THE FUTURE OF HEALTH SPENDING

Joint OECD and ESRI workshop on “Long-term prospect of

the world economies up to 2060 and its policy implications”

OECD, Paris 31 Jan 2014

Joaquim OLIVEIRA MARTINS OECD, Public Governance Directorate

1

SOME FACTS

Health spending growth has decreased recently…

3 Source: OECD Health database

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Average OECD health expenditure growth rates in real terms, 2000 to 2011, public and total

Total Health Expenditure Public health expenditureSource: OECD Health Data 2013.

… but Public spending continues to increase

in % of GDP

Public Health and LTC expenditure as a % of GDP, OECD countries

4 Source: OECD Health database (2011).

The share of Health in Public Budgets has also increased

(Health+LTC expenditures in % of Total Public Expenditures

unweighted average of OECD countries)

5

Health is now one of the largest public spending area

Source: OECD Health Accounts

General public services

14%

Defence 6%

Economic affairs 16%

Health 16%

Education 13%

Social protection 24%

Other 11%

General Government Expenditure by function (OECD average, 2010)

WHAT DRIVES PUBLIC HEALTH CARE EXPENDITURES?

Main expenditure drivers

Health care expenditure

Demography (I)

Income (II)

Residual (III)

a) Relative prices

b) Technology

c) Institutions and policies

An income elasticity of 1.8

could explain most of the

expenditure growth

If price elasticity is below 1 then price

increases also increase expenditure

8

Estimation of the expenditure residual (assuming an income elasticity of 0.8)

Health spending per capita (average 1995-2009 annual growth rate in %)

Health

spendingAge effect

Income

effectResidual

Memo item:

Residual with

unitary income

elasticity

Selected countries:

Australia 4.1 0.4 1.7 1.8 1.4

Canada 2.6 0.6 1.3 0.8 0.5

France 1.6 0.5 0.9 0.3 0.0

Germany 1.7 0.6 0.8 0.2 0.0

Italy 3.1 0.6 0.4 2.1 2.0

Japan 2.7 1.2 0.4 0.7 0.5

Korea 11.0 1.1 3.1 6.5 5.7

Portugal 4.6 0.6 1.2 2.4 2.0

Sweden 3.2 0.2 1.6 1.4 1.0

United States 3.6 0.3 1.1 2.3 2.0

Brazil 4.8 0.6 1.2 2.9 2.6

China 11.2 0.6 7.3 3.0 1.3

India 6.6 0.3 4.2 2.0 1.0

OECD total average 4.3 0.5 1.7 2.0 1.5

BRIICS average 6.2 0.5 3.2 2.5 1.7

Total average 4.6 0.5 2.0 2.0 1.5

9

Modelling the drivers of the expenditure residual

a) Relative prices

A health relative price was derived from the STAN value-added database (more comparable and producing similar trends as CPI sources): (Health deflator/GDP deflator)

b) Technology (quality effect)

Technology is proxied for country i by (OECD Data):

𝑄 = R&𝐷

GDP∙

Total OECD Patents in the Health sector

Total OECD patents

c) Institutions and policies

Currently captured by country specific effects + a time trend (current research using OECD policy indicators on institutional set-up of health care systems)

10

Estimation results

Combining effect of prices and technology = (-0.4+1)*1.7% + (0.9-1)*2.4% ≈ 0.8% per year

+ 0.9% time trend Residual = 1.7% out of 2% on average for OECD.

Dependent variable:

log(Real health expenditure per capita deflated by quality adjusted health prices)

Pooled

Fixed

effects

with Time

dummies

Fixed

effects

with Time

trend

Fixed

effects

with Time

dummies

Fixed

effects

with Time

trend

Fixed

effects

with Time

dummies

Fixed

effects

with Time

dummies

Fixed

effects

with time

trend

Income

elasticity

=0.8

Memo item :

First

differences

estimates

log(gdpv per capita) 0.914*** 0.394** 0.495*** 0.775*** 0.634*** 0.964*** 0.749*** 0.532*** 0.535***

(0.02) (0.18) (0.13) (0.14) (0.14) (0.14) (0.12) (0.12) (0.12)

log (average age of

population) 2.603*** 3.007*** 1.399*** 1.396*** 2.611*** 2.606*** 1.342*** 1.471*** 0.962** 1.509

