Chapter

Chapter 2 Curbing Corruption

Author(s):
International Monetary Fund. Fiscal Affairs Dept.
Published Date:
April 2019
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Introduction

Corruption—the abuse of public office for private gain—distorts the activities of the state and ultimately takes a toll on economic growth and the quality of people’s lives. It weakens key functions of the public sector, including the ability to collect taxes or to make expenditure choices in a fair and efficient way. If, in exchange for bribes, civil servants facilitate tax evasion or corrupt politicians provide ad hoc tax breaks for some people or firms, others will end up facing higher tax rates, and the government may be unable to generate enough revenue to pay for productive spending. Likewise, the quality of public services and infrastructure suffers when project selection reflects opportunities for kickbacks or nepotism. Bribery of foreign officials by multinationals and the use of opaque financial centers, or secrecy jurisdictions, to hide corrupt gains or to evade taxes add a global dimension to the challenge.1 Against this backdrop, and by contributing to growing inequality, corruption undermines trust in government and can lead to social and political instability.

The widespread acknowledgment that tackling corruption is critical for macroeconomic performance and economic development has led to its inclusion in the United Nations Sustainable Development Goals; it has also prompted several initiatives, including the Framework for Enhanced IMF Engagement in Governance (IMF 2018).2 This chapter assesses the fiscal costs of corruption and explores the practices and institutions in the fiscal area that can help curb opportunities and incentives for corruption.

Corruption’s hidden nature and diverse manifestations make it hard to measure, posing challenges to systematic analysis. To gauge the prevalence of corruption across countries and over time, most assessments rely on indirect measures based on perceptions by political experts or those conducting business in the country, or surveys of the experiences of corporate employees or ordinary people.3 Although these measures are imperfect and need to be interpreted with caution, they reveal two important patterns in the data.4 First, corruption is persistent: over the past two decades, large improvements have been rare and have built on opportunities created by major political changes. In more stable political environments, progress has been gradual, highlighting the need for perseverance over many years or even decades. Second, perceptions of control of corruption are positively correlated with GDP per capita (Figure 2.1). This raises the question of whether reduced corruption is a cause or a symptom of economic development, or whether both reflect stronger institutions or other factors. Fully disentangling the links between corruption, institutions, and fiscal outcomes may not be feasible. Even so, the country experiences presented in this chapter, complemented with cross-country analysis, provide suggestive evidence on the ways in which policymakers can reduce vulnerabilities to corruption.

Figure 2.1.Perceptions of Corruption over Time and at Different Income Levels

Sources: IMF, World Economic Outlook database; and Worldwide Governance Indicators.

Note: The Control of Corruption Index provides a relative measure of perceived corruption that ranges from –2.5 (high corruption) to 2.5 (low corruption). Panel 2 shows the logarithm of GDP per capita in PPP-adjusted US dollars. p = p value; PPP = purchasing power parity; r = coefficient of correlation.

More specifically, this chapter has three main goals:

  • Raise the veil on how corrupt activities affect government decisions and operations: Corruption can pervert the drafting of laws and the core operations of the state, such as collecting taxes, building roads, or managing public schools or hospitals.
  • Assess the fiscal costs of corruption: Corrupt activities can lead to leakages of public money. Governments will collect less tax revenues and pay too much for goods and services or for investment projects. But the cost of corruption is larger than the sum of the lost money: distortions in spending priorities undermine the ability of the state to promote sustainable and inclusive growth.
  • Highlight the core elements of an effective fiscal governance framework: The chapter discusses how fiscal institutions can strengthen integrity and accountability in the public sector. It provides evidence based on the analysis of new data on a large set of fiscal institutions and individual country experiences.5

In view of corruption’s persistence, curbing corruption is a challenging endeavor requiring persevering with efforts on many fronts. As documented in the chapter, with opportunities for funds to leak at myriad points as they flow through the public sector, plugging a few holes would simply lead wrongdoers to exploit other vulnerabilities. Indeed, the chapter’s findings highlight the importance of a comprehensive approach and the need for several institutions to complement one another. The following lessons are also identified:

  • Politicians need to take a stand to fight corruption. It is vital for heads of agencies, ministries, and public enterprises to promote ethical behavior by setting a clear tone at the top.
  • Countries need to invest in a high degree of transparency and independent external scrutiny. This will allow audit agencies and the public at large to provide effective oversight and promote accountability.
  • To reduce opportunities for corruption, institutions need to be upgraded continuously, to keep pace with new challenges as technologies and opportunities for wrongdoing evolve. It is necessary to ensure integrity of processes, especially in higher-risk areas (for example, procurement, tax administration, public enterprises), and to promote effective internal controls. The chances of success are higher when countries improve several, mutually supporting institutions. For example, reforms to tax administration will have greater payoff if tax laws are simplified and the scope for discretion by tax officials is reduced.
  • Finally, corruption is also a global problem demanding greater international cooperation to tackle it. For example, countries should be more proactive in combating bribery by national companies that bribe officials in foreign countries, aggressively pursuing anti–money laundering activities, and reducing opportunities to hide corruption proceeds in opaque destinations. There is also room to improve international exchange of information to fight tax evasion, as well as investigate and prosecute corrupt acts.

Corruption and Government: Channels and Fiscal Costs

What Is Corruption?

In this chapter, corruption is defined as the abuse of public office for private gain.6 This implies a focus on corrupt practices involving civil servants or elected officials that are detrimental to the public interest. The private sector is involved in corrupt acts either by being a counterpart—for example, when it obtains a public contract by paying a bribe—or by facilitating the corrupt act (for example, by helping to hide corrupt proceeds).

Fighting corruption requires an understanding of the multifaceted forms through which it operates, including administrative corruption, in which corrupt acts take existing laws and regulations as given; and state capture, whereby politicians or officials accept bribes in exchange for altering legislation or regulation to favor private firms or individuals (Hellman, Jones, and Kaufmann 2000). Depending on the scale of the amounts involved, one can also distinguish between grand corruption (as in the allocation of large investment projects) and petty corruption (for example, bribes to avoid a traffic violation). Drawing on Rose-Ackerman and Palifka (2016), corrupt acts include the following (among others):

  • Payment of bribes (whether offered or extorted) to get public services or to evade taxes (Figure 2.2).
  • Embezzlement and public service fraud, even if not involving bribes. For example, officials may steal money from investment funds, or civil servants may pilfer supplies or neglect their jobs for private sector work.
  • Nepotism or cronyism to benefit family or a particular group.
  • Influence peddling and conflicts of interest, when individuals take advantage of their position in government to extract favors or personal benefits from a government decision. Kleptocracy is the most extreme form of state capture, in which the state is managed to maximize the personal wealth of its leaders.

Figure 2.2.Share of Firms Expected to Pay Bribes to …

(Percent)

Source: World Bank, Enterprise Surveys.

Corrupt activities can be pervasive, and deeply concealed, throughout the public sector. While corruption can have significant negative impacts in other areas, including regulatory and judicial state functions (IMF 2016), this chapter will focus on the fiscal costs. Figure 2.3 illustrates the way corruption causes leakages as funds flow into, through, and out of the public sector. The remainder of this section describes the “hotspots” for corruption and provides evidence regarding its fiscal costs. Beyond the leakage of funds, these effects include the negative impact on the quality of public policies, wasted talent and effort in the private sector as individuals and firms engage in unproductive activities to capture economic rents,7 as well as the loss of revenues that stems from corruption’s harmful effects on economic growth.

Figure 2.3.Corruption Leakages in the Public Sector

Source: IMF staff.

How Corruption Undermines the Funding of the Government

Corruption can harm revenue collection at both the legislative and collection stages.8 For example, the introduction of tax exemptions or other tax loopholes in exchange for bribes reduces revenue potential. Furthermore, a complex and opaque tax system enables corruption by requiring more discretion in its administration (Asher 2001) and by facilitating hidden corrupt dealings. Customs administration is also vulnerable to corruption. In many countries, customs officials enjoy discretionary powers (including the power to delay the clearance of goods) with limited supervision.9 The distortion of tax laws and the corruption of tax officials,10 by reducing trust in the state, weaken the culture of tax compliance.11

A cross-country comparison confirms that government revenues are significantly lower in countries perceived to be more corrupt.

  • The pattern holds among the different country groups (Figure 2.4). For example, among advanced economies, a country in the top 25 percent in terms of control of corruption collects 4½ percent of GDP more in revenues, on average, than a country in the lowest 25 percent. The gap in revenue collection is 2¾ percent of GDP among emerging market economies and 4 percent of GDP among low-income countries.
  • The empirical association between corruption and revenues is confirmed by cross-country econometric analysis, controlling for the level of economic development (Figure 2.5) and other factors. An improvement in the Control of Corruption Index by one-third of a standard deviation (equivalent to the average improvement for those countries that reduced corruption between 1996 and 2017) is associated with an increase of 1.2 percentage points in government revenues as a share of GDP. If that improvement is applied to all countries, the implied increase in total tax revenues could be $1 trillion, or 1¼ percent of global GDP; the gains would be greater considering that lower corruption would raise economic growth, further boosting revenues. It is also important to note that although the dominant effect is likely to be corruption affecting fiscal outcomes, it is also possible that fiscal outcomes have an impact on the indicators of corruption. It is also not possible to fully disentangle the effect of corruption from the quality of institutions. As such, the results could be interpreted as the benefits of improved governance more generally.12

Figure 2.4.Government Revenues and Corruption

Sources: IMF, World Economic Outlook database; and Worldwide Governance Indicators.

Note: The figure shows the average government revenues as a share of GDP (excluding grants) for countries with the lowest levels of corruption (top 25 percent of control of corruption) and highest levels of corruption (bottom 25 percent) for each of these groups: low-income countries, emerging market economies, and advanced economies. It excludes oil exporters, for which oil revenues are a key driver of total revenues. The Control of Corruption Index provides a relative measure of perceived corruption that ranges from –2.5 (high corruption) to 2.5 (low corruption).

Extractive industries stand out as a hotspot of potential corruption. This reflects the large profits associated with oil and mining exploration. More-over, because these government revenues come from export receipts and multinationals and do not involve taxing citizens, there is a tendency for less scrutiny and accountability.13 Areas particularly prone to corruption include the following:

  • Allocation of exploration rights, especially if government officials can exercise discretion without proper vetting, and if secrecy around the terms of the contract prevents governments and companies from being held accountable.
  • Revenue collection, if companies and tax officials have opportunities to negotiate tax payments in exchange for bribes.
  • State-owned enterprises (SOEs) in the natural resources sector, which present specific concerns because they manage a large share of a country’s natural resources. Some may directly negotiate the terms of exploration with foreign corporations (for example, in the case of subcontractor services) with limited oversight. This is one of the most common areas of international corruption. Noncommercial activities of SOEs can also be an area of revenue leakage in the absence of proper vetting.14

Figure 2.5.Corruption and Revenue Collection

Sources: IMF, World Economic Outlook database; and Worldwide Governance Indicators.

Note: Revenue efficiency is calculated based on personal income tax efficiency and value-added tax c-efficiency. It compares what countries collect relative to what they should collect, based on average statutory tax rates. See the online-only Annex 2.1. Both the revenue variables and the Control of Corruption Index are adjusted for GDP per capita. Revenue data is the average of 2015–17 (excludes oil exporters), and revenue efficiency is an average of 2013–16. Control of corruption shows 2017 data. r = coefficient of correlation.

How Corruption Distorts the Use of Public Resources

Corruption affects spending choices and their efficiency at various points in the budget formulation and implementation process. At the budget formulation stage, spending choices can be diverted to projects or activities that offer greater opportunities for kickbacks or spending that is exempt from some controls. Examples include spending on large investment projects or complex defense equipment for which there are limited price comparators. By comparison, in the areas of education and healthcare, it is relatively more difficult for policymakers to levy bribes (Mauro 1998). Indeed, corruption is associated with fewer resources allocated to education or health spending, especially for low-income and emerging market economies (Figure 2.6).

Figure 2.6.Control of Corruption and Public Spending on Education and Health

(Percent)

Sources: IMF, Governance Finance Statistics; and IMF staff estimates.

Note: Percentiles are computed for each country group. See the online-only Annex 2.1.

The budget execution stage is more likely to involve civil servants exploiting weaknesses in the control environment in the purchase of goods and services or the wage and pension bills (for example, “ghost” workers). It could also involve extortion of bribes in providing public services or subsidies. For example, according to one study, subsidies for research and innovation became more effective after an anticorruption campaign in China (Fang and others 2018). Greater opportunities for corruption exist in of-budget spending (usually encompassing extra-budgetary funds—for example, road or oil funds— and SOEs), where controls and external scrutiny are often more lax.15

Purchase of goods and services by the government as part of its current and capital spending is another hotspot for corruption because of its size (13 percent of GDP among Organisation for Economic Co-operation and Development [OECD] countries). It is not surprising that procurement is the government activity with the highest perception of bribery risk (OECD 2013; World Bank 2012b). An analysis based on five sectors in eight EU countries finds that the direct public loss from corruption varied between 7 and 43 percent of the value of individual procurement contracts that were suspected of being corrupt (PwC 2013). These amounts reflect cost overruns, implementation delays, and loss of effectiveness (for example, poor quality). Corrupt activities involved bid rigging, kickbacks, and conflicts of interest.

In procurement, public investment is particularly vulnerable to corruption. Investment projects often have unique features, rendering cost comparisons difficult and thus making it easier to conceal bribes and inflate costs. In addition, projects often require numerous licenses and permits, each one providing an opportunity for bribery. Moreover, projects can be designed in a complex way to prevent competition and facilitate corruption. Some estimates suggest that losses from corruption range between 10 and 30 percent of construction value (Matthews 2016). An investigation in the Canadian province of Quebec also found a widespread bribe-for-contracts scandal in the construction industry involving local politicians, contractors, and organized crime groups.16 Public-private partnerships also present specific challenges because of (1) their complexity; (2) confidentiality clauses in contracts; and (3) frequent renegotiation of contract terms, which opens the door to changes with limited transparency and significant discretion.

The public sector’s activities extend beyond the budget through the operations of SOEs. These companies range from small enterprises owned by local governments providing core public services, to some of the largest companies in the world. The risks of corruption tend to be higher either because these enterprises operate in corruption-prone sectors, including energy, utilities, and transportation, or, more generally, because of weaker controls and conflicts of interest. SOEs may be unduly influenced by civil servants or elected officials over the company’s management for personal benefit. Mismanagement, lending to related entities, and corruption of prudential authorities can also lead to large fiscal costs associated with subsidizing or bailing out public banks—or even private banks (Laeven and Valencia 2012).

The evidence confirms that corruption is one of the main challenges faced by SOEs, including bribes by foreigners:

  • In an OECD survey, 42 percent of SOE respondents reported that corrupt acts or other irregular practices occurred in their company during the past three years (OECD 2018a). Several high-profile corruption probes involving SOEs underscore the risk of abuse of public resources, including Petrobras in Brazil, Elf in France, and Eskom and Transnet in South Africa. Corruption has also been highlighted as a key obstacle to reform of SOEs in Ukraine (OECD 2018c).
  • In addition, the evidence suggests that 80 percent of foreign bribes go to SOE officials (OECD 2014).
  • Cross-country evidence, based on a large SOE data set covering 38 countries, suggests that SOEs’ performance (profitability and efficiency) is weaker in countries with high levels of corruption (Figure 2.7).

Figure 2.7.Corruption and Performance of State-Owned Enterprises

Sources: Orbis; Worldwide Governance Indicators; and IMF staff estimates.

Note: The figure shows performance indicators for state-owned enterprises in the electricity, mining, transport, and water sectors. The database comprises 1,446 firms in 38 countries. The boxes show the median and the 25th and 75th percentiles, while the whiskers show the maximum and minimum values. Countries are divided into high, medium, and low corruption, based on the Control of Corruption Index. Data are from 2000–17.

How Corruption Impairs the Effectiveness of Government Policies

By distorting the incentives of policymakers and civil servants, corruption undermines the quality and effectiveness of government policies. Core public services, such as the provision of quality public infrastructure and education, can be severely hampered (Gupta and others 2000). This, in turn, has a negative effect on governments’ ability to promote economic growth and reduce poverty.

Countries with lower levels of perceived corruption have significantly less waste in public investment projects. To assess waste, this analysis uses a measure of public investment efficiency—that is, the degree to which countries turn public investment spending into physical capital.17 If two countries spend different amounts for a similar output (for example, a mile of two-lane paved road), the country that spends less is more efficient. The difference between a given country and the most efficient one—the efficiency gap—provides a measure of waste, which reflects corruption (for example, cost overruns, bid rigging) and other factors such as weak project design or poor investment allocation. Panel 1 of Figure 2.8 shows that public investment efficiency is positively associated with control of corruption.18 The estimates suggest, for instance, that an emerging market economy in the top 25 percent of the control of corruption scale wastes half as much as one in the bottom 25 percent.19

Figure 2.8.Countries with Less Corruption Have Higher Test Scores and Less Waste in Public Investment

Sources: Patrinos and Angrist 2018; Worldwide Governance Indicators; and IMF staff estimates.

Note: Public investment efficiency is estimated using efficiency frontier analysis and measures inefficiency as the distance to the frontier—that is, the maximum level of output for given levels of inputs. Output is measured by a physical indicator of the volume of economic infrastructure and social infrastructure. Inputs include capital stock and income. Test scores for school-age students are harmonized across sources (and adjusted for GDP per capita). See the online-only Annex 2.1. The Control of Corruption Index provides a relative measure of perceived corruption that ranges from –2.5 (high corruption) to 2.5 (low corruption). r = coefficient of correlation.

The quality of education, measured by test scores, is also positively associated with control of corruption (Figure 2.8, panel 2). This effect can be explained by several factors. In some countries, access to teaching positions in public schools is influenced by bribes or connections rather than merit. In addition, teacher absenteeism is a widespread form of petty corruption in several developing economies (Chaudhury and others 2006). Ferraz, Finan, and Moreira (2012) also find evidence that corruption leakages in education grants have a negative impact on test scores and are associated with higher dropout rates.

Governments’ ability to borrow as well as to manage risks may also be undermined by corruption, together with other institutional weaknesses. By harming revenue mobilization or through outright theft of public assets, corruption makes it more difficult for governments to service their debt obligations. Some studies find that countries with weaker institutions and weaker policies default more often (Fournier and Bétin 2018; Kraay and Nehru 2006; IMF and World Bank 2012).

The Role of Fiscal Institutions: Country Experiences and Lessons

Can fiscal institutions curb corruption? Is it possible to identify specific budget or tax administration procedures that are more effective in this regard? This section—while acknowledging the role of other institutions, including an effective judicial system—explores the potential role of fiscal institutions in reducing vulnerability to corruption. The discussion highlights the main lessons from selected country experiences and cross-country evidence.

Country Cases: Reducing and Containing Corruption

Corruption tends to be persistent. Government agencies, cities, and even countries can get trapped in an environment of pervasive corruption. A public official will be more tempted to accept a bribe when “everyone” takes bribes.20 (The opposite is also true: if corruption is rare, individuals will be less tempted to accept bribes because they face a greater chance of being caught.) Thus, escaping the trap of high corruption is difficult. A few countries—such as Estonia, Georgia, Liberia, and Rwanda—have made significant progress over a relatively short period. In these cases, the authorities seized the opportunity of a major political change. These countries reached a “tipping point,” often as a result of a broad-based domestic consensus or an external push to aggressively fight corruption. Some countries also have been able to sustain levels of corruption lower than their regional or income peers (for example, Chile). These country experiences can provide lessons on how to reduce corruption and improve fiscal and economic outcomes.

Georgia and Rwanda have shown the largest improvements on the Control of Corruption Index since 1996. Both countries have made wide-ranging efforts to overcome a pervasive culture of corruption within a relatively short period. While challenges remain, both countries have achieved remarkable improvements relative to pre-reform periods.

