Transcript Demographic Implications for Asset Values Webcast Moderator

Demographic Implications for
Asset Values Webcast
MODERATOR:
DOUGLAS W. ANDREWS FSA, FCIA, FIA
PRESENTERS:
STEPHEN P. BONNAR, FSA, FCIA
KATHLEEN RYBCZYNSKI
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Overview of Research
Stages
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Today we will review
• Background on research leading to current project
• Economic Demographic Modeling structure and
results
• Considerations for Asset Modeling
•Q&A
Stage 1 – first SOA funded project
• Will the retirement of the baby boomers cause an asset
meltdown?
• Literature review by researchers at uW and Kent
• 4 severe, 33 modest, 14 no impact, 10 little relevance
• Analysis of 2 papers supporting “asset meltdown”
• Abel “The Effects of a Baby Boom on Stock Prices and Capital
Accumulation in the Presence of Social Security”
• Liu & Spiegel “Boomer Retirement: Headwinds for U.S. Equity
Markets?”
Stage 2 – second SOA funded project
• Investigating the link between population aging and deflation
• Changes in the relative share of different age groups in the
population may present inflationary, disinflationary or even
deflationary tendencies
• VAR model used to analyze data from 21 countries from 1990 – 2010
and to provide robustness check on results
• Extension of analysis of 2 papers shows that “older old” is deflationary
• Juselius & Takats “Can Demography Affect Inflation and Monetary Policy?”
• Yoon, Kim, & Lee “Impact of Demographic Changes on Inflation and the
Macroeconomy”
Cumulative inflation (1955 – 2010)
vs. Average share of population
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Age cohort impacts on inflation:
OECD sub-periods
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0.5
Coefficient
0
-0.5
-1
-1.5
80+
75-79
70-74
65-69
60-64
55-59
50-54
1955-1979
45-49
40-44
35-39
30-34
25-29
20-24
15-19
10-14
5-9
0-4
1955-2010 (80+)
1980-2010
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Age cohort impacts on inflation:
refined age groups
Refined age groups: OECD 1990-2010
1
0
Coefficient
-1
-2
-3
-4
-5
100+
95-99
90-94
85-89
80-84
75-79
70-74
65-69
1990-2010 (80+)
60-64
55-59
50-54
45-49
40-44
35-39
30-34
25-29
20-24
15-19
10-14
5-9
0-4
1955-2010 (80+)
1990-2010 (100+)
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Summary
• Our analysis suggests that it is the sub-period, rather
than the panel sample, that shapes the pattern of the
impact of aging on inflation
• A finer adjustment to age categories is needed to capture
the potentially different effects of the older and younger
of the 65+ age group
• For the old population, the older the age, the more
deflationary the cohort is
• Studies on the old should use a greater number of age
groups, especially because the size and the length of this
age group is increasing due to increasing longevity
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Findings, Cautions and Challenges
• Our results indicate that the age profile of the population can have
both an economically and a statistically significant impact on output
growth, investment, savings, hours worked, interest rates and
inflation
• Demographic structure does affect economic factors such as
inflation
• Measurement and quantification of this impact remain challenging
problems , partly due to data issues (coarse age groupings and short
time periods)
• Empirical studies are in danger of failing to control for other more
salient factors that affect inflation
• There is very little evidence of deflationary episodes in our sample
period, making it difficult to analyze the prospects for deflation as
opposed to disinflation, or inflation falling to low levels
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Stage 3 – current project
• Population Aging, Implications for Asset Values, and
Impact for Pension Plans: An International Study
• Multi-year, multi-disciplinary, international project with
SOA, CIA and IFoA as partners, along with SSHRC and the
Universities of Kent and Waterloo
• Three modeling stages
• Economic Demographic Model
• Asset Model
• Pension Model
Economic Demographic
Modeling
Structure and Results
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Population Structure and Asset Values
We develop a computable Over-Lapping Generations
(OLG) model that
• Has multiple cohorts
• Matches demographic structure
• Incorporates labor supply decisions and constraints
• Includes an aggregate productivity shock
• Generates a realistic portfolio allocation between two assets
• Introduces heterogeneity (female, male) within each cohort
OLG Model
We use the model to study demographic effects on
• asset returns and risk premium
• portfolio allocation
• generational risk sharing
• business cycle moments
Highlighted Results
The model generates
• typical age-specific consumption, labor and asset holdings
• reasonable portfolio allocation
• reasonable business cycle moments of macro variables
• very small risk premium
• significant impact on economy of population aging
OLG Model Framework
• Model includes households, firms, and government
• Time is discrete and goes forever
• Households live for J periods, j ∈ {1, 2, . . . , J } where each period
represents 4 years of living. We let age j=1 represent ages 18-22,
and the last period of life, J=20, represents ages 94-97. Thus, we
model ages 18-97.
• Households have five life stages
• young-working (YW) Ages 18-33 years, j=1-4 (born at age 18)
• middle-working (MW) Ages 34 − 49 years, j=5-8
• mature-working (W) Ages 50 – 65 years, j=9-12
• semi-retired (SR) Ages 66-81 years, j=13-16
• retired (R) Ages 82-97, j=17-20
OLG Model Framework
• A new generation is born into economy each time period, t
• Exogenous growth rate of each generation is n
• At each age j, household i has a fixed marginal probability φij of
progressing to the next period (aging 1 period), and so
probability of death is 1-φij
• The oldest generation, j = J , dies deterministically in the
subsequent period, that is φiJ = 0 (dies with probability=1)
• We are also working on intra-cohort heterogeneity, e.g.
modeling differences across gender in labor and asset holding
Demographics – five major segments
Period:
Life Stage:
Generation g
t
t+4
YW
t+8
MW
t+12
W
t+16
SR
R
Demographics
Period:
t
t+4
t+8
t+12
t+16
Generation g-16
Generation g-12
Generation g-8
Generation g-4
Generation g
Generation g+4
Generation g+8
Generation g+12
Generation g+16
Such that, during each life stage, each generation will overlap with several generations that precede
it, and several generations that will follow it.
