 0.87) and in PSY-NV compared with HC (2.7 years, d = 0.41). Total PCL-R scores were negatively associated with BAG in the violence groups (d = 1.17, p < 0.05). Additionally, there was a positive association between psychosis symptoms and BAG in the psychosis groups (d = 1.12, p < 0.05). While the significant BAG differences related to psychosis and not violence suggest larger BAG for psychosis, the negative associations between BAG and psychopathy suggest a complex interplay with psychopathy traits. This proof-of-concept application of brain age prediction in severe mental disorders with a history of violence and psychopathy traits should be tested and replicated in larger samples

White Matter Matters: Unraveling Violence in Psychosis and Psychopathy

Abstract Individuals with psychotic disorders have an increased risk of committing acts of violence. Neurobiological support for the extent to which violence in psychosis is driven by psychotic symptoms and/or antisocial traits could have clinical and legal implications. Neuroimaging studies have reported white matter (WM) abnormalities in individuals with psychosis and in those with antisocial traits. However, it is unknown whether WM abnormalities in psychosis patients with a history of violence (violent-PSY) resemble those found in nonviolent psychosis patients (nonviolent PSY), violent nonpsychotic individuals (violent non-PSY), or both. Diffusion tensor imaging scans from 301 males including violent-PSY (n = 28), violent non-PSY (n = 20), nonviolent PSY (n = 58), and healthy controls (HC, n = 195) were analyzed with tract-based spatial statistics. Fractional anisotropy (FA), mean, axial and radial (RD) diffusivity were compared between groups. Psychopathic traits in the violent groups were measured with Psychopathy Checklist-revisited (PCL-R). Violent-PSY had globally lower FA and higher RD, compared with nonviolent PSY. Both psychosis groups and violent non-PSY group had widespread disruptions in WM compared with HC. There were no significant WM differences between violent-PSY and violent non-PSY. PCL-R scores did not differ between the violence groups and were associated with higher RD in corpus callosum. Here we demonstrate a widespread pattern of reduced WM integrity in violent-PSY compared with nonviolent PSY. The lack of significant WM and PCL-R differences between the violence groups, together with the positive association between PCL-R and WM deficits in violent-PSY and violent non-PSY may indicate shared neurobiological underpinnings of trait violence

White Matter Matters: Unraveling Violence in Psychosis and Psychopathy

Individuals with psychotic disorders have an increased risk of committing acts of violence. Neurobiological support for the extent to which violence in psychosis is driven by psychotic symptoms and/or antisocial traits could have clinical and legal implications. Neuroimaging studies have reported white matter (WM) abnormalities in individuals with psychosis and in those with antisocial traits. However, it is unknown whether WM abnormalities in psychosis patients with a history of violence (violent-PSY) resemble those found in nonviolent psychosis patients (nonviolent PSY), violent nonpsychotic individuals (violent non-PSY), or both. Diffusion tensor imaging scans from 301 males including violent-PSY (n = 28), violent non-PSY (n = 20), nonviolent PSY (n = 58), and healthy controls (HC, n = 195) were analyzed with tract-based spatial statistics. Fractional anisotropy (FA), mean, axial and radial (RD) diffusivity were compared between groups. Psychopathic traits in the violent groups were measured with Psychopathy Checklist-revisited (PCL-R). Violent-PSY had globally lower FA and higher RD, compared with nonviolent PSY. Both psychosis groups and violent non-PSY group had widespread disruptions in WM compared with HC. There were no significant WM differences between violent-PSY and violent non-PSY. PCL-R scores did not differ between the violence groups and were associated with higher RD in corpus callosum. Here we demonstrate a widespread pattern of reduced WM integrity in violent-PSY compared with nonviolent PSY. The lack of significant WM and PCL-R differences between the violence groups, together with the positive association between PCL-R and WM deficits in violent-PSY and violent non-PSY may indicate shared neurobiological underpinnings of trait violence