- Benedict Clements, Juan Toro R., and Victoria Perry
- Published Date:
- October 2010
Figure A.1.Advanced G-20 General Government Primary Expenditure Trends 1990–2008: Economic Classification
Sources: Eurostat; and OECD.
Figure A.2.Advanced G-20 General Government Primary Expenditure Trends, 1997–2008: Functional Classification
Sources: OECD; and Eurostat.
Notes: Or latest year available; averages are PPP GDP weighted.
Figure A.3.Emerging G-20 Primary Public Expenditure Trends, 1995–2008: Economic Classification
Sources: WEO; and IMF staff estimates.
1Nonfinancial public sector.
4PPP GDP weighted.
|Of which: economic classification||Of which: age-related|
|Country (end-year)||Length (years)||Size of adjustment||of which: Primary expenditure||Compensation of employees||Social benefits and social transfers in kind||Gross fixed capital formation||Other||Health||Pensions||of which: Old age pensions||of which: Survivor pensions|
|United Kingdom (2000)||7||8.3||-5.1||-1.2||-2.7||-0.9||-0.2||0.0||-0.2||-0.1||-0.1|
|Hong Kong SAR (2005)||4||5.8||-1.5||…||…||…||…||…||…||…||…|
|New Zealand (1995)||4||5.8||-7.1||-1.5||-1.6||0.4||-4.2||-0.5||-4.2||-2.8||-1.4|
|United States (2000)||8||5.7||-2.6||-1.4||-1.1||0.2||-0.4||0.0||-0.4||-0.3||-0.1|
|Country (end-year)||Length (years)||Size of adjustment||of which: Total expenditure||General public services||Defense||Public order and safety||Economic affairs||Environment protection||Housing and community amenities||Health||Recreation, culture, and religion||Education||Social protection|
|United Kingdom (2000)||7||8.3||-5.7||-0.7||-0.8||-0.1||-1.1||0.1||-0.5||0.1||0.0||0.2||-2.9|
|Hong Kong SAR (2005) 3/||4||5.8||…||…||…||…||…||…||…||…||…||…||…|
|New Zealand (1995)||4||5.8||…||…||…||…||…||…||…||…||…||…||…|
|United States (2000)||8||5.7||-3.8||-1.1||-1.5||0.1||-0.2||0.0||-0.2||-0.1||0.0||0.2||-1.1|
Methodology for Projecting Pensions
Projections for public pensions reflect official projections where available (see sources below). For countries where official projections are not available, the following assumptions are made: (i) constant coverage ratio of pensioners to population aged above 65 years and constant replacement rate; and (ii) changes are driven by employment ratio and old-age dependency ratio. Demographic projections are based on projections from the European Commission (2009) and U.S. Bureau of Census. Economic projections are broadly based on the convergence criteria assumed in the European Commission’s Ageing Report, 2009, and staff estimates of labor participation rates.
- European countries: European Commission Ageing Report (2009); for Cyprus, staff calculations of the recent reform;
- Australia: Productivity Commission (2005);
- New Zealand: New Zealand Treasury (2009);
- United States: Congressional Budget Office Report on Social Security (2009);
- Canada: CPP and QPP Actuarial Reports (2006);
- Japan: Ministry of Health, Labor and Welfare, 2009 Actuarial Report on Pensions; and
|2010||2015||2020||2030||2040||2050||Change, 2010 to 2030||NPV of 2011-2030 spending Increase||NPV of 2031-2050 spending Increase|
|Emerging market economies:|
- Others: Staff projections using ILO (2010), IMF, World Bank documents and country authorities estimates.
- Population Projections: European Commission and U.S. Bureau of Census; and
- Employment Ratio: World Economic Outlook.
|Earliest eligibility age for pension benefits, 2010||Statutory retirement age, 2010||Life expectancy after statutory retirement age, 2010||Increase in statutory retirment age by 2030 (planned or legislated)||Life expectancy after statutory retirement age, 2030|
|Emerging market economies:|
All advanced G-20 have undertaken reforms to stabilize pension finances. These reforms often included a combination of significant measures to increase revenues, raise statutory retirement ages, and reduce the generosity of benefits. Many of these changes come into effect beyond 2020. If implemented as legislated, these reforms are expected to largely offset the adverse effects of demographic developments, including through their effects on labor force participation rates—in the absence of reforms, pension spending in advanced G-20 countries would increase by 4½ percentage points of GDP to nearly 11½ percent of GDP in 2050 (Figure A.4). Nevertheless, pension spending is projected to rise from 7 percent of GDP in 2010 to 8½ percent in 2050. Reforms implemented by country were as follows:65
In Australia, the 2009 reform envisaged a gradual increase in the statutory retirement age from 65 years to 67 years starting in 2017, and changed the income test by increasing the reduction in pensions from 40 cents to 50 cents for each dollar of non-pension income.
