Chapter

CHAPTER 9 Fiscal Policy in Commodity- Exporting Countries: Stability and Growth

Author(s):
Amadou Sy, Rabah Arezki, and Thorvaldur Gylfason
Published Date:
January 2012
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Author(s)
Rabah Arezki

INTRODUCTION

In the late 1950s, Richard Musgrave made the case for a “three-function framework” which has influenced the way economists approach fiscal policy and its objectives to this day. This framework suggests that government activity should be separated into three branches, namely macroeconomic stabilization, resource allocation, and income redistribution. The stabilization branch is to assure the achievement of high employment and price stability, the allocation branch is to see that resources are used efficiently, and the distribution branch is to achieve an equitable distribution of income. (Musgrave, 1959). The present chapter is concerned specifically with the performance of commodity-exporting countries in terms of macroeconomic stability and long-run economic growth, based on an examination of a new dataset on nonresource GDP from a panel of up to 134 countries during the period 1970–2007.1, 2

This chapter links to the literature on the role of fiscal policy in shaping the economic performance of developing countries. There is ample evidence that fiscal policy in developing countries has achieved mixed results, in both the short run and the long run. In the short run, Kaminsky, Reinhart, and Végh (2004), among others, provide evidence that fiscal policy tends to be procyclical in developing countries, especially when compared to industrialized countries. Three important characteristics of commodity-exporting countries complicate the conduct of fiscal policy and are likely to make government spending more procyclical than in non-commodity-exporting countries. First, government revenues derived from the exploitation of natural resources are more volatile than other sources of government revenue. Second, the size of the revenues derived from natural resources is disproportionately large in commodity-exporting countries, notwithstanding the distinction between resource dependence and resource abundance. Third, those revenues are prone to rent-seeking behavior, as they more directly transit to government coffers.

Cuddington (1989) provides some evidence supporting the claim that fiscal policy is more procyclical in commodity-exporting countries. In the long run, there is also mixed evidence that government spending has helped boost developing countries’ economic performance (Blejer and Khan, 1984; Khan, 1996). In commodity-exporting countries, Gelb and associates (1988) provide evidence that governments in those countries often embark on large investment projects following commodity price booms. They argue that those investment projects have been plagued by inefficiencies and also contributed to resource misallocation. Disproportionally large investment projects also get depreciated quickly or even become obsolete when governments become unable to cover the associated high maintenance costs due to lack of financing. Robinson and Torvik (2005) provide a political economy model in which “white elephants” may be preferred to socially efficient projects when the political benefits are large compared to the surplus generated by the efficient projects. This evidence could suggest that poor long-run economic performance in commodity-exporting countries may stem from inefficiencies in government investments rather than from underinvestment.

Further, this chapter relates to the literature on the so-called resource curse, focusing specifically on the consequences that resource endowment has on the economic performance of commodity-exporting countries. This literature has emphasized several channels through which resource windfalls may affect economic performance, including the so-called Dutch disease and a deterioration of institutions, to name a few (Frankel, 2011a). Overall, there is some evidence, albeit controversial, that commodity-exporting countries’ growth performance compares less favorably with the growth performance of non-commodity-exporting countries. Among others, Alexeev and Conrad (2009) provide evidence supporting a more skeptical view of the resource curse. Using traditional cross-sectional growth regressions, they find for instance that the empirical association between resource dependence and economic performance is not robust when using samples with different starting years. In a recent attempt to reconcile this conflicting evidence regarding the existence of a resource curse, Collier and Goderis (2007) use panel cointegration techniques, allowing them to disentangle the short- and long-run effects of resource windfalls on overall GDP growth. They find that commodity price shocks have a positive effect in the short run but a negative effect in the long run.

This chapter makes two main contributions to the existing literature. First, it focuses on the effect resource windfalls have on the nonresource sector. To examine this, we use a new dataset on nonresource GDP, allowing us to avoid the noise introduced by the resource-sector contribution to overall GDP.3 As argued by the World Bank, “There are no sustainable diamond mines, but there are sustainable diamond-mining countries” (World Bank, 2006). Hartwick (1977) provides a canonical rule for sustainability in resource-dependent economies: If genuine saving is set equal to zero at each point in time (that is, traditional net saving just equals resource depletion), then consumption can be maintained indefinitely, even in the face of finite resources and fixed technology. From a policy perspective, nonresource-sector GDP is thus the relevant measure to be used when assessing both the macroeconomic stability and the long-run economic performance of commodity-exporting countries. Indeed preserving the macroeconomic stability of the nonresource sector specifically will contribute to fostering investments in that sector and will therefore contribute to sustained economic growth after natural resources are depleted.

