Since the emphasis of this pamphlet is on the role of macroeconomic policy in supporting a country’s poverty reduction strategy, the discussion of macroeconomic policies in this section focuses on countries that have broadly achieved macroeconomic stability. Recent data indicate that many developing countries are presently in a state of macroeconomic stability (see Tables 1–3 at the end of this pamphlet). When formulating a country’s poverty reduction strategy, policymakers will need to assess and determine what is the most appropriate combination of key macroeconomic targets that would preserve macroeconomic stability in their particular circumstance. Three key issues are discussed in this section: (1) how to finance poverty-reducing spending in a way that doesn’t endanger macroeconomic stability; (2) what specific policies can be adopted to improve macroeconomic performance; and (3) policies to protect the poor from domestic and external shocks.
Financing Poverty Reduction Strategies
Once a country has developed a comprehensive and fully costed draft of its poverty reduction strategy, it will need to ensure that the strategy can be pursued and financed in a manner that does not jeopardize its macroeconomic stability and growth objectives.20 To do so, policymakers need to integrate their poverty reduction and macroeconomic strategies into a consistent framework. The following paragraphs present a conceptual framework that could be useful to policymakers in determining whether their poverty reduction strategy is consistent with their macroeconomic objectives.
Given that it is difficult to determine beforehand what the growth target should be, policymakers may wish to consider developing alternative macroeconomic scenarios that take into consideration possible variations in the rate of economic growth. Such scenarios could be usefully discussed with stakeholders and development partners with a view to assessing the impact of lower-than-projected economic growth on key macroeconomic targets and poverty outcomes and to developing appropriate contingencies. The most likely or “base case” scenario would then be used as the basis for carrying out an initial attempt aimed at integrating the macroeconomic and poverty reduction strategies into a consistent framework. Once this has been accomplished, similar exercises could be carried out regarding the other contingency scenarios for reference during the implementation stage of the strategy.
Figure 1 shows the various macroeconomic linkages and constraints within a country and highlights the main tradeoffs facing policymakers. The starting point is the initial articulation of the country’s poverty reduction strategy, based on discussions with representatives of the government, stakeholders, and development partners. Ideally, these discussions will have resulted in the development of a comprehensive action plan that identifies priority sectoral policies to be pursued in support of poverty reduction, including in the areas of education, health, and rural infrastructure. Given that poverty is multidimensional, the action plan will also likely include priority measures with regard to governance, structural reform, and other relevant areas, each of which may have budgetary implications.


Financing Poverty Reduction Strategies in a Sustainable Manner


Financing Poverty Reduction Strategies in a Sustainable Manner


Financing Poverty Reduction Strategies in a Sustainable Manner


Financing Poverty Reduction Strategies in a Sustainable Manner
Financing Poverty Reduction Strategies in a Sustainable Manner
The first step will be to provide a full costing of the envisaged poverty reduction strategy. A comprehensive system for budget formulation of poverty reduction strategies requires the development of Medium-Term Expenditure Frameworks (MTEF), which currently exist in only a limited number of countries (e.g., Ghana and Uganda). Details regarding how such costing exercises can be carried out are presented in Chapter 5 of the Poverty Reduction Strategy Sourcebook, “Public Spending for Poverty Reduction”21
The second step involves an assessment of the government’s spending program with regard to priority spending, nondiscretionary spending, and discretionary nonpriority spending. In doing so, policymakers should consider the scope for reallocating existing government spending into priority areas and away from nonproductive, nonpriority spending, as well as from areas where a rationale for public intervention does not exist.
The third step involves an assessment of domestic and external sources of budget finance. This would include a review of (1) the existing tax and nontax revenue base, including the effect of any changes in the tax system envisaged under the poverty reduction strategy; (2) the scope for financing public spending through net domestic borrowing in light of the need to maintain macroeconomic stability and to ensure adequate availability of credit to the private sector in support of private sector development and economic growth; and (3) the scope for external financing (e.g., grants, net external borrowing, and debt relief) that is realistic and sustainable under the present circumstances.
Once policymakers have carried out these assessments, they can then determine whether the desired poverty reduction strategy can be financed in a manner consistent with the country’s growth and stability objectives. In this regard, it is important to note that there are no rigid, pre-determined limits regarding a country’s fiscal stance (such as, for example, “the budget deficit must not be more than ‘x’ percent of GDP”). Rather, arriving at an appropriate, integrated poverty reduction and macroeconomic framework will require juggling a large number of parameters and weighing the trade-offs between multiple objectives. The linkages in Figure 1 are meant to illustrate that this is an iterative process. In this regard, quantitative frameworks that could assist policymakers in assessing the distributional implications of their macroeconomic policies would be particularly useful. Such frameworks, however, are presently only at a nascent stage of development (see Box 3).
If there remains an imbalance between spending and expected financing that could jeopardize the country’s macroeconomic growth and stability objective, one option would be to ascertain the extent to which additional external financing may be available. But, as discussed earlier, policymakers would need to assess the extent to which accommodating such expenditure could place pressure on the price of nontraded goods and jeopardize stability. Since the development of a poverty reduction strategy involves a participatory process that includes the country’s development partners, the case for additional donor support can be examined. To the extent possible, donors should be encouraged to make medium-term aid commitments in support of a country’s poverty reduction strategy so that the country can have confidence as it begins new spending programs that these activities can be sustained.22
Quantitative Frameworks for Assessing the Distributional Impact of Macroeconomic Policies
In developing poverty reduction strategies, policymakers would benefit from a quantitative framework that they could use to assess the distributional impact of the macroeconomic policy options under consideration. Such a framework would be useful because the links between macroeconomic policies and poverty are complex. A quantitative framework that identifies the critical relationships on which the outcome depends could therefore assist countries in assessing these trade-offs.
What would be some of the desirable characteristics of such a quantitative framework? First, the framework should be capable of identifying some of the critical trade-offs in poverty-reducing macroeconomic policies. For example, how do the costs (in terms of poverty) of higher spending (and higher fiscal deficits) compare with the benefits of targeting that spending on the poor? Second, the framework should be consistent with economic theory on the one hand, and with basic data availability, such as national accounts and household income and expenditure surveys, on the other. Otherwise, the frameworks will not be able to foster a dialogue between conflicting parties on these issues. Third, and most important, the framework should be simple enough that government officials can use it on their desktop computers. This means that it should not make undue demands on data, and it should be based on readily available software, such as Microsoft Excel™.
World Bank staff is presently developing alternative quantitative frameworks that could be used to evaluate some of the macroeconomic aspects of poverty reduction strategies.1 It is expected that other possible quantitative frameworks will be developed over time that could assist country teams in this regard.
1 See Agenor and others (2000). In developing this particular framework, the authors opted for a modular approach that allows different models to be incorporated as alternative sub-components of the overall framework.If the desired poverty reduction program cannot be financed in a manner consistent with the country’s economic stability and growth objectives, then policymakers will need to reconsider the parameters discussed above. Key questions would include: Is there further scope for domestic revenue mobilization? Can discretionary nonpriority spending be cut back more? Is there scope for cutting back certain priority spending without undermining the poverty reduction objective? Can the domestic financing target be relaxed without jeopardizing macroeconomic stability or private sector development objectives? Can the macroeconomic targets be modified in a manner that would not undermine the interrelated objectives of rapid economic growth, low and stable inflation, and poverty reduction? The answers to these questions will determine the extent to which the desired poverty reduction programs can be pursued in the current period.
Fiscal Policy
Fiscal policy can have a direct impact on the poor, both through the government’s overall fiscal stance and through the distributional implications of tax policy and public spending. Structural fiscal reforms in budget and treasury management, public administration, governance, transparency, and accountability can also benefit the poor in terms of more efficient and better targeted use of public resources. As indicated above, there is no rigid, pre-determined limit on what would be an appropriate fiscal deficit. An assessment would need to be based on the particular circumstances facing the country, its medium-term macroeconomic outlook, and the scope for external budgetary assistance. The terms on which external assistance is available are also important. There is a strong case, for instance, for allowing higher grants to translate into higher spending and deficits, to the extent that those grants can reasonably be expected to continue in the future, and provided that the resources can be used effectively.
With regard to the composition of public expenditure, policymakers will need to assess not only the appropriateness of the proposed poverty reduction spending program, but also of planned nondiscretionary, and discretionary nonpriority, spending. In so doing, they will need to take into particular consideration the distributional and growth impact of spending in each area and place due emphasis on spending programs that are pro-poor (e.g., certain programs in health, education, and infrastructure) and on the efficient delivery of essential public services (e.g., public health, public education, social welfare, etc.). In examining these expenditures, policymakers should evaluate the extent to which government intervention in general, and public spending in particular, can be justified on grounds of market failure and/or redistribution.
Policymakers must also ask themselves whether the envisaged public goods or services can be delivered efficiently (e.g., targeted at the intended beneficiaries) and, if not, whether appropriate mechanisms and/or incentives can be put in place to ensure such efficient delivery. Countries should begin by assessing in a frank manner their administrative capacity at both the national and subnational levels to deliver well-targeted, essential public services in support of poverty reduction. In this regard, policymakers should consider the extent to which both technical assistance and the private sector can play a role in improving the delivery of these services.