Figure A.4.Effects of Pension Reforms on Pension Expenditures in Advanced G-20 Countries, 2010-50
Source: IMF staff estimates.
In Canada, the contribution rate increased by 0.2 percent a year from 1987 to 1997. The 1997 reform further raised it from 5.85 percent in 1997 to 9.9 percent in 2003 and reduced basic contribution holidays. Two stabilizing provisions were also introduced: (i) future increases in benefits are financed by increases in the contribution rate; and (ii) contribution rates and benefits indexation respond automatically to actuarial imbalances.
France increased the contribution rate from 4.7 to 6.55 for employees from 1985 to 1991. The 1993 reform increased the base wage for calculating pensions from the top 10 years to the top 25 years and changed the basis for calculating pensionable earnings from wages to prices. The minimum contribution period for a full pension increased from 37½ to 40 years. The 2003 reform linked the contribution years for a full pension to life expectancy. In the early 1990s, Germany changed the indexation of pensions from gross to net wages and tightened the requirements to receive a full pension before age 65 and increased the minimum age for early retirement after unemployment, after a transitional period, from 60 years to 63 years. The 2001 reform included a privately funded second pillar and changed the formula to reduce benefits with increases in the contributions to the first and second pillars. The 2004 reform introduced a “sustainability factor” to partially offset the effect of increases in the dependency ratio. In 2007, the statutory retirement age was increased from 65 today to 67 after 2030.
In Italy, the 1992 reform cut net pension liabilities by about 25 percent through (i) an increase in the retirement age for full benefits from 60 to 65 for men; (ii) an increase in reference earnings from 5 to 10 years (lifetime earnings for younger workers); (iii) a change in the basis of calculating pensionable earnings to prices plus 1 percent; (iv) an increase in contributing years for a full pension from 15 to 20 years; and (v) a change in indexation from wages to prices. The 1995 reform adopted a Notional Defined Contribution system in which pensions depend on lifetime contributions and GDP growth. The 2004 reform raised the minimum retirement age to 60 years with 35 years of contributions. In 2007, the minimum retirement age was raised to reach 61 years in 2013.
In Japan, the 2004 reform increased contributions rates for the employees’ pension from 13.6 percent in 2005 to 18.3 percent in 2017. Benefits were reduced to offset the effects of a shrinking base of contributors and longer life expectancies. Earlier reforms changed the indexation of pensions from wages to prices, increased the retirement statutory to 65 years and extended the base of contributors to include employees 65 to 69 years.
In Korea, contribution rates were increased from 3 percent in 1988 to 6 percent in 1993 to 9 percent in 1998. The 1998 reform cut replacement rates from 70 to 60 percent and raised the pensionable age from 60 to 65 years. The 2007 reform stabilized contribution rates at 9 percent and reduced replacement rates from 60 percent in 2007 to 50 percent in 2008 to 40 percent in 2028. Contribution rates are set to increase further (from 9 percent) after 2010. The reform also expanded the basic pension from 5 percent of earnings in 2008 to 10 percent in 2028.
In the United Kingdom, the National Insurance Contribution rates have been generally increasing. The 2007 reform raised the statutory retirement age from 65 in 2008 to 68 in 2027 (the pension age of women will be equalized by 2020). This reform also loosened eligibility for a full pension from about 44 years to 30 years.
In the United States, the 1983 reform accelerated scheduled increases in the payroll tax to 12.4 percent of covered earnings after 1990, levied taxes on social security benefits and raised the statutory retirement age from 65 years to 67 years in 2027. It also expanded the base of participants to include federal employees.