Second, unlike previous studies, the econometric investigation in this chapter explicitly takes into account the role of fiscal policy in the analysis of the resource curse. In commodity-exporting countries, the resource sector often lacks direct structural linkages with the rest of the economy but exercises a significant externality, mostly through the fact that a large chunk of government spending is financed from revenues originating in the resource sector (through state ownership, taxation, or export tariffs). Identifying the nature of that externality can help foster our understanding of both the short-run dynamics of the nonresource sector and the sector’s long-run economic viability after natural resources are depleted.

Our main findings are twofold. First, we find that overall government spending in commodity-exporting countries has been procyclical. We also find that resource windfalls initially crowd out nonresource GDP, which then increases as a result of the fiscal expansion. Second, we find that in the long run, resource windfalls have negative effects on the nonresource sector’s GDP growth but not over government spending. Both effects—of resource windfalls and government spending on macroeconomic stability and economic growth—are moderated by the quality of political institutions.

The remainder of this chapter is organized as follows. The next section describes the data. The section following that presents the estimation strategy and results, and the final section offers four concluding remarks.

DATA

Nonresource GDP

Nonresource GDP is constructed by subtracting the real values of natural resources depletion from total GDP in 2005 purchasing power parity (PPP)-adjusted U.S. dollars.4 Natural resources give rise to rents because they are not produced; in contrast, for produced goods and services competitive forces will expand supply until economic profits are driven to zero. An economic rent represents an excess return to a given factor of production. The value of resource depletion is therefore calculated as the total rents on resource extraction and harvest, where rents are estimated as the difference between the value of production at world prices and total costs of production, including depreciation of fixed capital and return on capital (see Hamilton and Ruta, 2008, for more details). The energy resources include oil, natural gas, and coal, while metals and minerals include bauxite, copper, gold, iron ore, lead, nickel, phosphate, silver, tin, and zinc.

Resource Windfalls

To capture revenue windfalls from international commodity price booms, the analysis constructs a country-specific index which consists of a geometric average of international prices of various commodities using (time-invariant) weights based on the average value of exports of each commodity as measured in the GDP of a given country. Annual international commodity price data are for the 1970—2007 period, reported in the United Nations Conference on Trade and Development (UNCTAD) Commodity Statistics; data on the value of commodity exports is from the National Bureau of Economic Research (NBER)-United Nations Trade Database. Because the time-series behavior of many international commodity prices is highly persistent, commodity price shocks are identified by the (log) change in the international commodity price.5

Democracy

Democracy is measured by the revised combined Polity score (Polity2) of the Polity IV database (Marshall and Jaggers, 2009). The Polity2 score ranges from -10 to + 10, with higher values indicating more democratic institutions. Following Persson and Tabellini (2003, 2006) and the Polity IV project, we code countries as democracies if their Polity2 score is strictly positive and as autocracies if it is strictly negative. We further classify countries as deep democracies if their Polity2 score is higher than 6, and as deep autocracies if their Polity2 score is lower than -6.

ESTIMATION STRATEGY AND MAIN RESULTS

Macroeconomic Stability

A preliminary comparison between the evolution of our resource windfalls index and government spending indicates that for most commodity-exporting countries, those two aggregates co-move, and the extent of the co-movement has been increasing during the past decade following the commodity price boom of the 2000s. Figure 9.1 illustrates such findings for the case of Venezuela. The co-movement between government spending and resource windfalls provides some evidence of the procyclicity of fiscal policy for most commodity-exporting countries. In contrast, for a limited number of commodity-exporting countries, such as Norway, government spending appears to move countercyclically with respect to resource windfalls, as illustrated in Figure 9.2. The latter evidence indicates some degree of heterogeneity in the fiscal policy of commodity-exporting countries. We now turn to a more systematic analysis of the short-run dynamics of government spending and nonresource GDP in the face of resource windfall shocks.