In the context of medium-term budget planning, policymakers should consider the scope for reallocating existing government spending into priority areas23 and away from nonproductive spending, including areas where a rationale for public intervention does not exist. Operation and maintenance expenditure tied to capital spending should also be reviewed with a critical eye. The quality of public expenditure could be assessed in the context of a public expenditure review with the assistance of multilateral and/or bilateral donors. Policymakers could then assess the new poverty reduction projects and activities that have been identified in the context of the poverty reduction strategy and integrate them into the preliminary spending program. In so doing, they should attempt to rank the poverty programs in order of relative importance in line with the country’s social and economic priorities, the market failure/redistribution criteria identified above, and the country’s absorptive capacity in the light of existing institutional and administrative constraints. If spending cuts are deemed necessary in the context of the integrated poverty reduction/macroeconomic framework, policymakers should refer back to the ranking of the spending program based on the relative importance and priority assigned to each activity.
A key aspect of any poverty reduction strategy will be an assessment of the impact of the present tax and nontax system on the poor. An important medium-term objective for many developing countries will be to raise domestic revenue levels with a view to providing additional revenue in support of their poverty reduction strategies.24 The existing revenue base should be reviewed relative to its capacity to provide for the poverty spending requirements from nonbank domestic financing. Revenues should be raised in as economically neutral a manner as possible, while taking into consideration equity concerns and administrative capacities (see Box 4).
In a developing country , taking account of allocational effects means that the tax system in particular should not attempt to affect savings and investment—experience indicates that aggregate savings and investment tend to be insensitive to taxes, with the result that the tax system typically only affects the allocation of those aggregates across alternative forms. As regards equity, the tax system should be assessed with respect to its direct and indirect impact on the poor. It is difficult to have a tax system that is both efficient and progressive, particularly in those countries without a well-developed tax administration. Therefore, governments should seek to determine a distribution of tax burdens seen as broadly fair rather than use the tax system to achieve a drastic income redistribution.
Tax policy should aim at moving toward a system of easily administered taxes with broad bases and moderate marginal rates. To the extent that some revenue provisions may be regressive, they should be offset through the expenditure system (e.g., transitory, well-targeted food subsidies could offset the impact of a broad-based consumption tax and cushion the adverse impact of adjustment policies on the poor). Finally, where revenue systems are being administered by a civil service that is highly constrained in terms of human resources, technical support, and funding, countries should rely heavily on final withholding, and keep to the absolute minimum any exemptions, special provisions, or multiple rates.
Tax Policy
The best tax systems typically include most or all of the following elements:
A broad-based consumption tax, such as a VAT, preferably with a single rate, minimal exemptions, and a threshold to exclude smaller enterprises from taxation. The VAT generally should extend through the retail sector, and should apply equally to domestic production and imported goods and services. The VAT should cover agricultural products and inputs, subject to the threshold, which will exclude small farmers.
Excise taxes should apply to petroleum products, alcohol, and tobacco; should be collected at the point of production or import; and should apply equally to domestic production and imports.
Taxes on international trade should play a minimal role. Import tariffs should have a low average rate and a limited dispersion of rates, to reduce arbitrary and excessive rates of protection. Exemptions should be kept at a minimum and nontariff barriers should be avoided altogether. Exporters should have duties rebated on imported inputs used for producing exports and export duties should generally be avoided.
The personal income tax should be characterized by only a few brackets and a moderate top marginal rate, by limited personal exemptions and deductions, by a standard exemption that excludes persons with low incomes, and by extensive use of final withholding.
The corporate income tax should be levied at one moderate rate. Depreciation allowances should be uniform across sectors, and there should be minimal use of tax incentives other than permitting net operating losses to be carried forward for some reasonable period of time.
The use of a simplified regime for small businesses and the informal sector may complement these major taxes. Real property taxes may also be used if they can be administered appropriately, though this may be difficult in developing countries.
The scope for domestic budgetary financing will depend on a number of factors, including the sustainable rate of monetary growth, the credit requirements of the private sector, the relative productivity of public investment, and the desired target for net international reserves. Sacrificing low inflation (through faster monetary growth) to finance additional expenditure is generally not an effective means to reduce poverty because the poor are most vulnerable to price increases. At the same time, since private sector development stands at the center of any poverty reduction strategy, governments need to take into account the extent to which public sector borrowing “crowds out” the private sector’s access to credit, thereby undermining the country’s growth and inflation objectives. At times, public sector borrowing can also “crowd in” private sector investment by putting in place critical infrastructure necessary for private enterprise to flourish. Given that at any point in time there is a finite amount of credit available in an economy, policymakers must therefore assess the relative productivity of public investment versus private investment and determine the amount of domestic budgetary financing that would be consistent with the need to maintain low inflation and support sustainable economic growth.
The amount and type of available external resources to finance the budget will vary depending on the particular circumstances facing the country. Countries that have access to external grants need to consider what amount is available and sustainable under the present circumstances. The same is true in the case of external debt, but policymakers also need to determine whether the terms on such borrowing are appropriate and whether the added debt burden is sustainable. To the extent that a country is benefiting from, or may benefit from, external debt relief under the enhanced Heavily Indebted Poor Countries (HIPC) Initiative, net resource flows—flows that are predictable over the medium term—will be freed up to finance poverty-related budgetary expenditure. Domestic debt reduction could also represent a viable use of additional concessional foreign assistance, since it would both free up government resources to be directed at priority poverty expenditure, as well as free up additional domestic credit for use by the private sector.
There may be a limit to the amount of additional external financing that a country would deem to be appropriate, however. For example, there may be absorptive capacity constraints that could drive up domestic wages and prices, as well as appreciate the exchange rate and render the country’s exports less competitive, thereby threatening both stability and growth. The extent of such pressures will depend on how much of the additional aid is spent on imports versus domestic nontraded goods and services. There may also be uncertainty regarding aid flows, especially over the medium term, as well as considerations regarding long-term dependency on external official aid. In the absence of medium-term commitments of aid, policymakers may therefore wish to be cautious in assuming what levels of assistance would be forthcoming in the future.
Monetary and Exchange Rate Policies
Monetary and exchange rate policies can affect the poor primarily through three channels: inflation, output, and the real exchange rate. As mentioned above, inflation hurts the poor because it acts as a regressive tax and curbs growth. Fluctuations in output clearly have a direct impact upon the incomes of the poor, and monetary and exchange rate policies affect these fluctuations in two ways: first, changes in the money supply can have a short-run effect on real variables such as the real interest rate,25 which in turn affect output; and second, a country’s chosen exchange rate regime can buffer, or amplify, exogenous shocks. Finally, the real exchange rate can affect the poor in two ways.26 First, it influences a country’s external competitiveness and hence its growth rate. Second, a change in the real exchange rate (through, for example, a devaluation of the nominal rate) can have a direct impact on the poor.27
Given that monetary and exchange rate policies affect the poor through their impact on inflation, output, and the real exchange rate, it might seem, at first glance, that such policies should therefore be used to target all three of these variables. However, although monetary and exchange rate policies may affect the poor through all of these channels, the monetary authorities cannot necessarily control the size and nature of the resulting impact. For example, changes in the money supply may affect output and employment in the short run, but they do so in a way that is at best uncertain and imperfectly understood. As a result, monetary authorities are typically unable to exploit this impact systematically. Similarly, monetary and exchange rate policies are unable to manipulate the real exchange rate beyond a short period of time. Therefore, actively using these policies to pursue a particular short-run exchange rate goal, which may be inconsistent with underlying economic fundamentals, could introduce instability.
Monetary and exchange rate policies should target those variables over which they have the most control, namely the long-run impact of inflation on the rate of growth. Broadly speaking, this can be achieved by setting one objective for monetary and exchange rate policies: the attainment and maintenance of a low and stable rate of inflation. In practice this means (1) choosing, and firmly committing to, an inflation rate target within the context of the overall poverty reduction strategy and the associated macroeconomic framework; (2) adopting the required policies to achieve the target; and (3) not using monetary and exchange rate policies to pursue, overtly or otherwise, additional or alternative objectives. Formulated and implemented in this way, monetary and exchange rate policies can form the basis for a stable macroeconomic environment.
Improving Inflation Performance
In some cases, it may be desirable to target a lower rate of inflation. What policies can help meet this objective? Ultimately, this question has to be answered on a case-by-case basis. However, policymakers should consider two general policies that are essential parts of any effort to improve inflation performance: strong and sustained fiscal adjustment; and the use of a nominal anchor and other measures (e.g., inflation targeting) to enhance policy credibility.
Fiscal Adjustment
A loose fiscal stance can put upward pressure on prices through two channels: aggregate demand and financing. Such a fiscal stance increases the demand for domestic goods, which, in the absence of a corresponding increase in supply, puts upward pressure on their prices. It can also increase demand for imports, putting downward pressure on the value of the domestic currency and, hence, (in a flexible exchange rate regime) upward pressure on the prices of imported goods. Further, if the fiscal stance is financed by printing money, this expands the money supply and tends to increase inflation.
