- International Monetary Fund. European Dept.
- Published Date:
- November 2015
|Real GDP Growth||Real Domestic Demand|
|Real Export Growth|
(goods and services)
|Real Private Consumption|
|Central and Eastern Europe1||1.2||3.1||3.4||3.1||0.2||4.1||3.2||3.5||4.0||6.6||5.9||5.8||0.6||2.4||3.1||3.1|
|Bosnia and Herzegovina||2.5||1.1||2.1||3.0||0.6||3.2||2.0||3.4||8.2||4.6||5.2||7.0||2.4||2.4||2.6||3.3|
|European CIS countries1||1.2||0.0||−4.3||−0.4||1.5||−1.9||−13.2||−0.7||2.6||−1.1||1.7||−0.9||5.2||0.4||−10.7||0.4|
|New EU member states1,4||1.6||2.8||3.2||3.1||0.1||3.6||3.1||3.6||6.3||6.4||5.9||5.5||0.7||2.7||3.4||3.6|
(End of period)
|Current Account Balance to|
|Total External Debt to GDP|
|Central and Eastern Europe1||1.2||0.0||−0.4||1.3||0.8||−0.7||0.4||1.8||0.1||0.2||1.0||0.5||81.0||74.5||78.9||73.7|
|Bosnia and Herzegovina||−0.1||−0.9||0.5||1.1||−1.4||−0.5||1.0||1.6||−5.8||−7.7||−7.7||−7.6||52.2||51.9||55.8||55.9|
|European CIS countries1||6.6||8.6||18.6||9.3||6.3||12.7||16.5||9.0||0.1||2.0||3.9||4.3||40.0||43.1||58.5||59.4|
|New EU member states1,4||1.6||0.1||−0.4||1.0||0.8||−0.5||0.3||1.6||0.1||0.1||0.6||0.1||81.8||74.6||77.1||72.7|
(Percent of GDP)
|General Government Balance||Public Debt|
|Central and Eastern Europe2||−3.5||−3.0||−2.6||−2.3||57.3||54.0||53.9||53.7|
|Bosnia and Herzegovina||−1.9||−3.6||−1.5||−1.2||41.6||44.8||45.5||45.0|
|European CIS countries2||−1.6||−1.4||−5.4||−3.8||17.5||23.6||28.0||28.5|
|New EU member states2,8||−3.2||−2.8||−2.4||−2.3||51.5||50.2||50.4||50.5|
A cyclical adjustment was applied to revenues/expenditures following the disaggregated approach proposed in Bornhorst and others (2011). The purpose of cyclical adjustment is to decompose the overall balance into cyclical and cyclically adjusted components:
where OB is the overall balance, CB is the cyclical balance (the part of the fiscal overall balance that automatically reacts to the business cycle), and CAB is the cyclically adjusted balance (the part of the overall balance that is left after cyclical movements are taken out), expressed in nominal terms. The disaggregated approach computes the cyclically adjusted balance as a function of individual cyclically adjusted revenue and expenditure categories:
where represents the cyclically adjusted component of the i-th revenue category, GCA represents cyclically adjusted primary expenditures, while RNCA and GNCA contain all revenue/ expenditure categories that do not require cyclical adjustment (Girouard and Andre, 2005).
On the revenue side, the elasticity of each revenue category can be decomposed into two factors. The output elasticity of tax revenue (εRi,Y) is the product of the elasticity of tax revenues (Ri), with respect to the relevant tax base (Bi),εRiBi, and the elasticity of the tax base relative to the output gap, εBi,Y:
Applying this decomposition to the computation of cyclically adjusted revenue yields:
Assuming, or deriving, the value of the tax elasticity with respect to its base is the first step. In addition to statutory tax rates, derivation also requires knowledge of the income distribution. The second step is an econometric estimation of the sensitivity of the relevant tax bases with respect to the output gap. This requires specifying macroeconomic proxies for the tax bases. For income taxes and social security contributions a common proxy is the wage bill, for corporate income taxes, the tax base is a measure of corporate profits, whereas private consumption serves as a base for indirect taxes. With these two elasticities at hand, the elasticities of tax revenue with respect to the output gap can be computed. The resulting elasticities of revenue categories with respect to the output gap are usually larger than one for income taxes (reflecting progressivity), around one for indirect taxes (reflecting generally flat indirect (VAT) tax rates), and somewhat smaller than one for social security contributions. For practical reasons, the elasticities of the several revenue components with respect to the output gap were drawn from Girouard and Andre (2005), taking the mid-point of their estimated elasticities. As such, we assume an elasticity of 1.3 for personal income taxes, of 1.5 for taxes on corporate profits, of 0.7 for social security contributions, and of 1 for indirect taxes, including taxes on goods and services and property tax.
