Projecting Mortality Rates Using a Markov Chain
نویسندگان
چکیده
We present a mortality model where future stochastic changes in population-wide are driven by finite-state hierarchical Markov chain. A baseline an initial ‘Alive’ state is calculated as the average logarithm of observed rates. There several more states and jump to next leads change (typically, improvement) mortality. In order estimate parameters, we minimized weighted quadratic distance between rates expected two-step estimation procedure was used, closed-form solution for optimal estimates parameters derived first step, which means that could be parameterized very fast efficiently. The then extended allow age effects whereby improvements also depend on age. Forecasting relies space augmentation innovations time series model. show that, terms forecasting, our outperforms naïve static within few years. approach permits exact computation indices, such complete expectation life annuity values, key insurance pension industries.
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ژورنال
عنوان ژورنال: Mathematics
سال: 2022
ISSN: ['2227-7390']
DOI: https://doi.org/10.3390/math10071162