Fully Bayesian Analysis of SVAR Models under Zero and Sign Restrictions

The paper proposes the methodologically sound method to deal with set identified Structural VAR (SVAR) models under zero and sign restrictions. What distinguishes our method from that proposed by Arias, Rubio-Ramírez and Waggoner (2016) is that we isolated many special cases for which we arrive at more efficient algorithms to draw from the posterior. We illustrate our approach with the help of two serious empirical examples. First of all we challenge the output puzzle found by Uhlig (2005). Second, we check the robustness of the results given by Beaudry et al. (2014) concerning impact of optimism shocks on economy.