Figure 9.1.Venezuela: Evolution of government spending and resource windfalls, 1970–2007

Sources: Heston, Summers, and Aten (2009); UNCTAD Commodity Statistics; NBER-United Nations Trade Database; and author’s analysis

Figure 9.2.Norway: Evolution of government spending and resource windfalls, 1970–2007

Sources: Heston, Summers, and Aten (2009); UNCTAD Commodity Statistics; NBER-United Nations Trade Database; and author’s analysis.

To do so we use panel vector autoregression (VAR) techniques, making it possible to isolate the dynamics of a statistical relationship and the interdependencies between multiple economic variables, namely resource windfalls assumed to be exogenous, and two endogenous variables, namely nonresource GDP and government spending as share of nonresource GDP.6 Another advantage of panel VAR techniques is that they allow one to simultaneously estimate all relationships while taking into account specific country characteristics through the use of fixed effects.7 The results of the estimations are illustrated by the impulse responses presented in Figure 9.3. These suggest that the average effect of an increase in resource windfalls is followed by a statistically and economically significant increase in government spending. This provides supportive evidence of procyclical government spending policy in commodity-exporting countries. Figure 9.3 also shows that resource windfall shocks initially crowd out nonresource GDP, which in turn increases as a result of the fiscal expansion. The intuition behind this result is that an increase in resource windfalls raises the return on investing in the resource sector, which in turn leads to a reallocation of factors away from the nonresource sector in favor of the resource sector. As government spending increases in response to an increase in government revenues following a resource windfall, the nonresource sector expands. The latter results provide empirical evidence of a resource sector externality onto the nonresource sector, stemming from resource windfalls spurring government spending.

Figure 9.3.Norway: Estimations of impulse response, panel VAR

Source: Author’s analysis.

When expanding the empirical analysis to the real exchange rate and the nonresource current account, we find that resource windfalls lead to increased growth of the real effective exchange rate and to a deterioration in the nonresource current account (results not reported in tables). 8 Those results are consistent with Dutch disease. Indeed, government spending directed toward the nontradable sector, where supply is inelastic, leads to an increase in the price of nontradable compared to tradable goods. This increase leads to an appreciation of the real exchange rate, with potentially harmful effects on external competitiveness consistent with a deterioration of the nonresource current account following a resource windfall shock.

A relevant question is whether countries that have implemented fiscal rules defined as numerical targets to constraint budget aggregates differ in their macroeconomic stability. To answer this, we added to the previous VAR specification an interaction term between our resource windfall index and fiscal-rule dummies obtained from IMF (2009) (results not reported in tables). Our results indicate no evidence of a dichotomous effect of resource windfalls depending on whether a fiscal rule has been implemented. One explanation could be that it is simply too early to tell. Indeed, as documented by Ossowski and others (2008), many of those fiscal rules in commodity-exporting countries were only put in place in the early 2000s. An alternative explanation could be that fiscal rules are not necessarily effective, since they can be circumvented, especially in weak institutional environments. If that is true, the design of fiscal rules in commodity-exporting countries should perhaps be revisited to adapt them to the challenges posed by the institutional environment. One country that has successfully implemented a fiscal rule, Chile, has targeted a structural budget balance set by a panel of experts. This could certainly be a source of inspiration (Frankel, 2011b).

A related policy issue is whether fiscal rules in commodity exporters should take into account the composition of government spending. Indeed, fiscal rules may indeed impact the composition of spending, since the politically sensitive nature of some types of spending could lead to a fiscal rule’s having adverse effects on long-run economic growth. Blanchard and Giavazzi (2003) provide an interesting discussion of those issues in the context of the European Stability and Growth Pact. Arezki and Ismail (2010) find that fiscal rules in oil-exporting countries have forced the adjustment on capital spending in bust times, raising some concern over the consequences on economic growth. Arezki and Alichi (2009) provide theoretical and empirical evidence of the negative effects of current spending on non-oil GDP growth in oil-exporting countries. The United Kingdom and Peru are among the few countries that have shielded the composition of their spending from the implementation of fiscal rules.

Another relevant question is whether countries endowed with mineral and energy resources have fared differently in macroeconomic stability when compared to countries endowed with agricultural resources. To answer this, we partition our sample, distinguishing countries where agricultural exports dominate from countries where minerals and energy exports dominate. We find that countries that export mostly minerals and energy commodities display a statistically significant increase of government spending following an increase in resource windfalls, whereas countries exporting mainly agricultural commodities do not display any statistically significant increase (results not reported in tables).