Similarly on the expenditure side, the elasticities can also be decomposed into two factors. Current transfers—in particular unemployment benefits—are most likely to display a cyclical behavior owing to the benefit system. In contrast, nominal spending on other items such as wages and goods and services or capital spending is likely to be largely independent of the business cycle, not requiring any adjustment. As with revenues, the elasticities of expenditure with respect to the base can be assumed or derived. For simplicity, we only adjust the expenditure on social benefits, assuming an elasticity of -0.5. For all other expenditure categories, the elasticity relative to the output gap is assumed to be zero. All results in the chapter are robust to changes in elasticities.
The empirical analysis in this chapter covers 76 countries during 1990-2014 including CESEE, as well as other advanced and emerging economies whose 2014 GDP (constant 2005 USD, PPP) is greater than 3.7 billion USD (20th percentile of all advanced and emerging economies), and for which cyclically-adjusted fiscal variables can be computed.
The sample includes the following countries:
CESEE: Bulgaria, Bosnia and Herzegovina, Croatia, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Moldova, Poland, Romania, Russia, Serbia, Slovak Republic, Slovenia, Turkey, Ukraine.
Advanced Europe: Austria, Belgium, Switzerland, Cyprus, Germany, Denmark, Spain, Finland, France, Greece, Ireland, Italy, Luxemburg, Netherlands, Norway, Portugal, Sweden, and United Kingdom.
Other advanced: Australia, Canada, Israel, Japan, New Zealand, and United States of America.
Asia: China, Indonesia, India, Malaysia, Philippines, Singapore, and Thailand.
Latin America and the Caribbean: Argentina, Bahamas, The, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Peru, Uruguay, and Venezuela.
Africa: Kenya, Mauritius, and South Africa.
Middle East and Central Asia: Armenia, Algeria, Egypt, Georgia, Kazakhstan, Korea, Lebanon, Pakistan, and Tunisia.
To compare the budget structure of CESEE countries with that of comparator countries, expenditure and revenue categories are regressed on structural country characteristics. Using the sample of countries defined in Annex V, we estimate equations of the form:
where the index i=1,…,N and t=2008, 2014 are respectively country- and time-indicators. In Eq. (1), Fiscal is a set of cyclically-adjusted expenditure and revenue variables, expressed relative to potential GDP, and X is a set economic characteristics. In order to assess changes to the budget structure since the global financial crisis, Eq. (1) is estimated for two separate years: 2008 and 2014.
Revenues and expenditure, taken from the World Economic Outlook (WEO) Database, refer to consolidated general government, and are cyclically adjusted in percent of potential GDP. In addition, the IMF’s Fiscal Affairs Department Revenue database and Article IV consultation reports were used to fill gaps in the data series. For spending categories, four categories are considered in addition to total spending: public consumption of goods and services, compensation of employees, transfers, and capital spending. For revenues, four categories are considered on top of total revenues: taxes on corporate profits (CIT), taxes on goods and services, social security contributions, and the personal income tax (PIT). Structural country characteristics are from the World Development Indicator Database: GDP per capita (in 2005 USD, PPP), log of GDP, dependency ratio (the ratio of dependents—people younger than 15 or older than 64—to the working-age population—those ages 15-64), trade openness (sum of exports and imports of goods and services to GDP), population density (number of people per sq. km. of land area), and natural resource rents (in percent of GDP).
Annex Table VI.1 below presents the results for spending and revenue categories. Per capita GDP is generally found positively and statistically significantly correlated with expenditure and revenue components, which is supportive of the Wagner’s law. A higher GDP per capita potentially increases the demand for public services in reflection of a higher degree of economic and institutional sophistication, also requiring higher government revenues. The negative coefficient on public investment could, in turn, reflect structural economic transformation (e.g. Turrini (2004)). Economy size (log GDP) appears to be negatively correlated with public investment, but has strong positive correlation with revenues from social contributions and expenses related to transfers. In addition a high dependency ratio tends to be associated with lower expenditure and lower revenues from consumption taxes. Coefficient estimates on trade openness are mostly statistically insignificant, except for revenues from social contributions, which may reflect higher demand for social insurance against external risks in more open economies (e.g. Rodrik (1998)). Population density matters according to the empirical results: higher population density could imply higher urbanization of the economy which helps improve efficiency of public sector operation. Resource rich economies have different budget structures that are broadly reflected in the estimated coefficients: on the revenue side, resource-rich economies tend to collect less from non-resource tax revenues (Crivelli and Gupta, 2014), except for the CIT tax on companies operating in natural resource sectors. On the expenditure side, there is usually high infrastructure investment needs from natural resource sectors.
|GDP per capita||0.278***||0.095***||0.033**||−0.034**||0.108***||0.363***||−0.012||0.172***||0.035*||0.008|
The residuals from the estimated equations on revenue and expenditure components are used to assess budget structures in CESEE relative to their structural characteristics. On the expenditure side, current spending (wages and consumption of goods and services) is relatively high in CESEE as compared to the level consistent with the country’s structural characteristics, except for Turkey. When assessing the changes over time, however, both categories of spending—in particular the public sector wage bill—shows a significant drop in SEE, CIS, and Baltic countries from 2008 to 2014. As for public investment, its level in 2008 appears particularly high in SEE and Turkey, with SEE, CIS, and Baltic countries experiencing a significant drop over time. Transfers, however, have remained high among CEE, SEE, and CIS countries. On the revenue side, many CESEE countries except for CIS countries managed to increase their reliance on taxes on goods and services since 2008, although some countries, such as CEE and SEE, already had relatively high levels. Additionally, CESEE economies have on average brought down CIT revenues, expect for Turkey. Nevertheless, changes in labor income taxes—including social contributions—are moderate, and levels remain high compare to country’s structural characteristics.