In theory, if inflationary pressures from the fiscal stance are being transmitted exclusively through the financing channel, then inflationary pressures could be reduced without fiscal adjustment if alternative (sustainable) sources of financing, such as external financing, are available. In practice, however, some fiscal adjustment is typically also necessary because either the amount of alternative finance is insufficient and/or the fiscal stance is also putting upward pressure on prices through the aggregate demand channel. Indeed, evidence shows that successful disinflation episodes have typically been accompanied by sizable and sustained fiscal adjustment (Phillips, 1999). Therefore, countries that wish to target a significantly lower rate of inflation need to ensure that the corresponding fiscal adjustment is adequate.
Credibility and Nominal Anchors
Setting policy targets is important. Consistently achieving those targets is equally important. When targets under a policy are systematically missed, the policy loses credibility. If a policy lacks credibility, the private sector does not believe that the authorities are truly committed to their policy targets, and hence does not fully factor the authorities’ targets into its inflation expectations, for instance when setting wage bargains. This can result in an inflation bias—that is, higher inflation outcomes brought on solely by the lack of policy credibility itself.
Credibility can sometimes be enhanced by imposing restrictions on policy (i.e., limiting the degree of discretion of the monetary authorities), or by adopting specific institutional arrangements. For example, the adoption of a fixed exchange rate regime involves a commitment to exchange domestic currency for foreign currencies at a predefined rate. This imposes an automatic discipline upon domestic monetary policy. In effect, control over monetary policy is surrendered to the central bank of the country whose currency has been chosen as the peg—typically a low inflation country—which, in turn, imparts credibility to the domestic policy objective of achieving low inflation.
More generally, evidence shows that inflation performance has been better in countries using a nominal anchor (Phillips, 1999). Using a nominal anchor involves specifying and committing to a predetermined path for a nominal variable—such as the exchange rate (i.e., the fixed exchange rate discussed above is a nominal anchor) or a money aggregate—that is to a certain degree under the control of the authorities.28 If the variable threatens to deviate from its targeted path the authorities take corrective action.29 In this way, inflation, and inflationary expectations, can be anchored.
In some countries, fixed exchange rate regimes have clearly been effective in establishing and maintaining low inflation. More generally, there is empirical evidence that inflation performance has been better in countries running fixed exchange rate regimes (see, for example, Ghosh and others, 1999). However, the choice of a fixed exchange rate has to be based on broader considerations than simply its merits as a nominal anchor. In particular, the underlying structural features of an economy need to be supportive of a fixed regime broadly speaking (for example, the degree of price rigidity, the nature of its predominant exogenous shocks, the degree of political support, etc.—these issues are discussed below). Adopting a fixed exchange regime to serve only temporarily as a nominal anchor can be risky. Exiting a fixed regime once inflation performance is satisfactory can be difficult. Moreover, if a country’s economic conditions are not supportive, or political support for the policy insufficient, the peg could come under considerable pressure, which may, in the end, force a costly abandonment of the regime and undermine the original objective of stabilizing inflation.
Both types of nominal anchors restrict the use of monetary instruments.30 A standard critique has been that, although the use of a nominal anchor may improve inflation performance, it comes at the cost of reducing the discretion of the authorities to respond to short-run shocks. In practice this trade-off may not be significant, however. Even if the monetary authorities have full discretion,31 as discussed above, their ability to influence short-run output movements systematically is limited. Moreover, their ability to exercise discretion is likely to be limited by the need to preserve, or enhance, policy credibility.
Inflation targeting has been adopted as the monetary regime in an increasing number of industrialized and developing countries in recent years. It is typically and preferably associated with a flexible exchange rate system. Inflation targeting sets an inflation target for the central bank and gives the responsibility for achieving the target to the central bank. To enhance accountability, credibility, and efficiency, the central bank in an inflation targeting regime is generally required to be extremely transparent about its operations, explaining its decisions to the public, publishing, in most cases, a regular inflation report.
In the long run, however, only policies to which the authorities are fully committed can be credible. Imposing restrictions on policy when the necessary policy commitment is absent (or even when the private sector erroneously suspects a lack of commitment) can have disastrous results. For example, the private sector’s belief that a country’s authorities are not committed to defending its fixed exchange rate may lead to a speculative attack on the peg. Although devices may be used to accelerate the attainment of a policy’s credibility, there is no substitute for commitment to the policy, as demonstrated through sustained adherence to a prudent macroeconomic stance.
External Shocks and the Choice of Exchange Rate Regime
The choice of exchange rate regime—fixed or flexible—depends crucially on the nature of the economic shocks that affect the economy, as well as the structural features of the economy, which may either mitigate or amplify these shocks. Choosing a fixed exchange rate regime when these underlying features of the economy are not supportive leaves a country more exposed to the possibility of an external crisis, which can result in the ultimate abandonment of the peg. In addition, shocks to output can have a strong impact on the poor. Since different exchange rate regimes have different insulating properties vis-à-vis certain types of shocks, choosing the regime that best insulates the economy will serve to moderate fluctuations in output, and thereby best serve the poor.
For example, if the predominant source of disturbance to an economy is shocks to the terms of trade, a flexible exchange rate regime may be best because the nominal exchange rate is free to adjust in response to the shock and bring the real exchange rate to its new equilibrium (see, for example, Devarajan and Rodrik, 1992). Alternatively, if domestic monetary shocks predominate, such as shocks to the demand for money, output may be best insulated by a fixed exchange rate that allows these shocks to be absorbed by fluctuations in international reserves. Of course, one of the challenges facing the policymaker is to identify which shocks are in fact predominant in a particular economy.
The structural features of the economy may also affect the impact a particular shock has on the economy, as well as the insulating properties of exchange rate regimes. For example, if an economy is characterized by a significant degree of nominal wage rigidity, wages will not fully adjust (at least in the short run) in response to small real shocks, and hence the effect of those shocks on output will be amplified. In these circumstances, even if domestic monetary shocks are important, a flexible exchange rate regime may well be preferable (in contrast to the conclusions above). Another important structural feature is the degree of an economy’s openness. Typically the more open an economy is, the greater is its exposure to external shocks. This would argue generally in favor of a flexible exchange rate regime. However, if an open economy is sufficiently diversified (i.e., it trades a wide range of goods and services) and if its prices are sufficiently flexible, then a fixed exchange rate may be preferable because the volatility of flexible exchange rates may impede international trade, and thus lower external demand (although the evidence on this is mixed). In conclusion, these various pros and cons of fixed versus flexible exchange rate regimes need to be carefully assessed and weighed on a case-by-case basis—again, there is no universal “right answer.”
Policies to Insulate the Poor Against Shocks
Given that the poor are adversely affected by macroeconomic shocks, what should governments do about it? The question can be divided into two parts: How should economic policy be designed to cushion the impact of shocks on the poor, in particular during times of crisis and/or adjustment? What specific policies can governments undertake to insulate the poor from the consequences of shocks by removing existing distortive policies?
Social Safety Nets
Sound macroeconomic policies will help a country to reduce its exposure to macroeconomic shocks, but there is no cost-effective policy that will insure against all possible shocks. It is therefore crucial to have social safety nets in place to ensure that poor households are able to maintain minimum consumption levels and access to basic social services during periods of crisis. Social safety net measures are also necessary to protect the poor from shocks imposed on them during periods of economic reform and adjustment.32 Safety nets include public work programs, limited food subsidies, transfers to compensate for income loss, social funds, fee waivers, and scholarships for essential services such as education and health. The specific mix of measures will depend on the particular characteristics of the poor and their vulnerability to shocks and should be well-targeted and designed in most cases to provide temporary support.
Equally important, the resources allocated to social safety nets should be protected during economic crises and/or adjustment, when fiscal tightening may be necessary. Governments should have budgetary guidelines approved by their legislatures that prioritize and protect poverty-related programs during periods of crisis and provide a clear course of action that ensures access of the poor to basic social services during periods of austerity (see Lustig, forthcoming). As will be discussed below, countercyclical fiscal policies can also ensure the availability of funds for financing safety nets during crises.
Another important factor to consider is that safety nets should already be operating before economies get hit by shocks so that they can be effective in times of distress (for a more detailed account, see World Bank, 2000). However, if a shock occurs before appropriate safety nets have been developed, then “second-best” social protection policies may be necessary. For instance, food subsidies have been found to be inefficient and often benefiting the non-poor, and most reform programs call for their reduction or even elimination. However, after a severe shock such as the 1997–98 East Asian financial crisis, when countries like Indonesia lacked comprehensive safety nets, existing food subsidies were probably the only means of preventing widespread malnutrition and starvation. In the context of a country’s reform process, however, these subsidies should be replaced with better targeted and less distorting transfers to the poor.
Removing Market Distortions and Distortive Policies
In addition to pursuing favorable economic policies and putting in place appropriate social safety nets, there are specific structural reforms that governments can undertake to insulate the poor from the adverse consequences of shocks. Most of these have to do with addressing the mechanisms through which macroeconomic shocks are transmitted to the poor. (see Box 5).
To the extent that asset market distortions prevent the poor from saving and insulating themselves against shocks, policies to remove these distortions can be valuable.33 For instance, foreign exchange controls can force the poor to hold their assets in domestic currency, whose value typically declines with adverse shocks. Relaxing these controls in a well-managed fashion could give the poor access to safer assets, such as foreign currency, that could protect them from devaluations, a typical outcome following negative shocks.34 Similarly, severe financial repression, such as controlled interest rates, can impede the poor’s ability to save.35 If properly managed, financial liberalization policies can therefore have the additional benefit of increasing self-insurance for the poor.
