Abstract

Oil-producing countries have benefited from rising oil prices in recent years. The increase in oil exports and oil revenues has had major implications for these countries. These developments have revealed how governments manage their fiscal policies in light of changing oil-market conditions and the role of special fiscal institutions (SFIs). In this Occasional Paper, IMF experts examine the fiscal response of oil-producing countries to the recent oil boom and the role of SFIs in fiscal management, they review the experiences of selected countries, and they draw general lessons. In doing so, they link findings on best practice in the design of SFIs with broader fiscal management advice.

Appendix I Expenditure Patterns in Oil-Producing Countries, 1999–2005

Table A1.1.

Government Expenditures in Selected Oil-Producing Countries

(As a share of non-oil GDP, unless otherwise noted)

article image
Sources: IMF staff reports and staff estimates.

Excluding two large outliers (Angola and Equatorial Guinea).

Lower-income countries are those defined by the World Bank as low-income or lower-middle-income countries. Higher-income countries are those defined by the World Bank as high-income or upper-middle-income countries (i.e., 2005 gross national income (GNI) per capita above $3,465).

Excludes Kazakhstan, Russia, and Timor-Leste, for which 1999 data are not available.

For Kazakhstan, Russia, and Timor-Leste, the base year is 2000.

Includes extrabudgetary funds when information is available.

Based on 12 countries with available data: Algeria, Azerbaijan, Cameroon, Chad, the Republic of Congo, Gabon, Indonesia, Nigeria, Saudi Arabia, Sudan, the United Arab Emirates, and the Republic of Yemen.

Appendix II Sustainable Fiscal Benchmarks—Key Assumptions and Further Considerations

Key Assumptions

The sustainable fiscal benchmark is based on a standard theoretical approach linked to the permanent income hypothesis (PIH) used to determine a sustainable fiscal policy for oil-producing countries. It is defined as the (permanent) annual non-oil primary deficit derived from government net wealth, which is the present value of projected future oil revenues plus the value of net government financial assets.1 IMF teams have increasingly applied similar analytical tools to oil-producing countries, with various intertemporal welfare criteria and country-specific assumptions. In this paper, a standardized and simple approach to estimate the sustainable benchmark has been applied to the whole sample to facilitate comparability.

Constructing a sustainability benchmark for oil-producing countries inclusive of estimated oil wealth depends on key assumptions in a similar way to the debt sustainability analysis (DSA) for other countries. In oil-producing countries, the analysis makes explicit a number of sensitive intertemporal welfare issues. Similar judgments about intertemporal welfare choices are made in the DSA for other countries, but are usually not made explicit. The following key assumptions were made:

  • Estimates of proven oil reserves were taken from British Petroleum (2005). This report includes annual series of estimated proven reserves dating back to at least 1980, which can be taken as “real-time” information available for each year. In addition to the discovery or incorporation of new oil reserves and their depletion, changes in reserves also reflect updated estimates.

  • Oil production during the projection period was assumed to remain constant at the level of the year for which the sustainability exercise was done (i.e., 2000 and 2005) until depletion.

  • Oil prices during the projection period were assumed to remain constant in real terms at the level observed in each particular year for which the analysis was carried out.

  • The government take from oil production used in the exercise was the average of the latest three to four years, to smooth out the effect of one-off oil revenue sources.

  • An interest rate of 3 percent in real terms (the historical average of long-dated U.S. treasury bonds) was used to discount future oil revenue flows.

  • A lower interest rate in real terms (2 percent) was applied to the estimated net government wealth in 2000 and 2005 to estimate a “sustainable” level of consumption for each of those years (“sustainable” non-oil primary deficits). The 2 percent rate was set as a “middle of the road” scenario between (1) a constant non-oil primary deficit in real terms but declining over time in terms of non-oil GDP (using a real interest rate of 3 percent, i.e., the return on financial risk-free assets) and (2) a constant non-oil primary deficit relative to non-oil GDP (using a real interest rate equivalent to 3 percent minus the longterm growth rate of the non-oil economy). The former approach would imply a more lax fiscal policy in the short run but a tighter one in the future, whereas the latter would require a tighter fiscal policy in the short run relative to option (1). Hence, using a 2 percent rate implies a more gradual adjustment of the non-oil primary deficit relative to non-oil GDP than in (1), but allows a higher deficit in the short run than in (2).2

Other approaches or assumptions could give different results, and therefore this exercise should be seen as a reference scenario for the analysis. There is substantial uncertainty about the appropriate parameters for the oil sector in the short run and more so in the long run. More conservative oil price assumptions would lead to lower estimated sustainable non-oil primary deficits. The opposite would be the case if probable reserves were included in the calculations. In addition, multiple dynamic paths could be designed to be equivalent to the (constant) sustainable benchmark.