Annex Figure 1.Residuals from Expenditure Benchmarking Regressions
Sources: IMF World Economic Outlook database; and IMF staff calculations.
Annex Figure 2.Residuals from Revenue Benchmarking Regressions
Sources: IMF World Economic Outlook database; and IMF staff calculations.
The relationship between revenue and expenditure variables and economic growth is estimated using unbalanced panel data for 76 developing and advanced countries during 1990-2014. The empirical methodology follows that in Afonso and Alegre (2011), in estimating a dynamic growth equation as follows:
where the index i=1,…,N and t=1,…,L are respectively country- and time-indicators (so that αi and μt are country- and time-specific effects). In Eq. (1), y indicates the growth rate of per capita output of country i during year t (yit = ΔlnGDPit), Fiscal is a set of fiscal variables expressed as a percentage of GDP, and X is a set of non-fiscal control variables. Eq. (1) is estimated using ordinary least squares with country and time fixed effects (OLS-FE). The long-term effect of different fiscal variables on growth is captured by . We also investigate whether the effect of revenues and expenditures on growth differs across regions by interacting the variable of interest with regional dummies for CESEE and Advanced Europe.
As described in Kneller et al. (1999), when estimating the impact of each spending category on output growth, an omitted variable represents the underlying assumption about how to finance the additional expenditure. In all cases, the omitted variables are the reminder of the public expenditures. Similarly for revenues, the omitted variables are the remaining public revenues. Data are cyclically adjusted, inter alia to prevent reverse causality from growth to revenue/expenditure categories. Feedback effects cannot be excluded as cyclical adjustment is difficult to get right, especially for corporate taxes. Results could also capture things like governments adjusting budgets in response to high/low growth. This said, results do not change materially when varying the set of elasticities used in cyclical adjustment, and neither when using Blundell and Bond (1998) system generalized method of moments estimator (GMM) instead of OLS-FE.
The fiscal variables, taken from the World Economic Outlook (WEO) database, refer to consolidated general government and are expressed as ratios to GDP. In addition, the IMF’s Fiscal Affairs Department Revenue database and Article IV consultation reports were used to fill gaps in the data series. For spending categories, five categories are considered: public consumption (purchase/use of goods and services), compensation of employees, transfers, capital spending, and other expense. For revenues, seven categories are considered: taxes on corporate profits (CIT), taxes on labor income (PIT), taxes on goods and services, taxes on property, social contributions, other tax revenues, and other (non-tax) revenue.
In addition, we have included six control variables: labor force (as a growth rate), private investment (in percent of GDP), terms of trade (as a growth rate constructed from an index series in which the year 2000 takes the value 100), population (growth rate), oil rents (in percent of GDP), and the overall budget balance (in percent of GDP). The inclusion of the production factors related to capital increase (proxied by private investment) and labor force growth follows from the related literature. Population growth may explain output growth. Several studies have suggested the relevance of terms of trade (Odedokun, 2001; Bose et al., 2003; Gupta et al., 2005). Oil rents are included to capture potential negative influence of natural-resource revenues on domestic revenues and expenditures (Crivelli and Gupta, 2014). The unit specific term in our panel model αi takes into account the effect of time-invariant idiosyncratic characteristics of each country, whose impact has been suggested in previous studies, such as the initial levels of GDP or human capital, etc.
Annex Table VII.1 and VII.2 below present the long-term results for different government spending and revenue categories. The coefficients shown there are the estimated computed as explained above. Annex Table VII.1, Column 1 presents the results for public consumption spending. The computed long-run effects for CESEE as well as for advanced Europe show a negative and significant relationship with economic growth. Also a statistically significant and negative coefficient has been estimated for transfers (column 3), while capital spending appears to have a positive and significant relationship to long-term economic growth (column 4). As such, for instance, an increase in public investment by 1 percentage point of GDP, financed by an equivalent decrease in current public expenditure (omitted variables), would increase long-term real per capita GDP growth by about 0.4 percentage points among CESEE countries. For the revenue categories, the estimated coefficients in Annex Table VII.2 point to a negative and significant impact of taxes on corporate profits (column 2) and social contributions (column 4) on growth, while a much smaller and not statistically significant impact of broad-base consumption taxes (column 1) or property tax (column 3).
