Republic of Moldova: Recent Economic Developments
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International Monetary Fund
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Publication Date:
25 Jan 2001
eISBN:
9781451824957
Language:
English
Keywords:
ISCR; CR; Moldova; public spending; debt; enrollment rate; Moldova's performance; illiteracy rate; rate of increase; FDH analysis; Total expenditures; Health care; Health care spending; State budget
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This paper analyzes the recent economic developments in Moldova by reviewing the real, fiscal, and external sectors developments; money banking; and structural policies. The study provides a statistical analysis on the composition of fiscal adjustments in the country, and describes the recent trends in social spending and social indicators in Moldova and in other transition economies in the 1990s, the methodology for estimating efficiency in public spending on education and health care, and assesses the current account determination in the country.

Abstract

This paper analyzes the recent economic developments in Moldova by reviewing the real, fiscal, and external sectors developments; money banking; and structural policies. The study provides a statistical analysis on the composition of fiscal adjustments in the country, and describes the recent trends in social spending and social indicators in Moldova and in other transition economies in the 1990s, the methodology for estimating efficiency in public spending on education and health care, and assesses the current account determination in the country.

IV. The Efficiency of Social Spending in Moldova35

A. Introduction

96. Moldova went through a period of unprecedented fiscal adjustment in 1999, with the commitments deficit of the consolidated general government contracting by nearly 6 percent of GDP relative to 1998. Central to the adjustment effort was a comprehensive rationalization of expenditures, particularly in the social area. Recent pressures have emerged to relax the government’s stance on social spending while, at the same time, improving the quality of publicly-funded social programs. These pressures have highlighted the need for a more in-depth analysis of spending and performance indicators in the formulation of social policies. Against this background, an important policy question is whether or not the ongoing fiscal consolidation efforts have been accompanied by measures to improve the quality and efficiency of public spending on social programs in Moldova, particularly health care and education.

97. Moldova’s performance on education and health indicators compares poorly with other transition economies, despite its higher share in GDP and total government of spending on these programs. The combination of relatively poor education and health indicators and high public spending on social programs suggests inefficiencies in program design and service delivery in the social area. To estimate the efficiency of government spending on health care and education in Moldova, an efficiency frontier is constructed for a sample of transition economies using the Free Disposal Hull methodology—a non-parametric estimation procedure to be described below.36 Moldova’s efficiency in the provision of health care and education services is compared with other transition economies.

98. This chapter is structured as follows. Section B describes recent trends in social spending and social indicators in Moldova and in other transition economies in the 1990s. Section C describes the methodology for estimating efficiency in public spending on education and health care. Section D reports the empirical findings and Section E concludes.

B. Measuring Efficiency in Social Spending: FDH Analysis

99. The efficiency of public spending on social programs can be measured in different ways. Regression analysis offers insights into how efficiently governments provide social services, after controlling for other determinants of social development. However, the elasticities calculated using standard regression analysis suffer from a number of limitations, including the sensitivity of parameter estimates to the functional specification of the reduced-form equations to be estimated. Also, most models from which estimating equations are derived rely on assumptions (on utility maximizing behavior, for instance) that are not easily applicable to public goods.

100. Alternative, non-parametric methods have been developed in recent years to measure efficiency in the provision of public goods and services (see, for example, Tulkens and Van den Eeckaut, 1995).

101. These methods consist of defining an efficiency frontier for the provision of social services treating public spending as an input in a social production function. Outputs are conventionally proxied by social indicators, such as school enrollment rates, illiteracy rates, life expectancy, among others. By using information on both inputs and outputs, the production frontier defines best practices for the production/provision of social outputs and the use of inputs in the set of producers under examination. The tradeoffs in the choice of inputs and outputs is well documented in the literature (Harbison and Hanushek, 1992; Jimenez and Lockheed, 1995). Unlike standard regression analysis, the calculation of these non-parametric efficiency frontiers does not depend on the assumptions used in the theoretical model or the functional specification of the social production function.