Further Considerations

The sustainability analysis used in this paper has a “static” dimension in that it focuses on the fiscal position of one specific year at a time. A sustainability gap can be closed in future years in various ways, including increased non-oil revenue, reductions in spending, or changes in the fiscal regime of the oil sector. These factors can only be captured explicitly in a dynamic setting.

The quality of government spending, in particular public investment, can influence growth and future government revenue, and thus fiscal sustainability. Public investment could yield higher returns to the government than investments in financial assets. As shown in Takizawa, Gardner, and Ueda (2004), government spending could exceed the level prescribed by standard PIH-based models in the short term if the economy starts with a capital stock that is below the “steady state level,” and if the impact of government investment on growth exceeds a threshold level. At the same time, spending with significant positive impact on economic growth will improve fiscal sustainability, provided that governments are able to realize the fiscal dividends of growth. Additional revenue that may be required to cover significant depreciation and maintenance costs of the new public capital stock also needs to be taken into account. The financial returns may need to be quite high for the additional spending to have a neutral or positive impact on the government’s cash flow, and therefore on sustainability.3

Sound expenditure management practices, including project design and implementation, are needed to ensure that additional public spending is of high quality, productive, and cost-effective. Research has shown that the quality of policies and institutions has a large influence on the ex post rate of return of public investment and on the rate of growth. In this regard, existing institutional capacity and indices of government effectiveness need to be considered when assessing the potential impact of higher public spending on private investment, growth, and fiscal sustainability. In addition, public investment should be adequately financed to ensure that the projects initiated can be completed and then properly maintained.

1
Barnett and Ossowski (2003) offer a formal derivation of this approach. A simplified formulation, which can be modified to account for GDP or population growth (as discussed below), is the following:

Sustainable non-oil primary deficit = r/(1 + r) * government wealth = r/(1 + r) * (present value of oil revenue + financial assets − debt), where r is the real interest rate.

2

The 2 percent rate can also be justified to reduce vulnerabilities to negative shocks or relatively low real returns on financial assets in most countries.

3

Domestic fuel subsidies and population aging are examples of other medium- and long-term fiscal issues that should be considered when assessing fiscal sustainability in a dynamic setting.

Appendix III Objectives and Design Features of Fiscal Institutions in the Sample of Oil-Producing Countries

Table A3.1.

Features of Fiscal Responsibility Legislation and Fiscal Rules

article image
Sources: IMF staff papers and studies.

E = expenditures, NB = non-oil balance, OB = overall balance, D = debt.

Table A3.2.

Features of Oil Funds

article image
article image
article image

Appendix IV Econometric Analysis of the Impact of Fiscal Institutions on Fiscal Outcomes

This section provides a more detailed description of the econometric analysis presented in Section IV on the impact of SFIs on the policy response of oil-producing countries to the current oil boom. It describes the methodology and data.

Methodology and Data

The econometric analysis uses panel data to ensure more robust estimates of the impact of SFIs on fiscal outcomes.1 To measure the impact of SFIs on key fiscal variables, a dummy variable is used, which takes the value 1 if a country has an oil fund and/or fiscal rules, and zero otherwise. The analysis looks at the current oil boom and a longer period (1992–2005). The longer period is particularly relevant to assess the impact of the new SFIs, because a number of oil funds and fiscal rules were introduced in the late 1990s or early 2000s.