Results are qualitatively similar for Advanced Europe. Note though that for the “rest of the world”—i.e. countries outside Europe, captured by the base coefficient for each spending/revenue category—some results deviate. Differences to Europe are notable especially on the revenue side, where for the “rest of the world” no category has a significant coefficient. This may reflect heterogeneity—the group contains a diverse set of advanced and emerging economies—or structural characteristics of these revenue systems that are insufficiently captured by the model specification.
In order to assess the overall growth friendliness of CESEE government budget structures, additional assumptions are needed to indentify the marginal impact of revenue and expenditure components on long-term growth. Given the omitted variable assumption used in estimating Eq. (1) above (controlling for total revenue and total expenditure, as well as for the overall budget balance), the parameter estimates of the expenditure and revenue components cannot be directly interpreted as the marginal impact on growth. For example, the impact of a one percentage point increase of a given expenditure component implies in the regressions, a drop of equivalent size in other expenditure components. As a result, the estimated coefficients can only be interpreted as the net impact (net of the impact of reducing other expenditure components) on long-term growth.
We make the following assumptions in order to identify the marginal impact of expenditure and revenue components on long-term growth21:
When computing the net growth impact, the compensating change of other expenditure (revenue) components is equally distributed among other expenditure (revenue) components.
The sum of the marginal impact of expenditure (revenue) components on long term economic growth is zero.
With these additional assumptions, and the estimated coefficients from the regressions on expenditure and revenue components above, a system of equations can be solved separately for revenue (expenditure) components that allows identification of the estimated marginal effects. This transformation results, as expected, in marginal effects on long-term growth that are consistently lower (in absolute value) than the estimated coefficients above.
|Public consumption X CESEE||−0.858*|
|Public consumption X AE||−0.922**|
|Compensation of employees||−0.174|
|Compensation of employees X CESEE||0.115|
|Compensation of employees X AE||0.243|
|Transfers X CESEE||0.207|
|Transfers X AE||0.268|
|Public investment X CESEE||0.106|
|Public investment X AE||0.049|
|Other expense X CESEE||−0.082|
|Other expense X AE||−0.011|
|Overall budget balance||0.216***||0.192***||0.155**||0.194***||0.214***|
|Terms of trade||0.001***||0.001***||0.001||0.001||0.002***|
|Labor force growth||−0.001||0.001||−0.001||0.001||−0.001|
|No. of countries||62||64||58||69||53|
|No. of observations||1089||1108||1015||1233||904|
|Taxes on goods and services||−0.038|
|Taxes on goods and services X CESEE||0.018|
|Taxes on goods and services X AE||0.084|
|Taxes on corporate profits||0.147|
|Taxes on corporate profits X CESEE||−0.824**|
|Taxes on corporate profits X AE||−0.219**|
|Taxes on property||−0.486|
|Taxes on property X CESEE||0.468|
|Taxes on property X AE||0.579|
|Social security contributions||−0.037|
|Social security contributions X CESEE||−0.646**|
|Social security contributions X AE||−0.159*|
|Taxes on Personal Income||−0.078|
|Taxes on Personal Income X CESEE||0.086|
|Taxes on Personal Income X AE||0.271|
|Other taxes X CESEE||0.501|
|Other taxes X AE||0.358|
|Other revenue X CESEE||−0.110|
|Other revenue X AE||−0.091|
|Overall budget balance||0.147**||0.135**||0.151**||0.197***||0.105||0.187***||0.177**|
|Terms of trade||0.001||0.001**||0.001***||0.000||0.000||0.001***||0.001***|
|Labor force growth||0.001||0.001||0.001||0.003||0.001||0.001||0.002*|
|No. of countries||56||59||65||56||44||53||62|
|No. of observations||964||996||1030||994||724||876||1082|
Several CESEE countries underwent sizeable consolidation in the wake of the global financial crisis. This Annex summarizes the main policies taken in countries with the largest fiscal efforts. Overall, many measures went into a growth-friendly direction, broadly corroborating the findings of the quantitative analysis. That said, they also comprised spending measures that came with hardship for certain segments of the population. Some revenue measures—such as sector-specific taxes—may be turn out to be harmful to growth.
Fiscal consolidation started in 2009 in the context of an IMF supported program. Adjustment focused on expenditure consolidation, seeking to contain entitlement and wage costs through cuts in wages and social transfers, parametric reforms to the pension system, including the removal of special pension regimes, and the introduction of a unified wage setting system.
Structural fiscal reforms complemented consolidation, including on the pension system, tax administration, and the public wage framework. A Fiscal Responsibility Law was enacted to streamline budgeting. A multi-year public financial management structure was introduced while limiting intra-year budget revisions. Fiscal rules were introduced to regulate spending, public debt, and the primary deficit. A framework for managing guarantees and other contingent liabilities was approved. The local public finance law was amended to bolster fiscal discipline. Reform implementation was uneven though, particularly in the areas of revenue administration and health care reform.