Changes in pension expenditures (PE) in percent of GDP can be decomposed into four main blocks reflecting eligibility, generosity, labor market effects, and demographic changes (See European Commission, 2009).66
PE = Pensioners* Average Pension
To contain the growth in pension expenditures, reforms need to affect one of these components:
Eligibility depends on the requirements to receive a pension. For example, increasing the age at which the pension is first received reduces the number of pensioners as ratio of the population over age 65. Generosity depends mainly on the benefit formula. Reducing benefits by 10 percent across the board reduces the generosity ratio by 10 percent. Labor market effects depend on the dynamism of the labor market. Pension expenditures are inversely related to labor force participation rate of the population 15–64. Old-age dependency ratio depends on demographics.
To contain the growth in pension expenditures, reforms need to affect one of these components, which is generally achieved by cutting benefits (reducing “generosity”) or by increasing the pensionable age (reducing eligibility and strengthening labor market effects by potentially increasing labor force participation of older workers). If expenditures cannot be contained, the remaining option is to increase revenues via contribution rate hikes.
Methodology to Project Health Spending67
Our approach to projecting health spending is two-fold: (1) we assess, but do not reestimate, official projections of countries that have produced them; and (2) we develop a simplified model to project health expenditure for those countries where official projections do not exist. In the second case, the model focuses on demographics and all other factors combined, and illustrates a range of possible spending trajectories under different assumptions about spending growth relative to income growth. This is described in greater detail below.
Projections of public spending in countries with official projections
- European countries: European Commission, The 2009 Ageing Report (2009): The baseline scenario from this report implicitly assumes that technological change reduces spending per capita at older ages, which is an optimistic assumption in light of past trends in spending. We therefore choose instead to use the most pessimistic scenario from the report, where technology and other factors grow 0.8 percent faster than income per capita per year, on average.
- Australia: Productivity Commission, Economic Implications of an Ageing Australia (2005): We use the alternative scenario of the report that assumes that non-demographic growth of health spending will exceed GDP per capita growth by 0.9 percentage points annually. The baseline scenario in the Productivity Commission report assumes this difference to be 0.6 percentage points.
- United States: Center for Medicare and Medicaid Services, Office of the Actuary, 2009 Medicare Trustees Report Work Files, and Congressional Budget Office The Long-Term Outlook for Health Care Spending (2007); the fiscal impact of the March 2010 health care reform is not included, as the Congressional Budget Office has not yet updated its long term projections to incorporate the reform.
- New Zealand: New Zealand Treasury Department, New Zealand’s Long-Term Fiscal Position (2006).
Projections of public spending in countries without official projections68
- The central element for the projections is a profile of public health spending per capita for 5-year age cohorts.
- We assume that the shape of the average OECD profile is the same for OECD countries and non-OECD countries. For each country, the profile of absolute spending in local currency units for each age cohort is calculated using data on public health spending, the number of people in each age cohort, and the relative spending weight of each cohort.
- The shape of this expenditure profile remains constant over the projection period.
- Changes in the number of people within each 5-year age cohort based on U.S. Census Bureau projections by country yield spending changes due to demographics.
- An increase in the spending level at a given age (i.e., the expenditure profile shifting up) represents changes in spending due to technology, income, insurance, and any other factors excluding demographics, which, following convention, we refer to as “excess cost growth.”
- The baseline scenario is that health spending grows 1 percent faster than projected GDP per capita (exclusive of demographic changes) for each age cohort.
- Given the large degree of uncertainty in non-demographic factors (Cutler and McClellan, 2001) we simulate two alternative scenarios to demonstrate the following possible spending trajectories: (i) an optimistic scenario where health spending grows at the same rate as GDP growth per capita; and (ii) a pessimistic scenario where health spending grows 2 percent faster than GDP growth per capita.
- Canada: Data on the expenditure profile by sex and between 1997 and 2002 exist for Canada. We follow a similar procedure as described above, except that we consider spending on men and women separately, using this additional information before aggregating the two to arrive at public spending.
To ensure comparability, we use data on public and total health spending measured in local currency units for OECD countries from the OECD Health Database. For most of the “old” OECD countries, this data extends from 1970 to 2007. Data of newer OECD members generally begins in the 1980s or 1990s. For non-OECD countries, data on health spending (also measured in local currency units) is taken from the WHO National Health Accounts which covers the period 1995 to 2007.