102. A widely-used non-parametric method is Free Disposal Hull (FDH) analysis. Accordingly, a producer is efficient in the provision of public goods and services if its combination of outputs and inputs lies near the efficiency frontier constructed for the sample of producers. The analysis allows for the ranking of producers according to their efficiency scores. The only assumption made is that inputs and outputs be freely disposed of; in other words, it is possible with the same production technology to lower outputs while maintaining the same level of inputs, and increasing inputs while maintaining the same level of output.

103. FDH analysis shows that a producer (i.e., the government) is relatively inefficient in the provision of, say, education services if another producer uses less input (public spending) to generate as much or more output (performance indicator). Efficiency is determined as follows. First, the relatively efficient production results are identified for the sample of countries under examination, based on their public spending levels and performance indicators in education and health care. Second, an efficiency score is calculated as the distance of individual production results to the production frontier (FDH). This distance can be calculated from the point of view of inputs and outputs.

104. The input efficiency score is the ratio of inputs used by a given producer A to the inputs used by producer B. This efficiency score indicates the excess use of inputs by the inefficient producer and therefore the extent to which resources are used inefficiently. By the same token, the output efficiency score is the ratio of producer A’s output to that of producer B. This ratio indicates the loss of output relative to the most efficient producer with equal or lower level of inputs. Finally, the producers in the sample are ranked according to their input and output scores. Alternatively, a producer is found to be dominated by other producers that achieve a higher level of output using the same, or lower, level of input (output efficiency); or the same level of output using less inputs (input efficiency). Dominance analysis is useful if the sample of producers is small.

C. Trends in Social Spending and Indicators

105. Moldova’s performance in the public provision of social services compares unfavorably with other transition economies for a wide range of standard health care and education indicators (Table 22).37

Table 22.

Moldova: Health and Education Spending and Indicators in Transition Economies, 1992-97

article image
Sources: Data provided by Moldovan authorities; and Fund staff calculations.

Comprises Albania, Armenia, Azerbaijan, Belarus, Bosnia and Herzegovina, Bulgaria, Croatia, Czech Republic, Estonia, Georgia, Hungary, Kazakhstan, Kyrgyz Republic, Latvia, Lithuania, Macedonia, Moldova, Poland, Romania, Russian Federation, Slovak Republic, Tajikistan, Turkmenistan, Ukraine, Uzbekistan, and Yugoslavia.

The initial observation is 1990 for illiteracy rate, net secondary school enrollment, and access to safe water and sanitation, and 1996 for births attended by health staff.

The initial observation is 1992.

106. With regard to education indicators:

  • The adult illiteracy rate is higher in Moldova than in the average transition economy. However, Moldova has reduced the adult illiteracy rate at a faster pace than other transition economies. This reflects, at least in part, a catch-up effect relative to other transition economies, given Moldova’s higher initial illiteracy rate.38

  • School enrollment rates are comparable in Moldova with the average transition economy. The gross primary enrollment rate is slightly higher than the average for the transition economies in the sample, whereas the gross secondary enrollment rate is slightly lower. Unfortunately, information on net enrollment rates is not available for Moldova. This would allow for a more detailed analysis of the impact of dropout and repetition rates on the gross enrollment rates, particularly in light of Moldova’s higher rate of growth of gross primary enrollment rate in the 1990s, relative to the average transition economy.39 On a positive note, unlike the average transition economy, Moldova’s gross secondary school enrollment rate rose in the period under examination.

107. With regard to health care indicators:

  • Moldova fares better than other transition economies in immunization indicators, with higher immunization rates for both DPT and measles than the average transition economy. Also, on average, Moldova’s rate of increase in the coverage of DPT immunization has outpaced that of other transition economies.

  • Access rates for safe water and sanitation are considerably lower in Moldova than in the average transition economy.

  • Mortality rates are slightly higher in Moldova than in the average transition economy. More importantly, whereas the infant mortality rate increased in the 1990s in Moldova, despite the downward trend in the transition economies, the reduction in the under-five mortality rate was impressive and outpaced the transition economy average reduction in the period.

  • The share of babies born with low birth weight is comparable in Moldova with the average for the transition economies.

  • Life expectancy is lower in Moldova and has fallen more rapidly than in the average transition economy.