Wage bill cut (2 percent of potential GDP, cyclically adjusted): A key objective was to reduce the public sector wage bill back to the 2007 level through a 25 percent cut in public wages. Public employment was reduced by about 16 percent. The resulting public wage bill in 2014 was consistent with the 7 percent of GDP cap set in Romania’s Fiscal Strategy.
Capital spending cut (2½ percent of potential GDP, cyclically adjusted): efficiency of Romania’s high capital spending had been compromised by the lack of a robust framework and capacity for developing, prioritizing, and executing public-investment projects. Cuts to capital spending focused on non-priority, inefficient projects. In recent years the focus has shifted to improve absorption of EU funds, by strengthening targeting rules and public procurement.
Transfer cuts (0.1 percent of potential GDP, cyclically adjusted): A parametric reform to the pension system was an essential pillar for long-term fiscal sustainability, including also the removal of special pension regimes. Short-term budgetary impact was only marginal, however, with the focus on preserving the scope and size of the safety net system (social protection).
Revenue increases: Only 1/3 of the adjustment was achieved through revenue measures, mostly explained by an increase to the VAT rate from 19 to 24 percent that triggered an increase in yields of about 1 percent of GDP. The modest revenue increase relative to the large VAT rate hike is explained by a weak revenue administration.
Reflecting the early onset of the crisis in Estonia, fiscal consolidation started early in 2008. Supplementary budgets in February and June of 2009 contained consolidation measures of 7½ percent. Many measures were on the revenue side, such as VAT increases and higher excise taxes. Other measures included social benefit reductions, cuts in operational spending, as well as land sales and discretionary spending cuts. Overall, the efforts led to a 2009 fiscal deficit of 1.7 percent of GDP (in ESA terms), which helped paving the way for euro adoption in 2011.
Wage bill and consumption spending cuts (2 percent of potential GDP, cyclically adjusted): Large increases, particularly in current spending, resulted in an ill-timed loosening of fiscal stance in boom years. Fiscal consolidation was aimed at reversing these earlier spending. Cuts in spending in Estonia were possible due to lower rigidities as compared to other Baltic countries.
Transfer cuts (1 percent of potential GDP, cyclically adjusted): Cuts in social transfers reflect lower replacement rates for unemployment benefits.
Revenue collection increases (1½ percent of potential GDP, cyclically adjusted): mostly base-broadening measures. Tax collection held up very well, as a result of improvements in tax administration at the onset of the crisis. Estonia has a revenue-productive and cost-effective tax system, characterized by an internationally acclaimed low compliance burden (with some 90 percent of taxpayers filing electronically). As a result, they achieved a sizeable increased in revenue collection despite only marginal increases to VAT rates (2 percent) and excise taxes.
Bosnia and Herzegovina
Financing constraints triggered fiscal consolidation in 2010-2011. A temporary financing rule restrained spending on capital goods to offset overruns in wage and other current spending. Since 2012, adjustment efforts have increasingly focused on rationalizing public expenditures and on improving the composition of spending. There have also been structural fiscal reforms, including strengthening tax administration and tax compliance, reforms of the system of rights-based benefits; a comprehensive overhaul of the health sector and pension systems; strengthening the medium term budget framework; and streamlining public administration.
Transfer cuts (2½ percent of potential GDP, cyclically adjusted): The largest contribution came from reduction in war-related benefits. As a result of a new privileged pension law in the Federation, benefits of existing war veterans were reduced substantially.
Capital spending cuts (1½ percent of potential GDP, cyclically adjusted): In addition, a temporary financing rule restrained non-priority spending on capital goods, in part explained by delays in official foreign financing.
Tax revenue increases (4 percent of potential GDP, cyclically adjusted): Mostly due to better tax administration and base-broadening measures. Large gains in revenue collection have been explained by a significant effort to strengthen tax administration. Tax compliance measures including among others, a broader exchange of information between collection agencies in the Federation, and compulsory registration of farmers to broaden the tax base for social security contributions have resulted in increased collection of all main taxes without major changes to tax rates.
The Czech Republic reacted to the global financial crisis at first with a fiscal stimulus: in 2007-09, the structural fiscal balance widened by more than 3 percent of GDP, while public debt increased to 38 percent of GDP by 2010. As the crisis intensified, stimulus was withdrawn and followed by large structural consolidation of more than 4 percent of GDP in 2010–13.
Revenue: Mostly due to tax rate changes. Fiscal stimulus at the onset through cutting the CIT rate, resulting in 1 percent of GDP lower CIT revenue collection. Afterwards, graudual increase in the VAT standard rate from 19 to 21 percent and increases in reduced VAT rates, resulting in higher revenue collection by 1½ percent of GDP.
Capital spending cuts (1½ percent of potential GDP, cyclically adjusted):
Nominal freezes in public consumption and wage bill (1½ percent of potential GDP, cyclically adjusted):
In 2008-10, fiscal adjustment was carried out in the context of an IMF–supported program. Consolidation focused on expenditures, seeking to reduce the size of the large public sector. Many expenditure measures were of a structural nature, such as the elimination of 13th-month pensions and wages. From late 2010, the government took increasingly recourse to revenue measures, such as VAT and excise increases, while seeking to reduce public consumption and capital transfers. Sector-specific taxes were levied on banks as well as retail, telecom, and energy firms. During the early phase of consolidation, several structural fiscal measures were implemented, such as the passage of a fiscal responsibility law and parametric pension reforms. However, many of these were reversed later.