Methodology to Estimate Percent of Increase due to Ageing, Non-Demographic Factors, and Interaction Effect
Increase due to ageing
To calculate the change in public health expenditure due to ageing, we set excess cost growth equal to zero so that the growth in public health spending in each age cohort is equal to the growth in GDP per capita. The resulting increase in spending is then due to changes in demographics alone, with the projected population sizes of each cohort taken from the Census Bureau projections.
Increase due to non-demographic factors
To calculate the change in expenditure due to non-demographic factors, we set excess cost growth equal to 1 percent as in the baseline outlined above but maintain the same age distribution in each year of the projection horizon. The rate of population growth is equal across age cohorts and set so that the total population is equal to the population estimate of the Census Bureau projections in 2050 for each country. We attribute this increase in spending due to excess cost growth or non-demographic factors alone.
Increase due to interaction of ageing and non-demographic factors
To calculate the size of the interaction of excess cost growth with an older population, we combine the Census Bureau projections of population with excess cost growth of 1 percent for all countries, including those with official projections. From this increase, we subtract the increases due to ageing and non-demographic factors alone to arrive at the increase due to the interaction effect. We do not subtract the ageing and nondemographic effects from the increase in the official projections because this residual would also include other differences in underlying assumptions.
Finally, we apply the shares of the increase: due to (i) ageing;
(ii) non-demographic factors; and (iii) the interaction; to the increase in the baseline projections. This serves as our decomposition of the baseline increases in public health spending in Figure 3.8.
Methodology to Estimate Expenditure Reductions from Health Policies
Provider payment reforms
As an illustration, we assume that fee-for-service payment constitutes 20 percent of public spending which, in turn, averages 6½ percent of GDP in advanced countries. This implies that switching from fee-for-service to prospective payment methods would reduce spending by 0.1 to 0.2 percent of GDP.
The expenditure savings from health IT clearly depend on institutional factors, such as how the administration of health care information currently operates. For countries with low levels of health IT, expenditure reductions from increased efficiency may be large, although not immediate. A RAND study estimated that if properly implemented and widely adopted, health IT would yield net annual savings of roughly $80 billion (less than 5 percent of total health spending) while also improving health outcomes in the United States (Hillestad and Bigelow, 2005). However, other studies have been more pessimistic on the size of these savings, partly because providers often do not have a strong incentive to implement health IT. This is because large upfront costs would be born entirely by current users while savings and efficiency improvements would be enjoyed by future generations, implying the need for government incentives (CBO, 2008). If average public spending were 6½ percent of GDP and savings were similar to those estimated in the RAND study, then widespread implementation of health IT could reduce spending by 0.2 percent of GDP.
|2010||2015||2020||2030||2040||2050||Change, 2010 to 2030|
|Emerging market economies:|
The best estimates of the price elasticity of demand for medical care are between –0.17 and –0.31 for hospital services and –0.17 to –0.22 for outpatient care (Newhouse and the Insurance Experiment Group, 1993). However, to the extent that different forms of medical care are substitutes, the effect on overall spending may be dampened. In a study of increases in patient cost-sharing for drugs, about 35 percent of savings achieved by reduction in drug spending were offset by subsequent increases in other medical spending (Gaynor, Li, and Vogt, 2006).
As a rough measure of the expenditure savings from higher copayments, we consider an increase in the share of the cost of outpatient treatment patients finance by 5 percentage points. We assume there are two effects that impact expenditure: (1) shifting 5 percent of public spending to patients (and reducing provider payments from the public sector by 5 percent); and (2) a reduction in the quantity demanded of outpatient care due to a higher price at the point of service. We also assume that average public spending is 6½ percent of GDP and that outpatient care makes up 30 percent of this spending. Based on a price elasticity of demand of –0.2, an increase of 5 percentage points in the coinsurance rate for outpatient care would reduce spending by 0.1 percent of GDP.
