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Dooyeon Cho
;
Seunghwa Rho

reassessing growth vulnerability (replication data)

This paper replicates the results of Adrian et al. (2019) that GDP growth volatility is mainly driven by the lower quantiles of the distribution which is predicted by the financial condition. It extends their study by estimating the model with the IVX-QR estimator of Lee (2016) and double weighted estimator of Cai et al. (2022) considering that the financial condition index is highly serially correlated. Both models are estimated with the smoothed estimating equation approach of Kaplan and Sun (2017). The results show that the findings of Adrian et al. (2019) are robust to possible bias due to the existence of persistent predictors. The out-of-sample forecasting exercises suggest that methods that are robust to the existence of persistent predictors can improve forecasting performance at the lower quantiles of the GDP growth distribution.

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Cho, Dooyeon; Rho, Seunghwa (2023): Reassessing growth vulnerability (replication data). Version: 1. Journal of Applied Econometrics. Dataset. http://dx.doi.org/10.15456/jae.2023175.1023353913

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