A Quantitative comparison of the Lee-Carter model under different types of non-Gaussian Innovations

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<title>Quantitative comparison of the Lee-Carter model under different types of non-Gaussian Innovations</title>
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<namePart>Liu, I - Chien</namePart>
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<abstract displayLabel="Summary">In the classical Lee-Carter model, the mortality indices that are assumed to be a random walk model with drift are normally distributed. However, for the long-term mortality data, the error terms of the Lee-Carter model and the mortality indices have tails thicker than those of a normal distribution and appear to be skewed. This study therefore adopts five non-Gaussian distributions Students t-distribution and its skew extension (i.e., generalised hyperbolic skew Students t-distribution), one finite-activity Lévy model (jump diffusion distribution), and two infinite-activity or pure jump models (variance gamma and normal inverse Gaussian) to model the error terms of the Lee-Carter model. With mortality data from six countries over the period 1900-2007, both in-sample model selection criteria (e.g., Bayesian information criterion, Kolmogorov Smirnov test, Anderson Darling test, Cramérvon-Mises test) and out-of-sample projection errors indicate a preference for modelling the Lee-Carter model with non-Gaussian innovations</abstract>
<note type="statement of responsibility">Chou-Wen Wang, Hong-Chih Huang, I-Chien Liu</note>
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<topic>Matemática del seguro</topic>
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<topic>Modelos actuariales</topic>
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<subject authority="lcshac" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080555306">
<topic>Mortalidad</topic>
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<topic>Longevidad</topic>
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<topic>Seguro de vida</topic>
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<title>Geneva papers on risk and insurance : issues and practice</title>
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<publisher>Geneva : The Geneva Association, 1976-</publisher>
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<identifier type="issn">1018-5895</identifier>
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<text>03/10/2011 Tomo 36 Número 4  - 2011 , p. 675-696</text>
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