Mortality Surface by Means of Continuous Time Cohort Models
AbstractWe study and calibrate a cohort-based model which captures the characteristics of a mortality surface with a parsimonious, continuous-time fac- tor approach. The model allows for imperfect correlation of mortality intensity across generations. It is implemented on UK data for the period 1900-2008. Calibration by means of stochastic search and the Differential Evolution opti- mization algorithm proves to yield robust and stable parameters. We provide in-sample and out-of-sample, deterministic as well as stochastic forecasts. Cal- ibration confirms that correlation across generations is smaller than one.
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Bibliographic InfoPaper provided by Collegio Carlo Alberto in its series Carlo Alberto Notebooks with number 264.
Length: 25 pages
Date of creation: 2012
Date of revision: 2013
stochastic mortality; age effect; cohort effect; differential evolution algorithm; mortality forecasting.;
Other versions of this item:
- Jevtić, Petar & Luciano, Elisa & Vigna, Elena, 2013. "Mortality surface by means of continuous time cohort models," Insurance: Mathematics and Economics, Elsevier, vol. 53(1), pages 122-133.
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-09-22 (All new papers)
- NEP-DEM-2012-09-22 (Demographic Economics)
- NEP-FOR-2012-09-22 (Forecasting)
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