The methodologies applied in this paper are directed at estimating a robust relationship between fiscal outcomes and fiscal institutions taking into account some standard econometric problems. The key challenges for the econometric analysis are the following:

  • Countries with relatively large non-oil deficits or difficulties in containing spending may be the ones more likely to introduce SFIs. This could lead to biased estimates, as the SFI would “appear” to cause higher deficits or expenditure growth that are explained by time-invariant country specific-factors (“fixed effects”) not captured in the standard regressions. One methodology used to address the possible estimation bias is to run regressions that correct for fixed effects. The basic intuition is that by looking at the changes in the fiscal variables (instead of levels) the regressions will better capture the impact of the introduction of (or changes in) the institutional variable. In this particular case, the fixed effects regressions will be capturing the impact of introducing an oil fund and/or fiscal rule in a country.2 Nevertheless, some information could be lost by focusing on within-country variation. As such, a specification that incorporates a linear combination of cross-country and within-country variation (random effects regressions) was also tested.3

  • SFIs could be influenced by the dependent variables (e.g., the fiscal outcomes could lead to changes in the institutions). In general, earlier studies have assumed that variations in economic variables are unlikely to have immediate feedback on institutions—which tend to change slowly over time. Nevertheless, in this study the SFI variable only measures whether an SFI is present, which should minimize the endogeneity problem.4 Nevertheless, an econometric tool that attempts to correct for the possibility of feedback from the dependent variable, developed by Arellano and Bond (1991), is used.

  • It may be difficult to distinguish the impact of the introduction of SFIs in countries where that overlapped with the beginning of the oil boom. If the “state of the world” changed (with perceived long-lasting increases in oil prices), regressions could show that the SFIs are “causing” increases in the non-oil deficit, even though this increase may be mainly a response to higher oil revenue. However, the regressions compare the impact of SFIs not only over time but also across countries, while controlling for changes in net wealth and oil revenue (which would capture the impact of the oil boom). Furthermore governments did not know, ex ante, to what extent the oil shock was likely to be long lasting, and a gradual adjustment would be expected.

Most of the fiscal and national accounts data were provided by country teams or taken from past staff reports. In addition, a measure of net government wealth was estimated for every year as described in Section II. The analysis uses the International Country Risk Guide (ICRG) indices as proxies for the quality of overall institutions. The econometric analysis uses the index of political risk (PR), a composite index of 12 variables, and some of the individual indices that are included in the PR, including government stability, corruption, law and order, democratic accountability, and bureaucratic quality. These indices are commonly used in the literature, particularly as annual data are available.

1
The econometric analysis is based on a common specification for panel data (Baltagi, 2005):
yit=α+βxit+μi+vit.

with i denoting countries and t denoting time; μi denotes the unob-servable country-specific effect, and ?it denotes the more common disturbance factor. See discussion below on how to address the presence of μi in the panel data regressions.

2

This is similar to the usual “omitted variables” problem. The fixed effects regressions focus on the within-country variation, correcting for possible bias from unobserved country-specific effects. See Baltagi (2005) for a more technical discussion.

3

Baltagi (2005) discusses the use of fixed or random effects regressions. Another possibility would be to use event-studies techniques. However, this is not feasible owing to data constraints and difficulties in distinguishing the impact of introducing the institutions from the oil boom using this technique.

4

This problem is likely to be more relevant if the SFI variable measured “qualitative” aspects of the institution, which could potentially be dependent on fiscal outcomes. See also Fabrizio and Mody (2006).

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Cited By

The Role of Fiscal Institutions
  • Aizenman, Joshua, and Jaewoo Lee, 2005, “International Reserves: Precautionary vs. Mercantilist Views, Theory, and Evidence,IMF Working Paper 05/198 (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation
  • Richard, Allen, Dimitar Radev, 2006, “Managing and Controlling Extrabudgetary Funds,IMF Working Paper 06/286 (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation
  • Manuel Arellano, Stephen Bond, 1991, “Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations,Review of Economic Studies, No. 58 (April), pp. 27797.

    • Search Google Scholar
    • Export Citation
  • Askari, Hossein, Vahid Nowshirvani, and Mohamed Jaber, 1997, Economic Development in the GCC: The Blessing and the Curse of Oil, Contemporary Studies in Economic and Financial Analysis (Greenwich, Connecticut: Jai Press).

