Post on 08-Jan-2018
description
National Institute of Economic and Social Research
Development and applications of the National Institute General Equilibrium model
of Ageing (NiAGE)
NIESR, London, November 30, 2015Katerina Lisenkova
Financial support from the Economic and Social Research Council under the grant: “A dynamic
multiregional OLG-CGE model for the study of population ageing in the UK” is gratefully acknowledged.
National Institute of Economic and Social Research
Background
Future Research Leaders ESRC grant November 2012 – December 2015
National Institute of Economic and Social Research
Overview
Why study the economic effects of population ageing
NiAGE development
Applications
Projecting healthcare spending
National Institute of Economic and Social Research
Population pyramids. England and Wales
1911 2014 2114*
* 2014-based principal ONS projections
males females
36M
57M 89M
3,000 2,000 1,000 0 1,000 2,000 3,0003,000 2,000 1,000 0 1,000 2,000 3,0000 ‒ 4
10 ‒ 14
20 ‒ 24
30 ‒ 34
40 ‒ 44
50 ‒ 54
60 ‒ 64
70 ‒ 74
80 ‒ 84
90 ‒ 94
100+
3,000 2,000 1,000 0 1,000 2,000 3,000
National Institute of Economic and Social Research
Projection
Old age dependency ratio*
* Population aged 65+ divided by population aged 20-64
197119761981198619911996200120062011201620212026203120362041204620512056206120662071207620812086209120962101210621110%
10%
20%
30%
40%
50%
60%
70%
24%
30%
61%
Source: 2014-based principal ONS projections
National Institute of Economic and Social Research
Economic effects
Labour supply Productivity Demand composition Technological progress Public spending Pensions Immigration
National Institute of Economic and Social Research
Overview
Why study the economic effects of population ageing
NiAGE development
Applications
Projecting healthcare spending
National Institute of Economic and Social Research
NiAGE is a Computable General Equilibrium model with an Overlapping Generations structure (CGE-OLG)
National Institute of Economic and Social Research
Structure of a CGE model
Firms Households
Goods market
External sector
Capital market
Factors market
Public sector
GoodsGoods Goods
Factors
Factors Savings Savings
Savings
Investment
Borrow
ing
Export
Import
Migration
Taxes Taxes
National Institute of Economic and Social Research
Overlapping generations structure
A1 A2 A3 A4 A5
T1 G1
T2 G2 G1
T3 G3 G2 G1
T4 G4 G3 G2 G1
T5 G5 G4 G3 G2 G1
T6 G6 G5
T7 G7 G5
T8 G8 G5
T9 G9 G5
T10 G10 G9 G8 G7 G6
T11 G11 G10
T12 G12 G10
T13 G13 G10
T14 G14 G10
Age
Time
Generation
• Alternative to a “representative agent”
• Several generations• Realistic life cycle (birth,
work, retirement, death)• Age-specific
characteristics/behaviour• productivity (age-earnings
profiles)• labour force participation
rates• demand for public services
National Institute of Economic and Social Research
Why OLG-CGE?
