Asymptotically minimax empirical Bayes estimation of a sparse normal mean vector

For the important classical problem of inference on a sparse high-dimensional normal mean vector, we propose a novel empirical Bayes model that admits a posterior distribution with desirable properties under mild conditions. In particular, our empirical Bayes posterior distribution concentrates on balls, centered at the true mean vector, with squared radius proportional to the minimax rate, and its posterior mean is an asymptotically minimax estimator. We also show that, asymptotically, the support of our empirical Bayes posterior has roughly the same effective dimension as the true sparse mean vector. Simulation from our empirical Bayes posterior is straightforward, and our numerical results demonstrate the quality of our method compared to others having similar large-sample properties.Comment: 18 pages, 3 figures, 3 table

Income Smoothing over the Business Cycle: Changes in Banks’ Coordinated Management of Provisions for Loan Losses and Loan Charge-offs from the Pre-1990 Bust to the 1990s Boom

We provide evidence that banks smooth income by managing provisions for loan losses and loan charge-offs in a coordinated fashion that varies across the bust and boom phases of the business cycle and across homogeneous and heterogeneous loan types. In particular, during the 1990s boom, we predict and find that banks accelerated provisioning for loan losses and made this less obvious by accelerating loan charge-offs, especially for homogenous loans for which charge-offs are determined using number-of-days-past-due rules. We also provide evidence that the valuation implications of banks’ provisions for loan losses and loan charge-offs vary across the phases of the business cycle and loan types reflecting the effect of these factors on banks’ income smoothing. In particular, during the 1990s boom, we predict and find that charge-offs of homogenous loans have a positive association with current returns and future cash flows, because these charge-offs are recorded primarily by healthy banks with good future prospects reducing over-stated allowances for loan losses. We also predict and find that these charge-offs have a positive association with future returns that is explained by their positive association with future net income and recoveries. Our results are consistent with the market only partially appreciating healthy banks’ overstatement of charge-offs of homogeneous loans based on number-of-days-past-due rules during the 1990s boom, because of the perceived non-discretionary nature of these charge-offs

Invasive fungal infections secondary to traumatic injury

Invasive fungal infection (IFI) is a rare but serious complication of traumatic injury. The purpose of this article is to review the epidemiology, natural history, mycology, risk factors, diagnosis, treatment, and outcomes associated with post-traumatic IFI in military and civilian populations. The epidemiology of post-traumatic IFI is poorly characterized, but incidence appears to be rising. Patients often suffer from severe injuries and require extensive medical interventions. Fungi belonging to the order Mucorales are responsible for most post-traumatic IFI in both civilian and military populations. Risk factors differ between these cohorts but include specific injury patterns and comorbidities. Diagnosis of post-traumatic IFI typically follows positive laboratory results in the appropriate clinical context. The gold standard of treatment is surgical debridement in addition to systemic antifungal therapy. Patients with post-traumatic IFI may be at greater risk of amputation, delays in wound healing, hospital complications, and death as compared to trauma patients who do not develop IFI. More research is needed to understand the factors surrounding the development and management of post-traumatic IFI to reduce the significant morbidity and mortality associated with this disease