Time-Series Evidence on the Nonlinearity Hypothesis for Public Spending

Barro-type endogenous growth models propose a nonmonotonic relationship between productive public spending and growth. Under this so-called nonlinearity hypothesis the size and direction of growth effects due to an increase in public spending depend on the share of public spending in GDP. Employing German time-series data we examine the validity of the nonlinearity hypothesis. We estimate growth effects by using models whose coefficients are allowed to vary with the share of public spending in GDP. Our results support the hypothesis for public consumption but not for public investment data. (JEL H54 , E62 , C22 )     

Gender disparity in the C-suite: Do male and female CEOs differ in how they reached the top?

Through a comparison of the life and career trajectories of thirty male and thirty female CEOs of large organizations, this study offers insights into the genesis of gender disparity in corporate leadership positions, discusses the implications for leadership development, and puts forward a model explaining the disparity in CEO roles. We found gendered patterns in the accumulation of career relevant experiences stretching back to birth into working lives that created significant and cumulative limitations upon the ability of women to access CEO roles and the types of CEO appointments available to them. Limited access to career relevant experiences in childhood, adolescence and in organizations lead to on-going limitations in capital accumulation throughout women's careers. Implications of our findings for both theory and practice are discussed.     

Heterogeneity in treatment effects across diverse populations

Differences in patient characteristics, including age, sex, and race influence the safety and effectiveness of drugs, biologic products, and medical devices. Here we provide a summary of the topics discussed during the opening panel at the 2018 Johns Hopkins Center for Excellence in Regulatory Science and Innovation symposium on Assessing and Communicating Heterogeneity of Treatment Effects for Patient Subpopulations: Challenges and Opportunities. The goal of this session was to provide a brief overview of FDA-regulated therapeutics, including drugs, biologics and medical devices, and some of the major sources of heterogeneity of treatment effects (HTE) related to patient demographics, such as age, sex and race. The panel discussed the US Food and Drug Administration's role in reviewing and regulating drugs, devices, and biologic products and the challenges associated with ensuring that diverse patient populations benefit from these therapeutics. Ultimately, ensuring diverse demographic inclusion in clinical trials, and designing basic and clinical research studies to account for the intended patient population's age, sex, race, and genetic factors among other characteristics, will lead to better, safer therapies for diverse patient populations.     

Methods to assess measurement error in questionnaires of sedentary behavior

Sedentary behavior has already been associated with mortality, cardiovascular disease, and cancer. Questionnaires are an affordable tool for measuring sedentary behavior in large epidemiological studies. Here, we introduce and evaluate two statistical methods for quantifying measurement error in questionnaires. Accurate estimates are needed for assessing questionnaire quality. The two methods would be applied to validation studies that measure a sedentary behavior by both questionnaire and accelerometer on multiple days. The first method fits a reduced model by assuming the accelerometer is without error, while the second method fits a more complete model that allows both measures to have error. Because accelerometers tend to be highly accurate, we show that ignoring the accelerometer's measurement error, can result in more accurate estimates of measurement error in some scenarios. In this article, we derive asymptotic approximations for the mean-squared error of the estimated parameters from both methods, evaluate their dependence on study design and behavior characteristics, and offer an R package so investigators can make an informed choice between the two methods. We demonstrate the difference between the two methods in a recent validation study comparing previous day recalls to an accelerometer-based ActivPal.     

Estimation of geodesic tortuosity and constrictivity in stationary random closed sets

We investigate the problem of estimating geodesic tortuosity and constrictivity as two structural characteristics of stationary random closed sets. They are of central importance for the analysis of effective transport properties in porous or composite materials. Loosely speaking, geodesic tortuosity measures the windedness of paths, whereas the notion of constrictivity captures the appearance of bottlenecks resulting from narrow passages within a given materials phase. We first provide mathematically precise definitions of these quantities and introduce appropriate estimators. Then, we show strong consistency of these estimators for unboundedly growing sampling windows. In order to apply our estimators to real data sets, the extent of edge effects needs to be controlled. This is illustrated using a model for a multiphase material that is incorporated in solid oxide fuel cells.