Partial equilibrium analysis demonstrates that other things being equal …– but other things will not stay equal– general equilibrium effects– change in labour supply wages
Macro model with micro foundation– Based on principals of optimisation (utility maximisation for
household, profit maximisation for firms)– Especially important for long-term simulations, as currently
observed relationships become less relevant Rich demographic structure and realistic life cycle
– Important for countries undergoing demographic transition
National Institute of Economic and Social Research
NiAGE
Several versions of the model– Multi-regional model
• three regions: Scotland, the rest of the UK (RUK) and the rest of the World (ROW)
• It can straightforwardly be extended to include Wales and Northern Ireland – Multi-sector model
• three sectors: 1) healthcare, 2) education and 3) the rest of the economy • detailed simulations of the effect of demographic change on provision of
public healthcare and education services– Qualification disaggregation
• three qualification levels• It is useful to study the effects of demographic change on human capital
accumulation and productivity– With migration
• This version has detailed treatment of migration flows and is suitable for simulations of interaction of demographic transition with migration policy
National Institute of Economic and Social Research
Overview
Why study the economic effects of population ageing
NiAGE development
Applications
Projecting healthcare spending
National Institute of Economic and Social Research
Applications
Migration policy – effect of reducing net migration from “hundreds of thousands to tens of thousands”
Scotland’s independence – is population ageing one of the factors favouring staying in the UK
Time-variable rate of time preferences – attempt to calibrate the model to closer fit age consumption profile
Projecting future public healthcare expenditures
National Institute of Economic and Social Research
Overview
Why study the economic effects of population ageing
NiAGE development
Applications
Projecting healthcare spending
National Institute of Economic and Social Research
Healthcare spending in OECD countries, % of GDPTu
rkey
Est
onia
Mex
ico
Pol
and
Kor
ea
Cze
ch R
epub
lic
Chi
le
Hun
gary
Isra
el
Slo
vak
Rep
ublic
Uni
ted
Kin
gdom
Finl
and
Icel
and
Slo
veni
a
Italy
Spa
in
Nor
way
Por
tuga
l
Gre
ece
New
Zea
land
Aus
tria
Bel
gium
Can
ada
Japa
n
Den
mar
k
Fran
ce
Ger
man
y
Sw
eden
Net
herla
nds
Sw
itzer
land
Uni
ted
Sta
tes
0
1
2
3
4
5
6
7
8
9
10
General government Private sector
Source: OECD database
National Institute of Economic and Social Research
Public sector healthcare expenditure in the UK, % of GDP
0
1
2
3
4
5
6
7
8
9
7.4% 2014
Source: OECD database
National Institute of Economic and Social Research
What factors determine future healthcare spending?
1. Size and age structure of the population– Real demand
2. Price of healthcare – Wages are expected to increase due to population
ageing and productivity growth– Healthcare is labour-intensive
• However indexing healthcare cost to wages is not correct– Multi-sector model
3. Growth rate of productivity4. Many other factors (technology, public
policy etc…)
National Institute of Economic and Social Research
How population affects demand for healthcare
Size– Larger population demands more healthcare– In relative terms (e.g. as a share of GDP) depends on age structure
Age – Demand for healthcare services increases with age– Relationship is very stable over time and across countries
Proximity to death– Growing body of literature demonstrates that demand for healthcare
also depends on proximity to death (Zweifel et al, 1999; 2004; Grey, 2005; Seshamani and Gray, 2004; Geue, 2013)
– Requires patient level longitudinal data linked to death data• The Scottish Longitudinal Study• Oxford Record Linkage Study• English Record Linkage Study
National Institute of Economic and Social Research
Population projections
2014 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 2058 2062 2066 2070 2074 2078 2082 2086 2090 2094 2098 2102 2106 2110 21140%
20%
40%
60%
80%
100%
120%
140%
160%
29%24%
151%
48%
0-19
20-64
65+
Total
Source: 2014-based principal ONS projections
National Institute of Economic and Social Research
Adjustment of healthcare spending for longevity improvement
Healthcare expenditures should depend on improvements in longevity– As longevity increases, healthcare expenditure for the same age groups
should get smaller Extrapolate 2007 healthcare spending profile for future
years– one year increase in life expectancy corresponds to one year increase
in healthy life expectancy ONS provides detailed life expectancy with its population
projection up to 2113 Between 2007 and 2113 life expectancy at birth for
males and females combined is projected to increase by almost 15 years
National Institute of Economic and Social Research
Age distribution of healthcare spending
0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85-89 90-94 95-99 100+0%
2%
4%
6%
8%
10%
12%
14%
16%
2007
2057
2107
National Institute of Economic and Social Research
Healthcare spending relationship with age, Finland
0-410
-1420
-2430
-3440
-4450
-5460
-6470
-7480
-8490
-94 100+
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
Age related
Death related
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
Source: ETLA
National Institute of Economic and Social Research
Healthcare spending relationship with age
0-410
-1420
-2430
-3440
-4450
-5460
-6470
-7480
-8490
-94 100+
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
Age relatedDeath related
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
0-410
-1420
-2430
-3440
-4450
-5460
-6470
-7480
-8490
-94 100+
0%
2%
4%
6%
8%
10%
12%
14%
16%
?
