How much should I hold? Reserve Adequacy in Emerging Markets and Small Islands / / Nkunde Mwase

• Record Nr.: UNINA9910971233503321
• Autore: Mwase Nkunde
• Pubbl/distr/stampa: Washington, D.C. : , : International Monetary Fund, , 2012
• ISBN: 9781475553673; 1475553676; 9781475581881; 1475581882
• Edizione: [1st ed.]
• Descrizione fisica: 1 online resource (45 p.)
• Collana: IMF Working Papers; IMF working paper ; ; WP/12/205
• Disciplina: 332.1/52
• Soggetti: Reserves (Accounting); Investments - Developing countries; Balance of payments; Currency; Current Account Adjustment; Current account; Economic & financial crises & disasters; Exchange rate arrangements; Exchange rate flexibility; Exports and Imports; Exports; Financial Crises; Financial crises; Financial Risk Management; Foreign Exchange; Foreign exchange; International economics; International Finance Forecasting and Simulation; International trade; Monetary base; Monetary economics; Monetary Policy, Central Banking, and the Supply of Money and Credit: General; Money and Monetary Policy; Money supply; Money; Open Economy Macroeconomics; Short-term Capital Movements; Trade: General; Dominican Republic
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references.
• Nota di contenuto: Cover; Abstract; Contents; I. Introduction; II. What Determines Reserve Holdings?; A. Data and Modeling Strategy; B. Empirical Results from Standard Panel OLS and Fixed Effects; C. Empirical Results from Quantile Regressions; III. A New Metric For Small Islands; A. Developing A Metric; B. Empirical Analysis to Determine Thresholds For the Metric; C. Estimation Results; IV. Conclusion; References; APPENDIX TABLES; 1. Country List; 2. Description of Variables; 3. SIs and EMs: Reserve Demand Regressions; 4. Full Sample: OLS and Quantile Regression Results; 5. SIs: OLS and Quantile Regression Results6. EM: OLS and Quantile Regression Results; 7. Full Sample: Inter-quantile Regression Results; 8. SIs: Inter-quantile Regression Results; 9. EM: Inter-quantile Regression Results; 10. SIs: Episodes of Exchange Market Pressure; 11. Comparison on Various Reserve Adequacy Metrics: Logit Regression; FIGURES; 1. EMs and SIs: Traditional Metrics, 2000-2010; 2. Sample Mean Average Actual and Predicted Reserves, 2007-2010; 3. Full Sample: Comparison of OLS and Quantile Regression Coefficient Estimate; 4. SIs: Comparison of OLS and Quantile Regression Coefficient Estimates5. EM: Comparison of OLS and Quantile Regression Coefficient Estimates; 6. EM and SIs: Concessional and Multilateral Debt, 1999-2009; 7. SIs: Exchange Market Pressure Crisis Episodes; 8. SIs: Exchange Market Pressure Crisis Episodes Triggers; 9. The Dominican Republic and Grenada: Balance of Payments Flows In Crisis Events; 10. Distribution of Export, Broad Money, and Short-Term Debt; 11. New Metric vs. Maximum of Traditional Metrics; 12. EMP Event Probability; 13. Reserves Against Risk-Weighted Metric
• Sommario/riassunto: This paper investigates the drivers of reserves in emerging markets (EMs) and small island (SIs) and develops an operational metric for estimating reserves in SIs taking into account their unique characteristics. It uses quantile regression techniques to allow the estimated factors driving reserves holdings to vary along the reserves’ holding distribution and tests for equality among the slope coefficients of the various quantile regressions and the overall models. F-tests comparing the inter-quantile differences could not reject the that the models for the different quantiles of SIs reserve distribution were similar but this was rejected for EMs distribution suggesting that models explaining drivers of reserve holdings should take into account the country’s reserve holdings. Empirical analysis suggests that the metric performs better than existing metrics in reducing crisis probabilities in SIs.