Policies that increase borrower information and relax barriers to access to credit markets can help the poor reduce consumption volatility, since credit availability makes them less dependent on current income. Also, to the extent that collateralized credit allocation amplifies the effects of negative shocks by reducing small- and medium-sized firms’ access to credit when asset prices fall (Kiyotaki and Moore, 1977, and Izquierdo, 1999), policies promoting better financial- sector credit allocation mechanisms based on project profitability and borrower information could reduce the incidence of this particular transmission channel and its indirect effects on the poor (i.e., lower employment opportunities).36
How Shocks Harm the Poor: Transmission Channels
Credit markets, as well as safe asset markets for appropriate saving, are major instruments for coping with income volatility. Distortions in these markets curtail the ability of the poor to follow consumption smoothing patterns. Government behavior in response to shocks is also a major determinant of the effects of these shocks on the poor. Financial sector behavior can also amplify the effects of shocks.
Distortions in asset markets. To self-insure against shocks, agents need to be able to save in assets whose value does not fall when they are needed to compensate for a fall in income. Such saving instruments are typically composed of foreign assets, domestic financial assets, and domestic real assets. To the extent that governments impose controls on these asset markets, it impedes the ability of the poor to use these savings instruments, and channels their savings into less effective instruments.1
Access to and structure of credit markets. Access to credit markets is extremely limited for the poor to buffer the effects of shocks, in part as a consequence of inadequate borrower information available to credit institutions. The structure of credit markets can also affect the poor indirectly: Firms may find that access to credit is typically collateralized. Therefore, shocks that drastically reduce the value of collateral will also reduce firms’ access to credit, amplifying the effect of shocks when firms become credit constrained. Severe downturns may dramatically cut employment of the poor and, hence, their welfare, especially since the poor are usually employed by small firms that depend on collateralized credit.
Procyclical fiscal policy. During booms, some governments have decreased export commodity taxes, reduced revenue collection effort, or heavily increased expenditures, amplifying the effects of positive shocks. These policies can make adjustment more severe during busts, since the resulting expenditure cuts following a negative shock have sometimes fallen on social programs and transfers to the poor—just when they are needed the most. Examples of these policies can be traced back to the experience of Côte d’Ivoire in 1976–79, and Colombia in 1975–1980. It has also been argued that synchronizing tax policies with shocks tends to obscure the information content of prices on which agents make their saving decisions, leading in many cases to lower saving rates than needed to buffer future adverse shocks (Collier, Gunning, and associates 1999).
Financial sector vulnerability and transmission to other sectors. Shocks can also be amplified through the banking system. For example, a negative terms of trade shock can adversely affect bank liquidity by reducing demand for domestic deposits, forcing banks to curtail credit roll-over, spreading the shock throughout the economy (IADB, 1995, and Hausmann, 1999). Similarly, if a sudden stop in capital flows renders many nontradable goods producers bankrupt because of big swings in relative prices, this may in turn create financial turmoil as loans become nonperforming, spreading the effect of the shock across the financial system (Calvo, 1998). Bankruptcies in the nontradable sector may translate into unemployment of the urban poor.
Finally, and most important, governments can do a lot to reduce the pro-cyclical nature of their fiscal policies by saving rather than spending windfalls following positive shocks and ideally using those savings as a buffer for expenditures against negative shocks. A cautious approach would be for the government to “treat every favorable shock as temporary and every adverse one as permanent,” although judgment would also depend on, among other things, the availability of financing (Little, and others, 1993). However, even this rule of thumb may not be enough. Governments need to find ways of “tying their hands” to resist the pressure to spend windfall revenues (Devarajan, 1999). For example, when the source of revenue is publicly owned, such as oil or other natural resource, it may be appropriate to save the windfall revenues abroad, with strict rules on how much of it can be repatriated. Countries such as Colombia, Chile, and Botswana have tried variants of this strategy, with benefits not just for overall macroeconomic management, but also for protecting the poor during adverse shocks, since saved funds during good times can be applied to financing of safety nets during crisis.