  • Until 2003, Georgia was considered one of the most corrupt countries in the world. Many interactions with the state required bribes, and corruption in tax administration decimated revenue collection. In late 2003, a new government launched an all-out anticorruption campaign. It focused on eliminating corruption in the civil service, reducing the number of regulations, and improving the business environment. To show that they were committed to change, the authorities dismissed the entire traffic police force and arrested high-level officials suspected of corruption.
  • Over the past two decades, Rwanda has enacted several legal and institutional reforms to fight corruption. The anticorruption legal framework includes legislation criminalizing different types of corruption and money laundering. The government also adopted a code of conduct and rules of disclosure for public officials. Several high-ranking officials were dismissed or prosecuted.

Strengthening fiscal institutions has been an integral part of anticorruption reforms.

  • Georgia and Rwanda both undertook major civil service reforms, including reductions in public employment (such as eliminating ghost workers) and increases in wages. The focus has been on establishing competitive, merit-based recruitment. Mandatory asset declarations were introduced in both countries. Public financial management and transparency were enhanced.
  • In Georgia, the tax code was simplified, including elimination of many tax loopholes and a reduction in the number of taxes and import tariffs. One-stop windows were introduced for procedures such as registering businesses and clearing customs. Rwanda undertook tax administration reforms, with significant improvements in collection efforts, auditing procedures, and scrutiny of large taxpayers.

The fight against corruption contributed to improvements in fiscal outcomes. Tax revenues in Georgia increased from 12 percent of GDP in 2003 to 25 percent of GDP in 2008—one of the largest increases recorded for any country, partly due to a new culture of taxpayer compliance (Figure 2.9). Compliance was fostered by renewed trust in government as public services improved, with lower crime rates and fewer power outages. Higher revenues made it possible to clear all wage and pension arrears. In Rwanda, the revenue-to-GDP ratio rose by 6 percentage points (Figure 2.10).

Figure 2.9.Georgia: Tax Compliance Surged with Anti-Corruption Reforms

Sources: Country authorities; IMF, World Economic Outlook database; Worldwide Governance Indicators; World Values Survey; and IMF staff estimates.

Figure 2.10.Rwanda: Tax Revenues Surged with Anti-Corruption Reforms, 1996–2018

(Percent of GDP)

Sources: IMF, World Economic Outlook database; Worldwide Governance Indicators; and IMF staff estimates.

Note: For the years in which Control of Corruption data are not available, an estimate was created from the average of the previous year and the subsequent year.

Sustaining the gains requires constant strengthening and modernizing of institutions.

  • Georgia and Rwanda have continued to take steps to strengthen institutions over the years after the first wave of reforms. For example, Georgia introduced an e-procurement system in 2011, which has made the system more transparent. Rwanda started implementing one in 2016.
  • The need to continue to strengthen institutions over time is also illustrated by other countries that have been able to sustain levels of corruption lower than their peers. One such case is Chile, which has had lower levels of corruption than comparators for decades. Part of the reason is the country’s willingness to respond aggressively to corruption cases by addressing institutional weaknesses. The Auditor General has been one of the institutional pillars in Chile since 1925. Legal reforms in the 1960s aimed to reduce the use of slush funds or pork-barrel spending. Economic reforms in the 1970s and 1980s simplified procedures and reduced the scope for excessive public discretion. In 2003, Chile launched ChileCompra (an electronic procurement system, e-procurement), increasing transparency and accountability. The oversight of public money was further strengthened with the 2009 Transparency Law. More recent advances include a 2016 law on public probity to prevent conflicts of interest in the public sector.
  • Estonia’s strategy of broader and reinforcing reforms over the past two decades also helped reduce corruption. After independence, Estonia undertook an ambitious program of reforms to make the economy more open and business-friendly and to reduce corruption. The judiciary and public administration underwent major transformations and SOEs were privatized. Estonia also embraced digitalization, and 99 percent of state services are now provided online (see the April 2018 Fiscal Monitor). Such reforms, together with the adoption of the Public Information Act in 2000 (Terracol 2015), had a large and positive impact, including on tax administration and promotion of transparency.
  • Liberia’s experience, especially since 2006, demonstrates the possibility of large governance improvements, and fiscal gains, for an aid-dependent country. In the aftermath of the civil war, a donor-supported anticorruption program involving significant reforms of fiscal institutions helped lead to an improvement in corruption perceptions.21 The reforms included promoting the independence of the General Auditing Commission, launching transparent budget processes, establishing the Liberia Anti-Corruption Commission, and ensuring compliance with the Extractive Industries Transparency Initiative (EITI).

Lessons from Policy Experiments: The Right Incentives and Effective Monitoring

Experiences with specific institutional reforms and the growing literature on policy experiments help shed light on how institutional design can affect incentives and monitoring and lead to better policy outcomes. This section highlights some lessons based on the existing literature (see the online-only Annex 2.2).

Institutional design, supported by technology, can create the right incentives to promote greater integrity in government activities.

  • Studies on public procurement show that the design of procedures can have a significant impact on the prices and quality of products. A study for Hungary (Szucs 2017) finds that abandoning an open auction for a negotiation procedure increases corrupt rents, raises the price of every dollar of public spending by 8 cents, and results in a drop in the productivity of selected contractors. In Italy, the introduction of a central procurement agency led to a reduction in waste, measured by the price gap in relation to prices paid by individual public entities. Bandiera, Prat, and Valletti (2009) estimate that corruption accounted for 20 percent of the waste, with the remainder of the gap attributed to inefficiency.22 The introduction of e-procurement in India and Indonesia also increased competition and led to better quality of construction (Lewis-Faupel and others 2016).
  • Some reforms in India show the benefits of digitalization and reducing opportunities for discretion and fraud. For example, the adoption of an electronic platform for managing a social assistance program in India resulted in a 17 percent decline in spending with no corresponding decline in benefits. Similarly, in the state of Andhra Pradesh, the use of smart ID cards that are used to identify beneficiaries of specific programs and improve beneficiaries’ access to information helped reduce leakage by 41 percent relative to the control group.23

A common element of many anticorruption reforms is increasing civil servants’ wages. In theory, this helps by (1) reducing the need for civil servants to request bribes to complement very low wages and (2) deterring corrupt activities by raising the cost of being caught. However, there is insufficient evidence that raising wages by itself can play a prominent role in fighting corruption.

  • Cross-country data provide tentative support that higher wages may help reduce corruption. For a sample of 90 countries, this chapter finds some evidence of a positive association between higher wages and lower corruption (see the online-only Annex 2.1). As noted by An and Kweon (2017), however, solely relying on higher wages to curtail corruption would likely be too costly and insufficient.
  • Country experiences show mixed results, depending on the overall environment and incentives. Studies on absenteeism of teachers and nurses in several developing countries find that the level of wages did not have an impact.24 On performance-related incentives, an experiment in Pakistan also shows the potential for undesirable consequences: while performance-based salaries of tax officials led to a significant increase in tax collection (by as much as 50 percent), bribe requests increased by 30 percent (Khan, Khwaja, and Olken 2015). Some studies suggest that higher wages can be effective if complemented with other institutional features, such as monitoring and sanctions.25

Tax evasion can be fought with the right incentives and by reducing opportunities for corruption. The evidence from policy experiments shows that deterrence approaches improve tax compliance (Hallsworth 2014). For example, a study of taxpayers in Denmark finds that prior audits and threat-of-audit letters have significant effects on self-reported income (Kleven and others 2011). Yang (2008) shows that preshipment inspections of containers increase import duty collection by 15–30 percentage points.26 In Tajikistan, introducing e-fling led to lower compliance costs, and tax payments doubled among firms previously more likely to evade, probably by disrupting collusion with officials (Okunogbe and Pouliquen 2018).

Monitoring and credible sanctions are another element on the anticorruption agenda. For example, audits can decrease costs of public purchases (Di Tella and Schargrodsky 2003), and performance monitoring helps improve the performance of public sector workers (Banerjee and others 2012). Several studies in Brazil show that increased audit risk or having been audited in the past tends to deter future corruption in subnational governments (Ferraz and Finan 2008; Zamboni and Litschig 2018). Muralidharan and others (2017) also find that increased frequency of inspections can help reduce teacher absenteeism. However, to be effective, audits may need to be supported by sanctions or other forms of penalties (Olken 2007).

Providing more information on public programs can help promote greater accountability. More transparency appears to be particularly effective when supported by the media and fostered by civil society participation. For example, in Brazil, the results of audits of municipalities have a significant impact on the reelection prospects of officials suspected of misuse of public money, but these effects were larger in areas with local radio stations. Similarly, two experiences in Uganda illustrate (1) the positive impact of information on local officials’ use of education grants; and (2) how community monitoring, together with the provision of “report cards” on the performance of health facilities, improved health outcomes. The introduction of ID cards for recipients of a social program in Indonesia, which displayed the copay to be paid by beneficiaries, led to a significant reduction in leakages (likely as a result of corruption) and a 26 percent increase in actual received benefits in villages with the new ID cards.27

Cross-Country Evidence

The case studies suggest that fiscal institutions can play a role in preventing and containing corruption. To assess whether these results hold more broadly, the chapter now turns to systematic analysis for a larger sample of countries. Some fiscal institutions—such as the quality of procurement systems or tax institutions—refer to specific areas (see the online-only Annex 2.1 for details). Others have an overarching impact on the public sector, such as the degree of fiscal transparency (Figure 2.11), digitalization (e-government), or the degree of administrative burden (red tape) citizens face when dealing with the state. The analysis explores whether these institutional measures are associated with indicators of perceptions of corruption.

Figure 2.11.Fiscal Transparency, Procurement Systems, and Corruption, 2017

Sources: IMF, World Economic Outlook database; International Budget Partnership, Open Budget Index; Worldwide Governance Indicators; and IMF staff estimates.

Note: The Fiscal Transparency Index was built by IMF staff, and the Public Procurement Systems Index is based on the World Bank’s GDP per capita adjusted data. See the online-only Annex 2.1.

Results from the cross-country analysis support the role of fiscal institutions found in the selected country experiences.

  • The analysis of individual institutions one by one shows that they are significantly associated with control of corruption (Figure 2.12). Institutional features for which the relationship holds, controlling for other factors, include tax complexity (time required to pay taxes) as well as other aspects of revenue administration (for example, audits). These results are in line with the view that complex tax laws and weaknesses in tax audits or systems to assess compliance risks lead to higher tax evasion. Fiscal transparency and a lower administrative burden are also correlated with lower corruption.
  • When assessing the impact of institutions together (Online Annex 2.1), the analysis suggests that fiscal transparency is particularly effective when there is more press freedom. The degree of digitalization of the government also has a positive relationship (Andersen 2009; Elbahasawy 2014).

Figure 2.12.Fiscal Institutions and Control of Corruption

Source: IMF staff estimates.

Note: The figure shows coefficients when regressing the control of corruption on different fiscal institutions. For example, the more complex the laws, the lower the control of corruption. Coefficients are shown if they are significant at the 5 percent level. Series are standardized. See the online-only Annex 2.1. CG = central government; PFM = public financial management; VAT = value-added tax.

The cross-country analysis explores complementarities among institutions. For example, complex tax laws may enhance opportunities for corruption, but the outcome will depend on the quality of the tax administration. Or, the ability of good public financial management or procurement processes to prevent corrupt (illicit) behavior may depend on the timeliness and impartiality of judicial proceedings. The analysis of these interactions provides the following insights:

  • Good revenue institutions and lower tax complexity, not surprisingly, reinforce each other; that is, they have a stronger association with lower corruption. Administratively efficient judiciary institutions display complementarities with some fiscal institutions (tax complexity and public financial management). Finally, the results further suggest that fiscal transparency is relevant only when there is press freedom.
  • Furthermore, the analysis indicates that revenue institutions are particularly important (higher correlation with control of corruption) when other institutions are weak.28

The importance of specific institutions also appears to vary depending on the history of corruption. Use of a regression tree approach, which allows for interactions between institutions,29 shows that for countries with a tradition of low corruption, the fiscal institutions that appear more relevant are the degree of digitalization, administrative burden, procurement, and complexity of the tax system (Figure 2.13). For countries that start with a high level of corruption, fiscal transparency and digitalization stand out as key institutional features associated with better control of corruption. Among other institutions, press freedom and the speed of judicial processes are also important.

Figure 2.13.Relative Importance of Fiscal Institutions

Source: IMF staff estimates.

Note: The results show the topmost relevant institutions out of more than 50 variables. See the online-only Annex 2.1. CG = central government.

Promoting Good Governance in the Public Sector

How can countries ensure that fiscal institutions are designed to help fight corruption? The previous sections indicated some of the key elements needed. First, strong political commitment is necessary for comprehensive and profound reforms to broader institutions (encompassing not just fiscal but also effective courts and supervision of the financial sector). Second, countries must ensure integrity of core fiscal operations (tax collection, procurement, management of public enterprises). Third, transparency and external oversight (audit agencies, free press) are needed to promote accountability. Finally, while promoting appropriate incentives, there is also a need to effectively sanction corrupt acts.

Building on the findings of the previous analysis and the experience of countries across the world, the chapter next discusses a comprehensive approach to strengthening fiscal governance (Figure 2.14). Such an approach will help to not only fight corruption but also more generally contribute to reducing tax evasion and waste in public programs and fostering accountability in decision making. The following are key elements of strong fiscal governance, with an emphasis on reducing vulnerabilities to corruption:

  • Overarching, cross-cutting elements that affect all agencies: the legal framework, a professional civil service, and the degree of digitalization (good information technology systems that support management, control, and transparency). An effective system of sanctions is also necessary to ensure good governance
  • Design of the organizational structures and integrity of the processes, especially those that are higher risk, to reduce opportunities for corruption.
  • An effective control framework, including (1) internal controls and internal audits and (2) an independent external oversight
  • Finally, fiscal transparency, a core pillar to ensure accountability and support the other elements of the governance framework.

Fiscal Governance Framework

As illustrated by country experiences and by the many vulnerabilities to leakages, the chances of successfully containing corruption are higher when countries improve several, mutually supporting institutions. When capacity is constrained, governments can prioritize areas of higher risk—for example, procurement or tax administration—but eventually should expand efforts to all the core institutions.

Figure 2.14.Fiscal Governance Framework

Source: IMF staff.

Overarching Legal Framework and Information Systems

County experiences highlight some overarching elements that promote a robust governance framework across the public sector:

  • A legal and regulatory framework clearly defining the accountability, transparency, and control environment for the use of public resources. For example, in Australia, the Public Governance, Performance and Accountability Act of 2013 established a system of governance and accountability for the use and management of public resources for all central government agencies and SOEs. Some countries are also moving toward an ex ante review of new laws (known as “corruption proofing”) to minimize the risk of future corruption (for example, Albania, Lithuania, South Korea).30
  • A professional civil service, based on transparent, merit-based hiring and remuneration procedures. Codes of conduct and financial accountability principles, including conflict of interest guidelines, mandatory reporting of gifts, and declaration of assets and interests accessible to the public, should be in place.
  • Investment in digitalization to improve the integrity of processes and facilitate transparency. Digitalization affects many areas of the government, including e-procurement, transparency (easier access to data), and controls. A core element is a robust and comprehensive integrated financial management information system to reduce human interaction and keep an audit trail of financial transactions. As part of larger reforms, France implemented a comprehensive system of this type for the central government in the 2010s, integrating all budget and accounting processes and strengthening financial controls.31 Governments will also need to invest in technology to fight evolving corrupt practices as new technologies present both a challenge to and an opportunity for the fight against corruption. Governments will need to tackle new threats, including cyberattacks (Kopp, Kaffenberger, and Wilson 2017).

Figure 2.15.Corruption Control and Attitude toward Tax Cheating

Sources: Afrobarometer; Latinobarómetro; Worldwide Governance Indicators; and World Values Survey.

Note: The Control of Corruption Index provides a relative measure of perceived corruption that ranges from –2.5 (high corruption) to 2.5 (low corruption).

Strong Institutions, Mechanisms, and Processes

A key pillar of governance is ensuring integrity in the normal processes across the public sector. Designing sound mechanisms and tools that create appropriate incentives, limit discretion by public servants, and include controls can reduce vulnerabilities to corruption. Most exposed to corruption are processes that involve bank transactions; interactions with third parties (revenue collection, public procurement, and management of SOEs); and recurrent, less-scrutinized operations (such as payments for wages or goods and services).

The ability of revenue administrations to fight corruption and tax evasion depends on the institutional framework of the agency and the broader governance context (Figure 2.15). For example, a study based on interviews with Greek experts on tax administration highlighted impunity and political interventions among the most frequently cited challenges (Antono-kas, Giokas, and Konstantopoulos 2013). In addition, a tax system that is clear, stable, and not overly complex will be easier to administer and harder to evade. Other features that can promote better governance include (1) processes that reduce compliance costs and are based on a risk-based approach, (2) operational independence and effective internal audit and anti-corruption units, (3) revenue administration processes that are digitalized and automated (including automated system of internal controls and risk assessment), and (4) institutional efforts to promote integrity (see the online-only Annex 2.3). For example, Estonia’s Tax and Customs Board is using big data analysis to create risk profiles of tax payment transactions and permit close monitoring of high-risk transactions.32

Tax authorities can also play a critical role in helping fight corruption. Tax crime and corruption are often linked, as criminals do not report income derived from corrupt activities for tax purposes or overreport to launder the proceeds of corruption. As such, tax and law enforcement authorities can benefit from more effective cooperation and sharing of information (OECD and World Bank 2018).

Public procurement and public investment management remain among the most challenging areas. Procurement processes should be competitive and transparent and should allow for fair and effective treatment of complaints. Noncompetitive procedures or unsolicited proposals should be limited and tightly regulated.33 For example, South Africa obtained significant savings on its public-private partner ship program by increasing competition.34 Initiatives in the areas of public procurement and public investment management include the following:

  • A growing number of countries and institutions use alert systems, or “red flags,” to minimize the risk of corruption and fraud in public procurement. The indicators that are more correlated with corruption are large tenders, lack of transparency and collusion among bidders, complaints from nonwinning bids, substantial changes in the project after the award, and a shortened time span for the bidding process (Ferwerda, Deleanu, and Unger 2017). For example, the European Commission assesses performance of procurement across EU countries based on a set of indicators,35 with several countries having unsatisfactory scores in many indicators (Greece, Italy, Portugal, Spain).36
  • An increasing number of countries are adopting e-procurement systems because they promote transparency and efficiency, thus reducing corruption opportunities. Korea has one of the most complete e-procurement systems, covering the entire procurement cycle electronically. A corrupt activity analysis system is in place and suspicious cases are investigated.
  • Investment projects, especially large ones, also require proper oversight in other stages—project planning, selection, and implementation—to ensure that decisions are consistent with the public interest. For example, in Malaysia, the central coordination unit produces weekly monitoring reports, measuring both financial and physical progress of investment projects.

Well-functioning budget and treasury systems are also critical for good management of public money. Budget execution processes should be governed by a strong chain of control throughout the process, with adequate segregation of duties. The budget system should be comprehensive, and borrowing should be centralized and authorized by law. The use of extra-budgetary funds (including donor-financed activities) should be avoided because it tends to involve less-stringent controls and scrutiny, increasing vulnerability to misuse of the funds. Digitalization of wage bill payments, combined with payroll monitoring systems, can help identify irregularities or ghost workers. Treasury systems and bank transactions should be comprehensive and subject to tightly controlled processes. A Treasury single account, consolidating all government receipts and payment transactions, is crucial to monitor and control flows.

Many countries either lack key elements of good corporate governance for SOEs in their laws or do not fully implement such elements in practice. The OECD guidelines on corporate governance for SOEs provide the core international standards.

