A major challenge for proxy vector autoregressive analysis is the construction of a suitable external instrument variable or proxy for identifying a shock of interest. Some authors construct sophisticated proxies that account for the dating and size of the shock while other authors consider simpler versions that use only the dating and signs of particular shocks. It is shown that such qualitative (sign-)proxies can lead to impulse response estimates of the impact effects of the shock of interest that are nearly as efficient as or even more efficient than estimators based on more sophisticated quantitative proxies that also reflect the size of the shock. Moreover, the sign-proxies tend to provide more precise impulse response estimates than an approach based merely on the higher volatility of the shocks of interest on event dates.
Keywords: GMM, heteroskedastic VAR, instrumental variable estimation, proxy VAR, structural vector autoregression