Wage bill and transfers cuts (5 percent of potential GDP, cyclically adjusted). Most expenditure measures were of a long-term nature, seeking to reduce the size of the large public sector, resulting in the elimination of the 13th month for pensions and wages.
Capital spending increased. In contrast to other countries, Hungary actually increased capital spending to the tune of 1½ percent of GDP, owing in part to leveraging EU Structural and Cohesion Funds..
Revenue: Mostly tax rate changes and new fees and sector specific taxes. Fiscal stimulus in 2010/11 through reforming the personal income tax to a flat-tax system at 16 percent (lower rate). This came at a significant revenue loss of about 2½ percent of GDP. To compensate for the loss, the government starting in 2010 introduced sector-specific taxes on banks as well as retail, telecom, and energy firms. In addition, an increase in the VAT rate—to become the highest in Europe at 27 percent—was introduced, followed by increases in excise taxes. These last measures resulted in increased revenue collection by about 3 percent of GDP.
Fiscal adjustment began in 2009 and relied mainly on expenditure measures. Spending cuts were roughly proportional to the size of spending categories in total expenditures. However, capital spending supported by EU funds was left untouched so as not to forgo external grants and the attendant growth benefits. On the revenue side, measures focused on indirect taxes and one-off measures. Public spending as a share of GDP is now among the smallest in the EU. Lithuania also has relatively low implicit and statutory tax rates.
Current spending cuts (5½ percent of potential GDP, cyclically adjusted). Evenly distributed among the public sector wage bill, consumption of goods and services, and transfers.
Capital spending increased (0.7 percent of potential GDP, cyclically adjusted). Capital spending supported by EU funds was left untouched lest to forgo external grants.
Revenue collection: A base broadening of social security contribution (by including self employed professions that previously did not pay social contributions) with a positive revenue impact of about 1½ percent of potential GDP. A reduction of the personal income tax rate, which explains deterioration in revenue collection by about 2 percent of potential GDP.
Fiscal tightening was at first mostly carried out through expenditure cuts in the context of an IMF supported program. Measures included a 4 percent of GDP cut in remuneration—by means of a sizeable wage cuts for central government employees—and cuts in public investment. The focus shifted subsequently to revenue-side measures Pension cuts were reversed by the Constitutional Court. Structural reforms such as a Fiscal Discipline Law (FDL) and a Medium-Term Budget Framework were implemented in 2013.
Wage bill cut (3½ percent of potential GDP, cyclically adjusted): through wage cuts for central government employees.
Capital spending (1½ percent of potential GDP, cyclically adjusted)
Revenue increases: Mostly tax rate changes that included a 3 percentage point increase in personal income tax rate (PIT) to 26 percent, a decrease in the tax-free PIT allowance e, which resulted in a revenue gain by about 1½ percent of potential GDP. A VAT increase from 18 to 21 percent resulted in a revenue gain of about 1 percent of potential GDP.
Asset Quality ReviewAUT
Bosnia and HerzegovinaBIS
Bank for International SettlementsBLR
Central and eastern EuropeCESEE
Central, eastern, and Southeastern EuropeCHF
Commonwealth of Independent StatesCZE
European Central BankEIB
European Investment BankEM
Emerging Markets Bond Index GlobalEPFR
Emerging Portfolio Fund ResearchEST
Foreign direct investmentFX
Gross domestic productGRC
Harmonised Index of Consumer PricesHUN
Interest coverage ratioIMF
International Monetary FundITA
Former Yugoslav Republic of MacedoniaMNE
Organisation for Economic Co-operation and DevelopmentPMI
Purchasing Managers IndexPOL
Regional Economic IssuesROU
World Economic Outlook
2005, “The Effect of Unemployment Insurance Sanctions on the Transition Rate from Unemployment to Employment,” Economic Journal, Vol. 115(505), pp 602–630.
2012, “Tax Composition and Growth: A Broad Cross-Country Perspective,” IMF Working Paper No. 12/257 (Washington: International Monetary Fund).
2013, “Can a Government Enhance Long-Run Growth by Changing the Composition of Public Expenditure?” IMF Working Paper 13/162 (Washington: International Monetary Fund).
2011, “Economic growth and budgetary components: a panel assessment for the EU,” Empirical Economics, Vol. 41, pp. 703–723.
2012, “How Does Fiscal Consolidation Impact on Income Inequality?,” Banque de France, Document de Travail 282.
2015, “The Flexible System of Global Models – FSGM,” IMF Working Paper 14/17 (Washington: International Monetary Fund).