(0.56) (0.59) (0.45) (0.42) (0.46) (0.42) (0.41) (0.44) (0.43) (1.45)

timetr 0.009*** 0.009*** 0.009*** 0.001

(0.00) (0.00) (0.00) (0.00)

log(GDP deflator) 0.453*** 0.482*** 0.929*** 0.777***

(0.08) (0.08) (0.06) (0.06)

log(Health prices) -0.415*** -0.505***

(0.07) (0.06)

lagged log(Technology) 0.908*** 0.918*** 0.919*** 0.912*** 0.930***

(0.03) (0.04) (0.04) (0.03) (0.03)

lagged dlog(Technology) 1.027***

(0.05)

lagged log(quality ajusted

health prices) -0.788*** -0.755***

(0.03) (0.03)

log(Relative prices (Health

prices/PGDP)) -0.503*** -0.415*** -0.492*** -0.626***

(0.06) (0.07) (0.06) (0.06)

_cons -11.591*** -7.824*** -3.513** -5.889*** -7.535*** -10.936*** -5.414*** -4.179*** -6.646*** 0.006

(2.08) (2.19) (1.78) (1.85) (1.86) (1.90) (1.54) (1.54) (1.38) (0.02)

N 474 474 463 463 453 453 463 463 463 447

Effect of other

exogenous factors:

additional annual

growth≈0.9%

Effect of

technology:

elasticity≈ +0.9

Pure price

elasticity≈ -0.4

11

Projecting the residual expenditure growth

• To sum, part of the residual expenditure growth can be explained by:

Relative Prices and Technology 0.8% p.a.

Other (eg. institutions and policies) 0.9% p.a.

• But there is not enough information to project these drivers individually

• Thus the residual is projected as a whole and sensitivity to different assumptions tested

• Residual growth is the same for all countries in order not to extrapolate country-specific idiosyncrasies over a long period (e.g. country-fixed effects)

12

1.7% p.a.

WHAT DRIVES PUBLIC LONG-TERM CARE EXPENDITURES?

Long-term care expenditure

Demographic drivers

(Nb of dependents)

Life expectancy

at birth

Health expenditure

Non-demographic

drivers

Income Cost-disease Informal care

supply: women 50-64 labour force participation

14

Main expenditure drivers

Income elasticity=1

Baumol effect=growth rate of total labour productivity (elasticity=1)

The profile of dependency ratios by age is similar

across European countries

Source: EC AWG

Nb: For the projections an average curve was computed

02

04

06

08

0

% o

f ag

e g

roup

s p

op

ula

tio

n

2 7 12 17 22 27 32 37 42 47 52 57 62 67 72 77 82 87 92 97

age (middle of 5-years age brackets)

LTC costs per dependent are not related to age

Assumption used in the projections: average constant

cost per age by country

05

01

001

502

00

% o

f GD

P p

er c

apita

2 7 12 17 22 27 32 37 42 47 52 57 62 67 72 77 82 87 92 97

age (middle of 5-years age brackets)

WHAT ARE THE PROJECTED HEALTH & LTC EXPENDITURES?

Projected levels of Public Health and LTC expenditure

(as a % of GDP in 2060)

18

0

2

4

6

8

10

12

14

16

OECD BRIICS

LTC

Health care

Average 2006-2010

Average 2006-2010

Cost-containment

scenario

Cost-pressure scenario

Cost-containment

scenario

Cost-pressure scenario

Cost pressure: healthy ageing, income elasticity=0.8, residual=1.7% per year

Cost containment: healthy ageing, income elasticity=0.8, residual phasing out over the

projection period

Convergence mechanism based on differences across countries in health shares to GDP

in the base year compared with OECD average

Projections by country of Public Health + Long-term care

expenditures (in % of GDP)

19

0

2

4

6

8

10

12

14

16

18% 2006-2010

Cost pressure, 2060

Cost containment, 2060

Changing structure of health expenditures

Shares of expenditure by age in total expenditure

0

10

20

30

40

50

60

70

2010 2030 2060

People aged below 65

People aged over 65

20

NB: Non-demographic effects are assumed to be homothetic across ages, so they do not change the structure

Comparison with other projections

21

Source: OECD, IMF, "The Economics of Public Health Care Reform in Advanced and Emerging Economies", European Commission, "The 2012 Ageing Report" and Congressional Budget Office, "The 2012 Long-term Budget Outlook".

