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Debt and growth: Historical evidence

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  • Breuer, Christian
  • Colombier, Carsten
Abstract
In this present paper, we examine the relationship between public debt and economic growth in a large historical panel dataset of 17 OECD economics over the period from 1870 to 2016. In contrast, the relevant literature focuses on the postWW-II period. Several empirical studies provide evidence in support of the 'conventional view' that public debt is adversely associated with economic growth. We show that the relationship between government debt and per-capita GDP growth is neither statistically significant and robust nor unambiguous regarding the sign. While our baseline regressions support the 'conventional view', particularly in the aftermath of World War II, these results are not robust to alternative specifications. This holds for a linear as well as a non-linear relationship between public debt and economic growth. Our outcome suggests that politicians should exercise great caution in using empirical studies on the debt-growth nexus as a guidance for fiscal policy and that further in-depth analyses are needed.

Suggested Citation

  • Breuer, Christian & Colombier, Carsten, 2020. "Debt and growth: Historical evidence," FiFo Discussion Papers - Finanzwissenschaftliche Diskussionsbeiträge 20-04, University of Cologne, FiFo Institute for Public Economics.
    • Handle: RePEc:zbw:uoccpe:2004
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    More about this item

    Keywords

    Government debt; economic growth; historical dataset; panel regressions; robustness analysis; Staatsschulden; Wirtschaftswachstum; historischer Datensatz; Panelregressionen; Sensitivitätsanalyse;
    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
    • H63 - Public Economics - - National Budget, Deficit, and Debt - - - Debt; Debt Management; Sovereign Debt
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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