Those results suggest that windfalls originating from point-based resources, that is, geographically more concentrated resources (mostly minerals and energy commodities) are more likely to lead to procyclical fiscal policies than windfalls originating from diffuse resources, that is, more geographically dispersed resources (mostly agricultural commodities). Our results are also consistent with those of Isham and others (2005), who provide evidence that mineral and energy exporters are plagued with weaker economic performance and in particular weaker recovery. Point-based as opposed to diffuse resources are indeed seen as more subject to rent-seeking behavior, weakening the effectiveness of monitoring mechanisms over how much the government receives and how much it spends, both from independent institutional bodies and from the public more generally. Given the potentially higher level of rent-seeking by governments in countries endowed with point-based resources, it is plausible that those governments would spend more in boom times in order to quell the masses whose grievances in times of plenty may be conducive to social instability.

We also explore whether the quality of political institutions influences the way resource windfall shocks affect macroeconomic stability in commodity-exporting countries. To do so, we split the sample between deep autocracies and deep democracies and run our panel VAR regressions for both subsamples (results not reported in tables). We find strong evidence that government spending in autocracies increases following a resource windfall shock. In contrast, we find evidence, albeit weaker, that government spending in deep democracies decreases on impact and then does not increase significantly following a resource windfall shock. These results suggest that deep democracies are less prone to the procyclical fiscal policies that have destabilizing effects. In the next subsection, we further elaborate on the theories that may explain why democracies, as opposed to autocracies, can experience superior macroeconomic stability and long-run growth. We also find that in both groups, resource windfall shocks initially crowd out nonresource GDP, which then increases following the fiscal expansion, although the evidence of this is weaker among deep democracies.

Economic Growth

The above-mentioned results suggest that commodity-exporting countries, on average, are subject to macroeconomic instability, which in turn can harm their long-run economic performance. In addition, one key challenge that these countries face is to reduce their dependence on commodities by rebalancing their wealth from natural capital in favor of reproducible capital and social capital, including human capital. Figure 9.4 illustrates the fact that commodity-exporting countries in sub-Saharan Africa and the Middle East hold a disproportionately higher share (over 30 percent) of their total wealth as natural capital. However, a large increase in government spending risks yielding poor efficiency in the execution of projects and misallocation of resources.

Figure 9.4.Worldwide map of natural capital as a share of total capital, 2005

Source: World Bank (2011) and author’s analysis.

To take stock of the historical experiences of commodity-exporting countries, we now systematically investigate the impact of government spending on long-run nonresource-sector growth in the face of resource windfall shocks. To do so, we use panel cointegration techniques to separate out the short-run from the long-run effects of government spending on nonresource GDP growth. The empirical model is specified so that GDP per capita growth in the nonresource sector is the dependent variable. The independent variables are our resource windfall index, the share of government spending in GDP, the change in the logarithm of the real exchange rate, and the quality of political institutions.

Table 9.1 presents the results of the Pool Mean Group estimations focusing on the long-run coefficients. On average, we find that resource windfall shocks have a statistically and economically significant negative effect on the long-run nonre-source-sector GDP growth, as shown throughout columns 1 to 5. We also find that, on average, an increase in the share of government spending has a negative effect on long-run nonresource GDP growth. Those two results are in line with the existing literature, providing evidence that resource windfalls and larger governments both lead to weaker long-run economic growth. However, what is new in the findings is that resource windfalls stop having a negative effect on long-run nonresource growth when controlling for government spending, as shown in columns 3 to 5. This result suggests that government spending is an important vehicle of the resource curse hypothesis. In other words, the externality stemming from the resource sector to the nonresource sector is mainly conveyed through government spending, chiefly financed by resource-sector-related government revenues.

Table 9.1.(Millions of U.S. dollars)
Variables(1)(2)(3)(4)(5)
Long-Run Coefficients
Initial GDP-0.089-0.051-0.074-0.107-0.061
0.0060.0040.0060.0060.006
Δ Resource Windfall-1.082-0.8045.399-0.160
0.4540.5010.6570.497
Government Size-0.049-0.022-0.081-0.042
0.0180.0200.0220.017
Δ REER0.018

0.005
Polity II0.004

0.002
Low income interaction
No. of Countries108129949494
No. of Observations35644257310222773094
Source: Author’s analysis.
Source: Author’s analysis.

