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Katja Hanewald - Lee-Carter and the Macroeconomy H U M B O L D T – U N I V E R S I T Ä T Z U B E R L I N - 1 - Mortality Modeling: Lee-Carter and the Macroeconomy Katja Hanewald Humboldt-Universität zu Berlin Collaborative Research Center 649: Economic Risk
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Katja Hanewald - Lee-Carter and the Macroeconomy H U M B O L D T – U N I V E R S I T Ä T Z U B E R L I N - 2 - Summary Mortality reacts to macroeconomic changes Effect is introduced into the Lee-Carter framework Important result for the regulation and risk management of life insurance companies
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Katja Hanewald - Lee-Carter and the Macroeconomy H U M B O L D T – U N I V E R S I T Ä T Z U B E R L I N - 3 - Outline Literature Review Data Analysis Correlation Analysis Regression Analysis Conclusion
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Katja Hanewald - Lee-Carter and the Macroeconomy H U M B O L D T – U N I V E R S I T Ä T Z U B E R L I N - 4 - Literature Review Combine two domains of the demographic literature (1)Stochastic Mortality Modeling Lee-Carter (1992): “The earliest model and still the most popular” Universal method, has been applied to various countries Standard variant: Lee-Miller (2001) Two stages: ln(m x,t ) = a x + b x ∙ k t + x,t k t usually modeled as random walk with drift
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Katja Hanewald - Lee-Carter and the Macroeconomy H U M B O L D T – U N I V E R S I T Ä T Z U B E R L I N - 5 - Literature Review Mortality index k t : Key driver of mortality dynamics in the LC model “Index of the level of mortality” (Lee and Carter, 1992) “Dominant temporal pattern in the decline of mortality” (Tuljapurkar et al., 2000) “Random period effect” (Cairns et al., 2008) k t – Just an unobserved latent variable?
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Katja Hanewald - Lee-Carter and the Macroeconomy H U M B O L D T – U N I V E R S I T Ä T Z U B E R L I N - 6 - Literature Review (2)Mortality and Macroeconomic Fluctuations Ruhm (2000): Mortality rates in the USA fluctuate procyclically over the period 1972–1991 Similar patterns observed for: -USA, Spain, and Japan (Tapia Granados, 2005a/b, 2008) -Germany (Neumayer, 2004, Hanewald, 2008) -Sweden (Tapia Granados and Ionides, 2008) -23 OECD countries, 1960–1997 (Gerdtham and Ruhm, 2006) Procyclical deaths: motor vehicle crashes, CVD, liver ailments, influenza/pneumonia Acyclical/countercyclical: cancer, suicide, diabetes mellitus
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Katja Hanewald - Lee-Carter and the Macroeconomy H U M B O L D T – U N I V E R S I T Ä T Z U B E R L I N - 7 - Central Idea Popular mortality forecasting framework: Lee-Carter model Introduce the link between mortality and the macroeconomy into the LC model via the mortality index k t Direct translation into age-specific death rates Reaction of age-specific mortality rates to economic fluctuations
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Katja Hanewald - Lee-Carter and the Macroeconomy H U M B O L D T – U N I V E R S I T Ä T Z U B E R L I N - 8 - Data Annual data for six OECD countries,1950-2005 Australia, Canada, France, Japan, Spain, USA Lee-Carter mortality index k t Lee-Miller (2001) variant Treat males and females separately Age range: 30-85 (0-99) Real GDP growth rates Unemployment rate changes
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Katja Hanewald - Lee-Carter and the Macroeconomy H U M B O L D T – U N I V E R S I T Ä T Z U B E R L I N - 9 - Correlation Analysis Correlations between Macroeconomic fluctuations ( Economic Indicator t ) Changes in the mortality index ( k t ) Different time horizons Entire sample period (1951-2005) Subperiods
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Katja Hanewald - Lee-Carter and the Macroeconomy H U M B O L D T – U N I V E R S I T Ä T Z U B E R L I N - 10 - Correlation Analysis Entire sample period (1951-2005): Significant procyclical correlations in Aus, Can, Jap, USA Corr. range between 27% (females, Aus) and 38% (males, Can) Cross-correlations: no lag Interpretation: Reductions in mortality tend to be smaller when the economy strengthens Findings agree with results of Ruhm (2000) and others for age- specific mortality rates
