Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/210728
Authors: 
Lewis, Daniel J.
Year of Publication: 
2018
Series/Report no.: 
Staff Report 876
Abstract: 
Identification via heteroskedasticity exploits differences in variances across regimes to identify parameters in simultaneous equations. I study weak identification in such models, which arises when variances change very little or the variances of multiple shocks change close to proportionally. I show that this causes standard inference to become unreliable, propose two tests to detect weak identification, and develop nonconservative methods for robust inference on a subset of the parameter vector. I apply these tools to monetary policy shocks, identified using heteroskedasticity in high frequency data. I detect weak identification in daily data, causing standard inference methods to be invalid. However, using intraday data instead allows the shocks to be strongly identified.
Subjects: 
heteroskedasticity
weak identification
robust inference
pretesting
monetary policy
impulse response function
JEL: 
C12
C32
E43
Document Type: 
Working Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.