When controlling for the change in the real exchange rate, as shown in column 4, resource windfall shocks have a positive effect on nonresource GDP growth. This result confirms that Dutch disease is an important channel of the resource curse. When controlling for the quality of political institutions, as shown in column 5, the above results do not appear to change significantly. Given the fact that the quality of political institutions changes little even over a relatively long time period, it is hard to meaningfully assess the individual effect of democracy on long-run economic growth when exploiting within-country variation.

In Table 9.2, we explore the potential heterogeneity in the effects of resource windfalls and government spending on nonresource GDP growth. We explore first whether the quality of political institutions helps alleviate the resource curse by interacting both our resource windfall index and government spending with our measure of the quality of political institutions. We find that the impact of resource windfalls and government spending are moderated by the quality of political institutions so much that at a high level of political institutions the effect of resource windfalls on long-run nonresource GDP becomes positive, as shown in columns 1 and 2. A large share of commodity windfalls accrues to the government sector (through state ownership or taxation or export tariffs). These results suggest that democracy, by promoting accountability and consensus, reduces the perverse effect that resource windfalls may have on the nonresource sector, for instance through fewer discretionary policies that are conducive to macroeconomic volatility. Some authors have indeed stressed the importance of political institutions in achieving better policy outcomes (see for example Persson, 2002). In their seminal contribution to the growth and institutions literature, Acemoglu, Johnson, and Robinson (2001, 2002) have shown that political institutions are key determinants for long-run economic development.

Table 9.2.
Variables(1)(2)(3)(4)
Long-Run Coefficients
Initial GDP-0.080-0.062-0.075-0.041
0.0060.0050.0050.004
Δ Resource Windfall-1.866-0.8340.388
0.5970.4970.429
Government Size-0.030-0.019-0.061
0.0170.0180.020
Polity20.0040.0030.0030.005
0.0020.0020.0020.002
Polity2 x Windfall0.0720.160
0.0400.037
Polity2 x Gov. Size0.0020.001
0.0010.000
No. of Countries94949494
No. of Observations3290329032903290
Source: Author’s analysis.
Source: Author’s analysis.

Following Melhum, Moene, and Torvik (2006), who provide some evidence that good economic institutions can alleviate the resource curse using standard cross-sectional growth regressions, we also try interacting resource windfalls with the quality of economic institutions rather than political institutions. We do not find any robust evidence that economic institutions moderate the effect of resource windfalls on non-resource GDP growth, supporting the primacy of political institutions over economic institutions as a tool to alleviate the resource curse. In columns 3 and 4, we also provide evidence that the quality of political institutions moderates the effect of government spending on long-run nonresource GDP growth, suggesting that the benefit of political institutions for economic growth is channeled through better fiscal policy. Indeed, a large share of commodity windfalls accrues to the government sector (through state ownership, taxation, or export tariffs). Therefore, more accountable governments can better support the nonresource sector’s long-run economic performance by reducing government spending inefficiencies and resource misallocation. This finding is consistent with Arezki and BrÜckner (2010a), who find that commodity price booms lead to increased government spending, external debt, and default risk in autocracies, but do not have the same effects in democracies. Arezki and Bruckner (2010b) also provide evidence of dichotomous effects on sovereign bond spreads in autocratic versus democratic commodity-exporting countries.

Finally, we explore whether countries that export mineral and energy commodities are subject to weaker long-run nonresource-sector performance as compared to countries that export agricultural commodities (results not reported in tables). We find once again that minerals and energy exporters perform less favorably than agricultural exporters in the face of resource windfall shocks. This result confirms that the negative effect of resource windfalls on long-run nonresource GDP is a robust feature of mineral- and energy-exporting countries.

CONCLUSION

This chapter examined the performance of commodity-exporting countries in terms of macroeconomic stability and growth in a panel of up to 134 countries during the period 1970–2007, using a new dataset on nonresource GDP. Our main findings are twofold. First, we find that on average government spending in commodity-exporting countries has been procyclical. We also find that resource windfalls initially crowd out nonresource GDP, which then increases as a result of the fiscal expansion. Second, we find that in the long run, resource windfalls have negative effects on nonresource-sector GDP growth, but these effects are not over government spending. The effects of resource windfalls on both macroeconomic stability and economic growth are moderated by the quality of political institutions.

