The dynamic analysis of continuous-time life-cycle savings growth models

Working with the framework of a continuous-time overlapping-generations model, this paper examines equilibrium growth paths (consistent with perfect foresight). In particular, we develop a methodology for characterizing the adjustment paths converging to new stationary states following exogenous shocks. The solution technique yields sequences of derivatives approximating the true dynamic paths and bounds for the errors of approximation. In practice, aggregating behavior over discrete-time intervals can save a great deal of effort -- considerably enhancing the set of models feasible for analysis; our error bounds enable us to aggregate without compromising our results to an unknown degree.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/26597/1/0000138.pd

Insights from the Federal Mediation and Conciliation Service

In recent years, mediation has become increasingly popular as a means to resolve conflict. One important issue that arises out of the recent explosive growth in the practice of mediation is. what do mediators need to know in order to assist the parties in resolving their conflicts? This research attemtps to identify the determinants of mediator competence by examining the knowledge, skills and abilities of mediators in public sector labor relations. The research focuses on the core competencies requirements for mediators with the Federal Mediation and Conciliation Service and suggests which of the competencies may be applicable to mediation in other contexts.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

BMI, Physical Activity, and Health Care Utilization/Costs among Medicare Retirees

Objective : To examine the influence of physical activity (PA) and BMI on health care utilization and costs among Medicare retirees. Research Methods and Procedures : This cross‐sectional study was based on 42, 520 Medicare retirees in a U.S.‐wide manufacturing corporation who participated in indemnity/perferred provider and one health risk appraisal during the years 2001 and 2002. Participants were assigned into one of the three weight groups: normal weight, overweight, and obese. PA behavior was classified into three levels: sedentary (0 time/wk), moderately active (1 to 3 times/wk), and very active (4+ times/wk). Results : Generalized linear models revealed that the moderately active retirees had $1456,$1731, and $1177 lower total health care charges than their sedentary counterparts in the normal‐weight, overweight, and obese groups, respectively ( p < 0.01). The very active retirees had$1823, $581, and$1379 lower costs than the moderately active retirees. Health care utilization and specific costs showed similar trends with PA levels for all BMI groups. The total health care charges were lower with higher PA level for all age groups ( p < 0.01). Discussion : Regular PA has strong dose‐response effects on both health care utilization and costs for overweight/obese as well as normal‐weight people. Promoting active lifestyle in this Medicare population, especially overweight and obese groups, could potentially improve their well‐being and save a substantial amount of health care expenditures. Because those Medicare retirees are hard to reach in general, more creative approaches should be launched to address their needs and interests as well as help reduce the usage of health care system.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/93683/1/oby.2005.175.pd

Awareness in Practice: Tensions in Access to Sensitive Attribute Data for Antidiscrimination

Organizations cannot address demographic disparities that they cannot see. Recent research on machine learning and fairness has emphasized that awareness of sensitive attributes, such as race and sex, is critical to the development of interventions. However, on the ground, the existence of these data cannot be taken for granted. This paper uses the domains of employment, credit, and healthcare in the United States to surface conditions that have shaped the availability of sensitive attribute data. For each domain, we describe how and when private companies collect or infer sensitive attribute data for antidiscrimination purposes. An inconsistent story emerges: Some companies are required by law to collect sensitive attribute data, while others are prohibited from doing so. Still others, in the absence of legal mandates, have determined that collection and imputation of these data are appropriate to address disparities. This story has important implications for fairness research and its future applications. If companies that mediate access to life opportunities are unable or hesitant to collect or infer sensitive attribute data, then proposed techniques to detect and mitigate bias in machine learning models might never be implemented outside the lab. We conclude that today's legal requirements and corporate practices, while highly inconsistent across domains, offer lessons for how to approach the collection and inference of sensitive data in appropriate circumstances. We urge stakeholders, including machine learning practitioners, to actively help chart a path forward that takes both policy goals and technical needs into account

Scared Straight and Other Juvenile Awareness Programs for Preventing Juvenile Delinquency: A Systematic Review

Programs like ‘Scared Straight’ involve organized visits to prison facilities by juvenile delinquents or children at risk for becoming delinquent. The programs are designed to deter participants from future offending by providing first-hand observations of prison life and interaction with adult inmates. Results of this review indicate that not only does it fail to deter crime but it actually leads to more offending behavior. Government officials permitting this program need to adopt rigorous evaluation to ensure that they are not causing more harm to the very citizens they pledge to protect