Tables
The following three tables show macroeconomic data, such as GDP growth, for a range of developing countries. The tables reveal that many developing countries are in a state of macroeconomic stability.
Real GDP Growth
(Annual percentage change)
Real GDP Growth
(Annual percentage change)
1994 | 1995 | 1996 | 1997 | 1998 | 1999 | 1994–99 Average | |
---|---|---|---|---|---|---|---|
High-growth countries | |||||||
Mozambique | 7.5 | 4.3 | 7.1 | 11.3 | 12.0 | 9.0 | 8.5 |
Sudan | 4.0 | 25.2 | 4.0 | 6.7 | 5.0 | 4.0 | 8.2 |
Vietnam | 8.8 | 9.5 | 9.3 | 8.1 | 5.8 | 4.2 | 7.6 |
Uganda | 6.4 | 11.5 | 9.1 | 4.7 | 5.6 | 7.8 | 7.5 |
Bhutan | 8.1 | 6.8 | 5.5 | 7.8 | 7.1 | 7.0 | 7.1 |
India | 7.9 | 8.0 | 7.3 | 5.0 | 6.1 | 6.2 | 6.8 |
Togo | 16.8 | 6.8 | 9.7 | 4.3 | –1.0 | 3.0 | 6.6 |
Myanmar | 7.5 | 6.9 | 6.4 | 5.7 | 5.0 | … | 6.3 |
Lao PDR | 8.2 | 7.0 | 6.8 | 7.0 | 4.0 | 4.0 | 6.2 |
Angola | 1.4 | 11.3 | 11.7 | 6.6 | 5.0 | –0.1 | 6.0 |
Eritrea | 9.8 | 2.9 | 6.8 | 7.9 | 3.9 | 3.0 | 5.7 |
Armenia | 5.4 | 6.9 | 5.9 | 3.3 | 7.2 | 5.5 | 5.7 |
Ethiopia | 3.5 | 6.1 | 10.9 | 5.9 | –1.0 | 7.0 | 5.4 |
Côte d’Ivoire | 2.0 | 7.0 | 6.9 | 5.9 | 4.5 | 4.3 | 5.1 |
Benin | 4.4 | 4.6 | 5.5 | 5.7 | 4.5 | 5.0 | 5.0 |
Bangladesh | 3.8 | 5.5 | 5.0 | 5.3 | 5.1 | 4.3 | 4.8 |
Senegal | 2.9 | 4.7 | 5.2 | 5.0 | 5.7 | 5.1 | 4.8 |
Rwanda | –50.2 | 34.4 | 15.8 | 12.8 | 9.5 | 5.9 | 4.7 |
Nicaragua | 3.3 | 4.3 | 4.7 | 5.1 | 4.0 | 6.3 | 4.6 |
Nepal | 8.2 | 3.5 | 5.3 | 5.0 | 2.3 | 3.4 | 4.6 |
Burkina Faso | 1.2 | 4.0 | 6.0 | 4.7 | 6.2 | 5.2 | 4.6 |
Malawi | –10.2 | 15.4 | 9.0 | 4.9 | 3.1 | 4.5 | 4.5 |
Chad | 10.2 | 1.0 | 3.7 | 4.1 | 8.1 | –1.0 | 4.4 |
Guinea | 4.0 | 4.4 | 4.6 | 4.8 | 4.4 | 3.7 | 4.3 |
Mali | 0.9 | 6.2 | 3.2 | 6.8 | 3.3 | 5.3 | 4.3 |
Mauritania | 4.6 | 4.6 | 5.5 | 3.2 | 3.2 | 4.3 | 4.2 |
Ghana | 3.3 | 4.0 | 4.6 | 4.2 | 4.7 | 4.4 | 4.2 |
Cambodia | 4.0 | 7.6 | 7.0 | 1.0 | 1.0 | 4.5 | 4.2 |
Niger | 4.0 | 2.6 | 3.4 | 3.3 | 8.3 | 2.3 | 4.0 |
Lesotho | 3.4 | 4.5 | 10.0 | 8.0 | –5.0 | 2.5 | 3.9 |
Zimbabwe | 6.8 | –0.5 | 8.7 | 3.7 | 2.5 | 1.2 | 3.7 |
Pakistan | 3.9 | 5.1 | 5.0 | 1.2 | 3.3 | 3.9 | 3.7 |
Yemen, Rep. of | –3.6 | 7.9 | 2.9 | 8.1 | 4.8 | 2.2 | 3.7 |
Central African Republic | 4.9 | 7.2 | –4.0 | 5.2 | 4.7 | 3.4 | 3.6 |
Mongolia | 2.3 | 6.3 | 2.4 | 4.0 | 3.5 | 2.7 | 3.5 |
Cameroon | –2.5 | 3.3 | 5.0 | 5.1 | 5.0 | 4.4 | 3.4 |
Tanzania | 1.4 | 2.6 | 4.3 | 4.0 | 3.5 | 4.3 | 3.4 |
Georgia | –11.4 | 2.4 | 10.5 | 11.0 | 2.9 | 2.0 | 2.9 |
Gambia, The | 0.2 | 0.9 | 2.2 | 4.9 | 4.7 | 4.2 | 2.9 |
Kenya | 2.6 | 4.4 | 4.1 | 2.1 | 1.8 | 1.6 | 2.8 |
Madagascar | 0.0 | 1.7 | 2.1 | 3.7 | 3.9 | 4.7 | 2.7 |
Indonesia | 7.5 | 8.2 | 7.8 | 4.7 | –13.2 | 0.2 | 2.5 |
Nigeria | 0.1 | 2.5 | 4.3 | 2.7 | 1.8 | 1.0 | 2.1 |
Solomon Islands | 5.2 | 7.0 | 3.5 | –0.5 | –7.0 | 4.0 | 2.0 |
Sāo Tomé and Príncipe | 2.2 | 2.0 | 1.5 | 1.0 | 2.5 | 2.5 | 2.0 |
Low-growth countries | |||||||
Congo, Rep. of | –5.5 | 4.0 | 6.3 | –2.4 | 3.6 | –0.7 | 0.9 |
Haiti | –8.3 | 4.4 | 2.7 | 1.4 | 3.1 | … | 0.7 |
Zambia | –3.4 | –2.3 | 6.5 | 3.4 | –2.0 | 1.3 | 0.6 |
Uzbekistan | –5.2 | –0.9 | 1.7 | 2.5 | 4.4 | … | 0.5 |
Guinea-Bissau | 3.2 | 4.4 | 4.6 | 5.4 | –28.1 | 8.7 | –0.3 |
Kyrgyz Republic | –20.1 | –5.4 | 7.1 | 9.9 | 1.8 | … | –1.3 |
Congo, Dem. Rep. of | –3.9 | 0.7 | –0.9 | –5.7 | 3.0 | … | –1.4 |
Comoros | –5.3 | –3.9 | –0.4 | 0.0 | 0.0 | 1.0 | –1.4 |
Azerbaijan | –24.3 | –11.8 | 1.3 | 5.8 | 10.0 | 10.0 | –1.5 |
Burundi | –3.9 | –7.3 | –8.4 | 0.4 | 4.8 | –1.0 | –2.6 |
Sierra Leone | 3.5 | –26.6 | 28.7 | –17.6 | –0.8 | –8.1 | –3.5 |
Tajikistan | –19.0 | –11.8 | –4.4 | 2.3 | 8.2 | … | –4.9 |
Turkmenistan | –17.3 | –7.2 | –6.7 | –11.3 | 5.0 | … | –7.5 |
Ukraine | –22.9 | –12.2 | –10.0 | –3.0 | –1.7 | –2.0 | –8.6 |
Moldova | –31.2 | –1.4 | –7.8 | 1.3 | –8.6 | –5.0 | –8.8 |
Afghanistan | … | … | … | … | … | … | … |
Korea, Dem. People’s Rep. of | … | … | … | … | … | … | … |
Liberia | … | … | … | … | … | … | … |
Somalia | … | … | … | … | … | … | … |
Real GDP Growth
(Annual percentage change)
1994 | 1995 | 1996 | 1997 | 1998 | 1999 | 1994–99 Average | |
---|---|---|---|---|---|---|---|
High-growth countries | |||||||
Mozambique | 7.5 | 4.3 | 7.1 | 11.3 | 12.0 | 9.0 | 8.5 |
Sudan | 4.0 | 25.2 | 4.0 | 6.7 | 5.0 | 4.0 | 8.2 |
Vietnam | 8.8 | 9.5 | 9.3 | 8.1 | 5.8 | 4.2 | 7.6 |
Uganda | 6.4 | 11.5 | 9.1 | 4.7 | 5.6 | 7.8 | 7.5 |
Bhutan | 8.1 | 6.8 | 5.5 | 7.8 | 7.1 | 7.0 | 7.1 |
India | 7.9 | 8.0 | 7.3 | 5.0 | 6.1 | 6.2 | 6.8 |
Togo | 16.8 | 6.8 | 9.7 | 4.3 | –1.0 | 3.0 | 6.6 |
Myanmar | 7.5 | 6.9 | 6.4 | 5.7 | 5.0 | … | 6.3 |
Lao PDR | 8.2 | 7.0 | 6.8 | 7.0 | 4.0 | 4.0 | 6.2 |
Angola | 1.4 | 11.3 | 11.7 | 6.6 | 5.0 | –0.1 | 6.0 |
Eritrea | 9.8 | 2.9 | 6.8 | 7.9 | 3.9 | 3.0 | 5.7 |
Armenia | 5.4 | 6.9 | 5.9 | 3.3 | 7.2 | 5.5 | 5.7 |
Ethiopia | 3.5 | 6.1 | 10.9 | 5.9 | –1.0 | 7.0 | 5.4 |
Côte d’Ivoire | 2.0 | 7.0 | 6.9 | 5.9 | 4.5 | 4.3 | 5.1 |
Benin | 4.4 | 4.6 | 5.5 | 5.7 | 4.5 | 5.0 | 5.0 |
Bangladesh | 3.8 | 5.5 | 5.0 | 5.3 | 5.1 | 4.3 | 4.8 |
Senegal | 2.9 | 4.7 | 5.2 | 5.0 | 5.7 | 5.1 | 4.8 |
Rwanda | –50.2 | 34.4 | 15.8 | 12.8 | 9.5 | 5.9 | 4.7 |
Nicaragua | 3.3 | 4.3 | 4.7 | 5.1 | 4.0 | 6.3 | 4.6 |
