Modelling and forecasting mortality in Spain

Experience shows that static life tables overestimate death probabilities. As a consequence of this overestimation the premiums for annuities, pensions and life insurance are not what they actually should be, with negative effects for insurance companies or policy-holders. The reason for this overestimation is that static life tables, through being computed for a specific period of time, cannot take into account the decreasing mortality trend over time. Dynamic life tables overcome this problem by incorporating the influence of the calendar when graduating mortality. Recent papers on the topic look for the development of new methods to deal with this dynamism. Most methods used in dynamic tables are parametric, apply traditional mortality laws and then analyse the evolution of estimated parameters with time series techniques. Our contribution consists in extending and applying Lee-Carter methods to Spanish mortality data, exploring residuals and future trends.

[1]  Steven Haberman,et al.  An investigation into parametric models for mortality projections, with applications to immediate annuitants' and life office pensioners' data , 2000 .

[2]  J. H. Pollard,et al.  The age pattern of mortality , 1979 .

[3]  Michel Denuit,et al.  A Poisson log-bilinear regression approach to the construction of projected lifetables , 2002 .

[4]  Steven Haberman,et al.  Lee-Carter mortality forecasting incorporating bivariate time series , 2003 .

[5]  E. Tabeau,et al.  A Review of Demographic Forecasting Models for Mortality , 2001 .

[6]  Examining Structural Shifts in Mortality Using the Lee-Carter Method , 2001 .

[7]  Montserrat Guillén,et al.  Recent Mortality Trends in the Spanish Population , 2002 .

[8]  Lawrence R. Carter,et al.  Modeling and Forecasting U.S. Mortality: Rejoinder , 1992 .

[9]  Montserrat Guillén,et al.  Forecasting Spanish Natural Life Expectancy , 2005, Risk analysis : an official publication of the Society for Risk Analysis.

[10]  J. Maindonald,et al.  Applying Lee-Carter under conditions of variable mortality decline , 2002, Population studies.

[11]  Ermanno Pitacco,et al.  Survival models in a dynamic context: a survey , 2004 .

[12]  M. Termote,et al.  The Analysis of Mortality , 1978 .

[13]  Ingrid Van Keilegom,et al.  Bootstrapping the Poisson log-bilinear model for mortality forecasting , 2005 .

[14]  Pollard Jh,et al.  The analysis of mortality and other actuarial statistics. 3rd ed. , 1972 .

[15]  Renwick C. J. Dobson,et al.  Modelling and forecasting , 1999 .

[16]  Katja Hanewald Mortality modeling: Lee-Carter and the macroeconomy , 2009 .

[17]  Ronald Lee,et al.  Modelación y proyección de la mortalidad en Chile , 1994 .

[18]  P. Diggle Time Series: A Biostatistical Introduction , 1990 .

[19]  P. Cox,et al.  The Analysis of Mortality and Other Actuarial Statistics , 1971 .

[20]  A. Prskawetz,et al.  Examining structural shifts in mortality using the Lee-Carter method , 2001 .

[21]  Ronald Lee The Lee-Carter Method for Forecasting Mortality, with Various Extensions and Applications , 2000 .

[22]  Arnold F. Shapiro,et al.  Evaluating and extending the Lee–Carter model for mortality forecasting: Bootstrap confidence interval , 2006 .

[23]  Steven Haberman,et al.  Lee–Carter mortality forecasting with age-specific enhancement , 2003 .

[24]  V. Kannisto Health and Mortality Among Elderly Populations , 1998 .

[25]  Heather Booth,et al.  The future aged: new projections of Australia. ‘s elderly population , 2003 .

[26]  Steven Haberman,et al.  Lee-Carter mortality forecasting: a parallel generalized linear modelling approach for England and Wales mortality projections , 2003 .