We use the US data gathered by Reinhart and Rogoff (2010) to assess whether debt affects economic growth differently at different phases of the business cycle. In order to do that, we extend the threshold regression model of Chudik et al. (2017) and propose a new threshold quantile ARDL regression model. Our results show that to stimulate growth policy makers can manage the debt/GDP percentage according to how well the economy is doing. The estimated quantile thresholds (range 31–53 per cent) are larger than the one found by Lee et al. (2017) using median regressions, but still (much) smaller than the 90 per cent of Reinhart and Rogoff. In particular, when the US economy observes growth rates above their median value, that is when a smaller debt-to-GDP threshold affects the performance of the economy. In a steady-state situation, in general, regardless of the position of the business cycle and whether the debt-to-GDP ratio is below or above its threshold effect, less debt as a percentage of GDP boosts the US growth. Remarkably, this effect was always greater before than after World War II. Moreover, the most recent decades have witnessed the negative (positive) effect of more (less) debt when the economy had growth rates at their first quartile (median and third quartile). That is, the US policy makers are advised to reduce the debt-to-GDP ratio during expansions to promote growth.

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Business cycle,Government debt,Growth,Threshold quantile regression

• Economics and Business - Social Sciences