This document presents a methodology for modeling mortality rates across Canadian provinces. It reviews literature on single and multi-population mortality models. Mortality indices from 1921-2009 for 9 provinces are analyzed using unit root tests and the Johansen cointegration test, which finds common trends among the indices. Vector error correction (VECM) and vector autoregressive (VAR) models are estimated and show better fit for female mortality. The models are used to project and forecast mortality indices 50 years into the future and to price annuities for cohorts from 1960-2000, with VECM producing more accurate pricing. In conclusion, mortality trends are declining across provinces with common factors, and VECM performs better than VAR or ARIMA models
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1. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
A multivariate approach to project the long run
relationship of mortality indices for Canadian
provinces
A. Ntamjokouen S.Haberman G. Consigli
Vietri sul Mare, 24th
Aprile 2014
2. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
Agenda
Literature review on multi and single population;
Analysis of Lee Carter parameters ;
Order of integration for each of the 9 mortality indices
using the ADF, PP, KPSS tests;
Optimal value of lag of VAR;
the Johansen cointegration test Analysis;
The estimation of VECM and the VAR models and the
forecasting of derived model.
Pricing of annuities by cohorts for both males and females
3. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
Motivations
One population model? Literature focuses on the modeling of 1
population mortality rates
Lee Carter Model(1992);
Lee Miller(2001);
Booth Maindonal Smith Variant(2002);
Hyndman and Ullah(2005);
De Jong and Tickle(2006);
Renshaw Haberman(2006) with cohort effect;
Currie(2004) with P-Splines, and Currie(2006) with Age
period Cohort;
Cairns-Blake-Dowd(2009).
4. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
Literature
Modeling mortality rates to improve the Lee Carter model
Lazar and Denuit(2009): common trends between 5 age
groups mortality;
Darkiewicz(2004): Lee Carter validity as a cointegration
approach;
Njenga and sherris(2009): cointegration among Heligman
Pollard;
DAmato(2013): Multipopulation longevity risk among
countries;
Mortality indices
Salhi(2010) and Zhou et al(2012) on the basis risk.
Sharon S. Yang et al. (2009) pricing of longevity bonds
derivatives among 4 countries;
5. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
Motivations
Why multiprovinces longevity risk?
Pricing of life insurance annuities accross countries or
regions within a country;
Engineering of longevity bonds derivatives;
Hedging variations of life expectancy pattern.
6. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
Data
We colllect data from Canadian Human Mortality Database
from 9 provinces: Prince Edward Island(PEI), Nova
Scotia(NS), News Brunswick(NB), Quebec(Q), Ontario(Q),
Manitoba(M), Saskatchewan(S), Alberta(A), British
Columbia(BC) from 1921 to 2009;
It is managed by the Department of Demography of the
Universit辿 de Montreal in collaboration with the Max Plank
Institute for Demographic Research and the Department of
demography of the University of California at
Berkeley(CHMD).
7. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
Data
We retrieve the mortality indices produced by the Lee
Carter model for the 9 mortality provinces;
The determination of order of integration for each of the 9
mortality indices using the Augmented Dickey Fuller,
Philips-Perron as well as KPSS Test;
The computation of the optimal value of lag of the vector of
autoregressive model;
the Johansen cointegration test which test the
cointegration rank and specify which variable will enter in
the cointegrated equations and in the Vector of Error
correction model;
The estimation of VECM and the VAR models and the
forecasting of derived model.
8. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
Lee Carter Model for each of 9 provinces
We retrieved the singular mortality indice from the 9 provinces
through Lee Carter model.
The Lee carter Model is described as followed:
ln(m1(t, 1)) = a1,x + b1k1,t + e1,t (1)
where:
ax describes the shape of age pro鍖le of mortality;
bx coef鍖cient describes the variation of death rates to variation in the
level of mortality;
kt is the mortality index;
ex,t is the error term with ex,t N(0, 2
u) is white noise which is the
age feature mortality not captured by the model.
9. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
Males Mortality indices for each province in Canada
10. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
Females Mortality indices for each province in Canada
11. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
VAR and VECM models
Since the two graphs show up common trends a priori, the test
of integration(after ADF, PP and KPSS tests of integration
con鍖rm) is 1 for all the 9 provinces analyzed in this framework.
Sex AIC HQ SC FPE
Males 6 1 1 1
Females 6 1 1 1
Table 1: The diagnostics tests of residuals under VAR model
12. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
VAR and VECM models
The VAR model is derived as described below: The vector of
autoregression for p lags is written in Lutkepohl(2005) as:
kt = A0 + A1kt1 + A2kt2 + ......Apktp + et (2)
where kt = (k1t, k2t, ....., kKt) for k = 1, ....., K time series,
(A0.....Ai) are the coef鍖cients and et is white noise.
According to Pfaff(2008), the VAR (p) can be converted into VECM as
follows:
kt = 1kt1 + 2kt2 + ... + p1ktp+1 + A0 + et (3)
where i = (I A1 ..... Ai), i = 1, ..., (p 1)
= (I Ai, ... Ap) is a N-dimensional time series, A0 is
the intercept term, et is white noise.
13. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
VAR and VECM models
If r = K the number, the number of cointegrated variables r
which are stationary equals the rank(K) of then the model will
be estimated by using the standard statistical model.
If r = 0 this means that there is no cointegrated relationships
relationships between the variables. The variables are
stationary if we take the take the differences of variables above.
If 0 < r < K there exists 2 matrices 留 and 硫 such that = 留硫
There will be r cointegrating relationship or n r common
trends. Variables into the VECM are all stationary.
14. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
Diagnostics of residuals for Males in Alberta
15. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
Evidence of the cointegrated equations for Canadian
provincial Mortality level with critical values at 5%,
10% and 1%
r test value 5% 10% 1%
r <= 8 3.34 9.24 7.52 12.97
r <= 7 11.38 19.96 17.85 24.6
r <= 6 25.50 34.91 32 41.07
r <= 5 46.40 53.12 49.65 60.16
r <= 4 84.23 76.07 71.86 84.45
r <= 3 127.73 102.14 97.18 111.01
r <= 2 175.99 131.7 126.58 143.09
r <= 1 229.25 165.58 159.48 117.2
r = 0 300.68 202.92 196.37 215.74
Table 2: Evidence of the cointegrated equations for Canadian
provincial Mortality level with critical values at 5%, 10% and 1%
16. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
Summary of the cointegration Johansen Test
We run the cointegrated equation with various tests Trace and
Eigen for both females and males. - Analysis reveal common
trends with Trace and Eigen Values tests
Sex group cointegrated equation common factors
Indices Trace | Eigen Trace | Eigen
Females 5 | 5 4| 4
Males 3 | 4 6|5
Table 3: Summary of the cointegration Johansen Test
17. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
Backtesting of the two models VAR and VECM
Out-of-samples VAR(M) VAR(F) VECM(M) VECM(F)
Portmanteau test 0.81 0.68 0.97 0.75
JB Multivariate 0.18 0.31 0.04 0.16
Skewness 0.88 0.17 0.17 0.062
Kurtosis 0.02 0.56 0.0507 0.59
Table 4: Diagnostics of residuals for VAR and VECM models in both
genders cases
18. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
Backtesting of the two models VAR and VECM
Sex group Females Males
Out-of-samples VAR | VECM VAR | VECM
h=2005-2009 5.63% | 5.13% 6.85%| 5.73%
h=2002-2009 6.66% | 6.52% 9.47%|10.96%
h=2000-2009 12.89%|7.43% 8.42%|22.91%
h=1995-2009 16.38%|9.79% 10.66%|2.45%
h=1990-2009 19.36%|15.14% 29.67%|24.51%
h=1984-2009 21.77%|16.80% 39.80%|30.01%
Table 5: The average MAPE for models VAR and VECM for the 9
provinces
19. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
We observe from table 1 that VECM is more precise than
the VAR model for females. The backtesting of the two
models for females presents good performance accuracy
overall. The cointegrated models work better for this sex
group;
It is uncertain for 3 periods as to males for lengths period
including 2005-2009, 2002-2009, 2000-2009 which model
is better;
Furthermore beyond the 10 years time horizons, errors are
too large. Almost 30% are unexplained for males. This is
due to the fact that models VAR and VECM do not cope
volatility of future mortality indices.
20. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
Volatility of the two models VAR and VECM
Out-of-samples Sex Historic VAR VECM
h=1995-2009 Males 166.31 37.23 48.10
Females 98.16 91.19 78.51
h=1990-2009 Males 172.9 52.17 59.75
Females 107.77 114.88 107.72
h=1984-2009 Males 213.93 67.46 69.44
Females 124.45 139.94 136.18
Table 6: Comparison of volatility of historical mortality with
out-of-sample forecasts produced by models VAR and VECM with in
sample
21. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
Projecting Males mortality indices for all other
provinces with VAR models
22. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
Projecting Females mortality indices for all other
provinces with VAR models
23. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
Forecasting Canadian Males Mortality indices from the
Vector of Error Correction model
24. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
Forecasting Canadian females Mortality indices from
the Vector of Error Correction model
25. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
Hypothesis on the pricing methodology
The retirement age will be set to 65 age old regardless the
cohort;
Payments are made monthly and will be equal to 12;
The actuarial present value of a yearly annuity of 1;
The interest rate for the evaluation is 4% and the in鍖ation
rate is about 2%.
26. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
Pricing annuities of females cohorts 1960,
1970,1980,1990 and 2000
Females (ARIMA) VAR VECM
Cohorts life time | APV life time | APV life time | APV
1960 80.89 | 7.74 81.13| 7.80 82.32| 8.52
1970 82.59 | 8.05 82.91| 8.12 84.59| 9.03
1980 84.13 | 8.33 84.39| 8.42 86.62| 9.49
1990 85.25 | 8.60 85.55| 8.70 88.05| 9.89
2000 86.18| 8.85 86.38| 8.96 89.19| 10.22
Table 7: Pricing annuities of females cohorts 1960, 1970,1980,1990
and 2000
27. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
Pricing annuities of Males cohorts 1960,
1970,1980,1990 and 2000
Females ARIMA VAR VECM
Cohorts Life time | APV Life time | APV Life time | APV
1960 75.64 | 6.56 76.68 | 7.20 77.02| 7.42
1970 77.87 |7.02 79.45| 7.97 79.79| 8.15
1980 80.49| 7.44 82.87| 8.7 83.36| 8.81
1990 82.82 | 7.82 85.91| 9.34 86.22| 9.38
2000 84.51 | 8.16 88.1| 9.89 88.30| 9.87
Table 8: Pricing annuities of males cohorts 1960, 1970,1980,1990
and 2000
28. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
Conclusion
Mortality indices from each province in Canada show
decrements and continuing declining with common trends;
The two models show better 鍖t for females gender but
uncertainty in the case of males particularly beyond 10
years period. Volatility is taken into account only partially;
We project mortality indices in 50 yearsperiod for both two
genders and for the two models. VAR projections have
narrow shape like in D Amato(2013) and VECM like in
Zhou(2013) and Njenga(2011);
We performed the pricing of annuities by group of cohorts
1960, 1970, 1980, 1990, 2000 and VECM presents better
performance in terms of pricing as well as life expectancy
over ARIMA and VAR models.
29. Agenda Review of Literature Database Methodology procedure Lee Carter Model theory Lee Carter Model theory Lee
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