  • One crucial element is the relationship between the state (as owner) and SOE management. The governance responsibilities of the state (at the national or subnational level) include proper exercise of its ownership duties. This implies monitoring performance regularly and avoiding undue political interference (including addressing conflicts of interest). One challenge has been transparently selecting SOE boards that are independent and qualified. For example, a study of local public utilities in Italy finds that when boards were dominated by politically connected directors, SOE employment was higher and firm performance was worse (Menozzi, Urtiaga, and Vannoni 2012).
  • Another challenge is to fully integrate good corporate governance practices in day-to-day activities, including effective internal controls and risk management systems. Good corporate governance also means ensuring a high degree of accountability through wide-ranging transparency. Even countries that were perceived to have relatively good monitoring and reporting of SOEs activities previously have been struggling with corruption in some of their largest companies, leading to further reforms to improve corporate governance (Brazil, South Africa). In 2017, Transparency International issued a guide to further strengthening corporate governance by committing to specific procedures to reduce corruption risks.

Figure 2.16.Corruption Is a Challenge for Many Resource-Rich Countries

Sources: Natural Resource Governance Institute 2017; and Worldwide Governance Indicators.

Note: Panel 1 shows the corporate governance and transparency scores of the sovereign wealth funds and the size of assets as a percentage of 2016 GDP. Caution is needed in interpreting scores for any individual country as the quality of underlying data can vary across countries and data sources. In panel 2, the boxes show the median as well as the 25th and 75th percentiles, while the whiskers show the bottom and top 5 percent of the data. The definition of resource-rich countries follows the October 2015 Fiscal Monitor. The Control of Corruption Index provides a relative measure of perceived corruption that ranges from –2.5 (high corruption) to 2.5 (low corruption).

The governance challenges of commodity-rich countries—that is, the management of public assets— call for ensuring a high degree of transparency and accountability in the exploration of such resources. Countries should develop frameworks that limit discretion, given the high risk of abuse, and allow for heavy scrutiny (Box 2.1). For example, Mexico adopted high transparency standards to recover public trust in the management of the oil sector.37 At the international level, the EITI has promoted new disclosure standards—both within countries and for foreign companies operating in the sector in a country—and monitors countries’ abidance. Some progress has been made, but only a few countries follow most EITI recommendations.

The sheer size of economic rents associated with natural resources demands especially strong institutional safeguards.38 Such rents create incentives for payment of bribes or even state capture to secure control over the country’s natural wealth. It is then critical to develop a strong institutional framework to manage these resources—including good management of the financial assets kept in sovereign wealth funds—and to ensure that proceeds are appropriately spent. This remains a significant challenge in many resource-rich countries that, on average, have weaker institutions and higher corruption (Figure 2.16). The economic costs (sometimes referred to as the “resource curse”) can be significant (see the October 2015 Fiscal Monitor).

Effective Internal Control Environment

Internal controls and audits are essential to help minimize waste, mismanagement, and corruption. Internal controls need to apply to all activities of the government units, and it is important to set a clear “tone at the top” for integrity. The control environment should be (1) based on risk assessments with corresponding mitigating measures, (2) documented and disseminated, and (3) regularly assessed by both internal and external auditors.

Implementation of an effective control system remains one of the major challenges. The public sector is usually characterized by considerable levels of “formal” controls (such as signatures and approvals), but their efficiency has proved uneven. In the private sector, the Sarbanes-Oxley Act of 2002 in the United States spurred a profound overhaul of financial controls, the oversight role of boards of directors, and the independence of the external auditor after major financial scandals in that country associated with weak governance, fraud, and corruption. The principles in this framework are being gradually adopted by public sectors around the world, especially in EU countries. Even so, weak internal controls continue to undermine the ability to ensure that public money is used properly (Peru, United States).39 More generally, countries are still making progress on core elements, including managerial accountability, independent internal audits, and development of capacity to prevent and detect fraud and corruption.

Independent External Oversight

External scrutiny by supreme audit institutions (SAIs), parliaments, and civil society helps safeguard the integrity of public finances and hold civil servants and elected officials accountable. SAIs certify that public resources are raised and spent in accordance with legal requirements; they also ensure that these activities are accurately reported to the public. Focused audits can help fight corruption by identifying waste and mismanagement. For example, social audits have been in place in India since 2005 to oversee the implementation of a large job guarantee program and to fight corruption in the program. These audits were endorsed and supported by the Indian SAI and relied on the strong and direct participation of citizens. SAIs also help promote integrity by reviewing the reliability of the internal control and audit framework.

Figure 2.17.Many Audit Agencies Are Constrained by a Lack of Resources

(Percent)

Source: International Budget Partnership, Open Budget Index 2017.

Note: SAI = supreme audit institution.

SAIs face challenges in fulfilling their role as independent external auditors. According to a 2014 survey of 177 such institutions (IDI 2014), 40 percent indicated that the executive interfered with their budget process, including unapproved cuts by the Ministry of Finance, undermining their effectiveness and independence (Figure 2.17). The survey also indicated that many SAIs in developing countries need further capacity-building and political support to fulfill their mandates of preventing, detecting, and reporting on corruption.

Transparency Standards

A high degree of transparency allows for more intrusive scrutiny, which is essential to ensure accountability. For example, timely and accurate fiscal reports are critical to monitor budget execution and help detect fraudulent use of public funds. Making fiscal information accessible to the public ensures that the legislature, audit institutions, the media, and civil society groups can effectively perform their oversight roles. In that context, the IMF’s Fiscal Transparency Code sets standards for international good practices in fiscal transparency.40

Transparency practices vary significantly (as shown earlier), with many countries still providing limited or incomplete reporting on their activities. A growing number of countries, recognizing the crucial role of transparency, have established legislation that sets out requirements for public disclosure of information. For example, after misreporting on the state of public finances in New Zealand and Australia in the early 1990s, both countries moved to strengthen fiscal transparency requirements through the Fiscal Responsibility Act and the Charter of Budget Honesty Act 1998, respectively, which mandate standards for disclosure of fiscal information. Some countries are taking advantage of new technologies to increase the availability and timeliness of information. For example, Colombia, Costa Rica, and Paraguay, with the support of the Inter-American Development Bank, use an online platform that allows citizens to monitor the physical and financial progress of investment projects, leading to increases in completion rates and more reporting of irregularities (Kahn, Baron, and Vieyra 2018).

Enforcement

The elements of the governance framework discussed above need to be supported by an effective system to detect and punish corrupt acts. The deployment of tip-off boxes, confidential public hotlines, and feedback mechanisms can encourage reporting of corrupt acts. Whistleblower protections are crucial for those who report misconduct (OECD 2016). Moreover, financial institutions should be obligated to report to their national financial intelligence units when they suspect that a client is involved in corruption or related money laundering. Different institutions and instruments can uncover corrupt transactions. Some SAIs can enforce sanctions, including requiring monies to be refunded and imposing fines, and some have a judicial role (France). Ministries of finance can also enforce a variety of sanctions (for example, administrative, disciplinary). But the main route is criminal enforcement by law enforcement agencies. These often are specialist units (and sometimes agencies) tasked to investigate, prosecute, and adjudicate corruption (Box 2.2). An effective system of sanctions is critically important in creating effective disincentives to corruption, but the system also needs to allow for flexibility to minimize damage to the economy and policy objectives. This has been a challenge, particularly when corruption is detected in large public investments (including public-private partner ships and SOEs). For example, in some Latin American countries, discovery of a corrupt act can lead to suspension of projects in line with a zero-tolerance policy (Michele, Prats, and Revol 2018).41 One possible approach is to continue a project if it is in the public interest, while adopting additional safeguards and still prosecuting and imposing sanctions on corrupt actors (Canada, European Union).

International Cooperation

Corruption is a global challenge with important transnational dimensions: multinational companies offer bribes to facilitate their business abroad; likewise, bribe recipients take advantage of opacity in secrecy jurisdictions, including international financial centers, to hide corruption proceeds. The involvement of multinationals in corrupt acts, in turn, is related to institutional weaknesses in recipient countries and usually involves bribes to obtain contracts or concessions (Figure 2.18).42 Conversely, corruption at home is facilitated by the ability to hide illicit gains abroad—in opaque offshore financial centers. These are estimated to hold about $7 trillion in hidden wealth deposited by individuals—equivalent to 10 percent of world GDP (Damgaard, Elkjaer, and Johannesen 2018). Although not all of these assets are related to corrupt activities, these flows greatly facilitate corruption.

Figure 2.18.Purpose of Foreign Bribes (Percent)

Source: OECD 2014.

International cooperation is an increasingly important element in anticorruption efforts and in building stronger institutions. More countries, especially OECD member countries, have been following the example of the US Foreign Corrupt Practices Act, which makes it an offense for US firms to pay bribes to get business abroad. These efforts include coordinated action through international initiatives, such as the OECD Anti-Bribery Convention. However, enforcement by individual countries has been uneven, and the flow of information between countries is slow and unreliable, making it harder to investigate and prosecute corrupt acts (OECD 2018b).43 Improving the sharing of information on international trade could also help fight corruption in customs.

International institutions and aid donors can also play a role. Donors can promote aid that supports good governance. They can also lead by example by improving transparency in how their aid is used—at present, practices vary greatly across donors.44 International institutions, including the IMF (Box 2.3), have promoted international standards and disseminated country experiences in areas such as transparency and good governance. The Group of 20 and the OECD have developed a new global standard on the automatic exchange of information to fight tax evasion.45 This includes stricter requirements to disclose beneficial owners.

Conclusion

Curbing corruption is a challenging endeavor, but one that can bring substantial benefits. On the fiscal front, less corruption means lower revenue leakage and less waste in expenditures, and higher quality of public education and infrastructure. It also increases the chances of success in meeting the Sustainable Development Goals and restoring trust in government. Whereas major political changes occasionally present opportunities for ambitious reforms and rapid improvements, in most circumstances, progress in fighting corruption is likely to be gradual and requires political will, perseverance, and a commitment to continuously upgrade institutions over many years.

Improving fiscal institutions and practices is essential to enhancing integrity and accountability throughout the public sector. The chances of success are greater when countries improve several mutually supporting institutions to tackle corruption. A fiscal governance framework requires a professional and ethical civil service as a key pillar. It demands assiduously upgrading fiscal processes, such as procurement and revenue administration, as well as internal controls. It also requires embracing high levels of transparency and independent external scrutiny, including by civil society and the media.

The benefits of better fiscal institutions will be enhanced if accompanied by other institutions, such as appropriate legal frameworks, as well as timely and evenhanded enforcement by the courts. Likewise, transparency has a more beneficial impact in the presence of press freedom and an active civil society. Moreover, adopting new technologies, such as digitalization, is key to fighting constantly evolving corruption challenges. For example, e-procurement can be an effective tool to promote greater transparency, increase competition, and reduce the scope for discretionary decisions.

Finally, to fight corruption effectively in a global economy, international cooperation is necessary in several areas, including the design and enforcement of legislation against bribery of foreign officials, transparency in international transactions in the natural resource sector, anti–money-laundering activities and greater international information sharing among the relevant authorities, and a reduction in the opacity of ultimate (or beneficial) ownership of assets abroad. Finally, international institutions can help by promoting dissemination of good practices and peer learning.

Box 2.1.Governance in the Extractive Industries

The IMF Fiscal Transparency Code sets out principles and practices for resource-rich countries at each stage of natural resource management. Areas to reduce opportunities for corruption include:

Allocation and Disclosure of Rights

  • Open and clear procedures for allocating resource rights are fundamental for the extractive industries to develop in an efficient and transparent manner. Procedures should be based on clear objectives, such as finding the most suitable investor to develop the resource (Mexico’s recent licensing rounds).
  • Disclosure of resource rights in a license or contract registry is internationally recognized as best practice (for example, Colombia, Liberia, United Kingdom). The availability of this information makes the government and company accountable to parliament and the public at large. Reducing opportunities for corruption also requires defining fiscal regimes in model contracts and legislation, establishing the variable parameters along with clear qualification and bid evaluation criteria ahead of time, and limiting officials’ discretion in negotiating new contracts, changes to existing contracts, or licensing procedures—for example, by using competitive and open allocation processes.
  • Reporting on beneficial owners of resource rights is emerging as an international norm, with all 51-member countries of the Extractive Industries Transparency Initiative (EITI) having established plans for such disclosure by 2020. As a next step, publication of the associated corporate structure (that is, the chain of intermediaries connecting the beneficial owner and license holder) would ensure complete transparency regarding the ultimate owner of a resource right.

Resource Revenue Administration and Collection

  • Clear resource revenue collection, audit, and compliance procedures are needed to ensure that the correct amounts of revenue are collected. Revenues should be reported at the project level. Several EITI members (Indonesia, Kazakhstan) have made progress in project-level reporting.
  • Governments can enhance transparency by requiring that companies report on all payments to government. The disclosure requirement should extend to any corporate entity engaging in natural resource exploration, extraction, or commodity trading.

National Oil and Mining Companies

  • Awareness of the need to strengthen transparency and governance among state-owned enterprises (SOEs), especially in the extractive sector, is growing. The 2016 EITI Standard outlines the requirements and recommendations applicable to SOEs from participating countries, including disclosure requirements on beneficial ownership, commodity sales, revenue transfers, and quasi-fiscal expenditures.
  • SOEs are increasingly defining clear governance guidelines and codes and publishing information on governance policies and practices (Chile’s Codelco and Brazil’s Petrobras provide such information on their websites). Transparency can be further strengthened with detailed disclosure of quasi-fiscal spending and procurement contract awards, both high-risk areas of mismanagement.

Sovereign Wealth Funds

  • Another challenge is to ensure that the large financial assets included in oil or other sovereign wealth funds are well managed in a transparent way to reduce the potential for misuse. While some sovereign wealth funds are highly transparent in governance and operations (Norway), others—including several major oil exporters in the Gulf—provide little information.
  • Sovereign wealth funds should abide by clearly established rules and governance arrangements, and report regularly on operations and investment performance, with externally audited annual financial statements. The Santiago Principles present a sound basis for the transparency practices of sovereign wealth funds (IWG 2008). Preferably they should not be allowed to undertake extrabudgetary spending.

Box 2.2.Supportive Legal Systems

Robust legal systems for detecting, investigating, and prosecuting acts of corruption are critical to the effectiveness of fiscal governance frameworks. They motivate compliance and discourage criminal behavior, such as violation of the relevant laws, rules, and regulations.

Anticorruption

An effective anticorruption regime includes a sound statutory framework implemented by effective institutions, focusing on detection and investigation, prosecution, and adjudication.

  • These functions often are carried out by the regular law enforcement agencies, sometimes with officers or sections specializing in corruption.
  • Some countries have anticorruption agencies. Most of these agencies are either preventive, repressive, or a hybrid pursuing both objectives (Hong Kong Special Administrative Region, Latvia). Preventive agencies typically provide policy advice and public information. Repressive covers investigation, prosecution, or both. Some have only investigative powers, while others also have prosecution powers.
  • Corruption cases are most often filed before the regular courts, sometimes staffed by specialized judges. However, when faced with judicial corruption, countries may opt for distinct courts (or court units) with distinct procedures, staffing, and other facilities, as well as special safeguards, to process corruption and financial crimes cases impartially and with efficiency.

Anti–Money-Laundering Regimes

The proceeds of corruption must almost always be laundered, that is, made to appear legitimate in order to be spent, transferred, or invested. As such, anti– money-laundering (AML) tools strengthen the deterrent value and effectiveness of “traditional” repressive frameworks by:

  • Helping to detect corrupt practices via the laundering of the related proceeds: The Financial Action Task Force, the global AML standards setter, requires countries to mandate and ensure that financial institutions monitor their customers’ transactions, with special attention to those conducted by “Politically Exposed Persons,”1 and report those that are suspicious.
  • Supporting the investigation of corrupt practices and related money laundering: Countries should conduct financial investigations (“follow the money”) in the case of proceeds-generating crimes and should ensure the transparency of beneficial ownership, typically by requiring that legal entities (for example, opaque investment vehicles) and arrangements (for example, trusts) disclose the names of the natural persons who ultimately own or control them— whether to official registries or to the financial institutions holding their accounts. This can help in the investigation of cases in which public officials steer government contracts to companies that they or their associates own.2
  • Establishing adequate sanctions for convicted officials and their accomplices: First, officials convicted of both corruption and money laundering face more severe penalties. Second, because money laundering is a stand-alone offense, the accomplices of corrupt officials may be convicted of money laundering even if they were not involved in the act of corruption. And third, the sanctions prescribed for money laundering should be “dissuasive,” such that corrupt officials face serious consequences for laundering the proceeds of their crimes.
1 Such as senior politicians, senior government, judicial, or military officials, and executives of state-owned enterprises.2 Nigeria illustrates the importance of transparency with respect to beneficial ownership. In 1998, a former oil minister granted himself the rights to exploit a large oil field by signing them over, right before leaving office, to an ostensibly independent firm that he secretly controlled.

Box 2.3.IMF Work on Fiscal Governance

Over the years, the International Monetary Fund has built up comprehensive diagnostics on the quality of fiscal institutions, supplying a wealth of information on many aspects of fiscal governance, including public financial management and revenue administration. These tools have been part of the IMF’s capacity-building work across its membership. They help strengthen core institutional processes, promote integrity in public administration, and promote fiscal transparency. This work has been undertaken in cooperation with other international institutions (for example, the World Bank) and donors.

Public Investment Management Assessments (PIMAs) help countries evaluate the strength of their public investment management practices.1 They evaluate 15 institutions that shape public investment decision making at three key investment stages: planning, allocation, and implementation. As of February 2019, 51 countries had completed a PIMA, providing a basis to set up a reform plan tailored to each country’s needs.

Fiscal Transparency Evaluations (FTEs) assess fiscal transparency practices against the principles outlined in the Fiscal Transparency Code with a focus on four pillars: (1) fiscal reporting; (2) fiscal forecasting and budgeting; (3) fiscal risk analysis and management; and (4) resource revenue management for specific needs of resource-rich countries. As of February 2019, 25 FTEs were publicly available.2

Other tools in public financial management include the long-established Public Expenditure and Financial Accountability assessment, which has covered many low-income countries, and the Public-Private Partnership Fiscal Risk Assessment Model, which gauges potential fiscal costs and risks arising from public-private partnerships. Another diagnostic tool related to resource revenue management is the Fiscal Analysis of Resource Industries framework, which assists countries in designing fiscal regimes for natural resources.

A similar suite of tools is available to assess the performance of tax and customs administrations. The Ta x Administration Diagnostic Tool (TADAT) is designed to provide an objective assessment of the health of key components of a country’s system of tax administration.3 TADAT assessments identify relative strengths and weaknesses, which helps in setting and prioritizing reform agendas and facilitating external support for reforms. Other IMF diagnostic tools for revenue administration include the Revenue Administration Fiscal Information Tool, which compiles a set of performance indicators, and the Revenue Administration–Gap Analysis Program, which helps countries estimate the size of tax gaps for major taxes; it provides a better understanding of factors affecting the size of, and changes in, those gaps—in particular, those stemming from taxpayer noncompliance.

1https://www.imf.org/external/np/fad/publicinvestment/#3.2https://www.imf.org/external/np/fad/trans/index.htm.3http://www .tadat.org/.
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Country Abbreviations

Code

Country name

AFG

Afghanistan

AGO

Angola

ALB

Albania

ARE

United Arab Emirates

ARG

Argentina

ARM

Armenia

ATG

Antigua and Barbuda

AUS

Australia

AUT

Austria

AZE

Azerbaijan

BDI

Burundi

BEL

Belgium

BEN

Benin

BFA

Burkina Faso

BGD

Bangladesh

BGR

Bulgaria

BHR

Bahrain

BHS

Bahamas, Te

BIH

Bosnia and Herzegovina

BLR

Belarus

BLZ

Belize

BOL

Bolivia

BRA

Brazil

BRB

Barbados

BRN

Brunei Darussalam

BTN

Bhutan

BWA

Botswana

CAF

Central African Republic

CAN

Canada

CHE

Switzerland

CHL

Chile

CHN

China

CIV

Côte d’Ivoire

CMR

Cameroon

COD

Congo, Democratic Republic of the

COG

Congo, Republic of

COL

Colombia

COM

Comoros

CPV

Cabo Verde

CRI

Costa Rica

CYP

Cyprus

CZE

Czech Republic

DEU

Germany

DJI

Djibouti

DMA

Dominica

DNK

Denmark

DOM

Dominican Republic

DZA

Algeria

ECU

Ecuador

EGY

Egypt

ERI

Eritrea

ESP

Spain

EST

Estonia

ETH

Ethiopia

FIN

Finland

FJI

Fiji

FRA

France

FSM

Micronesia, Federated States of

GAB

Gabon

GBR

United Kingdom

GEO

Georgia

GHA

Ghana

GIN

Guinea

GMB

Gambia, Te

GNB

Guinea-Bissau

GNQ

Equatorial Guinea

GRC

Greece

GRD

Grenada

GTM

Guatemala

GUY

Guyana

HKG

Hong Kong Special Administrative Region

HND

Honduras

HRV

Croatia

HTI

Haiti

HUN

Hungary

IDN

Indonesia

IND

India

IRL

Ireland

IRN

Iran

IRQ

Iraq

ISL

Iceland

ISR

Israel

ITA

Italy

JAM

Jamaica

JOR

Jordan

JPN

Japan

KAZ

Kazakhstan

KEN

Kenya

KGZ

Kyrgyz Republic

KHM

Cambodia

KIR

Kiribati

KNA

St. Kitts and Nevis

KOR

Korea

KWT

Kuwait

LAO

Lao P.D.R.