Nepal | 8.2 | 3.5 | 5.3 | 5.0 | 2.3 | 3.4 | 4.6 |
Burkina Faso | 1.2 | 4.0 | 6.0 | 4.7 | 6.2 | 5.2 | 4.6 |
Malawi | –10.2 | 15.4 | 9.0 | 4.9 | 3.1 | 4.5 | 4.5 |
Chad | 10.2 | 1.0 | 3.7 | 4.1 | 8.1 | –1.0 | 4.4 |
Guinea | 4.0 | 4.4 | 4.6 | 4.8 | 4.4 | 3.7 | 4.3 |
Mali | 0.9 | 6.2 | 3.2 | 6.8 | 3.3 | 5.3 | 4.3 |
Mauritania | 4.6 | 4.6 | 5.5 | 3.2 | 3.2 | 4.3 | 4.2 |
Ghana | 3.3 | 4.0 | 4.6 | 4.2 | 4.7 | 4.4 | 4.2 |
Cambodia | 4.0 | 7.6 | 7.0 | 1.0 | 1.0 | 4.5 | 4.2 |
Niger | 4.0 | 2.6 | 3.4 | 3.3 | 8.3 | 2.3 | 4.0 |
Lesotho | 3.4 | 4.5 | 10.0 | 8.0 | –5.0 | 2.5 | 3.9 |
Zimbabwe | 6.8 | –0.5 | 8.7 | 3.7 | 2.5 | 1.2 | 3.7 |
Pakistan | 3.9 | 5.1 | 5.0 | 1.2 | 3.3 | 3.9 | 3.7 |
Yemen, Rep. of | –3.6 | 7.9 | 2.9 | 8.1 | 4.8 | 2.2 | 3.7 |
Central African Republic | 4.9 | 7.2 | –4.0 | 5.2 | 4.7 | 3.4 | 3.6 |
Mongolia | 2.3 | 6.3 | 2.4 | 4.0 | 3.5 | 2.7 | 3.5 |
Cameroon | –2.5 | 3.3 | 5.0 | 5.1 | 5.0 | 4.4 | 3.4 |
Tanzania | 1.4 | 2.6 | 4.3 | 4.0 | 3.5 | 4.3 | 3.4 |
Georgia | –11.4 | 2.4 | 10.5 | 11.0 | 2.9 | 2.0 | 2.9 |
Gambia, The | 0.2 | 0.9 | 2.2 | 4.9 | 4.7 | 4.2 | 2.9 |
Kenya | 2.6 | 4.4 | 4.1 | 2.1 | 1.8 | 1.6 | 2.8 |
Madagascar | 0.0 | 1.7 | 2.1 | 3.7 | 3.9 | 4.7 | 2.7 |
Indonesia | 7.5 | 8.2 | 7.8 | 4.7 | –13.2 | 0.2 | 2.5 |
Nigeria | 0.1 | 2.5 | 4.3 | 2.7 | 1.8 | 1.0 | 2.1 |
Solomon Islands | 5.2 | 7.0 | 3.5 | –0.5 | –7.0 | 4.0 | 2.0 |
Sāo Tomé and Príncipe | 2.2 | 2.0 | 1.5 | 1.0 | 2.5 | 2.5 | 2.0 |
Low-growth countries | |||||||
Congo, Rep. of | –5.5 | 4.0 | 6.3 | –2.4 | 3.6 | –0.7 | 0.9 |
Haiti | –8.3 | 4.4 | 2.7 | 1.4 | 3.1 | … | 0.7 |
Zambia | –3.4 | –2.3 | 6.5 | 3.4 | –2.0 | 1.3 | 0.6 |
Uzbekistan | –5.2 | –0.9 | 1.7 | 2.5 | 4.4 | … | 0.5 |
Guinea-Bissau | 3.2 | 4.4 | 4.6 | 5.4 | –28.1 | 8.7 | –0.3 |
Kyrgyz Republic | –20.1 | –5.4 | 7.1 | 9.9 | 1.8 | … | –1.3 |
Congo, Dem. Rep. of | –3.9 | 0.7 | –0.9 | –5.7 | 3.0 | … | –1.4 |
Comoros | –5.3 | –3.9 | –0.4 | 0.0 | 0.0 | 1.0 | –1.4 |
Azerbaijan | –24.3 | –11.8 | 1.3 | 5.8 | 10.0 | 10.0 | –1.5 |
Burundi | –3.9 | –7.3 | –8.4 | 0.4 | 4.8 | –1.0 | –2.6 |
Sierra Leone | 3.5 | –26.6 | 28.7 | –17.6 | –0.8 | –8.1 | –3.5 |
Tajikistan | –19.0 | –11.8 | –4.4 | 2.3 | 8.2 | … | –4.9 |
Turkmenistan | –17.3 | –7.2 | –6.7 | –11.3 | 5.0 | … | –7.5 |
Ukraine | –22.9 | –12.2 | –10.0 | –3.0 | –1.7 | –2.0 | –8.6 |
Moldova | –31.2 | –1.4 | –7.8 | 1.3 | –8.6 | –5.0 | –8.8 |
Afghanistan | … | … | … | … | … | … | … |
Korea, Dem. People’s Rep. of | … | … | … | … | … | … | … |
Liberia | … | … | … | … | … | … | … |
Somalia | … | … | … | … | … | … | … |
GDP Deflator
(Annual percentage change)
GDP Deflator
(Annual percentage change)
1994 | 1995 | 1996 | 1997 | 1998 | 1999 | 1994–99 Average | |
---|---|---|---|---|---|---|---|
Low-inflation countries | |||||||
Gambia, The | 3.8 | 4.0 | 2.9 | 5.0 | 1.3 | 5.2 | 3.7 |
Guinea | 2.9 | 5.5 | 2.8 | 2.4 | 5.0 | 4.0 | 3.8 |
Bangladesh | 3.4 | 6.7 | 3.8 | 1.0 | 5.3 | 8.9 | 4.9 |
Comoros | 9.4 | 8.0 | 2.3 | 3.5 | 3.0 | 3.0 | 4.9 |
Ethiopia | 2.6 | 12.7 | 1.0 | 3.2 | 9.7 | 1.9 | 5.2 |
Mauritania | 6.4 | 4.4 | 4.6 | 5.5 | 9.9 | 1.9 | 5.5 |
Cameroon | 11.0 | 17.0 | 5.4 | 2.7 | 1.1 | –1.2 | 6.0 |
Uganda | 6.8 | 9.4 | 4.6 | 3.9 | 10.7 | 3.0 | 6.4 |
Central African Republic | 22.8 | 10.3 | 1.8 | 0.8 | 1.7 | 1.3 | 6.5 |
Senegal | 27.8 | 5.9 | 0.9 | 2.3 | 2.2 | 1.6 | 6.8 |
Nepal | 7.4 | 6.3 | 7.8 | 7.3 | 3.3 | 9.2 | 6.9 |
India | 9.7 | 8.6 | 7.9 | 5.6 | 8.9 | 5.5 | 7.7 |
Lesotho | 7.5 | 8.9 | 8.6 | 8.0 | 8.4 | 7.2 | 8.1 |
Burkina Faso | 27.8 | 9.8 | 4.2 | 2.2 | 3.1 | 1.6 | 8.1 |
Niger | 32.7 | 5.4 | 4.7 | 3.1 | 3.0 | 3.0 | 8.7 |
Eritrea | 22.2 | 11.3 | 2.9 | 2.7 | 2.7 | 12.6 | 9.1 |
Cambodia | 8.9 | 9.1 | 7.1 | 9.2 | 17.0 | 5.7 | 9.5 |
Bhutan | 9.3 | 9.8 | 11.4 | 14.7 | 5.9 | 7.8 | 9.8 |
Mali | 27.9 | 18.4 | 5.4 | 1.0 | 4.0 | 2.2 | 9.8 |
Solomon Islands | 11.5 | 7.1 | 12.1 | 8.1 | 12.0 | … | 10.2 |
Pakistan | 12.9 | 13.8 | 8.4 | 13.3 | 7.8 | 5.5 | 10.3 |
Côte d’Ivoire | 41.7 | 9.6 | 2.7 | 3.2 | 3.1 | 2.7 | 10.5 |
Nicaragua | 7.8 | 10.9 | 11.6 | 9.2 | 12.9 | 13.9 | 11.1 |
Togo | 33.8 | 12.2 | 5.1 | 11.4 | 2.7 | 1.1 | 11.1 |
Vietnam | 14.5 | 19.5 | 6.1 | 12.1 | 8.9 | 5.8 | 11.2 |
Benin | 33.5 | 15.4 | 6.7 | 4.7 | 4.2 | 3.5 | 11.3 |
Chad | 43.4 | 8.6 | 11.6 | 2.7 | 4.1 | –2.1 | 11.4 |
Congo, Rep. of | 36.8 | 22.6 | –3.0 | 7.5 | –19.1 | 24.1 | 11.5 |
Burundi | 6.7 | 15.3 | 19.0 | 23.3 | 12.1 | 0.6 | 12.8 |
Kenya | 35.2 | 11.2 | 8.7 | 15.5 | 10.6 | 5.0 | 14.4 |
Rwanda | 18.0 | 51.3 | 10.5 | 15.6 | 2.6 | –2.4 | 15.9 |
High-inflation countries | |||||||
Tanzania | 28.2 | 28.9 | 22.3 | 18.5 | 19.3 | 11.6 | 21.5 |
Indonesia | 7.8 | 9.9 | 8.7 | 12.6 | 73.1 | 17.2 | 21.6 |
Madagascar | 41.6 | 45.2 | 17.8 | 7.3 | 8.4 | 9.8 | 21.7 |
Haiti | 35.6 | 31.0 | 21.2 | 16.3 | 12.7 | … | 23.4 |
Nigeria | 27.8 | 56.0 | 36.9 | 1.4 | 21.6 | 11.9 | 25.9 |
Sierra Leone | 20.1 | 63.7 | 3.0 | 16.8 | 27.0 | 25.0 | 25.9 |
Myanmar | 22.1 | 19.4 | 23.0 | 32.9 | 34.0 | … | 26.3 |
Yemen, Rep. of | 33.2 | 54.8 | 39.6 | 12.9 | –9.3 | 26.8 | 26.3 |
Ghana | 30.1 | 43.2 | 39.8 | 19.5 | 17.0 | 11.5 | 26.9 |
Guinea-Bissau | 23.2 | 44.7 | 48.6 | 35.5 | 7.6 | 3.1 | 27.1 |
Mozambique | 59.4 | 52.0 | 40.9 | 11.1 | 3.8 | 5.2 | 28.7 |
