projecting ntas tim miller center for the economics and demography of aging, uc berkeley...
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Projecting NTAs
Tim MillerCenter for the Economics and
Demography of Aging, UC Berkeley [email protected]
Third NTA WorkshopHonolulu, HawaiiJanuary 20, 2006
Thanks to the United Nations CELADE for support in developing these models.
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Plans for next year (next 3 years?)
Deepen accounting:Details on consumption (capital/current), reallocations (capital/credit/land), and transfers (education, health, other).Develop Wealth Accounts.
Project accounts:2007 to 2100?
Widen accounts: Education and Gender
Extend accounts:Back to 1776?
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Three Models
1. UN Probabilistic Population Forecast
2. Forecasting Educational Distribution
3. Forecasting Public Sector Transfers
x
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UN Probabilistic Forecast:The 4 Steps of the Method
1. Select path of TFR, e0, and NMR by repeated random draws from a set of similar countries.
2. Forecast population based on standard cohort-component method.
3. Repeat steps 1 and 2; typically 1,000 or 10,000 times.
4. Calculate predictive distributions for variables of interest (population size, OADR, e0, etc).
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UN Probabilistic Forecast
• Advantages of Probabilistic Forecast
– Does not use expert opinion.
– Quantifies our uncertainty about the future.
– More “realistic” projections (since allow for variability).
• Advantages of Scenario Forecast
– Uses expert opinion.– What-if scenarios.– Truly unique forecasts
without historical precedent.
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UN Probabilistic Forecast
• Tells us what the future would look like based on the collective past experience of 192 UN member countries from 1950 to 2005.
• UN Probabilistic Forecasts assume: countries with similar demographic parameters are being exposed to the same set of unknown social forces which will shape their future demographic trajectories.
• Alternative Scenario Forecasts: Why this country is unique among UN member states?
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UN Scenario Forecasts Are Pessimistic about Future Longevity
20 30 40 50 60 70 80 90
0.0
0.5
1.0
1.5
2.0
2.5
Gain in life expectancy during 5 year period as function of current life expectancy
Life expectancy
Ga
in in
life
exp
ect
an
cy
Based on UN World Population Prospects, the 2004 revision.
ObservedForecast
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UN Scenario Forecasts Too Certain About Future Migration
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UN Probabilistic Forecast for Chile
1950 2000 2050 2100
5
10
15
20
25
30
35
40
Population of Chile , 1950 to 2100
Year
Mill
ions
with historical estimates, UN scenario forecasts, and UN probabilistic forecasts.
10th
50th
90th
Historical Record UN Probabilistic Forecasts (deciles)
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1950 2000 2050 2100
0.8
0.9
1.0
1.1
1.2
Year
Pro
duce
rs p
er c
onsu
mer
10th
50th
90th
Economic Support Ratio, Chile
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UN Probabilistic Forecast for the United States
1950 2000 2050 2100
200
400
600
800
Population of United States of America , 1950 to 2100
Year
Mill
ions
with historical estimates, UN scenario forecasts, and UN probabilistic forecasts.
10th
50th
90th
Historical Record UN Probabilistic Forecasts (deciles)
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1950 2000 2050 2100
0.8
0.9
1.0
1.1
1.2
Year
Pro
duce
rs p
er c
onsu
mer
10th
50th
90th
Economic Support Ratio, U.S.
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Forecasting Educational Distributions
• The history and future of educational distributions are interesting in their own right as measures of social progress.
• In addition, these serve as important components of economic growth models and perhaps NTA accounts.
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Educational Model
• Uses data from a single census to provide historical record as well as basis for forecasting the future.
• Easily replicated! Can measure the changing educational distribution of populations throughout the world over a considerable period of time.
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3 Box Model
Primary PopulationBy Age and Sex
Secondary PopulationBy Age and Sex
Tertiary PopulationBy Age and Sex
Alpha
Beta
Births Deaths
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20 40 60 80 100
0
20
40
60
80
100
Age
Per
cent
WomenMen
Secondary educationNone or primary education
Tertiary education
Educational Distribution From Chilean Census 2002
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Progression to Secondary Level
1920 1940 1960 1980 2000
30
40
50
60
70
80
90
100
Approximate year of birth
Per
cent
WomenMenContinued Progress Scenario.No Progress Scenario.
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Progression to Tertiary Level
1920 1940 1960 1980 2000
0
10
20
30
40
50
60
70
Approximate year of birth
Per
cent
WomenMenContinued Progress Scenario.No Progress Scenario.
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Rapid Change in Educational Distribution of Elderly
2000 2020 2040 2060 2080 2100
0
10
20
30
40
50
60
70
Year
Per
cent
Primary
Secondary
Tertiary
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Rapid Change in Educational Distribution of Work Force
2000 2020 2040 2060 2080 2100
0
10
20
30
40
50
60
70
Year
Per
cent
Primary
Secondary
Tertiary
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Forecasting Public Sector Transfers
• Basic Accounting Method for Aggregate Expenditures:
B(t) = sum { b(x,e,t) * p(x,e,t) }
where b(x,e,t) = per-capita expenditures by age x, education or other characteristic e, and time t.
and p(x,e,t) = population by age, education, and time.
?
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Simplifying Assumptions
Only Age and Time Matter:
B(t) = sum { b(x,e,t) * p(x,e,t) }
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Simplifying Assumptions
No change in policy nor behavior.
Simple period effects on budget factors:
B(t) = sum { b(x,2005)* exp(r*(t-2005))
* p(x,e,t) }
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Expenditures and Taxes by Age, Chile
0 20 40 60 80
500
1000
1500
2000
Government Expenditures and Taxes by Age: Chile 2004
Age
000s
pes
os
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Expenditures Projected to Grow More Rapidly Than Taxes
Due to Population Aging
2010 2020 2030 2040 2050
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
Government expenditures and taxes: Chile 2004-2050
Year
Rel
ativ
e to
200
4
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Taxes increase by 30% over the next 45 years due to population aging.
2010 2020 2030 2040 2050
1.00
1.05
1.10
1.15
1.20
1.25
1.30
Fiscal Tax Ratio: Chile 2004-2050
Year
Rel
ativ
e to
200
4
The Projected Fiscal Tax Ratio in Chile: 2004 to 2050
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In Chile, transition to a new joint public-private system offsets projected tax increase.
2010 2020 2030 2040 2050
0.0
0.5
1.0
1.5
2.0
2.5
3.0
Year
Tril
lions
of P
esos
Pensions - Phaseout of old systemINP BudgetPA/PM Budget
Pensions
New System
Old System
Pension projection due to population aging and policy changes.
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Projecting Public Transfers
• Requires expert country-specific knowledge. Like those of NTA teams!
• As we develop NTAs, we will learn more about public transfers and public/private composition of spending (education, health, etc). How this varies among countries and over time.
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Future Work
• Probabilistic Population Forecasts for NTA countries.
• History and forecasts of educational distributions for NTA countries. Implications of “educational dividend.”
• Revision of a generalized public transfer model:– Assumption of fixed age shape is often wrong. Model
should allow for cohort-effects. – Major use of the model: exploring effect of policy
changes.– As we develop NTAs, we will learn more about how
budget factors differ between countries and over time.