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Potential distortions from restraining capital spending and goods and services include underinvestment in infrastructure, inadequate teaching aids (such as textbooks or computers), and medical supplies.
This approach is analogous to an aggregated form of performance-based budgeting.
Fiscal data used in this section correspond to the general government sector from Eurostat Government Finance Statistics Template Table. Expenditure ratios are calculated using nominal GDP available from Eurostat. To calculate the sensitivity of spending to economic cycles we use GDP at constant prices from IMF’s World Economic Outlook (WEO). The wage share in 2004 of education, health and social protection is available from Eurostat Task Force on COFOG.
NMS-8 countries include Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Slovak Republic, and Slovenia.
The pattern of results in Table 1 is robust to detrended expenditure data using the Hodrick-Prescott filter.
Nondiscretionary spending is defined as social benefits, interest, compensation to employees, and subsidies.
Data on health and social protection transfers are drawn from the IMF Government Finance Statistics 2001 database. Eurostat provides data by economic classification while the IMF database provides data by functional classification. Education spending data is obtained from the UNESCO Institute for Statistics. Outcome indicators in the health, education and social protection areas are drawn from a variety of sources. Health outcome measures are obtained from the World Health Organization’s Core Health Indicators and World Health Statistics 2005. The at-risk-of-poverty measures are taken from Eurostat’s Population and Social Conditions. Primary and tertiary education outcomes are drawn from UNESCO while for secondary education we use the Trends in International Mathematics and Science Study (TIMSS) mathematics test scores. Table A1 summarizes the coverage of countries and time periods of key input and output/outcome data.
In practice, many factors affect the link between public spending and performance. Simar and Wilson (2007) outline a second stage bootstrapping procedure to control for these factors.
The input- and output-based efficiency scores are equal assuming constant returns to scale. The DEA models in this paper permit variable returns to scale given the sharp decrease in outcomes at higher spending levels. See Zhu (2003) for a detailed technical treatment of the DEA approach.
For instance, differences in geography could affect the efficiency of motorway investment, as a mountainous country could spend more per kilometer while still operating efficiently. Similarly, countries with higher initial GDP per capita levels tend to have better technology and stronger initial education and health outcomes.
In principle, the health spending input should be directly related to the performance indicator. For example, health spending on reducing child mortality should be linked to results in reducing child mortality rates. However, such disaggregated data on health spending are not available for most countries in the sample.
The maternal mortality rate is measured per 100,000 births. There are only about 18,000 births each year in Slovenia. As a result, a single outlier could result in sharp swings.
As the cost of voluntary health insurance for co-payments currently depends only on earnings rather than risk characteristics such as age and lifestyle, the private system is comparable to charging a higher social contribution rate through the compulsory insurance system. This was also a conclusion of the 2003 white paper on health care reform. Private insurers also face moral hazard, adverse selection and higher administrative costs compared to the mandatory insurance fund. This explains the need for a complex risk-adjustment mechanism that compensates private insurers for the risk attributes of their customers. For instance, the current rate structure pools risk so that younger workers subsidize older beneficiaries. However, companies with younger customers on average earn greater profits under this pooled-risk system, which requires compensating transfers between insurance companies.
The pupil-teacher ratio is a proxy for an outcome indicator, such as quality or effectiveness of primary education.
Based on the U.S. Department of Education’s Trends in Mathematics and Science Study (TIMSS).
The NMS-8 countries with available TIMSS scores include Estonia, Hungary, Latvia and the Slovak
With about 900 schools, educational facilities represent about half of all public sector institutions.
Secondary schools are more advanced in this direction, as they are more firmly under central government control.
The outcome indicator is calculated as the percentage point difference in the proportion of the population at risk of poverty before and after social protection transfers. An alternative approach would be to use the percent reduction in the ratio of the population at risk of poverty before and after transfers. However, this would treat a decline from 10 to 5 percent of the population equivalently to a decline from 30 to 15 percent. In the Slovenian context, the rate of poverty risk before transfers is almost the lowest in the sample while the level of social spending is relatively high, which motivates our focus on the percentage point reduction in poverty risk.
Income is defined as market earnings, pensions and nongovernment receipts, such as gifts and property sales. Transfers include social and unemployment benefits.
The output gap is measured using the Hodrick-Prescott (1997) filter on logged real GDP. This approach is consistent with the EC methodology until 2002 and Schadler and others (2005). The HP filter is also applied to primary spending as a percent of GDP to remove stochastic trends that would bias the results in Table 2. Regression analysis would be unreliable in estimating the relationship between primary spending and the output gap, given the limited number of time-series observations for most NMS-8 countries (11 or fewer) and significant structural shifts during the 1990s that could lead to spurious results in small regression models.
While primary spending appears relatively volatile in the NMS-8 countries compared to the EU-15 (Table 2), this could reflect structural as well as cyclical factors.
The DRG system was implemented during 2002-04 and is now operating in all 19 acute-care hospitals.
There is also a minimum service requirement, however most service providers easily fulfill this condition. Deviations from budgeted compensation also depends on an incentive and penalty scheme to discourage an overprescription of medication and over-referral of patients to secondary care specialists relative to the norm. Although individual compensation varies by 50 percent, overall health spending is generally within 3 percent of the budget target.
Although there might be strong efficiency-oriented reasons to structure health care financing in this manner as discussed in section IV, the implication of the arrangement is that the funding mechanism limits the scope to reduce health care spending in the short term on a discretionary basis. This problem points to a potential tradeoff between greater budget flexibility and efficiency in some circumstances.
The social agreement approach to collective bargaining is not without benefits, as the previous agreement restrained real wages below productivity growth to facilitate a smooth adoption of the Euro.