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Dynamics between the budget deficit and the government debt in the United States: a nonlinear analysis

  • Haydory Akbar Ahmed EMAIL logo

Abstract

This paper empirically investigates the dynamics between budget deficit and government debt in the U.S. using two different measures of the budget deficit: the current budget deficit and cyclically-adjusted budget deficit. A threshold Vector autoregression (VAR) model is estimated to explore the dynamics in different regimes using quarterly data from 1947:Q1 to 2017:Q3. The specification test rejects a linear VAR model against the threshold VAR. When we use the current budget deficit, regime 1 resemble governments prioritize minimizing budget deficit and debt, whereas, regime 2 resemble otherwise. When we use the cyclically adjusted budget deficit, regime 1 resemble economic expansions, whereas, regime 2 resemble recessions. The impulse responses show evidence of asymmetry and counter-cyclicality. The impulse responses also indicate that an increase in the debt dictate the government’s response towards minimizing the budget deficit and tend to prioritize budget deficit less when the economy expands.

JEL Codes: E31; E32; E37; E61; E63

Corresponding author: Haydory Akbar Ahmed, Missouri State University, Department of Economics, 901 S National Avenue, Springfield, 65897, MO, USA, E-mail:

  1. Author contribution: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: None declared.

  3. Employment or leadership: None declared.

  4. Honorarium: None declared.

  5. Conflict of interest: The authors declare no conflicts of interest regarding this article.

Appendix A. Graph for threshold estimation

Figure A.13: Threshold for the VAR.
Figure A.13:

Threshold for the VAR.

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Supplementary Material

The online version of this article offers supplementary material (DOI: https://doi.org/10.1515/snde-2018-0087).

Received: 2018-08-24
Accepted: 2020-04-18
Published Online: 2020-06-03

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