Mongolia | 66.6 | 42.5 | 33.5 | 24.4 | 11.5 | 2.8 | 30.2 |
Zambia | 56.6 | 36.9 | 24.3 | 25.9 | 23.2 | 25.6 | 32.1 |
Malawi | 26.2 | 90.3 | 40.4 | 13.5 | 23.2 | 46.4 | 40.0 |
Lao PDR | 7.7 | 19.7 | 13.9 | 17.7 | 84.0 | 125.4 | 44.7 |
Kyrgyz Republic | 180.9 | 42.0 | 35.3 | 19.3 | 8.5 | … | 57.2 |
Sāo Tomé and Príncipe | 73.5 | 74.5 | 50.8 | 100.2 | 37.1 | 16.0 | 58.7 |
Sudan | 80.8 | 41.1 | 107.4 | 64.9 | 28.9 | … | 64.6 |
Moldova | 278.1 | 38.7 | 30.5 | 12.9 | 8.0 | 37.3 | 67.6 |
Tajikistan | 236.2 | 285.0 | 397.9 | 100.2 | 49.9 | … | 213.8 |
Ukraine | 953.5 | 415.5 | 66.2 | 18.1 | 13.2 | … | 293.3 |
Azerbaijan | 1,428.6 | 545.7 | 26.4 | 9.2 | –8.3 | 4.8 | 334.4 |
Uzbekistan | 1,238.6 | 370.9 | 81.6 | 70.5 | 33.2 | … | 359.0 |
Turkmenistan | 1,022.1 | 705.7 | 1,174.3 | 61.6 | 13.5 | … | 595.4 |
Armenia | 4,107.3 | 161.2 | 19.6 | 17.7 | 11.2 | 1.1 | 719.7 |
Georgia | 9,349.2 | 162.7 | 40.2 | 7.0 | 3.4 | 15.0 | 1,596.3 |
Angola | 2,170.7 | 1,886.1 | 5,421.8 | 93.6 | 60.9 | 412.6 | 1,674.3 |
Congo, Dem. Rep. of | 26,762.4 | 466.4 | 613.1 | 187.3 | 15.0 | … | 5,608.8 |
Afghanistan | … | … | … | … | … | … | … |
Korea, Dem. People’s Rep. of | … | … | … | … | … | … | … |
Liberia | … | … | … | … | … | … | … |
Somalia | … | … | … | … | … | … | … |
GDP Deflator
(Annual percentage change)
1994 | 1995 | 1996 | 1997 | 1998 | 1999 | 1994–99 Average | |
---|---|---|---|---|---|---|---|
Low-inflation countries | |||||||
Gambia, The | 3.8 | 4.0 | 2.9 | 5.0 | 1.3 | 5.2 | 3.7 |
Guinea | 2.9 | 5.5 | 2.8 | 2.4 | 5.0 | 4.0 | 3.8 |
Bangladesh | 3.4 | 6.7 | 3.8 | 1.0 | 5.3 | 8.9 | 4.9 |
Comoros | 9.4 | 8.0 | 2.3 | 3.5 | 3.0 | 3.0 | 4.9 |
Ethiopia | 2.6 | 12.7 | 1.0 | 3.2 | 9.7 | 1.9 | 5.2 |
Mauritania | 6.4 | 4.4 | 4.6 | 5.5 | 9.9 | 1.9 | 5.5 |
Cameroon | 11.0 | 17.0 | 5.4 | 2.7 | 1.1 | –1.2 | 6.0 |
Uganda | 6.8 | 9.4 | 4.6 | 3.9 | 10.7 | 3.0 | 6.4 |
Central African Republic | 22.8 | 10.3 | 1.8 | 0.8 | 1.7 | 1.3 | 6.5 |
Senegal | 27.8 | 5.9 | 0.9 | 2.3 | 2.2 | 1.6 | 6.8 |
Nepal | 7.4 | 6.3 | 7.8 | 7.3 | 3.3 | 9.2 | 6.9 |
India | 9.7 | 8.6 | 7.9 | 5.6 | 8.9 | 5.5 | 7.7 |
Lesotho | 7.5 | 8.9 | 8.6 | 8.0 | 8.4 | 7.2 | 8.1 |
Burkina Faso | 27.8 | 9.8 | 4.2 | 2.2 | 3.1 | 1.6 | 8.1 |
Niger | 32.7 | 5.4 | 4.7 | 3.1 | 3.0 | 3.0 | 8.7 |
Eritrea | 22.2 | 11.3 | 2.9 | 2.7 | 2.7 | 12.6 | 9.1 |
Cambodia | 8.9 | 9.1 | 7.1 | 9.2 | 17.0 | 5.7 | 9.5 |
Bhutan | 9.3 | 9.8 | 11.4 | 14.7 | 5.9 | 7.8 | 9.8 |
Mali | 27.9 | 18.4 | 5.4 | 1.0 | 4.0 | 2.2 | 9.8 |
Solomon Islands | 11.5 | 7.1 | 12.1 | 8.1 | 12.0 | … | 10.2 |
Pakistan | 12.9 | 13.8 | 8.4 | 13.3 | 7.8 | 5.5 | 10.3 |
Côte d’Ivoire | 41.7 | 9.6 | 2.7 | 3.2 | 3.1 | 2.7 | 10.5 |
Nicaragua | 7.8 | 10.9 | 11.6 | 9.2 | 12.9 | 13.9 | 11.1 |
Togo | 33.8 | 12.2 | 5.1 | 11.4 | 2.7 | 1.1 | 11.1 |
Vietnam | 14.5 | 19.5 | 6.1 | 12.1 | 8.9 | 5.8 | 11.2 |
Benin | 33.5 | 15.4 | 6.7 | 4.7 | 4.2 | 3.5 | 11.3 |
Chad | 43.4 | 8.6 | 11.6 | 2.7 | 4.1 | –2.1 | 11.4 |
Congo, Rep. of | 36.8 | 22.6 | –3.0 | 7.5 | –19.1 | 24.1 | 11.5 |
Burundi | 6.7 | 15.3 | 19.0 | 23.3 | 12.1 | 0.6 | 12.8 |
Kenya | 35.2 | 11.2 | 8.7 | 15.5 | 10.6 | 5.0 | 14.4 |
Rwanda | 18.0 | 51.3 | 10.5 | 15.6 | 2.6 | –2.4 | 15.9 |
High-inflation countries | |||||||
Tanzania | 28.2 | 28.9 | 22.3 | 18.5 | 19.3 | 11.6 | 21.5 |
Indonesia | 7.8 | 9.9 | 8.7 | 12.6 | 73.1 | 17.2 | 21.6 |
Madagascar | 41.6 | 45.2 | 17.8 | 7.3 | 8.4 | 9.8 | 21.7 |
Haiti | 35.6 | 31.0 | 21.2 | 16.3 | 12.7 | … | 23.4 |
Nigeria | 27.8 | 56.0 | 36.9 | 1.4 | 21.6 | 11.9 | 25.9 |
Sierra Leone | 20.1 | 63.7 | 3.0 | 16.8 | 27.0 | 25.0 | 25.9 |
Myanmar | 22.1 | 19.4 | 23.0 | 32.9 | 34.0 | … | 26.3 |
Yemen, Rep. of | 33.2 | 54.8 | 39.6 | 12.9 | –9.3 | 26.8 | 26.3 |
Ghana | 30.1 | 43.2 | 39.8 | 19.5 | 17.0 | 11.5 | 26.9 |
Guinea-Bissau | 23.2 | 44.7 | 48.6 | 35.5 | 7.6 | 3.1 | 27.1 |
Mozambique | 59.4 | 52.0 | 40.9 | 11.1 | 3.8 | 5.2 | 28.7 |
Mongolia | 66.6 | 42.5 | 33.5 | 24.4 | 11.5 | 2.8 | 30.2 |
Zambia | 56.6 | 36.9 | 24.3 | 25.9 | 23.2 | 25.6 | 32.1 |
Malawi | 26.2 | 90.3 | 40.4 | 13.5 | 23.2 | 46.4 | 40.0 |
Lao PDR | 7.7 | 19.7 | 13.9 | 17.7 | 84.0 | 125.4 | 44.7 |
Kyrgyz Republic | 180.9 | 42.0 | 35.3 | 19.3 | 8.5 | … | 57.2 |
Sāo Tomé and Príncipe | 73.5 | 74.5 | 50.8 | 100.2 | 37.1 | 16.0 | 58.7 |
Sudan | 80.8 | 41.1 | 107.4 | 64.9 | 28.9 | … | 64.6 |
Moldova | 278.1 | 38.7 | 30.5 | 12.9 | 8.0 | 37.3 | 67.6 |
Tajikistan | 236.2 | 285.0 | 397.9 | 100.2 | 49.9 | … | 213.8 |
Ukraine | 953.5 | 415.5 | 66.2 | 18.1 | 13.2 | … | 293.3 |
Azerbaijan | 1,428.6 | 545.7 | 26.4 | 9.2 | –8.3 | 4.8 | 334.4 |
Uzbekistan | 1,238.6 | 370.9 | 81.6 | 70.5 | 33.2 | … | 359.0 |
Turkmenistan | 1,022.1 | 705.7 | 1,174.3 | 61.6 | 13.5 | … | 595.4 |
Armenia | 4,107.3 | 161.2 | 19.6 | 17.7 | 11.2 | 1.1 | 719.7 |
Georgia | 9,349.2 | 162.7 | 40.2 | 7.0 | 3.4 | 15.0 | 1,596.3 |
Angola | 2,170.7 | 1,886.1 | 5,421.8 | 93.6 | 60.9 | 412.6 | 1,674.3 |
Congo, Dem. Rep. of | 26,762.4 | 466.4 | 613.1 | 187.3 | 15.0 | … | 5,608.8 |
Afghanistan | … | … | … | … | … | … | … |
Korea, Dem. People’s Rep. of | … | … | … | … | … | … | … |
Liberia | … | … | … | … | … | … | … |
Somalia | … | … | … | … | … | … | … |
Primary Surplus1
(As a percentage of GDP)
Negative sign indicates a primary deficit.