LBN

Lebanon

LBR

Liberia

LBY

Libya

LCA

St. Lucia

LKA

Sri Lanka

LSO

Lesotho

LTU

Lithuania

LUX

Luxembourg

LVA

Latvia

MAR

Morocco

MDA

Moldova

MDG

Madagascar

MDV

Maldives

MEX

Mexico

MHL

Marshall Islands

MKD

Macedonia, former Yugoslav Republic of

MLI

Mali

MLT

Malta

MMR

Myanmar

MNE

Montenegro

MNG

Mongolia

MOZ

Mozambique

MRT

Mauritania

MUS

Mauritius

MWI

Malawi

MYS

Malaysia

NAM

Namibia

NER

Niger

NGA

Nigeria

NIC

Nicaragua

NLD

Netherlands

NOR

Norway

NPL

Nepal

NZL

New Zealand

OMN

Oman

PAK

Pakistan

PAN

Panama

PER

Peru

PHL

Philippines

P LW

Palau

PNG

Papua New Guinea

POL

Poland

PRT

Portugal

PRY

Paraguay

QAT

Qatar

ROU

Romania

RUS

Russia

RWA

Rwanda

SAU

Saudi Arabia

SDN

Sudan

SEN

Senegal

SGP

Singapore

SLB

Solomon Islands

SLE

Sierra Leone

SLV

El Salvador

SMR

San Marino

SOM

Somalia

SRB

Serbia

STP

São Tomé and Príncipe

SUR

Suriname

SVK

Slovak Republic

SVN

Slovenia

SWE

Sweden

SWZ

Swaziland

SYC

Seychelles

SYR

Syria

TCD

Chad

TGO

Togo

THA

Thailand

TJK

Tajikistan

TKM

Turkmenistan

TLS

Timor-Leste

TON

Tonga

TTO

Trinidad and Tobago

TUN

Tunisia

TUR

Turkey

TUV

Tuvalu

TWN

Taiwan Province of China

TZA

Tanzania

UGA

Uganda

UKR

Ukraine

URY

Uruguay

USA

United States

UZB

Uzbekistan

VCT

St. Vincent and the Grenadines

VEN

Venezuela

VNM

Vietnam

VUT

Vanuatu

WSM

Samoa

YEM

Yemen

ZAF

South Africa

ZMB

Zambia

ZWE

Zimbabwe

Glossary

Automatic stabilizers Revenue and some expenditure items that adjust automatically to cyclical changes in the economy—for example, as output falls, revenue collections decline and unemployment benefits increase, which “automatically” provides demand support.

Balance sheet Statement of the values of the stock positions of assets owned and liabilities owed by a unit, or group of units, drawn up in respect of a particular point in time.

Contingent liabilities Obligations that are not explicitly recorded on government balance sheets and that arise only in the event of a particular discrete situation, such as a crisis.

Countercyclical fiscal policy Active changes in expenditure and tax policies to smooth the economic cycle (by contrast with the operation of automatic stabilizers); for instance, by cutting taxes or raising expenditures during an economic downturn.

Coverage of public benefits Share of individuals or households of a particular socioeconomic group who receive a public benefit.

Cyclically adjusted balance (CAB) Difference between the overall balance and the automatic stabilizers; equivalently, an estimate of the fiscal balance that would apply under current policies if output were equal to potential.

Cyclically adjusted primary balance (CAPB) Cyclically adjusted balance excluding net interest payments (interest expenditure minus interest revenue).

Fiscal buffer Fiscal space created by saving budgetary resources and reducing public debt in good times.

Fiscal multiplier Measures the short-term impact of discretionary fiscal policy on output. Usually defined as the ratio of a change in output to an exogenous change in the fiscal deficit with respect to their respective baselines.

Fiscal stabilization Contribution of fiscal policy to output stability through its impact on aggregate demand.

General government All government units and all nonmarket, nonprofit institutions that are controlled and mainly financed by government units comprising the central, state, and local governments; includes social security funds and does not include public corporations or quasicorporations.

Gross debt All liabilities that require future payment of interest and/or principal by the debtor to the creditor. This includes debt liabilities in the form of special drawing rights, currency, and deposits; debt securities; loans; insurance, pension, and standardized guarantee programs; and other accounts payable. (See the IMF’s 2001 Government Finance Statistics Manual and Public Sector Debt Statistics Manual.) The term “public debt” is used in the Fiscal Monitor, for simplicity, as synonymous with gross debt of the general government, unless specified otherwise. (Strictly speaking, public debt refers to the debt of the public sector as a whole, which includes financial and nonfinancial public enterprises and the central bank.)

Liquid assets Assets that can be readily converted to cash.

Net debt Gross debt minus financial assets corresponding to debt instruments. These financial assets are monetary gold and special drawing rights; currency and deposits; debt securities; loans, insurance, pensions, and standardized guarantee programs; and other accounts receivable. In some countries, the reported net debt can deviate from this definition based on available information and national fiscal accounting practices.

Net (financial) worth Net worth is a measure of fiscal solvency. It is calculated as assets minus liabilities. Net financial worth is calculated as financial assets minus liabilities.

Nonfinancial public sector General government plus nonfinancial public corporations.

Output gap Deviation of actual from potential GDP, in percent of potential GDP.

Overall fiscal balance (also “headline” fiscal balance) Net lending and borrowing, defined as the difference between revenue and total expenditure, using the IMF’s 2001 Government Finance Statistics Manual (GFSM 2001). Does not include policy lending. For some countries, the overall balance is still based on the GFSM 1986, which defines it as total revenue and grants minus total expenditure and net lending.

Potential output Estimate of the level of GDP that can be reached if the economy’s resources are fully employed.

Primary balance Overall balance excluding net interest payments (interest expenditure minus interest revenue).

Procyclical fiscal policy Fiscal policy is said to be “procyclical” when it amplifies the economic cycle, for instance by raising taxes or cutting expenditures during an economic downturn.

Progressive (or regressive) taxes Taxes that feature an average tax rate that rises (or falls) with income.

Public debt See gross debt.

Public sector Includes all resident institutional units that are deemed to be controlled by the government. It includes general government and resident public corporations.

Structural fiscal balance Extension of the cyclically adjusted balance that also corrects for other nonrecurrent effects that go beyond the cycle, such as one-of operations and other factors whose cyclical fluctuations do not coincide with the output cycle (for instance, asset and commodity prices and output composition effects).

Methodological and Statistical Appendix

This appendix comprises four sections. “Data and Conventions” provides a general description of the data and conventions used to calculate economy group composites. “Fiscal Policy Assumptions” summarizes the country-specific assumptions underlying the estimates and projections for 2019–20 and the medium-term scenario for 2021–24. “Definition and Coverage of Fiscal Data” summarizes the classification of countries in the various groups presented in the Fiscal Monitor and provides details on the coverage and accounting practices underlying each country’s Fiscal Monitor data. Statistical tables on key fiscal variables complete the appendix. Data in these tables have been compiled based on information available through March 29, 2019.

Data and Conventions

Country-specific data and projections for key fiscal variables are based on the April 2019 World Economic Outlook database, unless indicated otherwise, and compiled by the IMF staff. Historical data and projections are based on information gathered by IMF country desk officers in the context of their missions and through their ongoing analysis of the evolving situation in each country; they are updated on a continual basis as more information becomes available. Structural breaks in data may be adjusted to produce smooth series through splicing and other techniques. IMF staff estimates serve as proxies when complete information is unavailable. As a result, Fiscal Monitor data can differ from official data in other sources, including the IMF’s International Financial Statistics.

Sources for fiscal data and projections not covered by the World Economic Outlook database are listed in the respective tables and figures.

The country classification in the Fiscal Monitor divides the world into three major groups: 35 advanced economies, 40 emerging market and middle-income economies, and 40 low-income developing countries. The seven largest advanced economies as measured by GDP (Canada, France, Germany, Italy, Japan, United Kingdom, United States) constitute the subgroup of major advanced economies, often referred to as the Group of Seven (G7). The members of the euro area are also distinguished as a subgroup. Composite data shown in the tables for the euro area cover the current members for all years, even though the membership has increased over time. Data for most European Union member countries have been revised following the adoption of the new European System of National and Regional Accounts (ESA 2010). The low-income developing countries (LIDCs) are countries that have per capita income levels below a certain threshold (currently set at $2,700 in 2016 as measured by the World Bank’s Atlas method), structural features consistent with limited development and structural transformation, and external financial linkages are insufficient open to be widely seen as emerging market economies. Zimbabwe is included in the group. Emerging market and middle-income economies include those not classified as advanced economies or low-income developing countries. See Table A, “Economy Groupings,” for more details.

Most fiscal data refer to the general government for advanced economies, while for emerging markets and developing economies, data often refer to the central government or budgetary central government only (for specific details, see Tables BD). All fiscal data refer to calendar years, except in the cases of Bangladesh, Egypt, Ethiopia, Haiti, Hong Kong Special Administrative Region, India, the Islamic Republic of Iran, the Lao People’s Democratic Republic, Myanmar, Nepal, Pakistan, Singapore, and Thailand, for which they refer to the fiscal year. For economies whose fiscal year ends on or before June 30, data are recorded in the previous calendar year. For economies whose fiscal year ends after June 30, data are recorded in the current calendar year.

Composite data for country groups are weighted averages of individual-country data, unless specified otherwise. Data are weighted by annual nominal GDP converted to US dollars at average market exchange rates as a share of the group GDP.

For the purpose of data reporting in the Fiscal Monitor, the Group of 20 (G20) member aggregate refers to the 19 country members and does not include the European Union.

In the majority of advanced economies, and some large emerging market and middle-income economies, fiscal data follow the IMF’s 2014 Government Finance Statistics Manual (GFSM 2014) or are produced using national accounts methodology following System of National Accounts 2008 (SNA 2008) or ESA 2010, both of which are broadly aligned with GFSM 2014. Most other countries follow the GFSM 2001, but some countries, including a significant proportion of low-income developing countries, have fiscal data which is based upon the 1986 Government Finance Statistics Manual. The overall fiscal balance refers to net lending (+) and borrowing (–) of the general government. In some cases, however, the overall balance refers to total revenue and grants minus total expenditure and net lending.

The fiscal gross and net debt data reported in the Fiscal Monitor are drawn from official data sources and IMF staff estimates. While attempts are made to align gross and net debt data with the definitions in the IMF’s Government Finance Statistics Manual, as a result of data limitations or specific country circumstances, these data can sometimes deviate from the formal definitions. Although every effort is made to ensure the debt data are relevant and internationally comparable, differences in both sectoral and instrument coverage mean that the data are not universally comparable. As more information becomes available, changes in either data sources or instrument coverage can give rise to data revisions that can sometimes be substantial.

As used in the Fiscal Monitor, the term “country” does not in all cases refer to a territorial entity that is a state as understood by international law and practice. As used here, the term also covers some territorial entities that are not states but whose statistical data are maintained on a separate and independent basis.

Argentina: Total expenditure and the overall balance account for cash interest only. The primary balance excludes profit transfers from the central bank of Argentina. Interest expenditure is net of interest income from the social security administration. For GDP and consumer price index (CPI) data, see the “Country Notes” section in the Statistical Appendix of the April 2018 World Economic Outlook.

Australia: For cross-country comparability, gross and net debt levels reported by national statistical agencies for economies that have adopted the 2008 System of National Accounts (2008 SNA) (Australia, Canada, Hong Kong Special Administrative Region, United States) are adjusted to exclude unfunded pension liabilities of government employees, defined-benefit pension plans.

Bangladesh: Data are on a fiscal year basis.

Brazil: General government data refer to the nonfinancial public sector—which includes the federal, state, and local governments, as well as public enterprises (excluding Petrobras and Eletrobras)— and are consolidated with those for the sovereign wealth fund. Revenue and expenditures of federal public enterprises are added in full to the respective aggregates. Transfers and withdrawals from the sovereign wealth fund do not affect the primary balance. Disaggregated data on gross interest payments and interest receipts are available from 2003 only. Before 2003, total revenue of the general government excludes interest receipts; total expenditure of the general government includes net interest payments. Gross public debt includes the Treasury bills on the central bank’s balance sheet, including those not used under repurchase agreements. Net public debt consolidates general government and central bank debt. The national definition of nonfinancial public sector gross debt excludes government securities held by the central bank, except the stock of Treasury securities used for monetary policy purposes by the central bank (those pledged as security reverse repurchase agreement operations). According to this national definition, gross debt amounted to 77.2 percent of GDP at the end of 2018.

Canada: For cross-country comparability, gross and net debt levels reported by national statistical agencies for economies that have adopted the 2008 SNA (Canada, Australia, Hong Kong Special Administrative Region, United States) are adjusted to exclude unfunded pension liabilities of government employees defined-benefit pension plans.

Chile: Cyclically adjusted balances refer to the structural balance, which includes adjustments for output and commodity price developments.

China: Public debt data include central government debt as reported by the Ministry of Finance, explicit local government debt, and shares—less than 19 percent, according to the National Audit Office estimate—of contingent liabilities the government may incur. IMF staff estimates exclude central government debt issued for the China Railway Corporation. Relative to the authorities’ definition, consolidated general government net borrowing includes (1) transfers to and from stabilization funds, (2) state-administered state-owned enterprise funds and social security contributions and expenses, and (3) of-budget spending by local governments. Defcit numbers do not include some expenditure items, mostly infrastructure investment financed of budget through land sales and local government financing vehicles. Fiscal balances are not consistent with reported debt because no time series of data in line with the National Audit Office debt definition are published officially.

Colombia: Gross public debt refers to the combined public sector, including Ecopetrol and excluding Banco de la República’s outstanding external debt.

Egypt: Data are on a fiscal year basis.

Ethiopia: Data are on a fiscal year basis.

Greece: General government gross debt includes short-term debt and loans of state-owned enterprises.

Haiti: Data are on a fiscal year basis.

Hong Kong Special Administrative Region: Data are on a fiscal year basis. Cyclically adjusted balances include adjustments for land revenue and investment income. For cross-country comparability, gross and net debt levels reported by national statistical agencies for countries that have adopted the 2008 SNA (Australia, Canada, Hong Kong Special Administrative Region, United States) are adjusted to exclude unfunded pension liabilities of government employees, defined-benefit pension plans.

Iceland: Gross debt excludes insurance technical reserves (including pension liabilities) and other accounts payable.

India: Data are on a fiscal year basis.

Ireland: General government balances between 2009 and 2012 reflect the impact of banking-sector support. Fiscal balance estimates excluding these measures are –11.4 percent of GDP in 2009, –10.9 percent of GDP in 2010, –8.6 percent of GDP for 2011, and –7.9 percent of GDP for 2012. In 2015, if the conversion of government’s remaining preference shares to ordinary shares in one bank were excluded, the fiscal balance would be –1.1 percent of GDP. Cyclically adjusted balances reported in Tables A3 and A4 exclude financial sector support measures. Ireland’s 2015 national accounts were revised as a result of restructuring and relocation of multinational companies, which resulted in a level shift of nominal and real GDP. For more information, see “National Income and Expenditure Annual Results 2015,” at http://www.cso.ie/en/releasesandpublications/er/nie/nationalincomeandexpenditureannualresults2015/.

Islamic Republic of Iran: Data are on a fiscal year basis.

Japan: Gross debt is on an unconsolidated basis.

Lao People’s Democratic Republic: Data are on a fiscal year basis.

Latvia: The fiscal deficit includes bank restructuring costs and thus is higher than the deficit in official statistics.

Mexico: General government refers to the central government, social security, public enterprises, development banks, the national insurance corporation, and the National Infrastructure Fund, but excludes subnational governments.

Myanmar: Data are on a fiscal year basis.

Nepal: Data are on a fiscal year basis.

Norway: Cyclically adjusted balances correspond to the cyclically adjusted non-oil overall or primary balance. These variables are in percent of non-oil potential GDP.

Pakistan: Data are on a fiscal year basis.

Peru: Cyclically adjusted balances include adjustments for commodity price developments.

Singapore: Data are on a fiscal year basis. Historical fiscal data have been revised to reflect the migration to GFSM 2001, which entailed some classification changes.

Spain: Overall and primary balances include financial sector support measures estimated to be –0.1 percent of GDP for 2010, 0.3 percent of GDP for 2011, 3.7 percent of GDP for 2012, 0.3 percent of GDP for 2013, 0.1 percent of GDP for 2014, 0.1 percent of GDP for 2015, and 0.2 percent of GDP for 2016.

Sweden: Cyclically adjusted balances take into account output and employment gaps.

Switzerland: Data submissions at the cantonal and commune level are received with a long and variable lag and are subject to sizable revisions. Cyclically adjusted balances include adjustments for extraordinary operations related to the banking sector.

Thailand: Data are on a fiscal year basis.

Turkey: Information on the general government balance, primary balance, and cyclically adjusted primary balance differs from that in the authorities’ official statistics or country reports, which include net lending and privatization receipts.

United States: Cyclically adjusted balances exclude financial sector support estimated at 2.4 percent of potential GDP for 2009, 0.3 percent of potential GDP for 2010, 0.2 percent of potential GDP for 2011, 0.1 percent of potential GDP for 2012, and 0.0 percent of potential GDP for 2013. For crosscountry comparability, expenditure and fiscal balances of the United States are adjusted to exclude the imputed interest on unfunded pension liabilities and the imputed compensation of employees, which are counted as expenditure under the 2008 SNA adopted by the United States, but this is not true for countries that have not yet adopted the 2008 SNA. Data for the United States may thus differ from data published by the US Bureau of Economic Analysis (BEA). In addition, gross and net debt levels reported by the BEA and national statistical agencies for other economies that have adopted the 2008 SNA (Australia, Canada, Hong Kong Special Administrative Region, United States) are adjusted to exclude unfunded pension liabilities of government employees, defined-benefit pension plans.

Uruguay: Data are for the consolidated public sector (as presented in the authorities’ budget documentation), which includes Banco Central del Uruguay, the nonfinancial public sector, local governments, and Banco de Seguros del Estado. In particular, Uruguay is one of the few countries for which public debt includes the debt of the central bank, which increases recorded public sector gross debt.

Venezuela: Fiscal accounts for 2010–23 correspond to the budgetary central government and Petróleos de Venezuela S.A. (PDVSA). Fiscal accounts before 2010 correspond to the budgetary central government, public enterprises (including PDVSA), Instituto Venezolano de los Seguros Sociales (IVSS—social security), and Fondo de Garantía de Depósitos y Protección Bancaria (FOGADE—deposit insurance).

Fiscal Policy Assumptions

Historical data and projections of key fiscal aggregates are in line with those of the April 2019 World Economic Outlook, unless noted otherwise. For underlying assumptions other than on fiscal policy, see the April 2019 World Economic Outlook.

