Reinventing the Risk Sharing Mechanism of Defined Benefit Pension Plans

In this paper, I will introduce several new mechanisms of risk sharing regarding occupational retirement provisions, based on the analysis of present risk sharing between sponsoring employers and plan participants, individual participants and participants as a group, active members and beneficiaries (including deferred members), etc. Among others, I will introduce "Ring-fenced" DB (RfDB) plans, which introduce "share" structure into contributions and reserves, prohibit "lending" from active members to beneficiaries when the plan is in an underfunded status (actuarial deficiency), and allow temporary benefit reductions within prescribed ranges according to the funding level. The risk active members bear will be eased in RfDB plans, and market interest risk sponsoring employers bear will also be eased, because some portion of benefits becomes conditional. RfDB plans allow investments with greater risk tolerance, which may benefit both labor and management from a long-term perspective. It will also be possible to ease funding rules substantially for RfDB plans. It is said that DB plans are on the verge of extinction mainly by the threats from accounting standards. Taking this into account, it is necessary to expand the variation of risk sharing mechanisms in occupational retirement provisions."Ring-fenced" DB plan, "Retrospective" DB plan, Sequential plan, Combination plan, Collective DC plan, DC conversion

Where do statistical models come from? Revisiting the problem of specification

R. A. Fisher founded modern statistical inference in 1922 and identified its fundamental problems to be: specification, estimation and distribution. Since then the problem of statistical model specification has received scant attention in the statistics literature. The paper traces the history of statistical model specification, focusing primarily on pioneers like Fisher, Neyman, and more recently Lehmann and Cox, and attempts a synthesis of their views in the context of the Probabilistic Reduction (PR) approach. As argued by Lehmann [11], a major stumbling block for a general approach to statistical model specification has been the delineation of the appropriate role for substantive subject matter information. The PR approach demarcates the interrelated but complemenatry roles of substantive and statistical information summarized ab initio in the form of a structural and a statistical model, respectively. In an attempt to preserve the integrity of both sources of information, as well as to ensure the reliability of their fusing, a purely probabilistic construal of statistical models is advocated. This probabilistic construal is then used to shed light on a number of issues relating to specification, including the role of preliminary data analysis, structural vs. statistical models, model specification vs. model selection, statistical vs. substantive adequacy and model validation.Comment: Published at http://dx.doi.org/10.1214/074921706000000419 in the IMS Lecture Notes--Monograph Series (http://www.imstat.org/publications/lecnotes.htm) by the Institute of Mathematical Statistics (http://www.imstat.org

Are language production problems apparent in adults who no longer meet diagnostic criteria for attention-deficit/hyperactivity disorder?

In this study, we examined sentence production in a sample of adults (N = 21) who had had attention-deficit/hyperactivity disorder (ADHD) as children, but as adults no longer met DSM-IV diagnostic criteria (APA, 2000). This “remitted” group was assessed on a sentence production task. On each trial, participants saw two objects and a verb. Their task was to construct a sentence using the objects as arguments of the verb. Results showed more ungrammatical and disfluent utterances with one particular type of verb (i.e., participle). In a second set of analyses, we compared the remitted group to both control participants and a “persistent” group, who had ADHD as children and as adults. Results showed that remitters were more likely to produce ungrammatical utterances and to make repair disfluencies compared to controls, and they patterned more similarly to ADHD participants. Conclusions focus on language output in remitted ADHD, and the role of executive functions in language production

Structural Nested Models and G-estimation: The Partially Realized Promise

Structural nested models (SNMs) and the associated method of G-estimation were first proposed by James Robins over two decades ago as approaches to modeling and estimating the joint effects of a sequence of treatments or exposures. The models and estimation methods have since been extended to dealing with a broader series of problems, and have considerable advantages over the other methods developed for estimating such joint effects. Despite these advantages, the application of these methods in applied research has been relatively infrequent; we view this as unfortunate. To remedy this, we provide an overview of the models and estimation methods as developed, primarily by Robins, over the years. We provide insight into their advantages over other methods, and consider some possible reasons for failure of the methods to be more broadly adopted, as well as possible remedies. Finally, we consider several extensions of the standard models and estimation methods.Comment: Published in at http://dx.doi.org/10.1214/14-STS493 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org