2008, “Do tax structures affect aggregate economic growth? Empirical evidence from a panel of OECD countries,” OECD Economics Department Working Paper 643, (Paris: Organization for Economic Co-operation and Development).
1989, “Is Public Expenditure Productive?,” Journal of Monetary Economics, Vol. 23, pp. 177–200.
2013, “The Distributional Effects of Fiscal Austerity,” IMF Working Paper No. 13/151 (Washington: International Monetary Fund).
1992, “Public Finance in Models of Economic Growth,” The Review of Economic Studies, Vol. 59, Issue 4 (October), pp. 645–661.
1998, “Initial Conditions and Moment Restrictions in Dynamic Panel Data Models,” Journal of Econometrics, Vol. 87, pp. 115–143.
1998, “Estimating labor supply responses using tax reforms,” Econometrica 66, pp. 827–861.
2009. “How Productive is Public Capital? A Meta-Regression Analysis,” Working Paper No. 0912, International Center for Public Policy, Andrew Young School of Policy Studies, Georgia State University.
2011, “When and How to Adjust Beyond the Business Cycle? A Guide to Structural Fiscal Balances,” Technical Notes and Manuals 11/02, April (Washington: International Monetary Fund).
2003, “Public expenditure and economic growth: a disaggregated analysis for developing countries,” Centre for Growth and Business Cycle Research Discussion Paper Series 30, University of Manchester.
2014, “Reconciling fiscal consolidation with growth and equity,” OECD Journal: Economic Studies, Vol. 2013/1, (Paris: Organization for Economic Co-operation and Development).
2014, “Resource blessing, revenue curse? Domestic revenue effort in resource-rich countries,” European Journal of Political Economy, Vol. 35, pp. 88–101.
2015, “Base Erosion, Profit Shifting, and Developing Countries,” IMF Working Paper 15/118 (Washington: International Monetary Fund).
2008, “corporate tax elasticities: A reader’s guide to empirical findings,” Oxford Review of Economic Policy24(4), pp. 680–697.
2014, “what do we know about base erosion and profit shifting? A review of empirical literature,” Fiscal Studies35, pp. 421–48.
2009, “Employment and growth in Europe and the US: the role of fiscal policy composition,” Oxford Economic Papers, Vol. 61, pp. 538–565.
1996, “Labor supply response to the earned income tax credit,” Quarterly Journal of Economics111, pp. 605–637.
2012, “The impact of tax cuts on economic growth: Evidence from the Canadian provinces,” National Tax Journal, Vol. 65(3), pp. 563–594.
2005, “Measuring Cyclically Adjusted Budget Balances for OECD Countries,” OECD Economics Department, Working Paper 434, (Paris: Organization for Economic Cooperation and Development).
2005, “Fiscal policy, expenditure composition and growth in low-income countries,” Journal of International Money and Finance, Vol. 24(3), pp. 441–463.
1967, “Tax policy and investment behavior,” American Economic Review57, pp. 391–414.
2014, “ Sovereign CDS Spreads in Europe: The Role of Global Risk Aversion, Economic Fundamentals, Liquidity, and Spillovers,” IMF Working Paper 14/17 (Washington: International Monetary Fund).
2005 “Efficiency of Public Spending in Developing Countries: An Efficiency Frontier Approach,” Policy Research Working Papers 3645 (Washington: The World Bank).
International Monetary Fund, 2013, “Fiscal Adjustment in an Uncertain World,” IMF Fiscal Monitor, April.
International Monetary Fund, 2014a, “Back to Work: How Fiscal Policy can Help,” IMF Fiscal Monitor, October.
International Monetary Fund, 2014b, “Fiscal Policy and Income Inequality,” Policy Paper 23, January.
International Monetary Fund, 2014c, “Budget Institutions in G20 Countries—An Update,” Policy Paper, April.
International Monetary Fund, 2015a, “Fiscal Policy and Long-Term Growth,” Policy Paper, June2015.
International Monetary Fund, 2015b, “Mind the Credit Gap,” Central, Eastern, and Southeastern Europe Regional Economic Issues, May.
International Monetary Fund, 2015c, “Making Public Investment More Efficient,” Policy Paper, June2015.
2008, “Tax and Economic Growth,” OECD Economics Department Working Paper 620 (Paris: Organization for Economic Co-operation and Development).
2003, “Fiscal Relations across Government Levels,” OECD Economics Department Working Paper 375 (Paris: Organization for Economic Co-operation and Development).
1990, “Public Policy and Economic Growth: Developing Neoclassical Implications,” Journal of Political Economy, Vol. 98(5).
1999, “Fiscal policy and growth: evidence from OECD countries,” Journal of Public Economics, Vol. 74(2), pp. 171–190.
2008), “The Political Economy of Fiscal Reform in Central and Eastern Europe,” OECD Journal of Budgeting 2008/3, (Paris: Organization for Economic Co-operation and Development).(
2005, “Tax structure and economic growth,” Journal of Public Economics, Vol. 89(5), pp. 1027–1043.
