The Effects Of Monetary Policy Shocks In Peru: Semi-Structural Identification Using A Factor-Augmented Vector Autoregressive Model

The main goal of this paper is to analyze the effects of monetary policy shocks in Peru, taking into account two important issues that have been addressed separately in the VAR literature. The first one is the difficulty to identify the most appropriate indicator of monetary policy stance, which is usually assumed rather than determined from an estimated model. The second one is the fact that monetary policy decisions are based on the analysis of a wide range of economic and financial data, which is at odds with the small number of variables specified in most VAR models. To overcome the first issue, Bernanke and Mihov (1998) proposed a semi-structural VAR model from which the indicator of monetary policy stance can be derived rather than assumed. Meanwhile, the data problem has been resolved recently by Bernanke, Boivin and Eliasz (2005) using a Factor-Augmented Vector Autoregressive (FAVAR) model. In order to capture these two issues simultaneously, we propose an extension of the FAVAR model that incorporates a semi-structural identification approach a la Bernanke and Mihov, resulting in a VAR model that we denominate SS-FAVAR. Using data for Peru, the results show that the SS-FAVAR's impulse-response functions (IRFs) provide a more coherent picture of the effects of monetary policy shocks compared to the IRFs of alternative VAR models. Furthermore, it is found that innovations to nonborrowed reserves can be identified as monetary policy shocks for the period 1995-2003.