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Katja Hanewald - Lee-Carter and the Macroeconomy H U M B O L D T – U N I V E R S I T Ä T Z U B E R L I N - 11 - Correlation Analysis Correlations between k t and real GDP growth rates: Measure AustraliaCanadaFrance Japan SpainUSA 1951–2005 Males0.326*0.384**0.109–0.0760.0000.285* Females0.269*0.0610.0000.0510.0360.286* 1951–1970 Males0.3260.520*0.229–0.0280.0130.400 † Females0.2950.409 + 0.1660.0950.0040.406 † 1971–1990 Males0.2350.369–0.1760.0170.0730.367 Females0.217–0.150–0.1750.0360.1020.321 1991–2005 Males–0.081–0.217–0.271–0.357–0.161–0.400 Females–0.0920.046–0.171–0.2220.031–0.113
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Katja Hanewald - Lee-Carter and the Macroeconomy H U M B O L D T – U N I V E R S I T Ä T Z U B E R L I N - 12 - Correlation Analysis Three subperiods Structural change observed in all six countries Relation reverses in most cases Results for unemployment rates support findings Study moving correlations: Correlations over 20-year subperiods Moving starting points
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Katja Hanewald - Lee-Carter and the Macroeconomy H U M B O L D T – U N I V E R S I T Ä T Z U B E R L I N - 13 - Correlation Analysis Moving correlations between k t and real GDP growth rates
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Katja Hanewald - Lee-Carter and the Macroeconomy H U M B O L D T – U N I V E R S I T Ä T Z U B E R L I N - 14 - Discussion Age-specific death rates of U.S. males 1951–1970 vs. 1991–2005: Correlations for 40 of 56 age groups reverse from positive to negative Tapia Granados (2008): similar tendency for age-specific mortality rates in Japan Explanation: Changes in the causes of death
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Katja Hanewald - Lee-Carter and the Macroeconomy H U M B O L D T – U N I V E R S I T Ä T Z U B E R L I N - 15 - Discussion Changes in the causes of death Early 1970s: Dramatic decline in CVD mortality 1990s: Reduced mortality from tobacco and alcohol consumption, motor vehicle crashes, influenza/pneumonia Ongoing: Substantial increase in deaths attributable to poor diet and lack of physical activity
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Katja Hanewald - Lee-Carter and the Macroeconomy H U M B O L D T – U N I V E R S I T Ä T Z U B E R L I N - 16 - Regression Analysis Standard RW model k t = + t, with t ~ N(0, ) iid Extended RW model: k t = + ∙ Economic Indicator t + t, with t ~ N(0, ) iid Separate models for males/females for all countries Example: Mortality index of Canadian males k t = –1.359*** + 15.173** ∙ ln(real GDP t ) + t (0.218) (5.004)
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Katja Hanewald - Lee-Carter and the Macroeconomy H U M B O L D T – U N I V E R S I T Ä T Z U B E R L I N - 17 - Regression Analysis Check all models’ error properties Test for parameter stability (Quandt-Andrews Test) Generalization of Chow’s break-point test Treats the date of a potential structural break as unknown Significant break years identified for males at the beginning of the 1970s (Aus: 1971, Jap & USA: 1973, Can: 1976) Further candidate years
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Katja Hanewald - Lee-Carter and the Macroeconomy H U M B O L D T – U N I V E R S I T Ä T Z U B E R L I N - 18 - Regression Analysis Stability of the coefficient on real GDP growth: Chow test sequence
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Katja Hanewald - Lee-Carter and the Macroeconomy H U M B O L D T – U N I V E R S I T Ä T Z U B E R L I N - 19 - Regression Analysis Model the structural change using dummy variables Example: Canadian males (1951-2005, adj. R² = 0.416)
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Katja Hanewald - Lee-Carter and the Macroeconomy H U M B O L D T – U N I V E R S I T Ä T Z U B E R L I N - 20 - Conclusion LC mortality index k t correlates significantly with macroeconomic fluctuations Common understanding of k t Link between economic conditions and aggregate mortality is subject to a structural change Established relationship Important implications for life insurers: Hanewald, Post, and Gründl (2009, SSRN
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