    • Search Google Scholar
    • Export Citation
  • Baltagi, Badi H., 2005, Econometric Analysis of Panel Data (Hoboken, New Jersey: John Wiley & Sons, 3rd ed.).

  • Barnett, Steven, and Rolando Ossowski, 2003, “Operational Aspects of Fiscal Policy in Oil-Producing Countries,” in Fiscal Policy Formulation and Implementation in Oil-Producing Countries, ed. by J. M. Davis, R. Ossowski, and A. Fedelino (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation
  • Barnett, Steven, and Alvaro Vivanco, 2003, “Statistical Properties of Oil Prices: Implications for Calculating Government Wealth,in Fiscal Policy Formulation and Implementation in Oil-Producing Countries, ed. by J. M. Davis, R. Ossowski, and A. Fedelino (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation
  • Bartsch, Ulrich 2006, “How Much Is Enough? Monte Carlo Simulations of an Oil Stabilization Fund for Nigeria,IMF Working Paper 06/142 (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation
  • British Petroleum, 2005, BP Statistical Review of World Energy (London).

  • Cashin, Paul, Hong Liang, and John McDermott, 1999, “How Persistent Are Shocks to World Commodity Prices?IMF Working Paper 99/80 (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation
  • Celasun, Oya, Xavier Debrun, and Jonathan David Ostry, 2006, “Primary Surplus Behavior and Risks to Fiscal Sustainability in Emerging Market Countries: A ‘FanChart’ Approach,IMF Working Paper 06/67 (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation
  • Davis, Jeffrey, Rolando Ossowski, James Daniel, Steven Barnett, 2001, Stabilization and Savings Funds for Non-renewable Resources, IMF Occasional Paper No. 205 (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation
  • Davis, Jeffrey, Rolando Ossowski, and Annalisa Fedelino, 2003, Fiscal Policy Formulation and Implementation in Oil-Producing Countries (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation
  • Diamond, Jack, 2006, Budget System Reform in Emerging Economies: The Challenges and the Reform Agenda, IMF Occasional Paper No. 245 (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation
  • Eifert, Benn, Alan Gelb, and Nils Borje Tallroth, 2003, “The Political Economy of Fiscal Policy and Economic Management in Oil-Exporting Countries,in Fiscal Policy Formulation and Implementation in Oil-Producing Countries, ed. by J. M. Davis, R. Ossowski, and A. Fedelino (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation
  • Fabrizio, Stefania, and Ashoka Mody, 2006, “Can Budget Institutions Counteract Political Indiscipline?IMF Working Paper 06/123 (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation
  • Iimi, Atsushi, 2006, “Did Botswana Escape from the Resource Curse?IMF Working Paper 06/138 (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation
  • International Monetary Fund, 2004, “Public Investment and Fiscal Policy” (Washington). Available via the Internet: www.imf.org/external/np/fad/2004/pifp/eng/PIFP.pdf

    • Search Google Scholar
    • Export Citation
  • International Monetary Fund, 2005a, “Oil Market Developments and Issues” (Washington). Available via the Internet: www.imf.org/ external/np/pp/eng/2005/030105.pdf

    • Search Google Scholar
    • Export Citation
  • International Monetary Fund, 2005b, “Public Investment and Fiscal Policy—Lessons from the Pilot Country Studies” (Washington). Available via the Internet: www.imf.org/external/np/ pp/eng/2005/040105a.pdf

    • Search Google Scholar
    • Export Citation
  • International Monetary Fund, 2006, “Oil Prices and Global Imbalances,in World Economic Outlook, April 2006: Globalization and Inflation, World Economic and Financial Surveys (Washington).

    • Search Google Scholar
    • Export Citation
  • International Monetary Fund, 2007, “Fiscal Policy Response to Scaled-Up Aid” (Washington). Available via the Internet: www.imf.org/external/np/pp/2007/eng/060507.pdf.