1997, “On the ineffectiveness of tax policy in altering long-run growth: Harberger’s superneutrality conjecture,” Journal of Public Economics, Vol. 66(1), pp. 99–126.
2002, “Labor supply at the extensive and intensive margins: The EITC, Welfare, and Hours Worked”, American Economic Review, Vol. 92(2), pp. 373–379.
Mulas-Granados Carlos, 2005, “Fiscal Adjustments and the Short-term Trade-off between Economic Growth and Inequality,” Revista de Economía Publica, Vol. 172(1), pp. 61–92.
2012, “Taxing Immovable Property: Revenue Potential and Implementation Challenges,” IMF Working Paper 13/129, (Washington: International Monetary Fund).
2001, “Public finance and economic growth: Empirical evidence from developing countries,” Research Discussion Paper 2001/72, World Institute for Development Economics.
Organization for Economic Co-operation and Development (OECD), 2006, Employment Outlook
1993, “Tax Structure and Growth in a Model with Human Capital” Journal of Public Economics, Vol. 52, pp. 251–271.
1998, “The impact of employment tax cuts on unemployment and wages; the role of unemployment benefits and tax structure,” European Economic Review42, pp. 155–183.
1998, “Why do more open economies have bigger governments?,” Journal of Political Economy, University of Chicago Press, vol. 106(5), pp. 997–1032, October.
2007, “Public capital and economic growth: A critical survey,” Perspektiven der Wirtschaftspolitik, 8(S1), 6–52.
2015, “The Spillover Effects of Russia’s Economic Slowdown on Neighboring Countries” IMF Departmental Paper (Washington: International Monetary Fund).
2000, “Fiscal reform over ten years of transition,” IMF Working Paper 00/113, (Washington: International Monetary Fund).
See “The Spillover Effects of Russia’s Economic Slowdown on Neighboring Countries”, 2015 IMF Departmental Paper.
See the Spring 2015 Regional Economic Issues report for a detailed discussion of the private sector balance sheet adjustment in CESEE.
Figures are drawn from the World Economic Outlook (WEO) database. All aggregates, including expenditure and revenue categories, are adjusted for the business cycle, using a methodology developed by Bornhorst et al. (2011). See Annex IV for the adjustment methodology, and Annex V for countries included in the sample.
The gap is smaller for corporate income tax. High CIT yields are a distinctive characteristic of many developing and emerging economies (Crivelli, Keen and De Mooij, 2015)
Total ageing-related costs are projected to increase, however, reflecting the impact of ageing on issues like health and long-term care expenditures.
In general, expenditure-based fiscal consolidations are found to increase income inequality while revenue-based consolidations are rather neutral (Ball and others, 2013) or may even decrease inequality (Mulas-Granados, 2005).
See Herrera and Pang (2005) for more on Data Envelopment Analysis methodology.
In line with the treatment in Kneller et al. (1999), regressions are run separately for each revenue (expenditure) category and control for total expenditures (total revenues). The implicit assumption is that an increase in one revenue (expenditure) category is, in the long run, offset by a reduction in the other revenue (expenditure) categories. The coefficients should thus not be interpreted as the direct, marginal impact of an increase in a revenue (expenditure) category on growth.
The coefficient is substantially lower than fiscal multipliers typically found for public investment, for example IMF (2014). This is by design: the focus here is, in contrast to multiplier studies, on investment increases offset by cuts in other public spending categories.
All other countries are grouped into one category as “rest of the world” (ROW). The spending regressions tend to display similar results as for Europe, but not the revenue regressions, which fail to report significant coefficients for ROW. This may reflect many things, including heterogeneity within ROW, structural and institutional differences insufficiently captured by the empirical specification, and/or residual or policy feedback.
This result is highly robust and not driven by insufficient cyclical adjustment: even doubling the elasticity of CIT to GDP compared to the base specification (1.5) does not materially change the result.
The end-date of 2014 used in this analysis may overstate somewhat the increase in EU structural and cohesion funds and the corresponding beneficial impact on public investment, as absorption of EU funds is projected to decline after 2015 reflecting a new “program period” (see Box 1.1).
Tax wedge data does not include most Balkan and CIS countries. Many of these countries, however, have increased tax rates on labor income since 2008, such as Albania, Kosovo, and Moldova.
As mentioned earlier, a consistent cross-country functional spending breakdown is not available. Eurostat figures for EU members through 2013 suggest that cuts on education and, especially, health spending have been limited (these numbers arguably include both public consumption and investment).
Prepared by Ernesto Crivelli.
Prepared by Ernesto Crivelli.
Prepared by Haonan Qu and Faezeh Raei.
Prepared by Ernesto Crivelli.
For this analysis, we focus on four expenditure components (wage, goods and services, investment, and transfers), and four revenue components (taxes on goods and services, CIT, PIT, and social contributions). Total expenditure (revenue) is equal to the sum of the four expenditure (revenue) components plus other expenditure (revenue).
Prepared by Ernesto Crivelli and Yan Sun.