Short-term fiscal policy assumptions are based on officially announced budgets, adjusted for differences between the national authorities and the IMF staff regarding macroeconomic assumptions and projected fiscal outturns. Medium-term fiscal projections incorporate policy measures that are judged likely to be implemented. When the IMF staff has insufficient information to assess the authorities’ budget intentions and prospects for policy implementation, an unchanged structural primary balance is assumed, unless indicated otherwise.

Argentina: Fiscal projections are based on the available information regarding budget outturn and budget plans for the federal and provincial governments, fiscal measures announced by the authorities, and IMF staff macroeconomic projections.

Australia: Fiscal projections are based on data from the Australian Bureau of Statistics; the fiscal year FY2018/19 budgets of the Commonwealth and States and Territories where available; otherwise FY2018/19 mid-year fiscal and economic reviews by States and Territories; and IMF staff estimates and projections.

Austria: Fiscal projections are based on data from Statistics Austria, the authorities’ projections, and IMF staff estimates and projections.

Belgium: Projections are based on the 2018–21 Stability Programme and other available information on the authorities’ fiscal plans, with adjustments for IMF staff assumptions.

Brazil: Fiscal projections for 2019 take into account the deficit target approved in the budget law.

Cambodia: Historical fiscal and monetary data are from the Cambodian authorities. Projections are based on the IMF staf’s assumptions following discussions with the authorities.

Canada: Projections use the baseline forecasts in the 2018 federal budget and latest provincial budgets as available. The IMF staff makes some adjustments to this forecast, including for differences in macroeconomic projections. The IMF staff forecast also incorporates the most recent data releases from Statistics Canada’s Canadian System of National Economic Accounts, including federal, provincial, and territorial budgetary outturns through 2018:Q3.

Chile: Projections are based on the authorities’ budget projections, adjusted to reflect the IMF staf’s projections for GDP and copper prices.

China: Fiscal expansion is expected for 2019, due to personal income tax reform and other measures to respond to economic slowdown.

Croatia: Projections are based on the macroeconomic framework and the authorities’ medium-term fiscal guidelines.

Cyprus: Projections are based on staff assessment of high-frequency fiscal data, budget plans, and IMF staff’s macroeconomic assumptions.

Czech Republic: Projections are based on the authorities’ budget forecast for 2018–19 with adjustments for the IMF staff’s macroeconomic projections. Projections for 2019 onward are based on the country’s Convergence Programme and Fiscal Outlook.

Denmark: Estimates for 2018 are aligned with the latest official budget numbers, adjusted where appropriate for the IMF staff’s macroeconomic assumptions. For 2019, the projections incorporate key features of the medium-term fiscal plan as embodied in the authorities’ 2018 Convergence Program submitted to the EU.

Estonia: Fiscal projections are on an accrual basis and are based on the authorities’ 2017 budget.

Finland: Projections are based on the authorities’ announced policies, adjusted for the IMF staff’s macro-economic scenario.

France: Projections for 2018 onward are based on the measures of the 2018 budget law, the multi-year law for 2018–22, and the 2019 budget law adjusted for differences in assumptions on macro and financial variables, and revenue projections. Historical fiscal data reflect the September 2018 revisions and update of the historical fiscal accounts, debt data, and national accounts.

Germany: The IMF staff’s estimates for 2019 and projections for 2019 and beyond are based on the 2019 Draft Budgetary Plan and data updates from the national statistical agency, adjusted for the differences in the IMF staff’s macroeconomic framework and assumptions concerning revenue elasticities. The estimate of gross debt includes portfolios of impaired assets and noncore business transferred to institutions that are winding up, as well as other financial sector and EU support operations.

Greece: Greece’s general government primary balance estimate for 2018 is based on preliminary data up to November 2018, provided by the Ministry of Finance as of February 1, 2019. Historical data since 2010 reflect adjustments in line with the primary balance definition under the enhanced surveillance framework for Greece.

Hong Kong Special Administrative Region: Projections are based on the authorities’ medium-term fiscal projections on expenditure.

Hungary: Fiscal projections include IMF staff projections of the macroeconomic framework and of the impact of recent legislative measures, as well as fiscal policy plans announced in the 2018 budget.

India: Historical data are based on budgetary execution data. Projections are based on available information on the authorities’ fiscal plans, with adjustments for IMF staff assumptions. Subnational data are incorporated with a lag of up to one year; general government data are thus finalized well after central government data. IMF and Indian presentations differ, particularly regarding divestment and license auction proceeds, net versus gross recording of revenues in certain minor categories, and some public-sector lending.

Indonesia: IMF projections are based on moderate tax policy and administration reforms, and a gradual increase in social and capital spending over the medium term in line with fiscal space.

Ireland: Fiscal projections are based on the country’s Budget 2019.

Israel: Historical data are based on Government Finance Statistics data prepared by the Central Bureau of Statistics. The central government deficit is assumed to increase to 3.5 percent of GDP in 2019. It is assumed to decline afterward but not in line with medium-term fiscal targets, consistent with long experience of revisions to those targets.

Italy: The IMF staff’s estimates and projections are informed by the fiscal plans included in the government’s 2019 budget. IMF staff assumes that the automatic value-added tax (VAT) hikes for future years will be canceled.

Japan: The projections reflect fiscal measures already announced by the government, including the consumption tax hike in October 2019 and the mitigating measures included in the FY2019 budget and tax reform.

Kazakhstan: Fiscal projections are based on the Budget Code and IMF staff projections.

Korea: The medium-term forecast incorporates the medium-term path for public spending announced by government.

Libya: Against the background of a civil war and weak capacities, the reliability of Libya’s data, especially medium-term projections, is low.

Malaysia: Fiscal projections are based on budget numbers, discussion with the authorities, and IMF staff estimates.

Malta: Projections are based on the authorities’ latest Stability Programme Update and budget documents, adjusted for the IMF staff’s macroeconomic and other assumptions.

Mexico: Fiscal projections for 2018 are broadly in line with the approved budget; projections for 2019 onward assume compliance with rules established in the Fiscal Responsibility Law.

Moldova: Fiscal projections are based on various bases and growth rates for GDP, consumption, imports, wages, and energy prices and on demographic changes.

Myanmar: Fiscal projections are based on budget numbers, discussions with the authorities, and IMF staff estimates.

Netherlands: Fiscal projections for the period 2018– 24 are based on the authorities’ Bureau for Economic Policy Analysis budget projections, after differences in macroeconomic assumptions are adjusted for. Historical data were revised following the June 2014 Central Bureau of Statistics release of revised macro data because of the adoption of the European System of National and Regional Accounts (ESA 2010) and the revisions of data sources.

New Zealand: Fiscal projections are based on the fiscal year 2018–19 budget; the 2018 Half-Year Economic and Fiscal Update; and IMF staff estimates

Norway: Fiscal projections are based on the latest 2018 revised budget.

Philippines: Revenue projections reflect the IMF staff’s macroeconomic assumptions and incorporate anticipated improvements in tax administration. Expenditure projections are based on budgeted figures, institutional arrangements, current data, and fiscal space in each year.

Poland: Data are on an ESA 2010 basis beginning in 2010. Data before 2010 are on the basis of ESA 95. Projections are based on the 2017 budget and take into account the effects of the 2014 pension changes.

Portugal: The projections for the current year are based on the authorities’ approved budget, adjusted to reflect the IMF staff’s macroeconomic forecast. Projections thereafter are based on the assumption of unchanged policies.

Romania: Projections for 2019 reflect the full effect of the budget measures adopted in 2018 (including the increases in wages and pensions, and changes to labor taxation), further implementation of the unified wage law, and the legislated increase in pensions. Apart from the impact of the unified wage law—which is set to be implemented gradually until 2022, and the indexation of public pensions, no additional policy changes are assumed beyond 2019.

Russia: Projections for 2018–21 are staff estimates based on the authorities’ budget. Projections for 2022–24 are based on the new oil-price rule, with adjustments by IMF staff.

Saudi Arabia: Staff baseline projections of total government revenues, except exported oil revenues, are based on staff understanding of government policies as announced in their 2019 Budget and the Fiscal Balance Program 2019 Update. Exported oil revenues are based on the WEO baseline oil prices and the assumption that Saudi Arabia will continue to meet its commitments under the OPEC+ agreement. Expenditure projections take the 2019 Budget and the Fiscal Balance Program 2019 Update as a starting point and reflect staff estimates of the latest changes in policies and economic developments.

Singapore: For fiscal year 2019/20, projections are based on budget numbers. For the remainder of the projection period, the IMF staff assumes unchanged policies.

Slovak Republic: Projections for 2015 take into account developments in the first three quarters of the year and the authorities’ new projections presented in the budget for 2016. Projections for 2016 consider the authorities’ 2016 budget. Projections for 2017 and beyond reflect a no-policy-change scenario.

Spain: For 2019, projections assume expenditures under the 2018 budget extension scenario and already legislated measures, including pension and public wage increases, and IMF staff projection of revenues. For 2020 and beyond, fiscal projections are IMF staff projections, which assume an unchanged structural primary balance.

Sri Lanka: Projections are based on the authorities’ medium-term fiscal framework and the revenue measures proposed.

Sweden: Fiscal projections take into account the authorities’ projections based on the 2018 December Budget. The impact of cyclical developments on the fiscal accounts is calculated using the 2014 Organization for Economic Cooperation’s elasticity1 in order to take into account output and employment gaps.

Switzerland: The projections assume that fiscal policy is adjusted as necessary to keep fiscal balances in line with the requirements of Switzerland’s fiscal rules.

Thailand: For the projection period, the IMF staff assumes an implementation rate of 50 percent for the planned infrastructure investment programs.

Turkey: The fiscal projections assume a more negative primary and overall balance than envisaged in the authorities’ New Economic Program (NEP) 2019–21, based partly on staff’s lower growth forecast and partly on definitional differences. The basis for the projections in the World Economic Outlook and Fiscal Monitor is the IMF-defined fiscal balance, which excludes some revenue and expenditure items that are included in the authorities’ headline balance.

United Kingdom: Fiscal projections are based on the United Kindom’s Spring 2019 Budget, with expenditure projections based on the budgeted nominal values and with revenue projections adjusted for differences between IMF staff forecasts of macroeconomic variables (such as GDP growth and inflation) and the forecasts of these variables assumed in the authorities’ fiscal projections. IMF staff data exclude public sector banks and the effect of transferring assets from the Royal Mail Pension Plan to the public sector in April 2012. Real government consumption and investment are part of the real GDP path, which, according to the IMF staff, may or may not be the same as projected by the UK Office for Budget Responsibility.

United States: Fiscal projections are based on the January 2019 Congressional Budget Office baseline adjusted for IMF staff’s policy and macroeconomic assumptions. Projections incorporate the effects of tax reform (Tax Cuts and Jobs Act, signed into law at the end of 2017) as well as the Bipartisan Budget Act of 2018 passed in February 2018. Finally, fiscal projections are adjusted to reflect IMF staff’s forecasts for key macroeconomic and financial variables and different accounting treatment of financial sector support and of defined-benefit pension plans and are converted to a general government basis. Data are compiled using SNA 2008, and when translated into GFS this is in accordance with GFSM 2014. Due to data limitations, most series begin 2001.

Venezuela: Projecting the economic outlook in Venezuela, including assessing past and current economic developments as the basis for the projections, is complicated by the lack of discussions with the authorities (the last Article IV consultation took place in 2004), incomplete understanding of the reported data, and difficulties in interpreting certain reported economic indicators given economic developments. The fiscal accounts include the budgetary central government, social security, FOGADE (insurance deposit institution), and a sample of public enterprises including Petróleos de Venezuela, S.A. (PDVSA), and data for 2018–24 are IMF staff estimates. The effects of hyperinflation and the paucity of reported data mean that IMF staff’s projected macroeconomic indicators need to be interpreted with caution. For example, nominal GDP is estimated assuming the GDP deflator rises in line with IMF staff’s projection of average inflation. Public external debt in relation to GDP is projected using IMF staff’s estimate of the average exchange rate for the year. Wide uncertainty surrounds these projections.

Vietnam: Fiscal data for 2015–17 are the authorities’ estimate. From 2018 onward, fiscal data are based on IMF staff projections.

Yemen: Hydrocarbon revenue projections are based on World Economic Outlook assumptions for oil and gas prices (the authorities use $55 a barrel) and authorities’ projections of production of oil and gas. Non-hydrocarbon revenues largely reflect authorities’ projections, as do most of the expenditure categories, with the exception of fuel subsidies, which are projected based on the World Economic Outlook price consistent with revenues. Monetary projections are based on key macroeconomic assumptions about the growth rate of broad money, credit to the private sector, and deposit growth.

Definition and Coverage of Fiscal Data
Table A.Economy Groupings

The following groupings of economies are used in the Fiscal Monitor.

Advanced EconomiesEmerging Market and Middle-Income EconomiesLow-Income Developing CountriesG7G201Advanced G201Emerging G20
AustraliaAlgeriaBangladeshCanadaArgentinaAustraliaArgentina
AustriaAngolaBeninFranceAustraliaCanadaBrazil
BelgiumArgentinaBurkina FasoGermanyBrazilFranceChina
CanadaAzerbaijanCambodiaItalyCanadaGermanyIndia
CyprusBelarusCameroonJapanChinaItalyIndonesia
Czech RepublicBrazilChadUnited KingdomFranceJapanMexico
DenmarkChileDemocratic RepublicUnited StatesGermanyKoreaRussia
EstoniaChinaof the CongoIndiaUnited KingdomSaudi Arabia
FinlandColombiaRepublic of CongoIndonesiaUnited StatesSouth Africa
FranceCroatiaCôte d’IvoireItalyTurkey
GermanyDominican RepublicEthiopiaJapan
GreeceEcuadorGhanaKorea
Hong Kong SAREgyptGuineaMexico
IcelandHungaryHaitiRussia
IrelandIndiaHondurasSaudi Arabia
IsraelIndonesiaKenyaSouth Africa
ItalyIranKyrgyz RepublicTurkey
JapanKazakhstanLao P.D.R.United Kingdom
KoreaKuwaitMadagascarUnited States
LatviaLibyaMali
LithuaniaMalaysiaMoldova
LuxembourgMexicoMozambique
MaltaMoroccoMyanmar
NetherlandsOmanNepal
New ZealandPakistanNicaragua
NorwayPeruNiger
PortugalPhilippinesNigeria
SingaporePolandPapua New Guinea
Slovak RepublicQatarRwanda
SloveniaRomaniaSenegal
SpainRussiaSomalia
SwedenSaudi ArabiaSudan
SwitzerlandSouth AfricaTajikistan
United KingdomSri LankaTanzania
United StatesThailandTimor-Leste
TurkeyUganda
UkraineUzbekistan
United Arab EmiratesVietnam
UruguayYemen
VenezuelaZambia
Zimbabwe
Note: Emerging market and developing economies include emerging market and middle-income economies as well as low-income developing countries.

Does not include European Union aggregate.

Note: Emerging market and developing economies include emerging market and middle-income economies as well as low-income developing countries.

Does not include European Union aggregate.

Table A.(continued)
Euro AreaEmerging Market and Middle-Income AsiaEmerging Market and Middle-Income EuropeEmerging Market and Middle-Income Latin AmericaEmerging Market and Middle-Income Middle East and North Africa and PakistanEmerging Market and Middle-Income Africa
AustriaChinaAzerbaijanArgentinaAlgeriaAngola
BelgiumIndiaBelarusBrazilEgyptSouth Africa
CyprusIndonesiaCroatiaChileIran
EstoniaMalaysiaHungaryColombiaKuwait
FinlandPhilippinesKazakhstanDominicanLibya
FranceSri LankaPolandRepublicMorocco
GermanyThailandRomaniaEcuadorOman
GreeceRussiaMexicoPakistan
IrelandTurkeyPeruQatar
ItalyUkraineUruguaySaudi Arabia
LatviaVenezuelaUnited Arab Emirates
Lithuania
Luxembourg
Malta
Netherlands
Portugal
Slovak Republic
Slovenia
Spain
Low-Income Developing AsiaLow-Income Developing Latin AmericaLow-Income Developing Sub-Saharan AfricaLow-Income Developing OthersLow-Income Oil ProducersOil Producers
BangladeshHaitiBeninKyrgyz RepublicCameroonAlgeria
CambodiaHondurasBurkina FasoMoldovaRepublic of CongoAngola
Lao P.D.R.NicaraguaCameroonSomaliaCôte d’IvoireAzerbaijan
MyanmarChadSudanNigeriaBahrain
NepalDemocratic RepublicTajikistanPapua New GuineaBrunei Darussalam
Papua New Guineaof the CongoUzbekistanTimor-LesteCameroon
Timor-LesteRepublic of CongoYemenYemenCanada
VietnamCôte d’IvoireColombia
EthiopiaRepublic of Congo
GhanaCôte d’Ivoire
GuineaEcuador
KenyaEquatorial Guinea
MadagascarGabon
MaliIndonesia
MozambiqueIran
NigerIraq
NigeriaKazakhstan
RwandaKuwait
SenegalLibya
TanzaniaMexico
UgandaNigeria
ZambiaNorway
ZimbabweOman
Papua New Guinea
Qatar
Russia
Saudi Arabia
Syria
Timor-Leste
Trinidad and Tobago
United Arab Emirates
Venezuela
Yemen
Table B.Advanced Economies: Definition and Coverage of Fiscal Monitor Data
Overall Fiscal Balance1Cyclically Adjusted BalanceGross Debt
CoverageAccounting PracticeCoverageAccounting PracticeCoverageValuation of Debt2
AggregateSubsectorsAggregateSubsectorsAggregateSubsectors
AustraliaGGCG,SG,LG,TGAGGCG,SG,LG,TGAGGCG,SG,LG,TGNominal
AustriaGGCG,SG,LG,SSAGGCG,SG,LG,SSAGGCG,SG,LG,SSFace
BelgiumGGCG,SG,LG,SSAGGCG,SG,LG,SSAGGCG,SG,LG,SSFace
CanadaGGCG,SG,LG,SSAGGCG,SG,LG,SSAGGCG,SG,LG,SSFace
CyprusGGCG,LG,SSAGGCG,LG,SSAGGCG,LG,SSFace
Czech RepublicGGCG,LG,SSAGGCG,LG,SSAGGCG,LG,SSNominal
DenmarkGGCG,LG,SSAGGCG,LG,SSAGGCG,LG,SSFace
EstoniaGGCG,LG,SSCGGCG,LG,SSNominal
FinlandGGCG,LG,SSAGGCG,LG,SSAGGCG,LG,SSFace
FranceGGCG,LG,SSAGGCG,LG,SSAGGCG,LG,SSFace
GermanyGGCG,SG,LG,SSAGGCG,SG,LG,SSAGGCG,SG,LG,SSFace
GreeceGGCG,LG,SSAGGCG,LG,SSAGGCG,LG,SSNominal
Hong Kong SARGGCGCGGCGCGGCGFace
IcelandGGCG,LG,SSAGGCG,LG,SSAGGCG,LG,SSFace
IrelandGGCG,LG,SSAGGCG,LG,SSAGGCG,LG,SSNominal
IsraelGGCG,LG,SSMixedGGCG,LG,SSMixedGGCG,LG,SSNominal
ItalyGGCG,LG,SSAGGCG,LG,SSAGGCG,LG,SSFace
JapanGGCG,LG,SSAGGCG,LG,SSAGGCG,LG,SSCurrent market
KoreaCGCG, SSCCGCG, SSCCGCG, SSNominal
LatviaGGCG,LG,SSCGGCG,LG,SSCGGCG,LG,SSNominal
LithuaniaGGCG,LG,SSAGGCG,LG,SSAGGCG,LG,SSNominal
LuxembourgGGCG,LG,SSAGGCG,LG,SSAGGCG,LG,SSFace
MaltaGGCG,SSAGGCG,SSAGGCG,SSNominal
NetherlandsGGCG,LG,SSAGGCG,LG,SSAGGCG,LG,SSNominal
New ZealandCGCGACGCGACGCGCurrent market
NorwayGGCG,LG,SSAGGCG,LG,SSAGGCG,LG,SSCurrent market
PortugalGGCG,LG,SSAGGCG,LG,SSAGGCG,LG,SSNominal
SingaporeGGCGCGGCGCGGCGNominal
Slovak RepublicGGCG,LG,SSAGGCG,LG,SSAGGCG,LG,SSFace
SloveniaGGCG,LG,SSCGGCG,LG,SSCGGCG,LG,SSFace
SpainGGCG,SG,LG,SSAGGCG,SG,LG,SSAGGCG,SG,LG,SSNominal
SwedenGGCG,LG,SSAGGCG,LG,SSAGGCG,LG,SSNominal
SwitzerlandGGCG,SG,LG,SSAGGCG,SG,LG,SSAGGCG,SG,LG,SSNominal
United KingdomGGCG,LGAGGCG,LGAGGCG,LGNominal
United StatesGGCG,SG,LGAGGCG,SG,LGAGGCG,SG,LGNominal
Note: Coverage: CG = central government; GG = general government; LG = local governments; NFPC = nonfinancial public corporations; PS = public sector; SG = state governments; SS = social security funds; TG = territorial governments. Accounting standard: C = cash; A = accrual; Mixed = combination of accrual and cash accounting.

