Kernel-based time-varying IV estimation: handle with care

Giraitis et al. (J Econom 224(2):394-415, 2021) proposed a kernel-based time-varying coefficients IV estimator. By using entirely different code, we broadly replicate the simulation results and the empirical application on the Phillips curve, but we note that a possible oversight might have affected some of the reported results. Further, we extend the results by using a different sample and a wider choice of smoothing kernels, including data-based ones; we find that the estimator is remarkably robust across a wide range of smoothing choices, but the effect of outliers may be less obvious than expected.

Automated summary

Giraitis et al. (J Econom 224(2):394-415, 2021) proposed a kernel-based time-varying coefficients IV estimator. We replicate the simulation results and empirical application on the Phillips curve using different code, and find that they are robust. However, we also identify a possible oversight that may have affected some of the reported results. Our findings show that the estimator is remarkably robust across a wide range of smoothing choices, but the impact of outliers may not be as evident as expected.