In response to rapid growth of public health spending in the 1970s, many EU countries enacted provider payment reforms to contain spending in the 1980s (Abel-Smith and Mossialos, 1994; and Mossialos and Le Grand, 1999). Those that did not pursue cost containment were driven by the desire to extend coverage from a low base (Greece and Spain), but later confronted the need to contain spending in the 1990s. The slowdown was most pronounced in Denmark, Germany, Ireland, Netherlands, and the United Kingdom. Policies targeted the supply-side by constraining reimbursement for physician fees and salaries, pharmaceuticals, and other technology, as well as limiting the number of providers and hospital capacity.
In the 1990s, demand-side measures, specifically increasing patient copayments and coinsurance, were introduced. These charges applied mostly to pharmaceuticals and dental care, but also to ambulatory and hospital services. Their primary objective was to deter demand. Since charges were relatively low, exemptions widespread, and demand inelastic, their impact was relatively limited.
Competition has also been used as tool to increase efficiency. Between 1991 and 1997, the United Kingdom attempted to create an “internal market” to increase hospital competition within the publicly financed National Health Service (NHS). The two major public payers that were designed to drive competition were District Health Authorities and General Practice (GP) Fundholders. District Health Authorities were ineffective at increasing competition because of weak financial incentives that did not allow them to fully capture savings. However, GP fundholding for primary care was more successful at increasing competition. Under the system of “fundholding”, GPs were allocated a set budget that could be used to purchase hospital services on behalf of their patients (in addition to the money they were allocated for delivering primary care services directly to their patients). The reform produced a number of positive effects, including reduced hospital prices; lower waiting times; decreased referral rates; and a reduction in prescription drug spending (which was a once-and-for-all decrease). There was also no evidence that GPs selected healthier patients. However, there is some evidence that 30-day mortality rates after a heart attack admission—an important measure of quality—suffered (Cookson and Dawson, 2005).
Reforms in 1990s brought copayment rates in Japan to one of the highest among OECD countries, to 30 percent in 2002, and separate proportionate copayments were introduced to the elderly in 2000. Medical unit price increases were strictly controlled in the biennial revisions of the fee schedule. Revisions in fee schedule between 1990 and 2006 contributed to a decrease in national medical expenditure by 0.1 percentage point during the period (Jones, 2009). In addition, a new public insurance for long-term care was established in 2000, mandating compulsory premium contribution from those older than forty. The new public insurance scheme aimed to achieve cost savings by shifting long-term care from hospitals.
Managed care was the key contributing force behind the slowdown in the growth of private health spending in the United States in the 1990s, when it grew at the same rate as GDP. Managed care refers to different forms of health insurance organization and management that attempt to control utilization of services and coordinate care in order to lower costs and improve health outcomes. While managed care existed before the 1990s, it became more widespread during this decade. Managed care organizations, if successful in covering a large share of population, can use their bargaining power to negotiate lower prices than traditional private insurance.
Research on how managed care affected health outcomes is mixed, but there is some consensus that managed care has not led to large deleterious impacts on health status (Cutler, 2004). In one sample of heart disease patients, health maintenance organizations (HMOs) reduced expenditure between 30 and 40 percent relative to traditional insurance (Cutler, McClellan, and Newhouse, 2000). These savings were driven by lower unit prices for services rather than lower quantities, and there was little evidence that health outcomes suffered. On the other hand, there is evidence that managed care reduced the adoption of a range of medical technologies (Mas and Seinfeld, 2008). Today managed care remains a key component of the U.S. health system, but it is far less restrictive than in the past, reflecting in part patient resistance to restrictions on choice under managed care (Enthoven and others, 2001). Partly as a result, private health spending has again grown faster than GDP since 2000.
A proper legal framework for tax administration that provides an appropriate balance between the rights of taxpayers and the powers of the tax agency.
Efficient organizational and staffing arrangements, featuring strong headquarters; function-based organizational design; minimal management layers and appropriate spans of control; streamlined field operations; organizational alignment to key taxpayer segments (e.g., a large taxpayer office); and sufficient numbers of staff assigned to each level of the organization and each function.
A system of self-assessment directed at creating an environment of taxpayer voluntary compliance (thereby minimizing intrusion of revenue officials in the affairs of voluntary taxpayers, while concentrating enforcement efforts on those representing a higher risk).
Streamlined collection systems and procedures aimed at securing timely revenues without imposing undue compliance costs and inconvenience on the business sector.
Service oriented approaches whereby the tax administration operates as a trusted advisor and educator, ensuring that taxpayers have the information and support they need to meet their obligations voluntarily.