Primary Surplus1
(As a percentage of GDP)
1994 | 1995 | 1996 | 1997 | 1998 | 1994–98 Average | |
---|---|---|---|---|---|---|
Surplus/low deficit countries | ||||||
Mauritania | 2.4 | 6.5 | 11.4 | 8.2 | 8.4 | 7.4 |
Kenya | 8.3 | 7.3 | 6.2 | 6.2 | 5.8 | 6.8 |
Lesotho | 8.1 | 6.3 | 6.5 | 2.1 | –4.5 | 3.7 |
Congo, Rep. | –1.1 | 5.9 | 7.0 | 4.4 | 2.2 | 3.7 |
Cameroon | –2.2 | 3.2 | 5.0 | 5.4 | 4.1 | 3.1 |
Zambia | 5.2 | 3.8 | 2.1 | 3.5 | 0.1 | 3.0 |
Côte d’Ivoire | 1.4 | 3.2 | 3.8 | 3.0 | 2.6 | 2.8 |
Sāo Tomé and Príncipe | … | … | –0.3 | 11.3 | –2.8 | 2.7 |
Nigeria | 0.5 | 8.1 | 7.5 | 3.3 | –6.9 | 2.5 |
Senegal | 1.6 | 2.7 | 2.1 | 2.2 | 1.7 | 2.1 |
Tanzania | 0.6 | –0.5 | 1.2 | 4.7 | 2.2 | 1.6 |
Zimbabwe | 0.0 | –0.7 | 0.7 | –0.4 | 8.0 | 1.5 |
Benin | 0.8 | –0.5 | 2.1 | 2.0 | 3.3 | 1.5 |
Bhutan | –0.5 | 0.1 | 2.0 | –2.1 | 3.0 | 0.5 |
Myanmar | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
Indonesia | 1.1 | 1.4 | 1.1 | –0.5 | –3.3 | 0.0 |
Vietnam | … | –0.6 | –0.2 | –0.8 | –1.6 | –0.8 |
Gambia, The | 2.6 | –2.9 | –5.3 | –1.4 | 2.9 | –0.8 |
Madagascar | –3.0 | –1.1 | –0.2 | 0.7 | –1.8 | –1.1 |
Uganda | –2.3 | –1.9 | –0.9 | –0.9 | 0.4 | –1.1 |
Niger | –4.5 | –1.5 | 1.4 | –1.1 | –0.4 | –1.2 |
Mali | –2.0 | –1.7 | 0.2 | –1.1 | –1.6 | –1.2 |
Guinea | –2.0 | –1.3 | –1.7 | –1.3 | –1.8 | –1.6 |
Burkina Faso | –1.8 | –2.2 | 0.3 | –2.3 | –2.1 | –1.6 |
Mozambique | –4.2 | –1.6 | –1.5 | –1.3 | –1.4 | –2.0 |
Ethiopia | –4.3 | –1.4 | –3.2 | 0.7 | –2.1 | –2.1 |
Malawi | –16.2 | 1.0 | 2.3 | –5.2 | 7.0 | –2.2 |
Central African Republic | –7.6 | –2.8 | –1.5 | –0.9 | 0.6 | –2.5 |
Ghana | –4.4 | –2.1 | –4.4 | –2.7 | 0.1 | –2.7 |
Rwanda | –7.0 | 0.0 | –4.1 | –1.3 | –1.9 | –2.9 |
Togo | –6.2 | –3.0 | –3.0 | 0.2 | –3.0 | –3.0 |
High deficit countries | ||||||
Chad | –3.5 | –3.4 | –4.0 | –2.9 | –4.1 | –3.6 |
Solomon Islands | –5.5 | –5.3 | –4.4 | –4.9 | 0.1 | –4.0 |
Burundi | –2.8 | –3.1 | –8.3 | –3.4 | –2.7 | –4.1 |
Bangladesh | –4.6 | –5.3 | –4.4 | –4.3 | –4.2 | –4.5 |
Haiti | –1.8 | –8.3 | –7.6 | –3.1 | –4.0 | –5.0 |
Sierra Leone | –4.5 | –7.8 | –4.4 | –5.0 | –5.1 | –5.4 |
Pakistan | –6.0 | –5.9 | –7.0 | –6.4 | –5.5 | –6.2 |
Lao PDR | … | –4.5 | –5.9 | –8.1 | –7.2 | –6.4 |
Nepal | –7.0 | –6.6 | –7.5 | –7.3 | –7.8 | –7.2 |
Angola | –8.1 | –16.5 | 1.1 | … | … | –7.8 |
India | –8.8 | –7.9 | –7.8 | –8.5 | –9.4 | –8.5 |
Nicaragua | –11.4 | –11.0 | –10.2 | –7.6 | –5.0 | –9.0 |
Mongolia | –22.8 | –4.1 | –8.2 | –8.6 | –11.3 | –11.0 |
Eritrea | … | … | … | … | –27.3 | –27.3 |
Afghanistan | … | … | … | … | … | … |
Cambodia | … | … | … | … | … | … |
Comoros | … | … | … | … | … | … |
Congo, Dem. Rep. of | … | … | … | … | … | … |
Guinea-Bissau | … | … | … | … | … | … |
Korea, Dem. People’s Rep. of | … | … | … | … | … | … |
Liberia | … | … | … | … | … | … |
Somalia | … | … | … | … | … | … |
Sudan | … | … | … | … | … | … |
Negative sign indicates a primary deficit.
Primary Surplus1
(As a percentage of GDP)
1994 | 1995 | 1996 | 1997 | 1998 | 1994–98 Average | |
---|---|---|---|---|---|---|
Surplus/low deficit countries | ||||||
Mauritania | 2.4 | 6.5 | 11.4 | 8.2 | 8.4 | 7.4 |
Kenya | 8.3 | 7.3 | 6.2 | 6.2 | 5.8 | 6.8 |
Lesotho | 8.1 | 6.3 | 6.5 | 2.1 | –4.5 | 3.7 |
Congo, Rep. | –1.1 | 5.9 | 7.0 | 4.4 | 2.2 | 3.7 |
Cameroon | –2.2 | 3.2 | 5.0 | 5.4 | 4.1 | 3.1 |
Zambia | 5.2 | 3.8 | 2.1 | 3.5 | 0.1 | 3.0 |
Côte d’Ivoire | 1.4 | 3.2 | 3.8 | 3.0 | 2.6 | 2.8 |
Sāo Tomé and Príncipe | … | … | –0.3 | 11.3 | –2.8 | 2.7 |
Nigeria | 0.5 | 8.1 | 7.5 | 3.3 | –6.9 | 2.5 |
Senegal | 1.6 | 2.7 | 2.1 | 2.2 | 1.7 | 2.1 |
Tanzania | 0.6 | –0.5 | 1.2 | 4.7 | 2.2 | 1.6 |
Zimbabwe | 0.0 | –0.7 | 0.7 | –0.4 | 8.0 | 1.5 |
Benin | 0.8 | –0.5 | 2.1 | 2.0 | 3.3 | 1.5 |
Bhutan | –0.5 | 0.1 | 2.0 | –2.1 | 3.0 | 0.5 |
Myanmar | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
Indonesia | 1.1 | 1.4 | 1.1 | –0.5 | –3.3 | 0.0 |
Vietnam | … | –0.6 | –0.2 | –0.8 | –1.6 | –0.8 |
Gambia, The | 2.6 | –2.9 | –5.3 | –1.4 | 2.9 | –0.8 |
Madagascar | –3.0 | –1.1 | –0.2 | 0.7 | –1.8 | –1.1 |
Uganda | –2.3 | –1.9 | –0.9 | –0.9 | 0.4 | –1.1 |
Niger | –4.5 | –1.5 | 1.4 | –1.1 | –0.4 | –1.2 |
Mali | –2.0 | –1.7 | 0.2 | –1.1 | –1.6 | –1.2 |
Guinea | –2.0 | –1.3 | –1.7 | –1.3 | –1.8 | –1.6 |
Burkina Faso | –1.8 | –2.2 | 0.3 | –2.3 | –2.1 | –1.6 |
Mozambique | –4.2 | –1.6 | –1.5 | –1.3 | –1.4 | –2.0 |
Ethiopia | –4.3 | –1.4 | –3.2 | 0.7 | –2.1 | –2.1 |
Malawi | –16.2 | 1.0 | 2.3 | –5.2 | 7.0 | –2.2 |
Central African Republic | –7.6 | –2.8 | –1.5 | –0.9 | 0.6 | –2.5 |
Ghana | –4.4 | –2.1 | –4.4 | –2.7 | 0.1 | –2.7 |
Rwanda | –7.0 | 0.0 | –4.1 | –1.3 | –1.9 | –2.9 |
Togo | –6.2 | –3.0 | –3.0 | 0.2 | –3.0 | –3.0 |
High deficit countries | ||||||
Chad | –3.5 | –3.4 | –4.0 | –2.9 | –4.1 | –3.6 |
Solomon Islands | –5.5 | –5.3 | –4.4 | –4.9 | 0.1 | –4.0 |
Burundi | –2.8 | –3.1 | –8.3 | –3.4 | –2.7 | –4.1 |
Bangladesh | –4.6 | –5.3 | –4.4 | –4.3 | –4.2 | –4.5 |
Haiti | –1.8 | –8.3 | –7.6 | –3.1 | –4.0 | –5.0 |
Sierra Leone | –4.5 | –7.8 | –4.4 | –5.0 | –5.1 | –5.4 |
Pakistan | –6.0 | –5.9 | –7.0 | –6.4 | –5.5 | –6.2 |
Lao PDR | … | –4.5 | –5.9 | –8.1 | –7.2 | –6.4 |
Nepal | –7.0 | –6.6 | –7.5 | –7.3 | –7.8 | –7.2 |
Angola | –8.1 | –16.5 | 1.1 | … | … | –7.8 |
India | –8.8 | –7.9 | –7.8 | –8.5 | –9.4 | –8.5 |
Nicaragua | –11.4 | –11.0 | –10.2 | –7.6 | –5.0 | –9.0 |
Mongolia | –22.8 | –4.1 | –8.2 | –8.6 | –11.3 | –11.0 |
Eritrea | … | … | … | … | –27.3 | –27.3 |
Afghanistan | … | … | … | … | … | … |
Cambodia | … | … | … | … | … | … |
Comoros | … | … | … | … | … | … |
Congo, Dem. Rep. of | … | … | … | … | … | … |
Guinea-Bissau | … | … | … | … | … | … |
Korea, Dem. People’s Rep. of | … | … | … | … | … | … |
Liberia | … | … | … | … | … | … |
Somalia | … | … | … | … | … | … |
Sudan | … | … | … | … | … | … |
Negative sign indicates a primary deficit.