This chapter provides an overview of recent developments in reserve accumulation in LICs. It also presents results of a reserve demand regression, which allows for a more systematic assessment of reserve holdings across countries relative to their peers. To the extent that these holdings reflect precautionary considerations, a model of reserve demand can shed light on the relative importance of different variables and provide a means of distinguishing between countries based on these revealed preferences.
Recent Trends
Figure 4.1 shows recent trends in reserve accumulation in LICs and emerging market economies (EMEs) measured by two traditional metrics, import coverage and as a share of broad money. Import coverage is viewed as a measure of the number of months of imports that could be sustained if all external inflows were to cease. Traditionally, three months’ coverage is used as a benchmark.1 Broad money coverage (typically 20 percent is used as an upper-bound benchmark) provides a measure of the potential for resident-based capital flight and is particularly relevant for dollarized economies and countries with greater capital account openness. As shown in Figure 4.1, reserve accumulation has generally outpaced traditional reserve adequacy metrics across both country groups in recent years.2 Although the buildup has been slower than in EMEs, most LICs have accumulated more reserves since 2002 than suggested by the standard rules of thumb, with median coverage ratios of about 4.7 months of imports, and 55 percent of broad money in 2009.
Recent Trends in Reserve Accumulation in Low-Income Countries and Emerging Markets
(Median reserve holdings)
Source: World Economic Outlook DatabaseNote: EMEs: emerging market economies; LICs: low-income countries.Recent Trends in Reserve Accumulation in Low-Income Countries and Emerging Markets
(Median reserve holdings)
Source: World Economic Outlook DatabaseNote: EMEs: emerging market economies; LICs: low-income countries.Recent Trends in Reserve Accumulation in Low-Income Countries and Emerging Markets
(Median reserve holdings)
Source: World Economic Outlook DatabaseNote: EMEs: emerging market economies; LICs: low-income countries.Figure 4.2 further breaks down reserve accumulation in LICs by various country groups and exchange rate regimes. Since 2003, the ratios of reserves to imports increased most sharply for oil exporters. Sub-Saharan African countries—a large number of which are commodity exporters—have had persistently higher reserve coverage than the median low-income country, although this difference has narrowed in recent years. On the other hand, reserve coverage in countries with GDP per capita less than US$500 has been well below the low-income country median throughout the 2000s. Finally, recent reserve accumulation has also outpaced the conventional rule of thumb of three months of import cover for both fixed and floating exchange rate regimes, but countries with fixed regimes generally tend to have higher reserve coverage.
Median Reserve Coverage in Low-Income Countries
(Months of current year’s imports)
Source: IMF, World Economic Outlook.Note: LICs: low-income countries; SSA: sub-Saharan Africa.Median Reserve Coverage in Low-Income Countries
(Months of current year’s imports)
Source: IMF, World Economic Outlook.Note: LICs: low-income countries; SSA: sub-Saharan Africa.Median Reserve Coverage in Low-Income Countries
(Months of current year’s imports)
Source: IMF, World Economic Outlook.Note: LICs: low-income countries; SSA: sub-Saharan Africa.These aggregate figures mask significant differences across individual countries. As of 2009, more than a quarter of all countries had reserve levels lower than suggested by the import coverage metric. The accelerating buildup of reserves reflects low initial reserve holdings, increasing openness of economies, a favorable global environment, and policy choices among LICs to build precautionary reserves to insure against balance of payment risks.3
Explaining Demand for Reserves
To assess whether the recent reserve accumulation in LICs has been in line with fundamentals, we estimated a cross-country empirical model of precautionary demand for reserves.4 The basic idea underlying the theory of reserves demand is that a country chooses a level of reserves to balance the macroeconomic adjustment costs incurred if reserves are exhausted (the precautionary motive) with the opportunity cost of holding reserves. Based on this theoretical idea, existing empirical studies have identified a set of variables to explain a long-term demand for reserves. There are five key elements to account for reserve holdings.
Economic size: To the extent that international transactions increase with economic size, reserve holdings are also expected to rise with economic size measured by population or real GDP per capita.
Current account vulnerability: A more open economy is more vulnerable to external shocks. Reserves held for precautionary purposes are intended to buffer absorption against such shocks. Thus, a higher degree of trade openness would be associated with higher reserve holdings; the greater the exposure to external shocks, the higher the level of reserves.
