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© 2022 International Monetary Fund
WP/22/230
IMF Working Paper
Statistics Department
Improving Sovereign Financing Conditions Through Data Transparency*
Authorized for distribution by Patrizia Tumbarello November 2022
IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.
ABSTRACT: Does it pay off to be transparent and, if so, can the benefits of transparency be measured? This paper provides an affirmative answer to both questions, supported by novel evidence on the link between transparency through dissemination of economic data and sovereign bond spreads. It explores changes in sovereign financing conditions when countries join the IMF Data Standards Initiatives—a multilateral framework that promotes data transparency as a global public good. The results from event studies and local projection models show a significant decrease in spreads following the adoption of the standards. In addition, countries with relatively weaker governance benefit the most from signaling their effort toward strengthening transparency.
RECOMMENDED CITATION: Gonzalez-Garcia, J. (2022), Improving Sovereign Financing Conditions Through Data Transparency, IMF Working Paper WP/22/230, Washington DC: International Monetary Fund.
| JEL Classification Numbers: | F30; G10; G20 |
| Keywords: | Data transparency; IMF Data Standards Inititatives; sovereign borrowing; EMBIG spreads; event studies; local projection methods; governance. |
| Author’s E-Mail Address: | jgonzalezgarcia@imf.org |
| JEL Classification Numbers: | F30; G10; G20 |
| Keywords: | Data transparency; IMF Data Standards Inititatives; sovereign borrowing; EMBIG spreads; event studies; local projection methods; governance. |
| Author’s E-Mail Address: | jgonzalezgarcia@imf.org |
Contents
1. Introduction
2. Empirical Analysis
2.1. Data
2.2. Event Studies
2.3. Local Projection Methods
2.4. Role of Institutional Environment
3. Conclusions
References
FIGURES
1. Countries Joining the Data Dissemination Standards Per Year
2. Event Studies Around the Date of Joining the Data Dissemination Standards
3. Cumulative Change of Sovereign Spreads after Joining Data Dissemination Standards
TABLES
1. Changes in Mean Sovereign Spreads After Joining SDDS, GDDS, and Launching NSDPs
2. Cumulative Effect of Joining Data Dissemination Standards
3. Comparison of Effects of Joining Data Dissemination Standards
4. Effects of Joining Data Dissemination Standards in Different Institutional Environments
This work has benefited from comments provided by Lusine Lusinyan and colleagues from the following IMF departments: Monetary and Capital Markets, Research, and Statistics. The usual disclaimers apply.