Finland
UK
National Institute of Economic and Social Research
Healthcare spending relationship with age
0-410
-1420
-2430
-3440
-4450
-5460
-6470
-7480
-8490
-94 100+
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
Age relatedDeath related
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
0-410
-1420
-2430
-3440
-4450
-5460
-6470
-7480
-8490
-94 100+
0%
2%
4%
6%
8%
10%
12%
14%
16%
0-410
-1420
-2430
-3440
-4450
-5460
-6470
-7480
-8490
-94 100+-2%
0%
2%
4%
6%
8%10%
12%
14%
16%
Age related
Death related
Finland
UK
National Institute of Economic and Social Research
Main features of the model
Closed economy– Interest rate reacts to population ageing
Demography:– 21 generations (0-4, … 100+)
Discounting– pure rate of time preference – probability of survival
Three sectors– Healthcare services– Education services– The rest of the economy (ROE)
Age-specific public consumption– Healthcare– Education
Balanced budget– taxation endogenous
National Institute of Economic and Social Research
Multi-sector model
K
L
ROE
Healthcare services
Education services
L
L
Household
Government
Investment
Government
Government
National Institute of Economic and Social Research
Multi-sector model 2
Population size and structure
Government spending on Healthcare
Government spending on Education
Healthcare services ROE Education
services ROE
59%41% 17%83%
Wage Price
PH
Wage Price
PE
National Institute of Economic and Social Research
Scenarios
Naive– Application of 2007 age profile for all future
years LE adjustment
– Adjustment of 2007 age profile in line with improvements in life expectancy
PTD– Differentiation of age related and death
related healthcare spending
National Institute of Economic and Social Research
TFP growth
Growth unexplained by change in the amount or quality of factors of production
In the UK– Past 10 years – -0.30% per year– Past 20 years – 0.43% per year– Past 30 years – 0.32% per year– Past 40 years – 0.36% per year
Source: ONS
National Institute of Economic and Social Research
Healthcare spending,% of GDP, pp difference – no TFP growth
2015 2020 2025 2030 2035 2040 2045 2050 2055 2060 2065 2070 2075 2080 2085 2090 2095 2100 2105 21100%
1%
2%
3%
4%
5%
6%
Naive
LE adjustment
PTD
National Institute of Economic and Social Research
Healthcare spending,% of GDP, pp difference – TFP growth 0.32%
2015 2020 2025 2030 2035 2040 2045 2050 2055 2060 2065 2070 2075 2080 2085 2090 2095 2100 2105 21100.0%
0.2%
0.4%
0.6%
0.8%
1.0%
1.2%
1.4%
1.6%
1.8%
Naive
LE adjustment
PTD
National Institute of Economic and Social Research
Healthcare spending,% of GDP, pp difference – TFP growth 0.43%
2015 2020 2025 2030 2035 2040 2045 2050 2055 2060 2065 2070 2075 2080 2085 2090 2095 2100 2105 2110
-0.6%
-0.4%
-0.2%
0.0%
0.2%
0.4%
0.6%
0.8%
1.0%
1.2%
1.4%
NaiveLE adjustmentPTD
National Institute of Economic and Social Research
Conclusions
Public healthcare expenditures in the UK are not very high compared to other OECD countries
Projecting future healthcare spending – Population size and age structure
• Taking into account proximity to death significantly reduces projections of future healthcare spending
• Adjusting age profile has smaller positive effect• It is important to produce UK estimates taking into account proximity to
death– Price
• Important to use multi-sector model– Productivity growth
• Very important• Historically UK experienced productivity growth sufficient to make projected
healthcare spending manageable• Recent productivity growth records are poor
National Institute of Economic and Social Research
Thank you for your attention
Follow us on Twitter @NiAGEproject
National Institute of Economic and Social Research
CGE model
General– All the markets, sectors and industries are modelled
together with corresponding inter-linkages Equilibrium
– All markets are in equilibrium in every period Computable
– Tend to be very complex and thus cannot be solved analytically
– Calibrated to “real world” data and rely on solver algorithms that find numerical solutions satisfying all of the model’s equations
National Institute of Economic and Social Research
CGE model 2
Mathematical description of an economy using a system of simultaneous equations
CGE models are very flexible, and can be used to analyse the macro-economic effects of variety of economic shocks and policies
Simulation (what if) not a forecasting tool!
National Institute of Economic and Social Research
Limitations
Complicated– Technical skills – Time/Data– Trade off between complexity and usability
Calibration– Some parameters are calibrated on base year data
Relies on serious assumptions– All assumptions are explicit – Perfect foresight/ rational decision making– Type of utility / productivity function– Assignment of exogenous variables