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Optimization in a Simulation Setting: Use of Function Approximation in Debt Strategy Analysis

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  • David Jamieson Bolder
  • Tiago Rubin

Abstract

The stochastic simulation model suggested by Bolder (2003) for the analysis of the federal government's debt-management strategy provides a wide variety of useful information. It does not, however, assist in determining an optimal debt-management strategy for the government in its current form. Including optimization in the debt-strategy model would be useful, since it could substantially broaden the range of policy questions that can be addressed. Finding such an optimal strategy is nonetheless complicated by two challenges. First, performing optimization with traditional techniques in a simulation setting is computationally intractable. Second, it is necessary to define precisely what one means by an "optimal" debt strategy. The authors detail a possible approach for addressing these two challenges. They address the first challenge by approximating the numerically computed objective function using a function-approximation technique. They consider the use of ordinary least squares, kernel regression, multivariate adaptive regression splines, and projection-pursuit regressions as approximation algorithms. The second challenge is addressed by proposing a wide range of possible government objective functions and examining them in the context of an illustrative example. The authors' view is that the approach permits debt and fiscal managers to address a number of policy questions that could not be fully addressed with the current stochastic simulation engine.

Suggested Citation

  • David Jamieson Bolder & Tiago Rubin, 2007. "Optimization in a Simulation Setting: Use of Function Approximation in Debt Strategy Analysis," Staff Working Papers 07-13, Bank of Canada.
  • Handle: RePEc:bca:bocawp:07-13
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. repec:eee:eneeco:v:71:y:2018:i:c:p:273-281 is not listed on IDEAS
    2. Andrea Consiglio & Stavros Zenios, 2015. "Risk profiles for re-profiling the sovereign debt of crisis countries," Journal of Risk Finance, Emerald Group Publishing, vol. 16(1), pages 2-26, January.
    3. Johannes Holler, 2013. "Funding Strategies of Sovereign Debt Management: A Risk Focus," Monetary Policy & the Economy, Oesterreichische Nationalbank (Austrian Central Bank), issue 2, pages 51-74.
    4. Balibek, Emre & Köksalan, Murat, 2010. "A multi-objective multi-period stochastic programming model for public debt management," European Journal of Operational Research, Elsevier, vol. 205(1), pages 205-217, August.
    5. Serhat Yuksel & Sinemis Zengin, 2017. "Influencing Factors of Net Interest Margin in Turkish Banking Sector," International Journal of Economics and Financial Issues, Econjournals, vol. 7(1), pages 178-191.
    6. David Jamieson Bolder & Yuliya Romanyuk, 2008. "Combining Canadian Interest-Rate Forecasts," Staff Working Papers 08-34, Bank of Canada.
    7. Udaibir S. Das & Yinqiu Lu & Michael G. Papaioannou & Iva Petrova, 2013. "Sovereign Risk and Asset and Liability Management—Conceptual Issues," Journal of Reviews on Global Economics, Lifescience Global, vol. 2, pages 330-355.
    8. David Jamieson Bolder & Simon Deeley, 2011. "The Canadian Debt-Strategy Model: An Overview of the Principal Elements," Discussion Papers 11-3, Bank of Canada.
    9. K. Batu Tunay, 2010. "Banking Crises and Early Warning Systems: A Model Suggestion for Turkish Banking Sector," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, vol. 4(1), pages 9-46.
    10. Consiglio Andrea & Zenios Stavros A., 2015. "Risk Management Optimization for Sovereign Debt Restructuring," Journal of Globalization and Development, De Gruyter, vol. 6(2), pages 181-213, December.
    11. repec:gam:jsusta:v:10:y:2018:i:1:p:132-:d:125900 is not listed on IDEAS

    More about this item

    Keywords

    Debt management; Econometric and statistical methods; Fiscal policy; Financial markets;

    JEL classification:

    • C0 - Mathematical and Quantitative Methods - - General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
    • E6 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook
    • G1 - Financial Economics - - General Financial Markets
    • H63 - Public Economics - - National Budget, Deficit, and Debt - - - Debt; Debt Management; Sovereign Debt

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