OECD (2013) OECD (2013) EC - AWG IMF US CBO

(Cost-containment

scenario)

(Cost-pressure

scenario)

(Reference

scenario)

(Extended Baseline

Scenario)

In 2060 % pp difference from 2010In 2050 % pp

difference from 2010

In 2060 % pp

difference from 2010

France 2.2 6.1 1.4 2.6 ..

Germany 2.3 6.2 1.4 1.5 ..

Italy 2.6 6.4 0.6 1.1 ..

Netherlands 2.4 6.3 1.0 4.9 ..

Spain 2.8 6.7 1.3 3.5 ..

United Kingdom 2.0 5.9 1.1 8.2 ..

EU15 2.4 6.2 1.1 4.5 ..

USA 2.2 6.1 .. 11.3 7.3

HOW TO FINANCE & MANAGE HEALTH SPENDING?

Temporary cuts vs. long-term effects Short term savings may come at the cost of long-term deteriorations in health service quality that will be hard to un-wind when fiscal capacities improve.

Revenues for health may be a challenge as population ages, meaning countries need to find alternative revenue sources

Close to half OECD countries rely on wage-based contributions as their predominant financing source. Falls in workforce participation may therefore imply a decline in wages as a share of total income, and therefore, a reduction of the base for financing health expenditure. “Sin taxes” (tobacco, alcohol and “fat” taxes) may provide some health benefits, but their ability to raise revenues is limited.

The politics of health care means reform is more incremental than in other areas

In addition, countries’ experiences are characterized by situations where Health & Finance interests are not easily split up by interest groups.

Main issues

Source: Main conclusions from the OECD SBO-Health Joint Network’s 2nd Annual

meeting – 25-26 March 2013

How Public Health care is financed?

General Taxation Taxes earmarked to the

health system Payroll contributions to social health insurance

Mandatory health insurance premiums

Australia

Belgium

Canada

Denmark

Finland

France

Germany

Greece

Iceland

Ireland

Italy

Japan

Luxembourg

Netherlands

New Zealand

Norway

Portugal

Spain

Sweden

Switzerland

United Kingdom

United States

Source: OECD Health Committee Survey on Health Systems Characteristics 2012

Sources of revenues for health

Policy options to contain expenditure

• A more intense use of generics

• A revision of re-imbursement practices for drugs with low medical service (and more stringent restrictions on exemptions to this rule)

• A more frequent re-evaluation of prices of new drugs (in general a more transparent and dynamic pricing of new drugs), centralized bargaining for the purchase of drugs and medical goods in public hospitals, reduction in excessive consumption of specific drugs

• On in-patient care: shorter length of stay, development of ambulatory hospitalization or more user choice among health providers could help reining in the expenditure growth

• On out-patient care: a more stringent health monitoring of patients affected by long-term diseases in order to reduce costly complications

• Financial incentives set on general practitioners to reduce prescription inflation and prevention could also help maintaining the health expenditure on a sustainable path.

Budget tools available if health spending exceeds targets – by option

How do countries control health budgets?

Source: OECD Health Committee Survey on Health Systems Characteristics 2012

Is Health generating productivity?

• Pension systems and labour markets favoured early retirement, thus the effect of better health did not materialise.

• Developed countries have had lower increases in longevity and only mortality rates below 40-year have an impact on growth (Aghion, Howitt and Murtin, 2009)

• Efforts to increase life expectancy at older ages may have a negative impact on growth, as the resources devoted to health care are at the expense of other factors (Aisa & Pueyo, 2005, 2006)

• With most of the population covered, an increase of health status is likely to have only a level effect, with little impact on labour productivity growth.

Policy issues

• Increasing share of health expenditures to GDP is mainly driven by technological progress, depending on the design of the health insurance and on the payment systems (Weisbrod, 1991)

• While some countries are doing well in longevity and health status, these potential resources have been wasted in low participation and early retirement of older workers

• There strong complementarities across health, labour market, pension reforms and related financial products. A broad reform package implemented at all levels of government could generate large gains

Thank you!

29

References: -de la Maisonneuve, C. and J. Oliveira Martins (2013), “Public spending on health and long-term care: a new set of projections”, OECD Economic Policy Papers no. 6. - de la Maisonneuve, C. and J. Oliveira Martins (2013), “A Projection Method for Public Health and Long-Term Care Expenditures”, OECD Economics Department Working Papers, No. 1048, OECD Publishing. http://dx.doi.org/10.1787/5k44v53w5w47-en