108. With regard to trends in health and education spending, Moldova has higher ratios of public health care and education spending to GDP and total government spending than the average transition economy. Also, unlike the average transition economy, there was an increase in these ratios in Moldova between 1992 and 1997 (Figure 11). Nevertheless, these spending indicators have to be treated with caution for several reasons.

  • As in other transition economies, expenditures are recorded on a cash, rather than commitment, basis and include netting operations. This underestimates the size of government when domestic expenditure arrears are accumulated.40 Data on expenditure arrears disaggregated by expenditure function are not readily available, which prevents the construction of an Internationally comparable expenditure data set on a commitment basis for Moldova and other transition economies.41

  • Expenditures within the social sector have often been reclassified in the period under examination. This complicates comparisons over time.42

  • A rise in the ratio of social spending to GDP may reflect the decline in Moldova’s GDP and total government spending in the 1990s, rather than an increase in social outlays over time.

Figure 11.
Figure 11.

Moldova: Health and Education Spending, 1992-1999

Citation: IMF Staff Country Reports 2001, 022; 10.5089/9781451824957.002.A004

Sources: Moldovan authorities; and Fund staff estimates.

D. Efficiency Analysis: The Results

109. With regard to education efficiency scores, Moldova fares poorly compared with other transition economies. In terms of input efficiency, Moldova scores 0.38 and 0.34 respectively when the gross primary school enrollment rate and the gross secondary school enrollment rate are used as the output indicators (Table 23 and Figure 12).43 These scores place Moldova in the last position in the efficiency ranking of the 12 transition economies for which data on gross school enrollment rates are available. As discussed above, these results mean that Moldova could achieve the same, or higher, gross primary (secondary) school enrollment rate using 38 percent (34 percent) of its public spending on education programs.44 Unfortunately, data on net enrollment rates, as well as other education performance indicators, are not available for Moldova, as discussed above.

Table 23.

Moldova: Transition Economies: FDH Analysis

(School Enrollment Rates)

article image
Sources: Data provided by authorities; and Fund staff calculations.
Figure 12.
Figure 12.

Transition Economies: Education Spending and Indicators, 1997 1/

Citation: IMF Staff Country Reports 2001, 022; 10.5089/9781451824957.002.A004

Source: Data provided by authorities; and Fund staff calculations.1/ The line depicts the efficiency frontier.

110. In the case of health care efficiency indicators, Moldova also fares poorly in immunization efficiency, despite its higher coverage rates than the average transition economy (Table 24 and Figure 13). The input efficiency scores are 0.51 and 0.73 respectively for DPT and measles immunization. These scores place Moldova in the 12th and 8th efficiency positions in respectively DPT and measles immunization. The input efficiency score for DPT immunization suggests that the same immunization rate could be achieved using nearly half of the public resources devoted to health care.

Table 24.

Moldova: Transition Economies: FDH Analysis

(Immunization Rates)

article image
Sources: Data provided by authorities; and Fund staff calculations.
Figure 13.
Figure 13.

Transition Economies: Health Indicators (Immunization), 1997 1/

Citation: IMF Staff Country Reports 2001, 022; 10.5089/9781451824957.002.A004

Source: Data provided by authorities; and Fund staff calculations.1/ The line depicts the efficiency frontier.

111. When mortality rates are used as the performance indicators (Table 25 and Figure 14), the FDH analysis shows that the same mortality rates could be reached using nearly half of the public resources devoted to health care. Moldova ranks 13th in the 20 transition economies for which data on infant mortality are available and 12th in the efficiency ranking of transition economies in under-five mortality.

Table 25.

Moldova: Transition Economies: FDH Analysis

(Mortality Rates)

article image
Sources: Data provided by authorities; and Fund staff calculations.
Figure 14.
Figure 14.

Transition Economies: Health Indicators (Mortality Rates), 1997 1/

Citation: IMF Staff Country Reports 2001, 022; 10.5089/9781451824957.002.A004

Source: Data provided by authorities; and Fund staff calculations1/ The line depicts the efficiency frontier.