In many economies, fiscal data follow the IMF’s Government Finance Statistics Manual 2014. The concept of overall fiscal balance refers to net lending (+) and borrowing (-) of the general government. In some cases, however, the overall balance refers to total revenue and grants minus total expenditure and net lending.

Nominal = debt securities are valued at their nominal values, that is, the nominal value of a debt instrument at any moment in time is the amount that the debtor owes to the creditor. Face = undiscounted amount of principal to be repaid at (or before) maturity. The use of face value as a proxy for nominal value in measuring the gross debt position can result in an inconsistent approach across all instruments and is not recommended, unless nominal and market values are not available. Current market = debt securities are valued at market prices; insurance, pension, and standardized guarantee schemes are valued according to principles that are equivalent to market valuation; and all other debt instruments are valued at nominal prices, which are considered to be the best generally available proxies of their market prices.

Note: Coverage: CG = central government; GG = general government; LG = local governments; NFPC = nonfinancial public corporations; PS = public sector; SG = state governments; SS = social security funds; TG = territorial governments. Accounting standard: C = cash; A = accrual; Mixed = combination of accrual and cash accounting.

In many economies, fiscal data follow the IMF’s Government Finance Statistics Manual 2014. The concept of overall fiscal balance refers to net lending (+) and borrowing (-) of the general government. In some cases, however, the overall balance refers to total revenue and grants minus total expenditure and net lending.

Nominal = debt securities are valued at their nominal values, that is, the nominal value of a debt instrument at any moment in time is the amount that the debtor owes to the creditor. Face = undiscounted amount of principal to be repaid at (or before) maturity. The use of face value as a proxy for nominal value in measuring the gross debt position can result in an inconsistent approach across all instruments and is not recommended, unless nominal and market values are not available. Current market = debt securities are valued at market prices; insurance, pension, and standardized guarantee schemes are valued according to principles that are equivalent to market valuation; and all other debt instruments are valued at nominal prices, which are considered to be the best generally available proxies of their market prices.

Table C.Emerging Market and Middle-Income Economies: Definition and Coverage of Fiscal Monitor Data
Overall Fiscal Balance1Cyclically Adjusted BalanceGross Debt
CoverageAccounting PracticeCoverageAccounting PracticeCoverageValuation of Debt2
AggregateSubsectorsAggregateSubsectorsAggregateSubsectors
AlgeriaCGCGCCGCGNominal
AngolaGGCG, LGMixedGGCG, LGNominal
ArgentinaGGCG,SG,SSCCGCGCCGCGNominal
AzerbaijanCGCGCCGCGFace
Belarus3GGCG,LG,SSCGGCG,LG,SSNominal
Brazil4NFPSCG,SG,LG,SS, MPC,NFPCCNFPSCG,SG,LG,SS,MPC,NFPCCNFPSCG,SG,LG,SS, MPC,NFPCNominal
ChileGGCG,LGAGGCG,LGAGGCG,LGFace
ChinaGGCG,LGCGGCG,LGCGGCG,LGFace
Colombia5GGCG,SG,LG,SSMixedGGCG,SG,LG,SSMixedGGCG,SG,LG,SSFace
CroatiaGGCG,LGAGGCG,LGAGGCG,LGNominal
Dominican RepublicGGCG,SG,LG,SS, NMPCMixedGGCG,SG,LG,SS,NMPCMixedGGCG,SG,LG,SS, NMPCFace
EcuadorNFPSCG,SG,LG,SS,NFPCCNFPSCG,SG,LG,SS, NFPCCNFPSCG,SG,LG,SS,NFPCFace
EgyptGGCG,LG,SSCGGCG,LG,SSCGGCG,LG,SSNominal
HungaryGGCG,LG,SS,NMPCAGGCG,LG,SS,NMPCAGGCG,LG,SS,NMPCFace
IndiaGGCG,SGCGGCG,SGCGGCG,SGNominal
IndonesiaGGCG,LGCGGCG,LGCGGCG,LGFace
IranCGCGCCGCGNominal
KazakhstanGGCG,LGAGGCG,LGNominal
KuwaitCGCGMixedCGCGNominal
LibyaGGCG,SG,LGCGGCG,SG,LGFace
MalaysiaGGCG,SG,LGCGGCG,SG,LGcGGCG,SG,LGNominal
MexicoPSCG,SS,NMPC,NFPCCPSCG,SS,NMPC,NFPCcPSCG,SS,NMPC,NFPCFace
MoroccoCGCGACGCGFace
OmanCGCGCCGCGNominal
PakistanGGCG,SG,LGCGGCG,SG,LGNominal
PeruGGCG,SG,LG,SScGGCG,SG,LG,SScGGCG,SG,LG,SSFace
PhilippinesGGCG,LG,SScGGCG,LG,SScGGCG,LG,SSNominal
PolandGGCG,LG,SSAGGCG,LG,SSAGGCG,LG,SSFace
QatarCGCGCCGCGNominal
RomaniaGGCG,LG,SSCGGCG,LG,SSCGGCG,LG,SSFace
RussiaGGCG,SG,SSMixedGGCG,SG,SSMixedGGCG,SG,SSCurrent market
Saudi ArabiaCGCGCCGCGNominal
South Africa6GGCG,SG,SSCGGCG,SG,SSCGGCG,SG,SSNominal
Sri LankaCGCGCCGCGNominal
Thailand7PSCG,BCG,LG,SSAPSCG,BCG,LG,SSAPSCG,BCG,LG,SSNominal
TurkeyGGCG,LG,SSAGGCG,LG,SSAGGCG,LG,SSNominal
UkraineGGCG,SG,LG,SSCGGCG,SG,LG,SSCGGCG,SG,LG,SSNominal
United Arab Emirates8GGCG,BCG,SG,SSCGGCG,BCG,SG,SSNominal
UruguayPSCG,LG,SS,MPC, NFPCAPSCG,LG,SS,MPC, NFPCFace
Venezuela9GGBCG,NFPCCGGBCG,NFPCCGGBCG,NFPCNominal
Note: Coverage: BCG = budgetary central government; CG = central government; GG = general government; LG = local governments; MPC = monetary public corporations, including central bank; NFPC = nonfinancial public corporations; NFPS = nonfinancial public sector; NMPC = nonmonetary financial public corporations; PS = public sector; SG = state governments; SS = social security funds. Accounting standard: C = cash; A = accrual; Mixed = combination of accrual and cash accounting.

In many countries, fiscal data follow the IMF’s Government Finance Statistics Manual 2014. The concept of overall fiscal balance refers to net lending (+)and borrowing (-)of the general government. In some cases, however, the overall balance refers to total revenue and grants minus total expenditure and net lending.

Nominal = debt securities are valued at their nominal values, that is, the nominal value of a debt instrument at any moment in time is the amount that the debtor owes to the creditor. Face = undiscounted amount of principal to be repaid at (or before) maturity. The use of face value as a proxy for nominal value in measuring the gross debt position can result in an inconsistent approach across all instruments and is not recommended, unless nominal and market values are not available. Current market = debt securities are valued at market prices; insurance, pension, and standardized guarantee schemes are valued according to principles that are equivalent to market valuation; and all other debt instruments are valued at nominal prices, which are considered to be the best generally available proxies of their market prices.

Gross debt refers to general government public debt, including publicly guaranteed debt.

Gross debt refers to the nonfinancial public sector, excluding Eletrobras and Petrobras, and includes sovereign debt held on the balance sheet of the central bank.

Revenue is recorded on a cash basis and expenditure on an accrual basis.

Coverage for South Africa is a proxy for general government. It includes the national and provincial governments and certain public entities, while local governments are only partly covered, through the transfers to them.

Data for Thailand do not include the debt of specialized financial institutions (SFIs/NMPC) without government guarantee.

Gross debt covers banking system claims only.

The fiscal accounts for 2010–22 correspond to the budgetary central government and Petroleos de Venezuela S.A. (PDVSA), whereas the fiscal accounts for years before 2010 correspond to the budgetary central government, public enterprises (including PDVSA), Instituto Venezolano de los Seguros Sociales (IVSS—social security), and Fondo de Garantfa de Depositos y Proteccion Bancaria (FOGADE—deposit insurance).

Note: Coverage: BCG = budgetary central government; CG = central government; GG = general government; LG = local governments; MPC = monetary public corporations, including central bank; NFPC = nonfinancial public corporations; NFPS = nonfinancial public sector; NMPC = nonmonetary financial public corporations; PS = public sector; SG = state governments; SS = social security funds. Accounting standard: C = cash; A = accrual; Mixed = combination of accrual and cash accounting.

In many countries, fiscal data follow the IMF’s Government Finance Statistics Manual 2014. The concept of overall fiscal balance refers to net lending (+)and borrowing (-)of the general government. In some cases, however, the overall balance refers to total revenue and grants minus total expenditure and net lending.

Nominal = debt securities are valued at their nominal values, that is, the nominal value of a debt instrument at any moment in time is the amount that the debtor owes to the creditor. Face = undiscounted amount of principal to be repaid at (or before) maturity. The use of face value as a proxy for nominal value in measuring the gross debt position can result in an inconsistent approach across all instruments and is not recommended, unless nominal and market values are not available. Current market = debt securities are valued at market prices; insurance, pension, and standardized guarantee schemes are valued according to principles that are equivalent to market valuation; and all other debt instruments are valued at nominal prices, which are considered to be the best generally available proxies of their market prices.

Gross debt refers to general government public debt, including publicly guaranteed debt.

Gross debt refers to the nonfinancial public sector, excluding Eletrobras and Petrobras, and includes sovereign debt held on the balance sheet of the central bank.

Revenue is recorded on a cash basis and expenditure on an accrual basis.

Coverage for South Africa is a proxy for general government. It includes the national and provincial governments and certain public entities, while local governments are only partly covered, through the transfers to them.

Data for Thailand do not include the debt of specialized financial institutions (SFIs/NMPC) without government guarantee.

Gross debt covers banking system claims only.

The fiscal accounts for 2010–22 correspond to the budgetary central government and Petroleos de Venezuela S.A. (PDVSA), whereas the fiscal accounts for years before 2010 correspond to the budgetary central government, public enterprises (including PDVSA), Instituto Venezolano de los Seguros Sociales (IVSS—social security), and Fondo de Garantfa de Depositos y Proteccion Bancaria (FOGADE—deposit insurance).

Table D.Low-Income Developing Countries: Definition and Coverage of Fiscal Monitor Data
Overall Fiscal Balance1Cyclically Adjusted BalanceGross Debt
CoverageAccounting PracticeCoverageAccounting PracticeCoverageValuation of Debt2
AggregateSubsectorsAggregateSubsectorsAggregateSubsectors
BangladeshCGCGCCGCGcCGCGNominal
BeninCGCGCCGCGNominal
Burkina FasoGGCGCBGGCGFace
CambodiaCGCG,LGACGCG,LGACGCG,LGFace
CameroonNFPSCG,NFPCCNFPSCG,NFPCCurrent market
ChadNFPSCG,NFPCCNFPSCG,NFPCFace
Democratic Republic of the CongoGGCG,LGAGGCG,LGNominal
Republic of CongoCGCGACGCGNominal
Cote d’lvoireCGCGACGCGNominal
EthiopiaCGCG,SG,LG,NFPCCCGCG,SG,LG,NFPCNominal
GhanaCGCGCCGCGFace
GuineaCGCGCCGCGNominal
Haiti3CGCGCCGCGNominal
HondurasGGCG,LG,SSMixedGGCG,LG,SSMixedGGCG,LG,SSNominal
KenyaCGCGACGCGCurrent market
Kyrgyz RepublicGGCG,LG,SSCGGCG,LG,SSFace
Lao P.D.R.4CGCGCCGCGCCGCG
MadagascarCGCG,LGCCGCG,LGNominal
MaliCGCGMixedCGCGNominal
MoldovaGGCG,LG,SSCGGCG,LG,SSCGGCG,LG,SSNominal
MozambiqueCGCG,SGMixedCGCG,SGMixedCGCG,SGNominal
Myanmar5NFPSCG,NFPCCNFPSCG,NFPCFace
NepalCGCGCCGCGCCGCGFace
NicaraguaGGCG,LG,SSCGGCG,LG,SSCGGCG,LG,SSNominal
NigerCGCGACGCGNominal
NigeriaGGCG,SG,LGCGGCG,SG,LGCurrent market
Papua New GuineaCGCGCCGCGFace
RwandaGGCG,LGMixedGGCG,LGNominal
SenegalCGCGCCGCGCCGCGNominal
SomaliaCGCGCCGCGCCGCG
SudanCGCGMixedCGCGNominal
TajikistanGGCG,LG,SSCGGCG,LG,SSNominal
TanzaniaCGCG,LGCCGCG,LGNominal
Timor-LesteCGCGCCGCGCCGCG
UgandaCGCGCCGCGNominal
Uzbekistan6GGCG,SG,LG,SSCGGCG,SG,LG,SSNominal
VietnamGGCG,SG,LGCGGCG,SG,LGCGGCG,SG,LGNominal
YemenGGCG,LGCGGCG,LGNominal
ZambiaCGCGCCGCGCurrent market
ZimbabweCGCGCCGCGCurrent market
Note: Coverage: BCG = budgetary central government; CG = central government; CPS = combined public sector; EA = extrabudgetary units; FC = financial public corporations; GG = general government; LG = local governments; MPC = monetary public corporations, including central bank; NC = non-cash; NFPC = nonfinancial public corporations; NFPS = nonfinancial public sector; NMPC = nonmonetary financial public corporations; PS = public sector; SG = state governments; SS = social security funds. Accounting standard: C = cash; A = accrual; CB = commitments basis accounting; Mixed = combination of accrual and cash accounting.

In many countries, fiscal data follow the IMF’s Government Finance Statistics Manual2014. The concept of overall fiscal balance refers to net lending (+) and borrowing (-) of the general government. In some cases, however, the overall balance refers to total revenue and grants minus total expenditure and net lending.

Nominal = debt securities are valued at their nominal values, that is, the nominal value of a debt instrument at any moment in time is the amount that the debtor owes to the creditor. Face = undiscounted amount of principal to be repaid at (or before) maturity. The use of face value as a proxy for nominal value in measuring the gross debt position can result in an inconsistent approach across all instruments and is not recommended, unless nominal and market values are not available. Current market = debt securities are valued at market prices; insurance, pension, and standardized guarantee schemes are valued according to principles that are equivalent to market valuation; and all other debt instruments are valued at nominal prices, which are considered to be the best generally available proxies of their market prices.

Haiti’s fiscal balance and debt data cover the central government, special funds and programs (Fonds d’Entretien Routier and Programme de Scolarisation Universelle, Gratuite, et Obligatoire), and the state-owned electricity company, EDH.

Lao RD.R.’s fiscal spending includes capital spending by local governments financed by loans provided by the central bank.

Overall and primary balances in 2012 are based on the monetary statistics and are different from the balances calculated from expenditure and revenue data.

Uzbekistan’s listing includes the Fund for Reconstruction and Development.

Note: Coverage: BCG = budgetary central government; CG = central government; CPS = combined public sector; EA = extrabudgetary units; FC = financial public corporations; GG = general government; LG = local governments; MPC = monetary public corporations, including central bank; NC = non-cash; NFPC = nonfinancial public corporations; NFPS = nonfinancial public sector; NMPC = nonmonetary financial public corporations; PS = public sector; SG = state governments; SS = social security funds. Accounting standard: C = cash; A = accrual; CB = commitments basis accounting; Mixed = combination of accrual and cash accounting.

In many countries, fiscal data follow the IMF’s Government Finance Statistics Manual2014. The concept of overall fiscal balance refers to net lending (+) and borrowing (-) of the general government. In some cases, however, the overall balance refers to total revenue and grants minus total expenditure and net lending.

Nominal = debt securities are valued at their nominal values, that is, the nominal value of a debt instrument at any moment in time is the amount that the debtor owes to the creditor. Face = undiscounted amount of principal to be repaid at (or before) maturity. The use of face value as a proxy for nominal value in measuring the gross debt position can result in an inconsistent approach across all instruments and is not recommended, unless nominal and market values are not available. Current market = debt securities are valued at market prices; insurance, pension, and standardized guarantee schemes are valued according to principles that are equivalent to market valuation; and all other debt instruments are valued at nominal prices, which are considered to be the best generally available proxies of their market prices.

Haiti’s fiscal balance and debt data cover the central government, special funds and programs (Fonds d’Entretien Routier and Programme de Scolarisation Universelle, Gratuite, et Obligatoire), and the state-owned electricity company, EDH.

Lao RD.R.’s fiscal spending includes capital spending by local governments financed by loans provided by the central bank.

Overall and primary balances in 2012 are based on the monetary statistics and are different from the balances calculated from expenditure and revenue data.

Uzbekistan’s listing includes the Fund for Reconstruction and Development.

