National Institute of Economic and Social Research Development and applications of the National Institute General Equilibrium model of Ageing (NiAGE) NIESR, London, November 30, 2015 Katerina 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 * * 2014-based principal ONS projections malesfemales 36M 57M 89M

National Institute of Economic and Social Research Projection Old age dependency ratio* * Population aged 65+ divided by population aged 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 FirmsHouseholds Goods market External sector Capital market Factors market Public sector Goods Factors Savings Investment Borrowing Export Import Migration Taxes

National Institute of Economic and Social Research Overlapping generations structure A1A2A3A4A5 T1G1 T2G2G1 T3G3G2G1 T4G4G3G2G1 T5G5G4G3G2G1 T6G6G5 T7G7G5 T8G8G5 T9G9G5 T10G10G9G8G7G6 T11G11G10 T12G12G10 T13G13G10 T14G14G10 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 GDP Source: OECD database

National Institute of Economic and Social Research Public sector healthcare expenditure in the UK, % of GDP 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 productivity 4.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 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

National Institute of Economic and Social Research Healthcare spending relationship with age, Finland Source: ETLA

National Institute of Economic and Social Research Healthcare spending relationship with age ? Finland UK

National Institute of Economic and Social Research Healthcare spending relationship with age 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

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% WagePrice PH WagePrice 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

National Institute of Economic and Social Research Healthcare spending,% of GDP, pp difference – TFP growth 0.32%

National Institute of Economic and Social Research Healthcare spending,% of GDP, pp difference – TFP growth 0.43%

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

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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