Chapter

Appendix III. A Model of Optimal Reserves

Author(s):
Paolo Mauro, Torbjorn Becker, Jonathan Ostry, Romain Ranciere, and Olivier Jeanne
Published Date:
April 2007
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This appendix presents background information on the Jeanne and Rancière (2006) model of a growing open economy where reserves are accumulated, at a cost, in order to reduce the frequency of sudden stops in financial flows and smooth their impact on domestic consumption. The simple version of the model presented in this study considers only the smoothing role of reserves. At the time of a sudden stop, the country’s authorities lend reserves to domestic agents whose lines of credit have been cut off by private lenders, thereby mitigating the drop in domestic consumption. The cost of holding reserves (the difference between the return on reserves and the long-term interest rate) translates into lower domestic consumption during noncrisis times. The optimal level of reserves equates the marginal costs and benefits of holding reserves. The parameters of the benchmark calibration (Table A3.1) are based on information drawn from a panel of 33 middle-income countries during 1980–2003. Defining a sudden stop as a worsening in the financial account balance by more than 5 percent of GDP, 77 sudden stops are observed during the sample period. This yields an unconditional probability of a sudden stop of 10 percent per year. The magnitude of a sudden stop is the mean size of sudden stops in the sample (11 percentage points of GDP). The output cost of a sudden stop is set equal to 6 percent of GDP (the difference in average real GDP growth between the year of the sudden stop, on the one hand, the following year and, on the other hand, the remaining years for all countries).

Table A3.1.Calibration Parameters
ParametersBaselineRange of Variation
Size of sudden stopλ = 0.11[0, 0.3]
Probability of sudden stopπ = 0.10[0, 0.25]
Output lossγ = 0.06[0, 0.2]
Potential output growthg = 0.033
Term premiumδ = 0.015[0.0025, 0.05]
Risk-free rater* = 0.05
Risk aversionσ = 2[1, 10]
Sources: IMF staff calculations. The parameters were chosen based on data from the U.S. Board of Governors of the Federal Reserve System and the IMF’s International Financial Statistics database.
Sources: IMF staff calculations. The parameters were chosen based on data from the U.S. Board of Governors of the Federal Reserve System and the IMF’s International Financial Statistics database.

The cost of holding reserves is the difference between the opportunity cost of borrowing long term and the return on reserves invested in safe, short-term liquid assets. In the benchmark calibration, this premium consists only of the term premium, set at 1.5 percent—that is, the mean difference between the yield on 10-year U.S. treasury bonds and the federal funds rate during 1987–2005. Variants of the model consider the case where the opportunity cost of holding reserves also includes the sovereign spread. The coefficient of risk aversion is allowed to vary in the 1–10 range, as is customary in existing studies on growth and business cycles. It is assumed that the authorities are benevolent and maximize the welfare of the representative domestic consumer. The risk-free rate is set at 5 percent. The potential output growth rate is set at 3.3 percent, the mean real GDP growth rate in middle-income countries during 1980–2003 excluding sudden-stop years.

To analyze the role of the parameters in determining the optimal level of reserves, the model is repeatedly simulated by letting each key parameter vary (one at a time) over a plausible range while keeping the other parameters fixed at their baseline values as in Table A3.1. For the sake of comparison, in each plot (Figure A3.1) the optimal level of reserves is presented alongside the level of reserves predicted by the Greenspan-Guidotti rule.

Figure A3.1.Optimal Level of Reserves as Function of Various Factors

Source: IMF staff calculations. See text and Jeanne and Rancière (2006).

When the size or probability of a sudden stop is sufficiently low, the optimal ratio of reserves is zero. (The costs of reserves exceed their benefits.) Optimal reserves rise near-linearly as the size of the sudden stop increases (beyond 2.5 percent of GDP), and non-linearly as the probability of a sudden stop increases. For some starting values of the sudden-stop probability, a relatively modest rise can imply a substantial adjustment in the optimal ratio of reserves to GDP: for example, an increase in the annual probability from 5 to 10 percent leads optimal reserves to rise from 4 to 10 percentage points of GDP. Changes in the opportunity cost of holding reserves (regardless of whether they stem from a change in the term premium or, when included, the sovereign spread) have a substantial impact on optimal reserve levels. For example, an increase in the opportunity cost by 1.5 percentage points above its baseline value reduces the optimal reserve ratio by more than 6 percentage points of GDP. Finally, the impact of changes in the degree of risk aversion on the optimal level of reserves is major when starting from relatively low values of the coefficient, but limited when starting from higher values.

Determinants of Vulnerability to Sudden Stops

The probability of a sudden stop can be estimated as a function of a country’s economic fundamentals by running a probit estimation of the probability of sudden stops in a sample of 33 middle-income countries over 1980–2003. The explanatory variables are selected using a general-to-specific approach—that is, by initially considering a large set of potential explanatory variables and iteratively eliminating those that are statistically less significant to arrive at the preferred specification reported in Table A3.2. The complete set of variables considered is listed in Jeanne and Rancière (2006). All explanatory variables are averages of the first and second lags, and are thus predetermined with respect to the sudden stop. The results are robust to the inclusion of time effects and fixed effects.