Table A1.Advanced Economies: General Government Overall Balance, 2010–24(Percent of GDP)
201020112012201320142015201620172018201920202021202220232024
Australia-5.1-4.4-3.5-2.8-2.9-2.8-2.6-1.5-1.2-1.5-0.70.00.10.00.0
Austria-4.5-2.6-2.2-2.0-2.7-1.0-1.6-0.7-0.2-0.1-0.3-0.3-0.5-0.6-0.6
Belgium-4.0-4.2-4.2-3.1-3.1-2.5-2.4-0.9-0.8-1.2-1.4-1.4-1.4-1.4-1.5
Canada-4.7-3.3-2.5-1.50.2-0.1-0.4-0.3-0.4-0.6-0.6-0.6-0.7-0.6-0.6
Cyprus1-4.7-5.7-5.6-5.1-0.2-0.30.31.82.91.82.02.12.12.22.6
Czech Republic-4.2-2.7-3.9-1.2-2.1-0.60.71.51.51.10.80.60.60.60.6
Denmark-2.7-2.1-3.5-1.21.1-1.3-0.11.2-0.1-0.4-0.4-0.3-0.2-0.10.1
Estonia0.21.2-0.3-0.20.70.1-0.3-0.30.20.20.20.10.00.00.0
Finland-2.6-1.0-2.2-2.6-3.2-2.8-1.7-0.7-1.0-0.30.00.10.0-0.10.0
France-6.9-5.2-5.0-4.1-3.9-3.6-3.4-2.7-2.6-3.3-2.4-2.5-2.5-2.6-2.6
Germany-4.2-1.00.0-0.10.60.80.91.01.71.11.10.80.80.70.7
Greece-11.2-10.3-6.6-3.6-4.0-2.80.61.00.4-0.20.10.10.0-0.5-0.6
Hong Kong SAR4.13.83.11.03.60.64.45.52.01.31.60.80.80.80.8
Iceland-9.5-5.4-3.6-1.8-0.1-0.812.40.51.10.70.50.50.50.50.5
Ireland1-32.0-12.8-8.1-6.1-3.6-1.9-0.5-0.20.00.00.20.30.50.70.9
Israel-3.7-3.0-4.4-4.0-2.4-1.0-1.4-1.0-2.2-2.5-2.5-2.5-2.5-2.5-2.5
Italy-4.2-3.7-2.9-2.9-3.0-2.6-2.5-2.4-2.1-2.7-3.4-3.5-3.7-3.7-3.8
Japan-9.5-9.4-8.6-7.9-5.6-3.8-3.7-3.2-3.2-2.8-2.1-1.9-1.8-1.9-2.1
Korea1.51.71.60.60.40.61.72.32.82.11.51.10.70.70.7
Latvia-6.5-3.20.2-0.6-1.7-1.5-0.4-0.8-0.7-0.8-0.5-0.7-0.5-0.5-0.2
Lithuania-6.9-8.9-3.1-2.6-0.7-0.20.30.40.90.40.30.30.30.30.2
Luxembourg-0.70.50.31.01.31.31.61.42.61.01.31.21.51.61.6
Malta-2.4-2.4-3.5-2.4-1.7-1.10.93.50.90.60.60.70.70.60.6
Netherlands-5.2-4.4-3.9-2.9-2.2-2.00.01.21.11.00.80.80.80.80.8
New Zealand-5.5-5.0-2.3-1.4-0.50.20.91.10.40.10.71.01.31.31.3
Norway11.013.413.810.88.76.14.05.17.57.57.27.37.37.57.7
Portugal-11.2-7.4-5.7-4.8-7.1-4.3-2.0-3.0-0.7-0.6-0.10.40.30.30.5
Singapore6.08.67.86.65.43.54.35.84.04.23.12.92.82.72.5
Slovak Republic-7.5-4.3-4.3-2.7-2.7-2.6-2.2-0.8-0.80.00.30.30.30.30.3
Slovenia-5.2-5.5-3.1-13.8-5.8-3.3-1.7-0.71.10.50.20.40.50.60.7
Spain1-9.4-9.6-10.5-7.0-6.0-5.3-4.5-3.1-2.7-2.3-2.3-2.4-2.5-2.7-2.8
Sweden0.0-0.2-1.0-1.4-1.60.21.11.50.80.50.30.30.30.30.3
Switzerland0.40.70.4-0.4-0.20.60.40.40.30.30.20.20.30.30.3
United Kingdom-9.3-7.5-7.5-5.3-5.3-4.2-2.9-1.8-1.4-1.3-1.2-1.1-0.8-0.6-0.6
United States2-10.6-9.3-7.6-4.1-3.7-3.2-3.9-3.8-4.3-4.6-4.4-4.4-4.4-4.0-3.7
Average-7.6-6.2-5.4-3.6-3.0-2.5-2.5-2.1-2.1-2.4-2.3-2.2-2.2-2.1-2.0
Euro Area-6.2-4.2-3.7-3.1-2.5-2.0-1.6-1.0-0.6-1.0-0.9-1.0-1.1-1.1-1.1
G7-8.7-7.3-6.3-4.1-3.4-2.8-3.1-2.8-2.9-3.2-3.0-3.0-3.0-2.7-2.6
G20 Advanced-8.2-6.9-5.9-3.9-3.2-2.7-2.9-2.6-2.6-3.0-2.7-2.7-2.7-2.5-2.4
Source: IMF staff estimates and projections. Projections are based on staff assessment of current policies (see “Fiscal Policy Assumptions” in text).Note: For country-specific details, see “Data and Conventions” in text, and Table B.

Data include financial sector support. For Cyprus, 2014 and 2015 balances exclude financial sector support.

For cross-economy comparability, expenditure and fiscal balances of the United States are adjusted to exclude the imputed interest on unfunded pension liabilities and the imputed compensation of employees, which are counted as expenditures under the 2008 System of National Accounts (2008 SNA) adopted by the United States, but not in countries that have not yet adopted the 2008 SNA. Data for the United States in this table may thus differ from data published by the US Bureau of Economic Analysis.

Source: IMF staff estimates and projections. Projections are based on staff assessment of current policies (see “Fiscal Policy Assumptions” in text).Note: For country-specific details, see “Data and Conventions” in text, and Table B.

Data include financial sector support. For Cyprus, 2014 and 2015 balances exclude financial sector support.

For cross-economy comparability, expenditure and fiscal balances of the United States are adjusted to exclude the imputed interest on unfunded pension liabilities and the imputed compensation of employees, which are counted as expenditures under the 2008 System of National Accounts (2008 SNA) adopted by the United States, but not in countries that have not yet adopted the 2008 SNA. Data for the United States in this table may thus differ from data published by the US Bureau of Economic Analysis.

Table A2.Advanced Economies: General Government Primary Balance, 2010–24(Percent of GDP)
201020112012201320142015201620172018201920202021202220232024
Australia-4.8-3.9-2.8-2.0-2.0-1.8-1.6-0.6-0.3-0.50.20.91.00.80.8
Austria-2.3-0.40.00.2-0.70.90.10.81.01.00.80.60.40.30.2
Belgium-0.7-1.0-1.0-0.2-0.20.20.11.31.20.60.30.20.20.10.1
Canada-3.9-2.7-1.8-1.00.50.60.20.0-0.1-0.20.00.30.40.40.4
Cyprus1-3.2-4.1-2.9-1.92.82.52.84.25.34.14.24.24.14.04.3
Czech Republic-3.2-1.7-2.8-0.2-1.00.31.52.22.11.81.61.41.41.41.4
Denmark-2.1-1.4-3.0-0.81.6-0.60.41.40.30.10.10.20.30.40.6
Estonia0.01.0-0.4-0.30.60.0-0.4-0.30.20.20.20.10.00.00.0
Finland-2.5-1.0-2.0-2.5-3.0-2.6-1.5-0.4-0.9-0.3-0.10.00.10.10.1
France-4.5-2.6-2.5-1.9-1.9-1.8-1.7-1.0-0.9-1.7-0.8-0.9-0.9-0.9-0.9
Germany-2.11.11.81.41.81.91.81.92.41.81.61.31.31.21.2
Greece-5.3-3.0-1.50.4-0.10.83.84.13.83.53.53.53.53.02.8
Hong Kong SAR2.31.91.3-0.73.60.63.64.70.6-0.20.1-0.8-1.0-1.3-1.3
Iceland-6.8-2.8-0.41.63.52.815.53.63.62.82.72.62.32.21.8
Ireland1-29.7-10.2-4.8-2.6-0.30.41.61.71.71.51.51.51.61.81.9
Israel0.00.6-1.2-0.9-0.30.80.51.0-0.3-0.5-0.5-0.5-0.5-0.4-0.4
Italy-0.10.82.11.71.41.31.21.21.40.90.30.30.30.40.5
Japan-8.6-8.3-7.5-7.0-4.9-3.2-3.0-2.7-2.9-2.7-2.1-1.9-1.9-1.9-2.1
Korea0.80.90.8-0.2-0.3-0.30.81.22.01.30.80.60.50.50.5
Latvia-5.1-1.81.70.9-0.20.30.80.30.20.00.40.20.20.30.5
Lithuania-5.2-7.2-1.2-0.91.01.31.61.61.81.21.00.90.90.90.8
Luxembourg-0.90.30.10.81.11.11.41.22.40.80.90.70.90.90.8
Malta0.70.8-0.50.41.01.33.05.32.52.01.91.92.01.81.8
Netherlands-3.9-3.0-2.5-1.6-0.8-0.81.12.11.81.61.41.41.41.41.4
New Zealand-4.9-4.2-1.4-0.60.10.91.51.81.00.91.41.71.91.91.9
Norway8.911.312.08.86.43.51.52.65.05.14.84.84.85.05.2
Portugal-8.5-3.6-1.4-0.6-2.70.01.90.72.62.53.13.53.13.13.2
Singapore
Slovak Republic-6.4-2.9-2.8-1.1-1.1-1.1-0.90.40.41.11.41.31.31.31.3
Slovenia-4.0-4.2-1.4-11.5-2.8-0.61.01.53.02.21.82.02.12.32.4
Spain1-7.8-7.7-8.0-4.0-3.0-2.6-1.9-0.7-0.4-0.2-0.2-0.2-0.3-0.3-0.4
Sweden0.30.1-0.8-1.2-1.40.11.01.40.60.30.20.10.10.10.1
Switzerland0.81.10.8-0.20.00.90.60.60.50.40.40.40.40.40.4
United Kingdom-6.8-4.7-5.2-4.0-3.5-2.7-1.3-0.10.10.10.20.40.50.50.5
United States2-9.1-7.5-5.9-2.5-2.1-1.7-2.3-2.2-2.6-2.9-2.4-2.2-2.2-1.8-1.4
Average-6.1-4.5-3.8-2.1-1.6-1.2-1.2-0.8-0.9-1.2-0.9-0.9-0.8-0.7-0.5
Euro Area-3.7-1.6-1.0-0.6-0.20.00.40.81.10.60.70.50.50.50.5
G7-6.9-5.3-4.4-2.5-1.8-1.4-1.6-1.3-1.5-1.8-1.4-1.3-1.3-1.1-0.9
G20 Advanced-6.6-5.1-4.2-2.4-1.8-1.4-1.5-1.2-1.3-1.6-1.3-1.2-1.2-0.9-0.8
Source: IMF staff estimates and projections. Projections are based on staff assessment of current policies (see “Fiscal Policy Assumptions” in text).Note: Primary balance is defined as the overall balance excluding net interest payments. For country-specific details, see “Data and Conventions” in text, and Table B.

Data include financial sector support. For Cyprus, 2014 and 2015 balances exclude financial sector support.

For cross-economy comparability, expenditure and fiscal balances of the United States are adjusted to exclude the imputed interest on unfunded pension liabilities and the imputed compensation of employees, which are counted as expenditures under the 2008 System of National Accounts (2008 SNA) adopted by the United States, but not in countries that have not yet adopted the 2008 SNA. Data for the United States in this table may thus differ from data published by the US Bureau of Economic Analysis.

Source: IMF staff estimates and projections. Projections are based on staff assessment of current policies (see “Fiscal Policy Assumptions” in text).Note: Primary balance is defined as the overall balance excluding net interest payments. For country-specific details, see “Data and Conventions” in text, and Table B.

Data include financial sector support. For Cyprus, 2014 and 2015 balances exclude financial sector support.

For cross-economy comparability, expenditure and fiscal balances of the United States are adjusted to exclude the imputed interest on unfunded pension liabilities and the imputed compensation of employees, which are counted as expenditures under the 2008 System of National Accounts (2008 SNA) adopted by the United States, but not in countries that have not yet adopted the 2008 SNA. Data for the United States in this table may thus differ from data published by the US Bureau of Economic Analysis.

Table A3.Advanced Economies: General Government Cyclically Adjusted Balance, 2010–24(Percent of potential GDP)
201020112012201320142015201620172018201920202021202220232024
Australia-4.9-4.2-3.3-2.6-2.5-2.4-2.2-1.2-1.0-1.2-0.40.20.20.00.0
Austria-4.1-3.2-2.5-1.5-1.80.0-0.9-0.6-0.6-0.6-0.8-0.7-0.6-0.7-0.6
Belgium-3.8-4.3-4.0-2.4-2.5-2.1-2.3-0.9-0.9-1.3-1.5-1.5-1.5-1.5-1.6
Canada-4.0-3.1-2.0-1.00.50.80.60.0-0.2-0.5-0.7-0.7-0.8-0.7-0.6
Cyprus-5.1-5.7-4.4-2.31.81.71.41.92.31.21.21.31.21.72.0
Czech Republic-4.1-3.0-3.10.4-1.0-0.60.81.21.20.80.50.40.40.40.5
Denmark-1.6-1.3-2.20.12.0-1.0-0.50.2-0.7-1.0-1.1-1.0-0.8-0.6-0.3
Estonia3.12.20.10.41.10.70.0-0.5-0.2-0.10.00.00.00.00.0
Finland-1.8-1.5-1.7-1.2-0.90.00.0-0.1-0.8-0.5-0.2-0.1-0.2-0.20.0
France-6.2-5.2-4.7-3.6-3.4-3.2-3.0-2.7-2.7-3.4-2.4-2.5-2.6-2.6-2.6
Germany-3.6-1.5-0.30.00.50.70.80.61.20.70.60.40.50.60.7
Greece-8.9-4.41.94.82.83.05.64.83.21.81.30.70.3-0.4-0.6
Hong Kong SAR10.7-1.6-1.1-4.3-1.2-3.3-1.3-2.3-3.7-4.7-3.7-4.4-4.5-4.1-4.1
Iceland-7.6-4.7-3.0-1.8-0.1-1.211.3-0.40.00.40.30.50.40.50.5
Ireland1-8.9-6.5-5.4-4.6-3.1-1.3-1.2-0.5-0.4-0.4-0.10.10.40.70.9
Israel-3.6-3.5-4.3-4.1-2.6-0.9-1.4-1.0-2.3-2.6-2.6-2.6-2.6-2.6-2.6
Italy-3.5-3.4-1.4-0.8-0.9-0.8-1.2-1.7-1.7-2.1-3.2-3.5-3.8-4.0-4.1
Japan-8.0-8.0-7.6-7.5-5.5-4.3-4.1-3.4-3.1-2.8-2.1-1.8-1.7-1.8-2.1
Korea1.51.61.70.90.60.82.02.52.92.31.71.20.70.70.6
Latvia-4.4-2.70.1-1.4-1.7-1.5-0.4-1.2-1.3-1.2-0.7-0.8-0.6-0.5-0.3
Lithuania-4.1-7.4-2.3-2.1-0.50.00.70.40.70.10.10.10.20.20.2
Luxembourg-0.50.31.21.41.20.81.31.62.61.01.11.11.41.51.5
Malta-2.5-1.9-2.5-1.1-1.4-2.10.63.20.50.40.50.70.80.60.6
Netherlands-4.8-4.4-2.7-1.1-0.5-0.80.81.20.50.10.10.20.40.60.8
New Zealand-4.5-4.0-1.3-0.5-0.10.30.80.7-0.1-0.20.30.50.80.90.9
Norway1-4.6-4.0-4.4-4.7-5.5-6.4-7.3-7.4-6.8-7.1-7.2-7.2-7.2-7.2-7.2
Portugal-11.0-6.3-2.8-1.6-4.3-2.5-0.8-2.6-0.7-0.8-0.30.40.20.30.4
Singapore6.58.57.86.55.43.64.35.63.84.23.12.92.82.72.5
Slovak Republic-6.2-3.1-3.1-1.6-2.1-2.9-2.8-1.3-1.3-0.40.20.20.30.30.3
Slovenia-4.8-4.3-2.0-1.4-2.2-0.9-0.30.50.5-0.1-0.4-0.30.00.30.5
Spain1-8.5-7.4-3.3-2.3-1.9-2.5-2.9-2.6-2.7-2.6-2.8-2.9-2.9-3.0-3.1
Sweden10.5-0.2-0.6-0.7-0.8-0.40.71.20.50.40.30.30.30.30.3
Switzerland10.40.70.6-0.3-0.30.70.50.40.10.20.20.20.30.30.3
United Kingdom1-7.2-5.9-5.9-3.9-4.6-3.9-2.8-1.9-1.4-1.2-1.0-0.9-0.7-0.6-0.6
United States1,2-9.3-7.9-6.1-4.0-3.4-3.2-3.9-4.0-4.7-5.2-5.0-4.9-4.9-4.5-4.1
Average-6.6-5.6-4.4-3.1-2.6-2.3-2.5-2.3-2.5-2.9-2.7-2.7-2.6-2.5-2.3
Euro Area-5.1-3.9-2.6-1.4-1.3-1.1-0.9-0.9-0.8-1.1-1.1-1.3-1.3-1.2-1.2
G7-7.5-6.4-5.2-3.7-3.0-2.7-3.0-2.9-3.1-3.5-3.3-3.3-3.2-3.0-2.8
G20 Advanced-7.1-6.0-4.9-3.5-2.9-2.6-2.8-2.7-2.8-3.2-3.0-3.0-3.0-2.8-2.6
Source: IMF staff estimates and projections. Projections are based on staff assessment of current policies (see “Fiscal Policy Assumptions” in text).Note: For country-specific details, see “Data and Conventions” in text, and Table B.

Data for these countries include adjustments beyond the output cycle.

For cross-economy comparability, expenditure and fiscal balances of the United States are adjusted to exclude the imputed interest on unfunded pension liabilities and the imputed compensation of employees, which are counted as expenditures under the 2008 System of National Accounts (2008 SNA) adopted by the United States, but not in countries that have not yet adopted the 2008 SNA. Data for the United States in this table may thus differ from data published by the US Bureau of Economic Analysis.

Source: IMF staff estimates and projections. Projections are based on staff assessment of current policies (see “Fiscal Policy Assumptions” in text).Note: For country-specific details, see “Data and Conventions” in text, and Table B.

Data for these countries include adjustments beyond the output cycle.

For cross-economy comparability, expenditure and fiscal balances of the United States are adjusted to exclude the imputed interest on unfunded pension liabilities and the imputed compensation of employees, which are counted as expenditures under the 2008 System of National Accounts (2008 SNA) adopted by the United States, but not in countries that have not yet adopted the 2008 SNA. Data for the United States in this table may thus differ from data published by the US Bureau of Economic Analysis.

Table A4.Advanced Economies: General Government Cyclically Adjusted Primary Balance, 2010–24(Percent of potential GDP)
201020112012201320142015201620172018201920202021202220232024
Australia-4.6-3.7-2.6-1.8-1.7-1.4-1.3-0.30.0-0.30.51.01.10.90.8
Austria-1.9-1.0-0.30.60.21.90.80.90.60.50.30.30.30.20.2
Belgium-0.6-1.1-0.80.40.40.50.21.31.10.50.30.10.10.10.0
Canada-3.2-2.5-1.4-0.50.81.41.20.30.10.00.00.20.30.30.3
Cyprus-3.9-4.5-2.40.03.93.73.23.74.13.02.82.82.83.13.3
Czech Republic-3.1-1.9-2.01.40.10.31.61.81.81.51.31.21.21.31.3
Denmark-1.0-0.7-1.70.52.4-0.30.00.4-0.3-0.5-0.6-0.5-0.3-0.10.2
Estonia3.02.00.00.31.00.6-0.1-0.5-0.2-0.10.00.00.00.0-0.1
Finland-1.8-1.5-1.5-1.1-0.70.10.20.1-0.7-0.4-0.3-0.2-0.10.00.1
France-3.8-2.6-2.2-1.4-1.4-1.4-1.3-1.0-1.0-1.7-0.8-0.9-0.9-0.9-0.9
Germany-1.40.51.61.61.71.81.71.41.91.31.20.91.01.11.2
Greece-3.32.06.28.26.26.18.47.66.35.44.64.13.73.02.8
Hong Kong SAR1-1.1-3.5-2.9-6.0-1.2-3.3-2.1-3.1-5.1-6.3-5.2-6.0-6.4-6.2-6.2
Iceland-5.0-2.10.11.63.52.514.42.82.52.52.62.52.22.21.7
Ireland1-6.7-4.0-2.3-1.20.31.11.01.51.21.11.21.31.51.81.9
Israel0.00.2-1.1-1.0-0.51.00.51.0-0.3-0.6-0.6-0.5-0.5-0.5-0.4
Italy0.61.03.43.73.33.02.51.91.81.40.50.30.20.20.2
Japan-7.1-6.9-6.5-6.6-4.7-3.7-3.4-2.9-2.8-2.7-2.1-1.9-1.8-1.9-2.1
Korea0.80.91.00.0-0.1-0.11.01.42.11.51.00.70.50.50.4
Latvia-3.1-1.31.60.0-0.20.30.9-0.1-0.3-0.30.20.10.20.30.5
Lithuania-2.6-5.7-0.4-0.41.11.52.01.61.60.90.70.70.80.80.8
Luxembourg-0.80.11.01.20.90.61.11.42.50.70.80.50.80.80.7
Malta0.61.20.51.61.30.32.75.02.11.81.71.92.01.91.9
Netherlands-3.4-2.9-1.40.20.80.41.92.11.30.80.70.81.01.21.4
New Zealand-3.9-3.2-0.40.20.51.01.51.40.60.51.01.21.51.51.5
Norway1-7.1-6.4-6.5-6.9-8.1-9.4-10.2-10.2-9.6-9.9-10.0-10.0-10.0-10.0-10.0
Portugal-8.3-2.61.22.4-0.11.63.01.12.62.43.03.53.13.13.2
Singapore
Slovak Republic-5.1-1.8-1.60.0-0.5-1.4-1.4-0.1-0.10.81.21.21.21.31.3
Slovenia-3.6-3.0-0.40.70.61.82.42.72.41.61.21.31.62.02.2
Spain1-6.9-5.5-0.90.40.90.1-0.4-0.3-0.4-0.5-0.6-0.7-0.6-0.7-0.7
Sweden10.80.2-0.4-0.6-0.7-0.50.61.00.30.20.10.10.10.10.1
Switzerland10.81.11.00.0-0.10.90.60.60.30.40.40.40.40.40.3
United Kingdom1-4.9-3.2-3.7-2.6-2.8-2.5-1.3-0.10.10.20.40.50.50.50.5
United States1,2-7.8-6.1-4.4-2.5-1.9-1.7-2.3-2.3-3.1-3.4-2.9-2.8-2.7-2.2-1.8
Average-5.1-3.9-2.8-1.7-1.2-1.1-1.2-1.0-1.3-1.6-1.3-1.3-1.2-1.0-0.9
Euro Area-2.6-1.30.01.01.01.01.00.90.90.50.40.30.30.40.4
G7-5.7-4.4-3.4-2.1-1.5-1.3-1.5-1.4-1.7-2.1-1.7-1.6-1.6-1.3-1.1
G20 Advanced-5.5-4.3-3.2-2.0-1.4-1.2-1.4-1.3-1.5-1.9-1.5-1.4-1.4-1.2-1.0
Source: IMF staff estimates and projections. Projections are based on staff assessment of current policies (see “Fiscal Policy Assumptions” in text).Note: Cyclically adjusted primary balance is defined as the cyclically adjusted balance plus net interest payable/paid (interest expense minus interest revenue) following the World Economic Outlook convention. For economy-specific details, see “Data and Conventions” in text, and Table B.

