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Shifting Motives: Explaining the Buildup in Official Reserves in Emerging Markets Since the 1980s

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Abstract

Why have emerging market economies (EMEs) been stockpiling international reserves? We find that motives have varied over time; vulnerability to current account shocks was relatively important in the 1980s but, as EMEs became more financially integrated, factors related to the magnitude of potential capital outflows gained importance. Reserve accumulation as a by-product of undervalued currencies has also become more important since the Asian crisis. Correspondingly, using quantile regressions, we find that the reason for holding reserves varies according to the country’s position in the global reserves distribution. High-reserve holders, who tend to be more financially integrated, are motivated by insurance against capital account rather than current account shocks and are more sensitive to the cost of holding reserves than are low-reserve holders. Currency undervaluation is a significant determinant across the reserves distribution, albeit for different reasons.

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Figure 1

Source: Authors’ calculations.

Figure 2

Source: Authors’ calculations.

Figure 3

Source: Authors’ calculations.

Figure 4

Source: Authors’ calculations.

Figure 5

Source: Authors’ calculations. Actual and quantile regression fitted change in log (reserves/GDP) excluding the effects of scale variables (population and per capita income) and exchange rate regime variables.

Figure 6

Source: Authors’ calculations.

Figure 7

Source: Authors’ calculations.

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Notes

  1. Assessments of reserves are relevant both to the IMF’s role in bilateral surveillance, as well as its mandate in overseeing the stability of the international monetary system (see Ghosh and others 2010).

  2. We focus on EMEs because much of the reserve accumulation over the past thirty years has been largely an emerging market phenomenon (both in absolute terms and in percent of GDP). Between 1980 and 2013, EM reserve holdings rose from US$0.08 trillion (5 percent of GDP) to US$8.30 trillion (31 percent of GDP), whereas reserve holdings of advanced economies rose from US$2.28 trillion (4 percent of GDP) to US$3.38 trillion (7.5 percent of GDP), and those of low-income countries rose from US$0.01 trillion (4.2 percent of GDP) to US$0.19 trillion (17 percent of GDP). Econometric analysis also suggests that the motives underlying reserve accumulation by the AEs are quite different (see Appendix A).

  3. These papers rely on the deviation of the price level from the trend implied by per capita income for their undervaluation measure, which ignores other fundamental drivers of currency misalignment.

  4. With the exception of Sula (2011), who focuses on mainly current account-related variables in the analysis and omits banking system liabilities as well as any proxy for mercantilism, to the best of our knowledge, none of the papers in the literature allows for the effect of regressors to vary according to the level of reserves.

  5. In the absence of data on the currency denomination of external short-term debt, we assume that external debt is denominated in foreign currency, which raises the need to hold (precautionary) reserves to buffer against currency mismatches. As EMEs are becoming more financially open, they are increasingly able to borrow in their own currencies, which could diminish the need to hold reserves.

  6. Heller (1966) appears to be the first to have formalized a model of optimal precautionary management; see Hamada and Ueda (1977), Frenkel and Jovanovic (1981), and Frenkel (1983) for extensions to his work.

  7. Some papers investigate demand elasticities explicitly. Kelly (1970) and Frenkel (1974) find that estimated reserve demand elasticities between developed and less developed countries and more open and less open economies are significantly different. Delatte and Fouquau (2012) and Sula (2011) using a time-varying threshold regression framework and a quantile regression framework, respectively, find evidence for non-constant reserve demand parameters.

  8. In addition to the production externality, other motivations for mercantilism include inefficiency and misallocation of capital in the domestic financial system, or excessive political power of exporters.

  9. Some trade models posit that more productive firms will serve the export market (Melitz, 2003), but there is also a rich literature on the productivity-enhancing effects of having to compete in the export- or import-competing sectors (Aw and Hwang, 1995, Kraay, 1999). See Tybout (2000) for a useful survey of the literature.

  10. This is a common assumption in the context of emerging market and developing countries; necessary here for sterilized intervention to be potent.