    • Search Google Scholar
    • Export Citation
  • International Monetary Fund, and World Bank, 2006, “Applying the Debt Sustainability Framework for Low-Income Countries Post Debt Relief” (Washington). Available via the Internet: www. imf.org/external/np/pp/eng/2006/110606.pdf

    • Search Google Scholar
    • Export Citation
  • Katz, Menachem, Ulrich Bartsch, Harinder Malothra, and Milan Cuc, 2004, Lifting the Oil Curse, Improving Petroleum Revenue Management in Sub-Saharan Africa (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation
  • Kaufmann, Daniel, Aart Kraay, Massimo Mastruzzi, 2005, “Governance Matters IV: Governance Indicators for 1996–2004,Policy Research Working Paper No. 3630 (Washington: World Bank).

    • Search Google Scholar
    • Export Citation
  • Kopits, George, and Steven Symansky, 1998, Fiscal Policy Rules, IMF Occasional Paper No. 162 (Washington: International Monetary Fund).

  • Kumar, Manmohan, and Teresa Ter-Minassian, 2007, Promoting Fiscal Discipline (Washington: International Monetary Fund).

  • Paolo, Manasse, 2006, “Procyclical Fiscal Policy: Shocks, Rules, and Institutions—A View from MARS,IMF Working Paper 06/27 (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation
  • Mehlum, Halvor, Karl Ove Moene, and Ragnar Torvik, 2006, “Institutions and the Resource Curse,Economic Journal, Vol . 116 (January), pp . 120.

    • Search Google Scholar
    • Export Citation
  • Oxford Policy Management (OPM), 2000, “Medium-Term Expenditure Frameworks—Panacea or Dangerous Distraction?OPM Review Paper No. 2 (Oxford, May).

    • Search Google Scholar
    • Export Citation
  • Potter, Barry, and Jack Diamond, 1999, Guidelines for Public Expenditure Management (Washington: International Monetary Fund).

  • Rodrik, Dani, 2006, “The Social Cost of Foreign Exchange Reserves,NBER Working Paper No. 11952 (Cambridge, Massachusetts: National Bureau of Economic Research).

    • Search Google Scholar
    • Export Citation
  • Feridoun Sarraf, 2005, Integration of Recurrent and Capital “Development” Budgets: Issues, Problems, Country Experiences, and the Way Forward (Washington: World Bank).

    • Search Google Scholar
    • Export Citation
  • Schick, Allen 1998, A Contemporary Approach to Public Expenditure Management (Washington: World Bank).

  • Herman, Schwartz, 1997, “Reinvention and Retrenchment: Lessons from the Application of the New Zealand Model to Alberta, Canada,Journal of Policy Analysis and Management, Vol . 16 (Summer), pp. 40522.

    • Search Google Scholar
    • Export Citation
  • Spackman, Michael, 2002, “Multi-Year Perspective in Budgeting and Public Investment Planning,” draft background paper for discussion at the OECD Global Forum on Sustainable Development, Organization for Economic Cooperation and Development, Paris, April 2426.

    • Search Google Scholar
    • Export Citation
  • Takizawa, Hajime, Gardner, Edward and Kenichi Ueda, 2004, “Are Developing Countries Better Off Spending Their Oil Wealth Upfront?IMF Working Paper 04/141 (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation
  • Tornell, Aaron, and Philip R. Lane, 1999, “The Voracity Effect,American Economic Review, Vol . 89 (March), pp. 2246.

  • United States Department of Energy, 1982, “1981 Annual Report to Congress, Vol. 3, Energy Projections” (Washington: Energy Information Administration).

    • Search Google Scholar
    • Export Citation
  • United States Department of Energy, 1986, “Annual Energy Outlook 1985, with Projections to 1995” (Washington: Energy Information Administration).

    • Search Google Scholar
    • Export Citation
  • United States Department of Energy, 1989, “Annual Energy Outlook 1989 with Projections to 2000” (Washington: Energy Information Administration).

    • Search Google Scholar
    • Export Citation
  • World Bank, 1998, Public Expenditure Management Handbook (Washington).

  • World Bank, 2005, “The Medium-Term Expenditure Framework: The Challenges of Budget Integration in SSA Countries,Africa Region Working Paper No. 82 (Washington).

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  • World Bank, 2006, Experiences with Oil Funds: Institutional and Financial Aspects, Energy Sector Management Assistance Program Report No. 321/06 (Washington).

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