Risk-based audit and other verification programs aimed at detecting taxpayers who present the greatest risks to the tax system, supported by effective dispute resolution.
Extensive use of IT to gather and process taxpayer information, undertake selective checking based on risk analysis, automatically exchange information between government agencies, and provide timely information to support management decision making and tax policy formulation.
Modern human resource management practices that provides incentives for high performance and non-corrupt behavior among tax officers as well as develops staff skills and professionalism.
Effective models for ongoing institutional change, including enhancing strategic planning capabilities, building coalitions with external stakeholders, and developing an internal culture that is receptive to change.
An environment of integrity and good governance with transparency of taxpayer rights and required staff conduct, with mechanisms to assure integrity of systems, procedures, staff practices, and to regularly inform the public of organizational goals, plans, efforts, and outcomes.
C-efficiency, defined as:
where τs is the standard rate, is not a measure of the perfection of a VAT—bad VATs can score well. But it can be a useful diagnostic tool.
One use is in calibrating potential revenue gains from raising it to levels found in comparator countries, and therefore presumptively attainable. Table A.6 illustrates, showing for each G-20 member with a VAT: (1) the potential revenue gain from raising C-efficiency from its current level, shown in the second column to the higher levels shown in columns 3–7, while keeping the standard rate unchanged;69 and (2) the potential gain from raising the standard rate at unchanged C-efficiency.70 The latter figures assume no behavioral response, and so likely overstate the revenue gain, there being evidence that VAT efficiency falls at higher VAT rates (reflecting perhaps the incentive to greater informality).71
|Current C-efficiency (2006)||Revenue impact (in percent GDP) of increasing C-efficiency to…||Revenue impact (in percent GDP) of 1 point increase in the standard rate|
The gains from increasing C-efficiency, without changing the standard rate, are clearly in many cases very substantial. Indeed, especially where C-efficiency is low, raising this to comparable levels elsewhere is far more revenue productive than even quite large increases in the standard rate. In Italy, for instance, a one point increase in the standard rate would raise around 0.3 percent of GDP; but increasing C-efficiency to the same level as France would raise around 1.5 percent of GDP.
Calculations of this kind do not indicate, however, precisely where such potential improvements in C-efficiency can be found: C-efficiency itself reflects a mix of implementation and design effects. Progress on this can be achieved, however, by noting that C-efficiency can be decomposed as:
So, combining both the VAT compliance gap referred to in the text and a corresponding ‘policy gap.’ The convenience of this is that estimates of any two elements in (2) enable the third to be inferred.
Table 4.2 of the text applies this approach to selected countries by combining C-efficiency measures with estimated VAT compliance gaps,72 the policy gap then emerging as a residual.
In principle, the policy gap can itself be further broken down73 into
where the first term on the right picks up the impact of exemptions (which could in fact increase C-efficiency, since tax cascading means that exempting intermediate products is actually revenue-increasing, if they are used by taxed enterprises) and the latter reflects departures from a uniform rate. This requires more information than is currently available for many countries. But in the United Kingdom, for example, overall C-efficiency can be decomposed into the combined effect of VAT compliance gap of 12.4 percent, an exemption effect of 8 percent (determined based upon the other two elements), and a statutory rate dispersion effect of 48 percent—suggesting that in this case it is the rate structure that is the most promising route for raising substantial additional revenue. Table A.7, while based on incomplete information, shows that other G-20 countries also make extensive use of VAT exemptions and reduced rates. The associated revenue cost in six countries that publish tax expenditures ranges from 0.3 percent of GDP in Canada to 3.2 percent of GDP in Mexico.
|Country||Food||Health||Drugs||Education||Financial Services||Non-profit organizations||Cultural services||Supply of land & buildings||Rent||New dwellings||Maintenance of housing||Public transport||Child care services||Water & sewerage services||Children’s clothing||Books & newspapers||Domestic Fuel||Agricultural products||Regions||Tourism||Total expenditures…|
|…As % total||…As % GDP|
|China, P.R.: Mainland||Most supplies of services and immovable property, including construction, are outside scope of VAT. Subject to 5% non-deductible Business Tax.|
|India||Central government VAT applies to services. State level VAT applies to goods.|
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