Using Multivariant Regression Analysis to Compute Longevity Risk and Actuarial Liability: The Case of Social Benefits for Workers in Venezuela

Evaristo Diz¹ and J. Tim Query^2,

¹Actuarial Science, Universidad Católica Andrés Bello, Caracas, Venezuela

²Finance Department, New Mexico State University, Caracas, Venezuela

Cite this paper:
Evaristo Diz and J. Tim Query. Using Multivariant Regression Analysis to Compute Longevity Risk and Actuarial Liability: The Case of Social Benefits for Workers in Venezuela. Journal of Finance and Economics. 2018; 6(4):144-153. doi: 10.12691/jfe-6-4-4

Abstract

In this study, a multivariate regression model is determined that allows computation of the actuarial liability of social benefits using a group of potential predictors. In general, the previous or independent predictors are the same as those utilized in an actuarial valuation of labor commitments. Several linear and non-linear models are considered and tested in this study. Among the most important findings of this research is that the PBO or Actuarial Liability depends fundamentally on a linear basis of two fundamental variables in the quantification of Social Benefits -- the Guarantees and the Social Benefits to Pay (PSP). The attractiveness of a relatively simple yet structurally robust model is a very attractive option in situations where managers are tasked to provide estimates in relatively short order, given that the two variables highlighted are generally readily available for most organizations. Realistically, companies are often required to give quick estimates, and they find it quite difficult to quantify an order of this magnitude. This model succeeds in filling this informational gap at the 4 percent interest rate.

Keywords:
multivariate analysis actuarial liability longevity

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