  11. Because R and i are dependent on each other, this is equivalent to assuming that the government sets i and then the household maximizes utility by taking i as given.

  12. The relative cost of the various policies becomes relevant if lump sum taxes are not available. By the Lerner symmetry theorem, a tax on the non-tradable sector should be equivalent to a subsidy to the tradable sector. In practice, however, the non-tradable sector is likely to be informal and therefore difficult to tax.

  13. The list of countries in the sample is based on the sample of EMEs covered in the IMF’s Early Warning Exercise (IMF, 2010). See Appendix B, Tables B1 and B2.

  14. Our measure is based on the Chinn–Ito financial openness index, which is, in turn, derived from the IMF’s AREAER. It is normalized between zero and one, with higher values indicating greater financial openness (see Chinn and Ito (2006)).

  15. A country can accumulate reserves through the current or the capital account (i.e., capital inflows), so undervaluation of the currency is not a necessary condition for reserve accumulation. In recent years, for example, Brazil and India have accumulated large stocks of reserves despite overvalued exchange rates and current account deficits.

  16. By our definition, currency undervaluation is necessary but not sufficient for mercantilism since there may be precautionary demand for reserves that is met by maintaining an undervalued currency; or the undervaluation may be unrelated to reserve accumulation (e.g., during a currency crisis). Since we include precautionary demand variables in the regression, the first of these cases is addressed: a significant coefficient on undervaluation controls for precautionary demand. In the robustness section below, we address the second possibility by setting the undervaluation dummy to zero in cases where the country’s reserves are declining, or alternatively, when it has suffered a currency crisis.

  17. Estimated misalignments based on the MB and ES methods are highly correlated (around 0.7 for the full sample, ranging from 0.5 to 0.8 during the sub-periods), while the ERER misalignments’ correlation with MB and ES is weaker, ranging from about 0.2 to 0.3.

  18. In the robustness tests, however, we add both time- and country-fixed effects. Estimated standard errors are clustered by country to allow for heteroskedasticity across countries and serial correlation in the error term within countries.

  19. Both by allowing the marginal impact of explanatory variables to vary by the value of the dependent variable, and by identifying factors that might be missed in OLS, quantile regressions potentially offer a richer picture of what has been driving reserve accumulation across time and countries. When quantile regressions include multiple independent variables, the quantiles refer to levels of reserves conditional on their expected values given the regressors.

  20. Bootstrapped standard errors with 1000 replications are used (see Rogers (1992)). Reported interquantile regressions, i.e., regressions of the difference in quantiles, test the differences of the coefficients at different quantiles where estimated standard errors are also obtained with bootstrapping.

  21. Excluding nominal exchange rate volatility or differentiating between hard and soft pegs makes no difference to the statistical insignificance of the pegged exchange rate regime dummy.

  22. The coefficient is statistically different across periods. Tests for significant difference of the coefficient across periods give the following results (F test, p value) for the following periods: 1980–1997 vs. 1998–2004 (8.22, 0.01); 1980–1997 vs. 2005–2010 (12.82, 0.00); 1998–2004 vs. 2005–2010 (15.13, 0.00).

  23. The Chinn–Ito capital account openness index, which ranges from −1 (fully closed) to +1 (fully open), averages −0.7 during the 1980s, −0.1 in the 1990s, and +0.7 in the 2000s for our sample of EMEs.

  24. Tests for groups’ joint significance across periods suggest that the joined proxies for current account, capital account, and mercantilist motives are statistically different across periods. Tests’ p values for broad money, exchange rate undervaluation, and imports, respectively, across the various periods are 1980–1997 vs. 1998–2004 (0.00, 0.00, 0.01), 1980–1997 vs. 2005–2010 (0.00, 0.00, 0.00), and 1998–2004 vs. 2005–2010 (0.00, 0.00, 0.00).

