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Sovereign debt portfolios are affected by financial and economic factors that are themselves deeply uncertain. Building on methodological developments for policy making under deep uncertainty, this dissertation examines and demonstrates how the Robust Decision Making (RDM) methodology could be applied to the problem of selecting the government's debt portfolio. Using a large set of non-probabilistic simulations coupled with data mining tools, the analysis identifies and characterizes bond issuance strategies that appear to perform well across a large set of possible assumptions and scenarios. This approach introduces a new framework for assessing funding strategies based on varying assumptions regarding the government's liquidity buffer. This proof-of-principle analysis illustrates possible improvements to debt management practices, both in government and in the private sector.
Table of Contents
Chapter One
Introduction and Background
Chapter Two
Existing Approaches to Sovereign Debt Management
Chapter Three
Incorporating Robustness into Debt Management Practices
Chapter Four
The Analysis
Chapter Five
Summary and Policy Implications
Appendix One
Examples of Sovereign Debt Modeling Efforts
Appendix Two
Model Description
Appendix Three
Additional Results of the Steady State Analysis
Appendix Four
Analysis using Median Regret and Maximum Value
Appendix Five
Additional Figures
Research conducted by
This document was submitted as a dissertation in September 2014 in partial fulfillment of the requirements of the doctoral degree in public policy analysis at the Pardee RAND Graduate School. The faculty committee that supervised and approved the dissertation consisted of Steven Popper (Chair), Robert Lempert, and Zvi Wiener.
This publication is part of the RAND Corporation Dissertation series. Pardee RAND dissertations are produced by graduate fellows of the Pardee RAND Graduate School, the world's leading producer of Ph.D.'s in policy analysis. The dissertations are supervised, reviewed, and approved by a Pardee RAND faculty committee overseeing each dissertation.
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