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How much should I hold? : Reserve adequacy in emerging markets and small islands / prepared by Nkunde Mwase.

By: Contributor(s): Material type: TextTextSeries: IMF working paper ; WP/12/205.Publication details: [Washington, D.C.] : International Monetary Fund, ©2012.Description: 1 online resource (44 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 1475529406
  • 9781475529401
  • 1475505558
  • 9781475505559
  • 1475581882
  • 9781475581881
  • 1475553676
  • 9781475553673
Other title:
  • Reserve adequacy in emerging markets and small islands
Subject(s): Additional physical formats: No title; No titleDDC classification:
  • 332.152 23
LOC classification:
  • HG3881.5.I58 W67 No. 12/205eb
Online resources:
Contents:
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.
Summary: 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 null 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.
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Title from PDF title page (IMF Web site, viewed August 14, 2012).

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 null 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.

Includes bibliographical references.

"Strategy Policy and Review Department."

"August 2012."

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.

English.

WorldCat record variable field(s) change: 650

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