Capital account vulnerability: The need to buffer absorption against capital account shocks is greater as countries become more financially integrated into the global economy. Thus greater financial openness could be associated with higher crisis vulnerability, affecting the demand for reserve holdings. The higher degree of financial openness would be associated with higher reserve holdings, and the larger the potential shocks, the higher the reserve demand.
Exchange rate flexibility: Greater exchange rate flexibility is expected to reduce demand for reserves as central banks will not need to hold a large amount of reserves to maintain a pegged rate or to enhance a peg’s credibility. Central banks may also intervene in an attempt to dampen appreciation of their currencies, increasing the level of international reserves. On the other hand, in countries where foreign exchange and capital markets are less developed, volatile movements of capital flows could result in substantial exchange rate and asset price volatilities. In such a case, the need for reserves may increase with greater exchange rate flexibility.
Opportunity cost: The opportunity cost of holding reserves is the difference between the yield on reserves and the marginal productivity of an alternative investment. Greater opportunity costs of holding reserves are expected to reduce the demand for reserves. This is proxied by the interest rate differential between the government treasury bill and the corresponding U.S. asset.
Following the empirical literature, the demand for reserves is modeled as a function of the size of the economy and other country fundamentals in the multivariate regression below. The model is estimated using panel data for 62 LICs (excluding economies with a population of less than 1 million) from 1992 to 2001. The remaining years are used to compare out-of-sample forecasts with actual reserve buildups.
Table 4.1 reports the regression results for the full sample of LICs, and separately for commodity and non-commodity exporters. For the full sample in column (1), reserve holdings are positively and significantly related to indicators of current account vulnerability (import ratio and export volatility) and capital account vulnerability, such as broad money. Exchange rate volatility and fixed exchange rate regimes are also significantly associated with higher reserve holdings, suggesting that pegged countries have greater precautionary demand for reserves than their peers. The proxy for the cost of holding reserves, measured as the interest rate differential between the government treasury bill and the corresponding U.S. asset, is of the expected sign but lacks statistical significance.
Estimating Reserve Demand in LICs
Estimating Reserve Demand in LICs
| 1992–2001 | |||
|---|---|---|---|
| Variables | All LICs (1) |
Commodity exporters (2) |
Non-commodity exporters (3) |
| Income | ‒0.0045*** | ‒0.0051*** | ‒0.0049*** |
| (0.0006) | (0.0009) | (0.0008) | |
| Log (population) | ‒2.2280*** | ‒0.9651 | ‒2.7470*** |
| (0.3743) | (0.6741) | (0.4570) | |
| Imports/GDP | 0.2611*** | 0.1758*** | 0.2783*** |
| (0.0198) | (0.0361) | (0.0230) | |
| Exchange rate volatility | ‒0.0351** | ‒0.0092 | ‒0.1334** |
| (0.0147) | (0.0164) | (0.0639) | |
| Export volatility (3 year standard deviation) | 0.0482** | 0.0930*** | ‒0.0367 |
| (0.0235) | (0.0340) | (0.0333) | |
| Broad money/GDP | 0.3374*** | 0.5694*** | 0.3077*** |
| (0.0326) | (0.0617) | (0.0394) | |
| Peg dummy | 1.2851* | 0.0731 | 0.8605 |
| (0.7792) | (1.4817) | (0.9293) | |
| Interest rate differential with U.S. | ‒0.2178 | ‒0.2172 | ‒0.579 |
| (0.5248) | (0.7717) | (0.6832) | |
| Observations | 414 | 140 | 274 |
| R-squared | 0.639 | 0.707 | 0.668 |
Estimating Reserve Demand in LICs
| 1992–2001 | |||
|---|---|---|---|
| Variables | All LICs (1) |
Commodity exporters (2) |
Non-commodity exporters (3) |
| Income | ‒0.0045*** | ‒0.0051*** | ‒0.0049*** |
| (0.0006) | (0.0009) | (0.0008) | |
| Log (population) | ‒2.2280*** | ‒0.9651 | ‒2.7470*** |
| (0.3743) | (0.6741) | (0.4570) | |
| Imports/GDP | 0.2611*** | 0.1758*** | 0.2783*** |
| (0.0198) | (0.0361) | (0.0230) | |
| Exchange rate volatility | ‒0.0351** | ‒0.0092 | ‒0.1334** |
| (0.0147) | (0.0164) | (0.0639) | |
| Export volatility (3 year standard deviation) | 0.0482** | 0.0930*** | ‒0.0367 |
| (0.0235) | (0.0340) | (0.0333) | |
| Broad money/GDP | 0.3374*** | 0.5694*** | 0.3077*** |
| (0.0326) | (0.0617) | (0.0394) | |
| Peg dummy | 1.2851* | 0.0731 | 0.8605 |
| (0.7792) | (1.4817) | (0.9293) | |
| Interest rate differential with U.S. | ‒0.2178 | ‒0.2172 | ‒0.579 |
| (0.5248) | (0.7717) | (0.6832) | |
| Observations | 414 | 140 | 274 |
| R-squared | 0.639 | 0.707 | 0.668 |
The empirical model for the full sample accounts for more than 60 percent of the variation in reserves (excluding country fixed effects), To assess whether the recent accumulation in LICs has been in line with fundamentals, we estimate a cross-country empirical model of precautionary demand for reserves. A breakdown of the sample into commodity exporters and non-commodity exporters in columns (2) and (3), however, reveals differences between the two groups in accounting for reserve demand. Exchange rate volatility is more important for non-commodity exporters, whereas export volatility is highly significant in explaining reserve demand in commodity exporters.
