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This paper was prepared for a research project on the Central African Economic and Monetary Community (CEMAC) region and will be included in a collection of papers on CEMAC’s recent economic policies. We would like to thank without implication, Rudolph Bems, Alcino Conceicao, Irineu de Carvalho Filho, Alun Thomas, and Uwatt Bassey Uwatt for insightful comments and suggestions on our work. Any errors are, however, our own.
In this paper, we include both oil and gas production in the term “oil producers”, although we recognize the importance of accounting for both resources in the economic analysis and policy discussions.
The impact of exchange rate adjustments on the current account is usually derived from the elasticity of the current account balance to the real exchange. This is the approach taken, for example, in the IMF’s Consultative Group on Exchange Rate Issues (CGER) outlined in Lee and others (2008). The CGER was formed in the IMF in the mid-1990s to provide exchange rate assessments for a number of advanced economies from a multilateral perspective.
The higher current account deficits are driven by high oil-related infrastructure investment imports.
CEMAC is the Central African Economic and Monetary Community comprising Cameroon, Central African Republic, Chad, Equatorial Guinea, Gabon, and the Republic of Congo.
In this paper, we limit the analysis to proven oil reserves and do not include natural gas, even though it is increasing in importance in a few countries. Gas reserves are not yet well delineated in the region and production is at an early stage, although they could become a significant part of the sub-regions total hydrocarbon wealth. Likewise, many oil-producing SSA countries are aggressively conducting both on- and off-shore exploration, which could lead to new discoveries of oil and gas and as a result, proven reserves could rise dramatically with implications for the analysis of external sustainability.
As discussed below, this consumption smoothing is very similar to the deterministic case with precautionary saving. However, we chose to present the two models separately. Consumption smoothing allows more flexibility for setting non-oil productivity growth, which is an important variable for low-income oil-producing countries in assessing external sustainability.
A stochastic case is discussed in the precautionary approach.
The consumption tilting factor shows the degree of the intertemporal substitution in consumption, i.e., how much individuals are more (or less) willing to sacrifice present consumption for an increase in future consumption. Even in a deterministic case, this factor could exist because individuals have different time preferences of consumption.
This is the average of the real discount rate adopted by the US Office of Management and Budget for 10 years and for 30 years in 2010 (see http://www.whitehouse.gov/omb/circulars_a094_a94_appx-c/) The UN data can be found on the internet at http://esa.un.org/unpp/. The population growth rates ranged from a low of 1.3 percent a year for Gabon to 2.0 percent a year for Angola.
Note that these estimates do not take into account the return on existing assets that these countries may have accumulated in the past.
Thomas, Kim, and Aslam (2008) ran a second-order autoregressive process on the change in real non-oil cash flow per capita with country dummies and the change in real oil wealth as regressors.
Thomas, Kims, and Aslam. (2008) base this share on the historical average of several oil-producing countries where reliable data is available.
Thomas, Kim, and Aslam (2008) examined Venezuela, Kuwait, Malaysia, Russia, Saudi Arabia, and United Arab Emirates. Domestic consumption ranged between 0 (United Arab Emirates) and 5.3 percent (Malaysia) of total GDP. Deléchat and Kireyev (2008) estimated Cameroon’s domestic consumption using the difference between production and exports and this amounted to only 0.7 percent.
This problem can be solved only when (1+n)/(1+r)>1. This condition is satisfied under the baseline and for the sensitivity tests.
The model confirms that the level of consumption under uncertainty is lower than with certainty in the earlier period. However, in the later period, consumption becomes higher with uncertainty than without as savings are accumulated and interest income grows.
We use four-year averages of these variables to avoid the volatility these variables display.
We trade off the benefits of a larger panel to focus on the particular characteristics of oil-producing countries. Our sample of these countries include Algeria, Bahrain, Indonesia, Iran, Kazakhstan, Kuwait, Libya, Norway, Oman, Qatar, Russia, Saudi Arabia, Syria, United Arab Emirates, and the eight countries from sub-Saharan Africa. We are grateful to Rudolph Bems and Irineu de Carvalho Filho for sharing their data on the countries outside of the SSA.
In Lee and others (2008), the variable for economic crises is a dummy for the Asian crises (1997–2004), which drastically reduced access to international financial markets for those countries. Since SSA oil-producing countries do not enjoy such access, this crisis variable is superfluous. The variable for the financial center is a dummy that represents the regional financial centers such as Belgium, Hong Kong SAR, Luxemburg, and Singapore. The financial centers are hubs for international financial flows and tend to run substantial current account surpluses. Because none of oil-producing countries plays such a role, this variable is also superfluous.
The old-age dependency ratio is calculated as the ratio of the population above 65 years old to the population of 15–64 years old.
As Lee and others (2008) note the impact of the demographic profile on the current account could be different among countries, depending on the characteristics of the retirement system and the development of financial markets. It is not, however, possible to accurately estimate this impact for all countries; consequently the deviations from trading partners are used to try to capture the main differences.
The methodology for estimating the return on wealth is outlined in the section above on consumption smoothing, although we further modify this calculation by correcting for population growth and netting out domestic consumption, as proposed by Thomas and Bayoumi (2009).
The public sector response to oil income should be assessed together with the regression of the non-oil fiscal balance on oil income variables. However, we did not pursue this analysis: as section V shows, in oil-producing SSA countries, the non-oil fiscal balance is insignificant as an explanatory variable.
In six of the eight SSA oil-producing countries, oil reserves (not including gas) could be exhausted over the next 20 years without further exploration and development; this compares with projections of 100 years for middle- and high-income oil producers.
In the standard consumption-smoothing approach (i.e., no uncertainty over oil prices), the source of non-oil growth is restricted to the labor force. Consequently, Bems and de Carvalho Filho (2009a) run a sensitivity analysis focusing on non-zero productivity growth, which requires the risk-free rate to be set rather high. We believe this constraint is overly restrictive for our set of countries because productivity growth in the non-oil sector could substantially change and, consequently, affect the sustainable external balance.
The estimates of the precautionary-saving component depend on the consumption-smoothing component in this model. Therefore it is not entirely consistent to extract only the precautionary saving component from this model and compare it with the standard consumption smoothing. Having said that, the estimates of the consumption-smoothing components from the two models are very similar, and their comparison is meaningful for policy discussion purposes. For 2006, for example, the difference between the two methods is only 3.7 percentage points on average across the oil-producing SSA countries.