112. The results reported above show that countries with higher spending levels relative to GDP are relatively less efficient than countries that yield comparable output with less use of inputs. For instance, countries that have education spending patterns skewed towards teachers’ compensation or have higher ratios of teachers to students tend to be less efficient in the provision of education services. Likewise, countries that spend proportionally more resources on expensive curative care programs relative to preventive care will also tend to fare poorly in terms of efficiency scores.

113. The results of the FDH analysis should be assessed with some caution for three main reasons. First, spending data for all countries in the sample, including Moldova, exclude private outlays on health care and education. The exclusion of private outlays underestimates the use of inputs in the provision of social services and therefore overestimates the efficiency of government spending. This upward bias is greater the higher the share of private outlays in total spending. Second, in many countries, public spending data on health care and education exclude subnational outlays. This underestimation of total public outlays overstates efficiency in the provision of education and health care. The upward bias is likely to be greater in countries where subnational governments are important providers of health care and education services. Third, performance in social indicators may be affected by factors other than (public and private) spending. For instance, social development is likely to be correlated with variables such as income levels, poverty incidence, and lagged spending levels, among others. Unfortunately, these explanatory variables cannot be taken into account in non-parametric models.

114. To test the sensitivity of the FDH efficiency scores, a number of options were entertained. First, the analysis was carried out using the ratio of health care and education spending to total government expenditures, rather than GDP. This would correct for the overestimation of social spending in the transition economies that experienced more dramatic contractions in GDP, such as Moldova. The results, not reported but available upon request, confirm the previous findings.

115. The sensitivity of the efficiency analysis was further tested by using both performance indicators in education jointly using the FDH methodology. In this case, the efficiency analysis is carried out for one input (public spending on education) and two outputs (gross primary and secondary school enrollment rates). The results, not reported but available upon request, confirm the previous findings and Moldova still ranks last in terms of input efficiency in the sample of transition economies for which the methodology could be applied. The same one input-two output procedure was used for the mortality and immunization performance indicators and the results, not reported, confirm the findings above.

E. Conclusions

116. The results of the efficiency analysis reported in this chapter suggest that Moldova has used its scare public resources on social programs inefficiently. Compared withother transition economies, Moldova has worse performance indicators and spends a higher share of GDP and total government spending on health care and education programs. The empirical results suggest that the same performance indicators could be achieved with substantially lower spending on social programs.

117. These empirical findings lend support to Moldova’s ongoing efforts to rationalize social spending. Important measures were taken in 1999 (Box 2). With the consolidation of fiscal adjustment, emphasis in social policymaking in Moldova should be shifted from preserving social spending from further retrenchment to a more in-depth assessment of the efficiency and effectiveness of government spending on social programs and the adequacy of the existing programs to alleviate poverty and improve social indicators. Despite the caveats of the efficiency analysis presented in this chapter, the results reported suggest that much remains to be done in ensuring that increases in social spending translate into progress in poverty alleviation and significant improvements in social indicators

Rationalization of Health Care and Education Services

In 1999, measures were taken to rationalize the provision of education services. These include:

  • Employment was reduced in the education sector (from 148,951 in 1997 to 148,463 in 1998), as well as payroll costs (from MdI 307,193 million in 1997 to MdI 284,991 million in 1998).

  • The average number of students per class increased by 0.4 compared to 1998 to 24.1 students per class. Measures were taken to increase class sizes to 20 children instead of 10 in creches; 25 instead of 15 in kindergartens; in primary, secondary, advanced secondary schools, 25 students per class instead of 20; and in colleges and universities, 30 students per class instead of 25. School curricula were changed to reduce the total number of teaching hours per subject in 1998 to 812,771, reflecting a decrease of 51,188 hours relative to 1997.

  • Pre-school fees were increased from 30 to 50 percent of the food costs. In 1998, there were 1,237 pre-schools with enrollment of 108,800 children, against 1,246 pre-schools with 115,996 children in 1997. Budget expenditure on these institutions fell from MdI 1988 million in 1997 to MdI 153.2 million in 1998.