  25. This is consistent with the findings of Obstfeld and others (2010) that many EMEs now hold reserves equivalent to more than 100 percent of short-term debt. In our sample, average reserves for the third and fourth quartiles of the reserves distribution is 14 and 26 percent of GDP, respectively, whereas short-term debt for these two groups is 14 and 17 percent of GDP. Thus, above-median reserve holders have more than 100 percent coverage of short-term debt, and short-term debt is not a significant determinant of their reserve holdings.

  26. High-reserve holders have both larger banking system liabilities (BSL) and short-term debt (STD) than low-reserve holders, but the ratio of BSL to STD is around 4 for them compared to 3 for low-reserve holders.

  27. The coefficient declines along the reserves distribution, which suggests that the results are not being driven by endogeneity bias. If endogeneity of undervaluation were responsible for the results, then we would expect a larger estimate for high-reserve holders, who have both a higher level, and faster accumulation of reserves.

  28. Undervaluation for low-reserve holders is typically in the context of declining reserves. On average, reserves declined by about 2 percent of GDP for low-reserve holders with undervalued exchange rates, whereas undervaluation for high-reserve holders is associated with increasing reserves of about 15 percent of GDP.

  29. Figure 5 is based on the full model (i.e., Table 2, cols [2–5]). For graphical convenience, the effects of the scale variables (population and per capita income) and of the exchange rate regime are suppressed from both the fitted and the “actual” change in reserves. The sample of countries changes due to data availability, but none of the results depends on this—holding the sample constant does not alter the conclusions.

  30. In part, this may be because countries experiencing debt servicing difficulties compressed imports. But all three components—imports level, export volatility, and trading partner growth volatility—decrease (cumulatively) during the 1980s, generating a commensurate decline in reserve holdings against these shocks.

  31. We estimate a bilateral gravity model for exports (see Qureshi and Tsangarides (2010)) and aggregate predicted exports for each country. Excess exports is the difference between the actual and this predicted exports.

  32. In some cases, the precautionary and mercantilist motives may coincide. For example, a country may keep its currency undervalued and at the same time subsidize credit for domestic firms in the tradable sector, or impose capital controls to restrict capital inflows and, therefore, undervalue its currency. Empirically, we do not find strong evidence of interactions between the mercantilist and precautionary motives such as the exchange rate regime, current account motives (imports to GDP, export volatility, and partner growth volatility), and the capital account motives (capital account openness, broad money, and short-term debt). One exception is that for the period 2005–2010, the interaction of undervaluation with broad money to GDP is statistically significant at the 10 percent level; one hypothesis is that mercantilist motives may induce the government to maintain an overvalued currency and also subsidize credit to the export sector, which often entails a higher M2/GDP ratio, in turn requiring higher precautionary reserves (we are grateful to an anonymous referee for this suggestion).

  33. One exception is Obstfeld and others (2010). They investigate the possibility of reverse causality operating through high-powered money where the broad money supply M2 and reserves may simultaneously rise in response to a rise in the monetary base M0.

  34. Fixed effects are incorporated by removing annual and country means from the dependent and independent variables.

  35. About 35 percent of our observations are undervalued (45, aligned). About half of our counties are undervalued for at least 5 years and about 15 percent for at least 10 years.

  36. We thank one anonymous referee for suggesting this motive. Machlup (1966) distinguishes between the need and demand for monetary reserves using an analogy between increasing the stock of outfits in a wardrobe and the monetary authorities’ desire to accumulate more and more reserves. This gives rise to the “peer-effects” hypothesis, suggesting that economies continue to add to their existing stock of reserves in order to “keep up with the Joneses.”

  37. The rivalry motive is positive and statistically significant across all quantiles (results available upon request). For two of the proxies, the effect is also marginally more important for low quantiles of reserve holders.

  38. The average contribution of the rivalry motive is always less than that of the mercantilist motive. The rivalry motive reached its peak in the late 1990s and its contribution has been declining since, to less than 2/3 of the contribution of the mercantilist motive (with the sole exception of 2009).

