Public debt and economic growth conundrum: nonlinearity and inter-temporal relationship
The influential paper by Reinhart and Rogoff (Reinhart, C. M., and K. S. Rogoff. 2010. “Growth in a Time of Debt.” 100: 573–578.) has triggered a debate about the effects of the public debt on GDP growth. They argue that a debt-to-GDP ratio of over 90 percent has a deleterious effect on long-run eco...
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Veröffentlicht in: | Studies in nonlinear dynamics and econometrics 2018-02, Vol.22 (1), p.1-20 |
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Zusammenfassung: | The influential paper by Reinhart and Rogoff (Reinhart, C. M., and K. S. Rogoff. 2010. “Growth in a Time of Debt.”
100: 573–578.) has triggered a debate about the effects of the public debt on GDP growth. They argue that a debt-to-GDP ratio of over 90 percent has a deleterious effect on long-run economic growth. In this paper, we examine the inter-temporal relationship between public debt and GDP growth rates. We examine debt-to-GDP thresholds in nonlinear panel models, using various econometric strategies, methodologies, and data samples. We also evaluate confidence intervals around the estimated thresholds to determine the accuracy of estimated thresholds. Our results demonstrate that in the majority of estimated models, threshold values are not uniquely defined and the estimated coefficients are insignificant in most model specifications, as in Enders, Falk, and Siklos (Enders, W., B. L. Falk, and P. Siklos. 2007. “A Threshold Model of Real US GDP and the Problem of Constructing Confidence Intervals in TAR Models.”
11: 1322.). Next, we examine the inter-temporal relationship between the public debt and economic growth using structural panel data models as well as reduced form panel VAR models. In contrast to the standard presumption in the literature, we find that the inter-temporal effect of economic growth on the public debt is strong, but the effect of the public debt on economic growth is weak. We find similar results in sub-samples that include countries where the public debt is over 90 percent of GDP. |
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ISSN: | 1081-1826 1558-3708 1558-3708 |
DOI: | 10.1515/snde-2016-0086 |