  • Free meals were replaced by cash benefits for students of vocational and professional schools. Accommodation fees were introduced (30 percent of the accommodation costs for undergraduates, and 50 percent of the accommodation costs for post-graduates). Other resident students pay rents at full cost-recovery level.

In health care, key measures include:

  • A number of village hospitals were closed, leading to a reduction in the number of hospital beds. The 1999 budget eliminated 4,000 beds in hospitals funded by local budgets, and 3,000 beds in hospitals funded by the State budget. The saving to the budget was estimated at approximately MdI 70 million in 1999.

  • The Law on Minimum Medical Services Guaranteed by the State was implemented on February 3, 1999. The implementation of this law was reviewed by the Government on July 2, 1999 including the goals achieved by the introduction of medical services guaranteed by the state; the regulation on paid medical services provided to the population; and the formulation of medical services charges and tariffs.

  • Over last five years, the personnel of medical institutions was reduced by 9,266 employees (10 percent), of which 3,944 in 1998. In most cases, downsizing was carried out mainly at the local level and amounted to 8,718 employees over last 5 years, including 3,944 employees in 1998.

References

  • de Mello, Luiz, 1999, Fiscal Federalism and Government Size in Transition Economies: The Case of Moldova, IMF Working Paper No. 99/176 (Washington, D.C.: International Monetary Fund).

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  • Harbison, R. W., and Hanushek, E. A., 1992, Educational Performance of the Poor: Lessons from Rural Northeast Brazil (Oxford: Oxford University Press).

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  • Jimenez, E., and Lockheed, M. E., 1995, “Public and Private Secondary Education in Developing Countries: A Comparative Study,” World Bank Discussion Paper No. 309 (Washington, D.C.: World Bank).

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  • Tulkens, H.; and Vanden Eeckaut, P., 1995, “Non-Parametric Efficiency, Progress and Regress Measures for Panel Data: Methodological Aspects,” European Journal of Operational Research, Vol. 80 pp. 474–99.

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  • World Bank, 1999, Moldova: A Poverty Assessment, Report No. 19846MD (Washington, D.C.: World Bank).

35

Prepared by Luiz de Mello. I am indebted to Emanuele Baldacci for helpful comments and discussions.

36

The data used in the calculation of the efficiency frontiers are available at the World Bank Development Indicators.

37

See World Bank (1999), for more information of education and health care indicators in Moldova.

38

Over a given period of time, countries with lower (worse) initial indicators tend to improve faster than their counterparts with higher (better) initial scores.

39

A wedge between net and gross school enrollment rates indicate high dropout and repetition rates.

40

In 1998, for instance, the accumulation of domestic expenditure arrears reached nearly 5 percent of GDP and constituted an important source of deficit financing in Moldova. Information of the volume of netting operations and other noncash transactions is not readily available before 1998.

41

See de Mello (1999), for more information.

42

For instance, in Moldova, some social assistance programs within the education and health care sectors (e.g., student grants and stipends) have been recorded as other social spending, instead of health care and education.

43

Countries with score equal to 1.0 define best practices for the set of countries under examination. These countries dominate those that produce less output with the same or higher level of input (input efficiency) or use more input to produce the same or lower level of output (output efficiency). These countries define the efficiency frontier, as depicted in Figure 12.

44

Information for illiteracy rates is not available for most countries in the sample. In this case, the efficiency scores would be based on a small sample size. The results of the efficiency analysis using the illiteracy rate as the output indicator are therefore not reported but confirm the findings above.

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Cover IMF Staff Country Reports
Republic of Moldova: Recent Economic Developments
Author:
International Monetary Fund
Volume/Issue:
Volume 2001: Issue 022
Publisher:
International Monetary Fund
ISBN:
9781451824957
ISSN:
1934-7685
Pages:
122
DOI:
https://doi.org/10.5089/9781451824957.002
Figure 11.

Moldova: Health and Education Spending, 1992-1999
Figure 12.

Transition Economies: Education Spending and Indicators, 1997 1/
Figure 13.

Transition Economies: Health Indicators (Immunization), 1997 1/
Figure 14.

Transition Economies: Health Indicators (Mortality Rates), 1997 1/