  39. For example, the specification investigating the effect of openness above the median adds to the baseline specification a dummy that is 1 if openness is above the median (and zero otherwise) and interactions of the dummy variable with all determinants. Restricting the sample to above the median or 75th percentile is not meaningful for the quantile regression analysis so we only focus on the OLS results.

  40. For observations above the 50th percentile, we find some weak evidence that undervaluation may be of greater importance for manufacturing than commodity exporters (statistically significant at the 10 percent level).

  41. Asia includes China, Korea, Indonesia, Malaysia, Philippines, Thailand, and Vietnam, while LAC includes Argentina, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Mexico, Panama, Peru, Uruguay, and Venezuela.

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Authors and Affiliations

  1. Research Department, IMF, Suite 9-612G, 700 19th Street, N.W., Washington, DC, 20431, United States

    Atish R. Ghosh, Jonathan D. Ostry & Charalambos G. Tsangarides

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  1. Atish R. Ghosh
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  2. Jonathan D. Ostry
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  3. Charalambos G. Tsangarides
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Correspondence to Atish R. Ghosh.

Additional information

*We thank Olivier Blanchard, Michael Bleaney, Roberto Rigobón, Cédric Tille, Jun Kim, Fund colleagues, and seminar participants at the 16th Annual LACEA Meeting, the 18th International Panel Data Conference, Banque de France, the 2012 Australasian Meeting of the Econometric Society, the 2012 Joint BIS/World Bank Public Investors Conference, the Geneva Graduate Institute of International Studies, and the Special Session on Global Imbalances and External Adjustment at the 2014 Royal Economic Society Meetings for useful comments and suggestions, and Edith Laget for excellent research assistance. The views expressed in this paper are those of the authors and do not necessarily represent those of the IMF or IMF policy. Ghosh (corresponding author): Research Department, IMF, Suite 9-612G, 700 19th Street, N.W., Washington D.C. 20431 (email: aghosh@imf.org); Ostry: Research Department, IMF, Suite 10-700F, 700 19th Street, N.W., Washington D.C. 20431 (email: jostry@imf.org); Tsangarides: Research Department, IMF, Suite 9-612B, 700 19th Street, N.W., Washington D.C. 20431 (email: ctsangarides@imf.org).

Appendices

Appendix A: Reserve Accumulation in Advanced Economies Vs. Emerging Economies

The massive rise in reserve holdings over the past 30 years has been almost entirely an EM phenomenon. Many AEs are reserve-currency issuers and do not hold reserves at all (or only as a historical legacy). Relatedly, the reasons why AEs hold or accumulate reserves are usually quite different from the motives driving EM reserve holdings. Therefore, there are both economic and econometric reasons why the EM and AE samples should not be pooled.

To demonstrate this, we estimate our baseline model for AEs and compare results with those for EMs (we omit short-term debt, which is not readily available for AEs). As expected, results shown in Table A1 make the case empirically that the AEs are different from the EMs. In particular, the AE coefficients are nearly always insignificant or quite different from the EM sample. This inherent heterogeneity explains why separate models have been proposed for studying AEs (e.g., Ghosh and Ostry (1997)) and EMs (e.g., Jeanne and Rancière (2006), Obstfeld and others 2010)) (Figure A1).

Figure A1
figure 8

Source: Authors’ calculations.

Reserves Held by Advanced and Emerging Economies, 1980–2010 (in percent of GDP, 3-year moving average)

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Table A1 Determinants of Reserve Demand, Advanced and EME Samples
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Appendix B: Data and Summary Statistics

Table B1 Countries in the sample and variable definitions and sources
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Table B2 Summary Statistics
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Table B3 Summary Statistics for Misalignment Proxy
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Ghosh, A.R., Ostry, J.D. & Tsangarides, C.G. Shifting Motives: Explaining the Buildup in Official Reserves in Emerging Markets Since the 1980s. IMF Econ Rev 65, 308–364 (2017). https://doi.org/10.1057/s41308-016-0003-3

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