The data for these economies include adjustments beyond the output cycle.

For cross-economy comparability, expenditure and fiscal balances of the United States are adjusted to exclude the imputed interest on unfunded pension liabilities and the imputed compensation of employees, which are counted as expenditures under the 2008 System of National Accounts (2008 SNA) adopted by the United States, but not in economies that have not yet adopted the 2008 SNA. Data for the United States in this table may thus differ from data published by the US Bureau of Economic Analysis.

Source: IMF staff estimates and projections. Projections are based on staff assessment of current policies (see “Fiscal Policy Assumptions” in text).Note: Cyclically adjusted primary balance is defined as the cyclically adjusted balance plus net interest payable/paid (interest expense minus interest revenue) following the World Economic Outlook convention. For economy-specific details, see “Data and Conventions” in text, and Table B.

The data for these economies include adjustments beyond the output cycle.

For cross-economy comparability, expenditure and fiscal balances of the United States are adjusted to exclude the imputed interest on unfunded pension liabilities and the imputed compensation of employees, which are counted as expenditures under the 2008 System of National Accounts (2008 SNA) adopted by the United States, but not in economies that have not yet adopted the 2008 SNA. Data for the United States in this table may thus differ from data published by the US Bureau of Economic Analysis.

Table A5.Advanced Economies: General Government Revenue, 2010–24(Percent of GDP)
201020112012201320142015201620172018201920202021202220232024
Australia31.931.933.133.733.934.634.834.935.635.936.035.835.735.635.6
Austria48.448.349.049.749.650.048.648.348.347.748.048.048.048.048.0
Belgium49.350.351.652.752.251.350.651.351.350.750.450.450.450.450.4
Canada38.338.338.438.538.540.040.139.940.140.140.140.140.140.140.1
Cyprus37.336.736.436.739.839.038.038.939.638.437.637.437.437.437.6
Czech Republic39.340.340.541.440.341.140.240.542.142.242.142.142.142.142.1
Denmark54.054.454.554.656.453.252.652.352.151.751.451.251.050.850.7
Estonia40.738.639.038.338.539.739.238.940.140.140.139.939.739.439.1
Finland52.153.354.054.954.954.454.253.351.851.851.751.851.951.951.8
France50.051.152.153.153.353.253.253.853.652.452.051.651.551.451.4
Germany43.043.844.344.544.544.544.845.045.645.545.345.045.044.944.9
Greece41.343.846.247.946.247.949.548.349.047.546.045.244.444.244.0
Hong Kong SAR20.722.421.421.020.818.622.622.820.520.721.020.921.220.720.7
Iceland38.338.840.240.643.740.656.943.842.742.141.941.641.341.341.1
Ireland33.033.734.034.233.827.027.026.125.825.925.425.324.524.224.0
Israel36.836.836.036.336.536.636.537.836.736.536.436.436.436.436.4
Italy45.745.747.948.147.947.746.546.446.446.546.546.646.746.846.9
Japan29.030.030.831.633.334.234.334.233.934.034.634.734.734.734.7
Korea21.021.622.121.521.221.522.423.224.324.624.624.524.424.424.4
Latvia36.535.637.436.736.136.236.235.636.935.935.934.734.734.734.7
Lithuania34.332.632.132.133.434.133.632.834.134.934.834.834.734.734.6
Luxembourg43.542.944.444.343.343.343.644.546.345.345.545.645.745.845.8
Malta38.738.839.239.539.338.537.439.238.237.537.337.037.136.036.0
Netherlands41.841.542.042.842.841.842.843.743.544.444.244.044.144.144.1
New Zealand37.637.337.537.237.237.637.537.337.337.237.337.237.137.137.2
Norway55.356.556.154.153.854.153.954.255.155.354.655.055.255.656.0
Portugal40.642.642.945.144.643.842.842.743.043.243.343.843.543.543.5
Singapore21.123.122.121.321.121.221.522.621.521.421.121.121.221.321.3
Slovak Republic34.736.536.338.739.342.539.239.439.239.239.338.638.538.637.6
Slovenia40.840.641.640.641.240.439.339.140.540.240.340.640.941.341.5
Spain36.236.237.638.638.938.537.737.938.738.938.738.638.638.538.4
Sweden49.749.049.349.548.548.949.949.949.549.449.349.149.149.149.1
Switzerland32.432.732.632.732.433.533.333.333.333.333.333.333.333.333.3
United Kingdom35.235.735.736.135.235.536.036.636.937.037.036.937.037.137.1
United States29.029.329.331.431.331.531.130.930.931.131.531.631.732.032.3
Average34.935.535.636.836.836.436.336.436.536.436.636.536.636.736.8
Euro Area44.344.946.046.746.646.145.946.146.245.945.745.545.445.445.4
G734.234.834.936.336.436.236.036.036.136.036.236.236.336.436.6
G20 Advanced33.734.234.435.735.835.635.435.535.635.535.835.735.835.936.1
Source: IMF staff estimates and projections. Projections are based on staff assessment of current policies (see “Fiscal Policy Assumptions” in text).Note: For economy-specific details, see “Data and Conventions” in text, and Table B.
Source: IMF staff estimates and projections. Projections are based on staff assessment of current policies (see “Fiscal Policy Assumptions” in text).Note: For economy-specific details, see “Data and Conventions” in text, and Table B.
Table A6.Advanced Economies: General Government Expenditure, 2010–24(Percent of GDP)
201020112012201320142015201620172018201920202021202220232024
Australia37.036.336.636.536.837.437.436.436.837.436.635.835.635.635.6
Austria52.850.951.251.652.351.050.249.048.547.848.248.348.448.548.6
Belgium53.354.555.955.855.353.753.052.252.151.951.851.851.851.851.9
Canada43.141.640.940.038.440.040.640.340.640.740.740.740.740.740.7
Cyprus42.042.341.941.940.039.337.737.136.636.635.735.235.335.135.0
Czech Republic43.543.044.542.642.441.739.539.040.641.141.341.541.541.541.5
Denmark56.756.458.055.855.254.552.751.252.252.151.751.551.250.850.5
Estonia40.537.439.338.537.939.639.539.239.839.939.939.839.739.339.1
Finland54.854.456.257.558.157.155.954.052.852.151.851.851.951.951.8
France56.956.357.157.257.256.856.656.556.255.754.454.154.054.054.0
Germany47.344.744.344.744.043.743.943.943.944.344.344.244.244.244.2
Greece52.554.152.851.650.250.648.947.348.647.745.945.144.444.744.7
Hong Kong SAR16.618.618.320.017.318.018.217.318.519.419.420.120.419.819.8
Iceland47.844.243.842.443.841.444.543.341.741.541.441.140.840.840.6
Ireland65.046.542.040.437.529.027.526.325.725.925.225.024.023.523.1
Israel40.439.740.440.338.937.737.838.839.039.039.039.039.039.039.0
Italy49.949.450.851.150.950.349.048.948.549.249.950.150.350.550.7
Japan38.539.439.439.538.938.037.937.437.136.936.836.536.436.536.8
Korea19.519.920.620.920.820.920.720.821.522.523.123.523.723.723.7
Latvia43.038.837.237.337.837.836.636.437.636.736.335.435.235.234.9
Lithuania41.241.535.234.734.034.333.332.433.134.534.534.534.534.434.4
Luxembourg44.142.444.143.342.042.041.943.143.744.244.344.444.244.244.3
Malta41.141.242.741.941.139.636.535.737.336.936.736.336.435.435.4
Netherlands47.046.045.945.744.943.842.842.642.443.443.543.243.343.343.3
New Zealand43.042.339.738.637.737.436.736.237.037.036.636.235.835.935.9
Norway44.343.142.343.345.148.049.949.147.747.847.447.747.948.148.3
Portugal51.850.048.549.951.748.144.845.743.743.943.543.443.243.243.1
Singapore15.014.514.414.815.717.617.216.917.517.217.918.218.418.618.8
Slovak Republic42.140.840.641.442.045.141.540.240.039.239.038.338.138.237.2
Slovenia46.046.144.754.447.043.741.039.839.439.740.140.240.440.740.8
Spain45.645.848.145.644.843.742.241.041.441.141.141.041.141.241.2
Sweden49.749.250.250.950.148.748.848.448.748.849.048.848.848.848.8
Switzerland32.031.932.233.132.732.932.933.033.033.133.133.133.133.133.1
United Kingdom44.543.243.341.440.539.738.938.438.338.338.237.937.837.837.8
United States139.638.637.035.535.034.635.034.835.135.735.935.936.236.036.0
Average42.541.741.040.439.838.938.838.538.638.838.838.738.838.838.8
Euro Area50.549.249.749.749.148.247.547.046.846.946.646.546.546.546.5
G742.842.141.240.439.839.039.038.839.039.239.239.239.339.239.2
G20 Advanced41.941.140.339.639.038.338.338.038.238.538.538.438.538.438.5
Source: IMF staff estimates and projections. Projections are based on staff assessment of current policies (see “Fiscal Policy Assumptions” in text).Note: For economy-specific details, see “Data and Conventions” in text, and Table B.

For cross-economy comparability, expenditure and fiscal balances of the United States are adjusted to exclude the imputed interest on unfunded pension liabilities and the imputed compensation of employees, which are counted as expenditures under the 2008 System of National Accounts (2008 SNA) adopted by the United States, but not in economies that have not yet adopted the 2008 SNA. Data for the United States in this table may thus differ from data published by the US Bureau of Economic Analysis.

Source: IMF staff estimates and projections. Projections are based on staff assessment of current policies (see “Fiscal Policy Assumptions” in text).Note: For economy-specific details, see “Data and Conventions” in text, and Table B.

For cross-economy comparability, expenditure and fiscal balances of the United States are adjusted to exclude the imputed interest on unfunded pension liabilities and the imputed compensation of employees, which are counted as expenditures under the 2008 System of National Accounts (2008 SNA) adopted by the United States, but not in economies that have not yet adopted the 2008 SNA. Data for the United States in this table may thus differ from data published by the US Bureau of Economic Analysis.

Table A7.Advanced Economies: General Government Gross Debt, 2010–24(Percent of GDP)
201020112012201320142015201620172018201920202021202220232024
Australia120.524.127.730.734.137.840.540.740.741.140.639.738.937.536.4
Austria82.482.281.781.083.884.482.978.574.271.268.466.164.362.761.2
Belgium99.7102.6104.3105.5107.6106.5106.1103.4101.499.698.196.494.793.191.0
Canada181.381.985.586.285.791.391.890.190.688.084.781.378.074.972.0
Cyprus55.865.279.2102.1108.0108.0105.595.8102.5101.094.389.579.673.067.3
Czech Republic37.439.844.544.942.240.036.834.733.031.630.729.928.126.425.1
Denmark42.646.144.944.044.339.837.334.834.333.632.935.237.338.939.5
Estonia6.66.19.710.210.59.99.28.78.17.67.26.86.46.15.8
Finland47.148.553.956.560.263.563.061.360.559.959.058.556.855.053.3
France85.387.890.693.494.995.696.698.598.699.298.798.297.697.096.2
Germany81.078.679.977.474.570.867.963.959.856.953.851.148.546.043.7
Greece146.2180.6159.6177.9180.2177.8181.1179.3183.3174.2167.3160.9153.8147.2143.2
Hong Kong SAR10.60.60.50.50.10.10.10.10.10.00.00.00.00.00.0
Iceland85.492.089.481.878.865.051.243.135.433.130.127.825.723.322.0
Ireland86.0110.9119.9119.8104.376.973.568.565.262.458.957.154.051.047.8
Israel70.768.768.467.065.863.862.060.459.659.058.157.256.455.654.9
Italy115.4116.5123.4129.0131.8131.6131.3131.3132.1133.4134.1135.3136.4137.5138.5
Japan207.9222.1229.0232.5236.1231.6236.3235.0237.1237.5237.0237.4237.8238.0238.3
Korea30.831.532.235.437.339.539.939.840.740.540.741.141.842.242.4
Latvia46.442.941.539.040.936.840.340.037.636.735.134.733.131.830.5
Lithuania36.237.239.838.840.542.639.939.435.933.831.830.028.326.825.4
Luxembourg19.818.721.723.722.722.220.723.021.821.621.321.020.520.019.6
Malta67.570.267.768.463.457.955.450.245.442.539.135.732.130.028.2
Netherlands59.361.766.267.767.964.761.957.054.452.049.947.444.942.339.8
New Zealand29.734.735.734.634.234.433.531.629.428.127.326.825.923.521.2
Norway42.328.830.030.428.432.936.236.836.836.836.836.836.836.836.8
Portugal90.5111.4126.2129.0130.6128.8129.2124.8121.4119.5117.3111.3107.4106.3102.7
Singapore97.0100.4104.8101.296.199.4103.7106.9108.3109.4111.2111.8112.6112.8117.0
Slovak Republic41.243.752.254.753.552.251.850.948.846.945.143.341.539.838.6
Slovenia38.246.453.870.480.482.678.774.168.565.463.461.259.156.954.9
Spain60.169.585.795.5100.499.399.098.197.096.094.994.193.392.792.3
Sweden38.637.838.140.745.544.242.440.839.037.235.533.932.330.929.4
Switzerland42.642.943.742.943.043.041.841.840.539.538.236.935.734.633.4
United Kingdom75.280.884.185.287.087.987.987.186.985.784.483.682.681.580.3
United States195.499.7103.2104.8104.4104.7106.9106.2105.8106.7107.5108.4109.4110.0110.3
Average98.2102.4106.6105.1104.6104.2106.7104.6103.6104.0103.7103.7103.6103.3103.0
Euro Area84.686.689.791.691.889.989.186.885.083.681.880.378.677.275.7
G7111.6116.8120.9118.6117.4116.2119.4117.6116.7117.3117.4117.7118.0118.1118.1
G20 Advanced105.9110.3114.2112.2111.3110.8113.9112.0111.2111.8111.8112.1112.3112.3112.2
Source: IMF staff estimates and projections. Projections are based on staff assessment of current policies (see “Fiscal Policy Assumptions” in text).Note: For economy-specific details, see “Data and Conventions” in text, and Table B.

For cross-economy comparability, gross debt levels reported by national statistical agencies for countries that have adopted the 2008 System of National Accounts (Australia, Canada, Hong Kong SAR, United States) are adjusted to exclude unfunded pension liabilities of government employees’ defined-benefit pension plans.

Source: IMF staff estimates and projections. Projections are based on staff assessment of current policies (see “Fiscal Policy Assumptions” in text).Note: For economy-specific details, see “Data and Conventions” in text, and Table B.

For cross-economy comparability, gross debt levels reported by national statistical agencies for countries that have adopted the 2008 System of National Accounts (Australia, Canada, Hong Kong SAR, United States) are adjusted to exclude unfunded pension liabilities of government employees’ defined-benefit pension plans.

Table A8.Advanced Economies: General Government Net Debt, 2010–24(Percent of GDP)
201020112012201320142015201620172018201920202021202220232024
Australia 14.08.111.213.215.517.918.918.419.220.420.219.518.817.716.7
Austria60.560.360.560.459.158.357.155.951.048.846.845.344.243.242.4
Belgium 288.490.891.692.594.193.392.490.188.587.085.984.683.382.080.3
Canada 127.127.629.029.828.628.528.827.627.926.625.825.024.323.623.0
Cyprus48.152.567.178.189.591.386.979.5
Czech Republic25.526.828.329.129.428.124.921.5
Denmark15.015.118.518.318.216.516.715.014.814.714.614.414.113.613.0
Estonia-8.5-6.8-4.9-4.4-3.9-2.2-2.6-2.1-0.4-0.4-0.4-0.4-0.3-0.3-0.2
Finland 33.25.19.512.917.418.721.522.222.321.821.220.419.919.318.7
France73.676.480.083.085.586.487.587.587.688.287.787.386.786.085.2
Germany60.959.258.457.554.051.048.244.541.038.636.234.132.130.228.4
Greece
Hong Kong SAR
Iceland 464.359.962.060.553.647.439.735.629.728.926.824.823.121.419.8
Ireland 566.979.787.590.486.466.364.459.155.753.651.949.847.044.341.4
Israel64.363.263.162.262.160.258.757.156.455.955.254.553.853.152.5
Italy104.7106.8111.6116.7118.8119.5118.9119.0120.1121.5122.5123.8125.2126.6127.8
Japan131.1142.4146.7146.4148.5147.8152.6151.1153.2153.6153.2153.6153.9154.1154.5
Korea29.229.9-2.01.93.56.411.811.612.612.412.613.013.714.114.3
Latvia28.531.229.429.329.631.131.032.130.429.928.728.627.326.325.3
Lithuania26.333.133.434.232.734.632.332.429.327.525.924.322.921.720.5
Luxembourg-13.5-11.5-10.7-9.0-10.8-12.2-11.8-11.5-10.9-9.6-8.6-7.5-6.8-6.1-5.4
Malta57.258.257.959.053.949.543.037.9
Netherlands45.748.451.953.554.752.950.646.644.542.640.838.836.734.632.5
New Zealand4.78.810.811.010.49.99.18.08.810.310.810.58.86.54.2
Norway 6-47.4-48.3-50.0-61.3-75.9-87.0-85.3-80.8-79.1-84.5-89.3-93.9-98.4-102.9-107.5
Portugal82.196.1104.8108.2112.8113.9112.5110.1108.2107.0104.0100.697.594.591.3
Singapore
Slovak Republic
Slovenia26.632.236.745.546.650.452.451.9
Spain45.856.371.580.885.285.386.284.884.183.582.982.482.181.981.8
Sweden13.611.911.511.711.511.28.96.25.95.24.64.23.73.43.0
Switzerland24.224.423.922.923.123.322.822.120.819.818.517.316.014.913.7
United Kingdom68.172.575.576.878.879.3