A policy recommendation that can be derived from the above results would consist in finding a creative way to promote government accountability in commodity-exporting countries. One could suggest to governments in these countries that they should increase their revenue mobilization in the nonresource sector, which is currently at a relatively low rate both statutorily and effectively. Indeed, Bornhorst, Gupta, and Thornton (2009) provide evidence that resource windfall shocks lower revenue mobilization. Keen and Mansour (2009) have found that a low statutory tax rate on natural-resource-sector activities and high informality are prevalent in the commodity-exporting countries in sub-Saharan African. One could explore nonresource-sector taxation as a way to generate a positive externality, while recognizing the classical argument against taxation stemming from its distortive nature. Indeed, a recent literature has emphasized the importance of taxation for state building. Grassroots taxpayer associations could exercise monitoring over the efficiency of government spending. Brautigam, Fjeldstad, and Moore (2008) provides anecdotal evidence that the imposition of a tax by the British colonial rule on the sugar industry in Mauritius led to the emergence of grassroots tax-payer associations, which up to this day exercise a monitoring role over the way taxpayers’ money is spent by the government. In addition, increasing nonresource-sector revenue mobilization would deliver other benefits, including combating volatility in government revenues by diversifying the sources of government revenues.

Further research should investigate the performance of resource-rich countries in addressing issues of income distribution. A cursory look at the data indicates that natural-resource-abundant countries are rich but unequal. Despite several authors, including Subramanian and Sala-i-Martin (2003), who have advocated direct redistribution, there are many reasons to think that it may not be a good idea to engage excessively in such action. Indeed, direct redistribution may fuel increased consumption as opposed to investment, which may infringe on the Hartwick rule. Indeed, individuals may underinvest the proceeds of resource revenues in, say, education and health, as they may not internalize the social benefits of those investments. One possibility would be to redistribute not necessarily directly, in the form of cash transfers, but rather in the form of greater information and enhanced transparency concerning the management of revenues and on the rationale behind the choice of the level and composition of spending. Citizens must take part in the major debates addressing public action. That will make it possible to improve the efficiency of government spending, which in turn will benefit the citizenry.

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Rabah Arezki is an economist at the IMF Institute, International Monetary Fund. This chapter is based on the author’s presentation at “Natural Resources, Finance, and Development: Confronting Old and New Challenges,” a high-level seminar organized by the Bank of Algeria and the IMF Institute, which took place in Algiers, on November 4 and 5, 2010. The author wishes to thank Bertrand Candelon, Reda Cherif, Kirk Hamilton, Aasim Husain, Mustapha Nabli, and the seminar participants, as well as Kazim Kazimov for outstanding research assistance. The author can be contacted at rarezki@imf.org.
1Arezki, Hamilton, and Kazimov (2011) provide a detailed technical discussion of the results presented in this chapter.
2We leave the analysis of the “third function” of fiscal policy in commodity-exporting countries—namely achieving an equitable distribution of income—for further research. A nascent literature has investigated the issue (see Ross (2007) and Goderis and Malone (2008) among others).
3The next section describes the estimation of nonresource GDP, which takes into account the depletion of the stock of natural resources.
4The resource depletion data are from World Bank (2011) and the GDP data are from Heston, Summers, and Aten (2009).
5The commodities included in the commodity export price index are aluminum, beef, coffee, cocoa, copper, cotton, gold, iron, maize, oil, rice, rubber, sugar, tea, tobacco, wheat, and wood. In case there were multiple prices listed for the same commodity, a simple arithmetic price average was used.
6Government spending data is from Heston, Summers, and Aten (2009).
7All the variables used in the panel VAR are used in log-difference. This is motivated by the fact that while panel-unit root tests suggest that those series are nonstationary, panel cointegration tests (first and second generations taking into account cross-sectional dependence) reject the evidence of cointegration relationship between those variables.
8The real exchange rate data is obtained from IMF (2010a) and the current account data is from IMF (2010b). The nonresource current account is constructed by subtracting commodity exports from overall current account.

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