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Debt ceiling and fiscal sustainability in Brazil: A quantile autoregression approach

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  • Lima, Luiz Renato
  • Gaglianone, Wagner Piazza
  • Sampaio, Raquel M.B.

Abstract

In this paper we investigate fiscal sustainability by using a quantile autoregression (QAR) model. We propose a novel methodology to separate periods of nonstationarity from stationary ones, allowing us to identify various trajectories of public debt that are compatible with fiscal sustainability. We use such trajectories to construct a debt ceiling, that is, the largest value of public debt that does not jeopardize long-run fiscal sustainability. We make an out-of-sample forecast of such a ceiling and show how it could be used by Policy makers interested in keeping the public debt on a sustainable path. We illustrate the applicability of our results using Brazilian data.

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  • Lima, Luiz Renato & Gaglianone, Wagner Piazza & Sampaio, Raquel M.B., 2008. "Debt ceiling and fiscal sustainability in Brazil: A quantile autoregression approach," Journal of Development Economics, Elsevier, vol. 86(2), pages 313-335, June.
    • Handle: RePEc:eee:deveco:v:86:y:2008:i:2:p:313-335
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    2. Gaglianone, Wagner Piazza & Guillén, Osmani Teixeira de Carvalho & Figueiredo, Francisco Marcos Rodrigues, 2018. "Estimating inflation persistence by quantile autoregression with quantile-specific unit roots," Economic Modelling, Elsevier, vol. 73(C), pages 407-430.
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    5. Wagner Piazza Gaglianone & Osmani Teixeira de Carvalho Guillén & Francisco Marcos Rodrigues Figueiredo, 2015. "Local Unit Root and Inflationary Inertia in Brazil," Working Papers Series 406, Central Bank of Brazil, Research Department.
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    16. Tilak Abeysinghe & Ananda Jayawickrama, 2013. "A segmented trend model to assess fiscal sustainability: The US experience 1929–2009," Empirical Economics, Springer, vol. 44(3), pages 1129-1141, June.
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    19. Boengiu, Tudor & Morar Triandafil, Cristina & Morar Triandafil, Adrian, 2011. "Debt Ceiling and External Debt Sustainability in Romania: A Quantile Autoregression Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 15-29, December.

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