How does the reserve buildup in LICs between 2002 and 2008 compare with the model’s forecasts? Figure 4.3 shows a comparison of out-of-sample forecasts derived from the model in column (1) of Table 4.1 with actual reserve buildups for the 2003–08 period (excluding the 2009 SDR allocation, which could have distorted reserve holdings). As can be seen in the figure, the growth in LIC reserve holdings has been broadly in line with evolving fundamentals.
Low-Income Countries: Actual and Predicted Reserves, 2003–2008
(Mean, percent of GDP)
Source: World Economic Outlook and IMF staff estimates.Low-Income Countries: Actual and Predicted Reserves, 2003–2008
(Mean, percent of GDP)
Source: World Economic Outlook and IMF staff estimates.Low-Income Countries: Actual and Predicted Reserves, 2003–2008
(Mean, percent of GDP)
Source: World Economic Outlook and IMF staff estimates.However, Figure 4.3, based on aggregated data, masks significant differences across LIC regions. Figure 4.4 reports the results of the same exercise conducted for each region of the world. In some regions, the growth in reserve holdings has been outpacing the movements in fundamentals significantly (South Asia, and the Middle East and North Africa), whereas in other regions reserve holdings have been broadly in line with fundamentals (East Asia and Pacific, Europe and Central Asia) or slightly lagging behind (Latin America and the Caribbean).
Actual and Predicted Reserves to GDP, by region
(Mean, percent of GDP)
Sources: IMF, World Economic Outlook; and IMF staff estimates.Actual and Predicted Reserves to GDP, by region
(Mean, percent of GDP)
Sources: IMF, World Economic Outlook; and IMF staff estimates.Actual and Predicted Reserves to GDP, by region
(Mean, percent of GDP)
Sources: IMF, World Economic Outlook; and IMF staff estimates.In sum, median reserve accumulation in LICs has outpaced standard rules of thumb in recent years. Although reserve demand regressions suggest that the recent growth in reserve holdings is largely in line with fundamentals with some regional variations, this analysis does not address the optimal level of reserves needed in light of the shocks faced by such countries. Instead, the analysis only provides a picture of the determinants of observed reserve holdings. Although traditional metrics are simple to use, they offer only rough guidance and lack empirical and theoretical foundations. The following chapters propose a new approach to assess reserve adequacy in LICs using a cost-benefit framework to determine optimal reserve levels.
This metric is typically applied to countries where shocks arise from the current account (i.e., where capital and financing account transactions may be small or restricted). The assumption of a complete cessation of balance of payments inflows seems rather drastic, except perhaps for the very poorest of countries; however, as a proxy for trade openness the measure does not seem unreasonable for a country whose balance of payments is dominated by the current account.
Short-term debt by remaining maturity, another commonly used measure for reserve adequacy in countries that face capital account pressures, is not reported because of the poor quality of short-term external debt data in a large number of LICs. For countries with reliable short-term debt data, reserve holdings were found to be significantly above the rule of thumb, reflecting their limited market access and reliance on concessional longer term financing from official sources.
It is also worth noting that the increase in reserves in 2009 is largely attributable to the SDR allocation in response to the global financial crisis. See http://www.imf.org/external/np/sec/pr/2009/pr09283.htm.
IMF (2003) and Aizenman and Marion (2003) develop models for EMEs. The use of this model for assessing reserve adequacy relies on the assumption that, averaged over countries and over the regression sample period, there is no systematic bias over under- or over-insurance across countries.