Demographics – a 16 year segment
Period:
t
t+4
All five life stages
(several generations)
are represented at any
16 year segment.
t+8
t+12
t+16
Household Time & Labor Constraints
• At each age j, households have Hj units of time to allocate
between labor and leisure
• In working ages, a household decides how much labor to supply
to firms and earns wage income based on its labor efficiency
• In YW and MW a household must spend FCj units of time on
child rearing and FEj units of time on education
• So household time constraints are represented by:
Household Time & Labor Constraints
• For the retired and semi-retired life stages, households
have H units to allocate, that is Hj=H, however:
• A semi-retired household receives some pension income
and can only supply labor to a maximum of ‫ﺂ‬pH (wherein
they would enjoy the remaining (1 - ‫ﺂ‬p)H units as leisure)
• Retirees are constrained to supply 0 labor and enjoy all
available time as leisure with full pension income
Household Utility
Households value both consumption and leisure:
Assets
Production
Taxes and Bequests
Recursive competitive equilibrium
Timeline
Beginning of period t, household i, of age j, holds a portfolio characterized by
theta and eta. The productivity shock is realized, such that productivity is given
by zt and the total amount of capital is given by Kt.
During the period, the firm produces and household supplies labor and earns an
income commensurate with its efficient hours and the market wage. Total
household resources include gross return on asset holdings, wage, and pension
income, less taxes.
Then, the household decides how to allocate these resources on consumption
and asset holdings. Any deaths occur at the end of the period.
Age profile of consumption
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Age profile of labor supply
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Age profile of total asset holding
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Risky vs non-risky assets: age profile
Risky vs non-risky assets: age profile
Reported
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Alternative Demographic Structures
• We construct counterfactuals to consider what
happens if the population structure is altered,
and find that asset prices are lower with an older
population
• A 4% increase in the survival probability for
households over age 65 results in:
• 20.8% drop in the return on capital,
• 20.9% drop in the return on bonds,
• Equity premium changes by less than 1%
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Conclusion
• We develop and compute a complex OLG model with
multiple cohorts, endogenous labor, aggregate
uncertainty and two assets
• The model can be used to study demographic and
pension policy’s effect on the economy, in particular
on asset returns
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Future
• Build on base model to enrich our contribution with
further demographic & policy implications, e.g.:
• Expand pension system (currently just a pay-go & private
savings) to include a partially funded employment based
pension (matching a 3 pillar system: private saving, partially
funded employment based, pay-go public retirement)
• Find a reasonable way to generate a larger risk premium
• Consider intra-cohort heterogeneity (investigating the
impact of gender differences)
• Study the transition path of the real economy under a
demographic change using extended function path analysis
Asset Modelling
– Status Update
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First Task – Literature Review
• Examined over 100 academic papers
• Selection criteria
• Papers written in 2000 or later that link demographic factors
to asset prices
• Seminal papers regardless of publication date or link to
demography
• Infrastructure papers written in 2000 or later
Literature Review – Seminal Papers
• Two seminal papers identified
• Fama & French (1993)
• Identify common risk factors in returns on stocks and bonds
•
•
•
•
•
Size
Book to Market ratio
Term premium
Default premium
Market return controlling for the preceding factors
Literature Review – Seminal Papers
• Mankiw & Weil (1989)
• Conclude that the number of births leads to large and
predictable changes in demand for housing
• This change in housing demand affects house prices
significantly
Demographic Effect on Stocks/Bonds
• Davis & Li (2003)
• Stock returns significantly affected by population structure
• Share of population age 20 – 39 up 1 percentage point, stock
returns up 2% - 3%
• Share of population age 40 – 64 up 1 percentage point, stock
returns up roughly 3%
• Bond yields also affected by population structure
• Share age 20 – 39 up 1 percentage point, real yields up by 15 to 25
basis points
• Share age 40 – 64 up 1 percentage point, real yields down by 45 to
50 basis points
Demographic Effect on Housing
• Several papers document relationship between the
Old Age Dependency (OAD) ratio and house prices
• Many time periods
• Many countries/regions
• For a 1 percentage point increase in OAD, house prices
reduce by 70 to 130 basis points
Demographic Effect on Infrastructure
• No literature connecting demographic variables to
infrastructure returns
• Little literature on infrastructure at all
• 7 papers since 2000
• Academic work is very preliminary
•
Two Approaches to Modeling
Current Thinking — Housing
• Structural model like Nishimura & Takats (2012)
U = ln(cyt) + ln(ht) + ln(Mt / Pt) + β ln(cot+1)
cyt ≤ Y - htqt - Mt / Pt
cot ≤ htqt+1 + Mt / Pt+1
• They assume housing is in fixed supply.
• Our extension plans to have variable housing supply
driven by demographic factors.
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Current Thinking — Equities
• Risk factor approach like Gospodinov, Maynard & Pesavento
(in progress)
dpt+1 = α + β1 dpt + β2 myt+1 + β3 mot+1
• “my” is ratio of population 40 - 49 to population 20 - 29
• “mo” is ratio of population 40 - 49 to population 60 - 69
• Preliminary results promising for US
• Looking to collaborate for Canada and the UK
• Potentially will consider extending to bond yields
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Future Plans
• All work still very preliminary
• Will work concurrently on modeling housing, equity
and bonds
• Will complete write-up of literature review
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Questions
50
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