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Does Uncertainty Matter for the Fiscal Consolidation and Investment Nexus?

Author

Listed:
  • Bournakis Ioannis

    (84289 SKEMA Business School, Lille, France)

  • Ramírez-Rondán Nelson R.

    (CEMLA, 61613, Mexico City, Mexico)

Abstract

The aim of this research paper is to investigate whether there are non-linearities in the relationship between fiscal consolidation and investment. To achieve this, we take into account the overall state of the economy, as represented by the level of uncertainty. We analyzed a sample of 27 OECD countries from 1996 to 2019 and identified two different regimes of low and high uncertainty. We found that the relationship between fiscal policy and investment is significantly different in these two regimes. In the low uncertainty regime, fiscal tightening has no significant effect on investment. In contrast, in the high uncertainty regime, fiscal tightening has a negative impact on investment, which is three times larger than in the low uncertainty regime. Our results are robust, and have been confirmed through a range of sensitivity tests.

Suggested Citation

  • Bournakis Ioannis & Ramírez-Rondán Nelson R., 2024. "Does Uncertainty Matter for the Fiscal Consolidation and Investment Nexus?," The B.E. Journal of Macroeconomics, De Gruyter, vol. 24(1), pages 529-559, January.
    • Handle: RePEc:bpj:bejmac:v:24:y:2024:i:1:p:529-559:n:7
    DOI: 10.1515/bejm-2023-0059
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    More about this item

    Keywords

    fiscal policy; real sector; threshold model; panel data;
    All these keywords.

    JEL classification:

    • E62 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Fiscal Policy; Modern Monetary Theory
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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