Table A3.2.Probit Estimation of Probability of Sudden Stop
(1)(2)(3)(4)(5)
Real effective exchange rate deviation from HP trend1.521.521.851.78
(3.1)***(2.9)***(3.4)***(3.1)***
GDP growth–1.25–1.56–1.42–1.87
(1.6)*(1.7)*(1.7)*(1.8)*
Public debt/GDP0.810.780.721.020.85
(3.3)***(3.5)***(2.6)***(2.4)**(1.6)
Ratio of foreign liabilities to money in banking sector0.230.200.220.220.20
(3.0)***(2.7)***(2.8)***(2.2)**(1.9)*
Financial openness as (|gross inflows|)/GDP9.1110.049.8211.15
(5.7)***(5.5)***(4.9)***(4.9)***
Dummy for fixed exchange rate regime0.29
(1.8)*
Constant–2.31–1.80–2.41
(12.6)***(12.9)***(5.3)***
Observations707690707537537
Pseudo R20.140.060.17
Time effectsNoNoYesNoYes
Fixed effectsNoNoNoYesYes
Sources: IMF, International Financial Statistics database; World Bank, Global Development Finance database; and IMF staff calculations.Note: One asterisk (*) denotes significance at 10 percent; two asterisks (**) denote significance at 5 percent; and three asterisks (***) denote significance at 1 percent. Absolute values of z statistics are in parentheses. All explanatory variables are taken as averages of first and second lags. The fixed exchange rate regime is a “fix” or “peg” in the Reinhart and Rogoff (2004) classification.
Sources: IMF, International Financial Statistics database; World Bank, Global Development Finance database; and IMF staff calculations.Note: One asterisk (*) denotes significance at 10 percent; two asterisks (**) denote significance at 5 percent; and three asterisks (***) denote significance at 1 percent. Absolute values of z statistics are in parentheses. All explanatory variables are taken as averages of first and second lags. The fixed exchange rate regime is a “fix” or “peg” in the Reinhart and Rogoff (2004) classification.

The probability of a sudden stop decreases with the pre-crisis growth performance and increases with the currency’s real appreciation, the ratio of public debt to GDP, openness to financial flows, and the ratio of foreign liabilities to money in the banking sector.32 The last two determinants suggest that the vulnerability to sudden stops rises with the degree of international financial integration.33 A fixed exchange rate regime is associated with a higher probability of a sudden stop, though only if financial openness and exchange rate overvaluation are omitted from the regression.

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32The ratio of foreign liabilities of the financial sector to money in the banking sector (International Financial Statistics (IFS) line 26C/line 34) is a reasonable proxy for, though not a direct measure of, the extent of mismatch in the currency denomination of assets and liabilities in countries’ balance sheets. It is available for almost all countries from 1970 onward.
33We find that trade openness does not significantly affect the probability of a sudden stop when financial openness is included as an explanatory variable.

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221. Deflation: Determinants, Risks, and Policy Options, by Manmohan S. Kumar. 2003.

220. Effects of Financial Globalization on Developing Countries: Some Empirical Evidence, by Eswar S. Prasad, Kenneth Rogoff, Shang-Jin Wei, and Ayhan Kose. 2003.

219. Economic Policy in a Highly Dollarized Economy: The Case of Cambodia, by Mario de Zamaroczy and Sopanha Sa. 2003.

218. Fiscal Vulnerability and Financial Crises in Emerging Market Economies, by Richard Hemming, Michael Kell, and Axel Schimmelpfennig. 2003.

217. Managing Financial Crises: Recent Experience and Lessons for Latin America, edited by Charles Collyns and G. Russell Kincaid. 2003.

216. Is the PRGF Living Up to Expectations? An Assessment of Program Design, by Sanjeev Gupta, Mark Plant, Benedict Clements, Thomas Dorsey, Emanuele Baldacci, Gabriela Inchauste, Shamsuddin Tareq, and Nita Thacker. 2002.

215. Improving Large Taxpayers’ Compliance: A Review of Country Experience, by Katherine Baer. 2002.

214. Advanced Country Experiences with Capital Account Liberalization, by Age Bakker and Bryan Chapple. 2002.

213. The Baltic Countries: Medium-Term Fiscal Issues Related to EU and NATO Accession, by Johannes Mueller, Christian Beddies, Robert Burgess, Vitali Kramarenko, and Joannes Mongardini. 2002.

212. Financial Soundness Indicators: Analytical Aspects and Country Practices, by V. Sundararajan, Charles Enoch, Armida San José, Paul Hilbers, Russell Krueger, Marina Moretti, and Graham Slack. 2002.

211. Capital Account Liberalization and Financial Sector Stability, by a staff team led by Shogo Ishii and Karl Habermeier. 2002.

210. IMF-Supported Programs in Capital Account Crises, by Atish Ghosh, Timothy Lane, Marianne Schulze-Ghattas, Aleš Bulĺř, Javier Hamann, and Alex Mourmouras. 2002.

209. Methodology for Current Account and Exchange Rate Assessments, by Peter Isard, Hamid Faruqee, G. Russell Kincaid, and Martin Fetherston. 2001.

208. Yemen in the 1990s: From Unification to Economic Reform, by Klaus Enders, Sherwyn Williams, Nada Choueiri, Yuri Sobolev, and Jan Walliser. 2001.

Note: For information on the titles and availability of Occasional Papers not listed, please consult the IMF’s Publications Catalog or contact IMF Publication Services.

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