What Do CEOs Do?

We develop a methodology to collect and analyze data on CEO’s time use. The idea sketched out in a simple theoretical set-up is that CEO time is a scarce resource and its allocation can help us identify the firm’s priorities as well as the presence of governance issues. We follow 94 CEOs of top-600 Italian firms over a pre-specified week and record the time devoted each day to different work activities. We focus on the distinction between time spent with insiders (employees of the firm) and outsiders (people not employed by the firm). Individual CEOs differ systematically in how much time they spend at work and in how much time they devote to insiders vs. outsiders. We analyze the correlation between time use, managerial effort, quality of governance and firm performance, and interpret the empirical findings within two versions of our model, one with effective and one with imperfect corporate governance. The patterns we observe are consistent with the hypothesis that time spent with outsiders is on average less beneficial to the firm and more beneficial to the CEO and that the CEO spends more time with outsiders when governance is poor.

Matching Firms, Managers and Incentives

We exploit a unique combination of administrative sources and survey data to study the match between firms and managers. The data includes manager characteristics, such as risk aversion and talent; firm characteristics, such as ownership; detailed measures of managerial practices relative to incentives, dismissals and promotions; and measurable outcomes, for the firm and for the manager. A parsimonious model of matching and incentive provision generates an array of implications that can be tested with our data. Our contribution is twofold. We disentangle the role of risk-aversion and talent in determining how firms select and motivate managers. In particular, risk-averse managers are matched with firms that offer low-powered contracts. We also show that empirical findings linking governance, incentives, and performance that are typically observed in isolation, can instead be interpreted within a simple unified matching framework.

Thyroid autoimmunity in bipolar disorder: A systematic review

Background Accumulating evidence points to the pathophysiological relevance between immune dysfunction and mood disorders. High rates of thyroid dysfunction have been found in patients with bipolar disorder (BD), compared to the general population. A systematic review of the relationship between BD and thyroid autoimmunity was performed. Methods Pubmed, EMBASE and PsycINFO databases were searched up till January 28th, 2017. This review has been conducted according to the PRISMA statements. Observational studies clearly reporting data among BD patients and the frequency of autoimmune thyroid pathologies were included. Results 11 original studies met inclusion criteria out of 340 titles first returned from the global search. There is evidence of increased prevalence of circulating thyroid autoantibodies in depressed and mixed BD patients, while there is no evidence showing a positive relationship between BD and specific autoimmune thyroid diseases. There is a controversy about the influence of lithium exposure on circulating thyroid autoantibodies, even if most of studies seem not to support this association. A study conducted on bipolar twins suggests that autoimmune thyroiditis is related to the genetic vulnerability to develop BD rather than to the disease process itself. Females are more likely to develop thyroid autoimmunity. Limitations The samples, study design and outcomes were heterogeneous. Conclusion Thyroid autoimmunity has been suggested to be an independent risk factor for bipolar disorder with no clear association with lithium exposure and it might serve as an endophenotype for BD

Aggressiveness in depression: a neglected symptom possibly associated with bipolarity and mixed features

OBJECTIVE: To evaluate aggressiveness during a major depressive episode (MDE) and its relationship with bipolar disorder (BD) in a post hoc analysis of the BRIDGE-II-MIX study. METHOD: A total of 2811 individuals were enrolled in this multicenter cross-sectional study. MDE patients with (MDE-A, n = 399) and without aggressiveness (MDE-N, n = 2412) were compared through chi-square test or Student's t-test. A stepwise backward logistic regression model was performed. RESULTS: MDE-A group was more frequently associated with BD (P < 0.001), while aggressiveness was negatively correlated with unipolar depression (P < 0.001). At the logistic regression, aggressiveness was associated with the age at first depressive episode (P < 0.001); the severity of mania (P = 0.03); the diagnosis of BD (P = 0.001); comorbid borderline personality disorder (BPD) (P < 0.001) but not substance abuse (P = 0.63); no current psychiatric treatment (P < 0.001); psychotic symptoms (P = 0.007); the marked social/occupational impairment (P = 0.002). The variable most significantly associated with aggressiveness was the presence of DSM-5 mixed features (P < 0.001, OR = 3.815). After the exclusion of BPD, the variable of lifetime suicide attempts became significant (P = 0.013, OR = 1.405). CONCLUSION: Aggressiveness seems to be significantly associated with bipolar spectrum disorders, independently from BPD and substance abuse. Aggressiveness should be considered as a diagnostic criterion for the mixed features specifier and a target of tailored treatment strategy

The implications of hypersomnia in the context of major depression: Results from a large, international, observational study

According to the DSM-5, 'reduction in the need for sleep' is the only sleep-related criteria for mixed features in depressive episodes. We aimed at studying the prevalence, clinical correlates and the role of hypersomnia in a sample of acutely depressed patients. Secondarily, we factors significantly increasing the odds of hypersomnia were studied. We conducted a post-hoc analysis of the BRIDGE-II-Mix study. Variables were compared between patients with hypersomnia (SLEEP+) and with insomnia (SLEEP-) with standard bivariate tests. A stepwise backward logistic regression model was performed with SLEEP+ as dependent variable. A total of 2514 subjects were dichotomized into SLEEP+ (n = 423, 16.8%) and SLEEP- (n = 2091, 83.2%). SLEEP+ had significant higher rates of obese BMI (p < 0.001), BD diagnosis (p = 0.027), severe BD (p < 0.001), lifetime suicide attempts (p < 0.001), lower age at first depression (p = 0.004) than SLEEP-. Also, SLEEP+ had significantly poorer response to antidepressants (AD) such as (hypo)manic switches, AD resistance, affective lability, or irritability (all 0<0.005). Moreover, SLEEP+ had significantly higher rates of mixed-state specifiers than SLEEP- (all 0 < 0.006). A significant contribution to hypersomnia in our regression model was driven by metabolic-related features, such as 'current bulimia' (OR = 4.21) and 'overweight/obese BMI (OR = 1.42)'. Globally, hypersomnia is associated with poor outcome in acute depression. Hypersomnia is strongly associated with mixed features and bipolarity. Metabolic aspects could influence the expression of hypersomnia, worsening the overall clinical outcome. Along with commonly used screening tools, detection of hypersomnia has potential, costless discriminative validity in the differential diagnosis unipolar and bipolar depression