Description: A mathematical framework for benefits and choices must be created to model benefit selection. This paper creates such a framework by defining benefit plans as reimbursement functions. These are then used with a defined choice function to calculate the cost deviation due to selection. Finally, utility functions can be applied to this framework to predict choice.

Description: ARCH Editor's Comments - 2016.2

Description: This article describes the primary goal of the Actuarial Research Clearing House [ARCH], its editorial policy and the proicedure for submitting manuscripts. From Actuarial Research Clearing House, 1991 Vol. 2.

Description: This article describes the primary goal of the Actuarial Research Clearing House [ARCH], its editorial policy and the procedure for submitting manuscripts. From Actuarial Research Clearing House 1991, Vol. 3.

Description: Most courses in Excel, Word, PowerPoint or other Microsoft Office products stop just short of teaching you the highly productive things you can do with Visual Basic for Applications VBA, the powerful language that comes free with your purchase of Microsoft Office. From the Record of the Society of Actuaries, Vol. 30, No. 3.

Description: This article describes the primary goal of the Actuarial Research Clearing House [ARCH], its editorial policy and the procedure for submitting manuscripts. From Actuarial Research Clearing House 1992, Vol. 1.

Description: This article describes the primary goal of the Actuarial Research Clearing House [ARCH], its editorial policy and the procedure for submitting manuscripts. From Actuarial Research Clearing House 1992, Vol. 2.

Description: Read the ARCH 2013.1 Proceedings editor's comments.

Description: An abstract for the paper Bayesian Cumulative Anti-Selection. From the Actuarial Research Clearing House 1995, Vol. 1

Description: This is a presentation From 38th Annual Actuarial Research Conference 8/9/2003, University of Michigan, Ann Arbor, Michigan. Pricing health insurance presents numerous statistical problems. This paper develops a non-parametric method for handling these problems. This method involves kernel density estimation of the charge level distribution and also kernel smoothing between the reimbursement function derivatives. It derives some properties of the estimates so obtained. It illustrates the method with some dental data and compares the results to some other simpler estimation techniques.