Data and Code for: What Can We Learn From Sign-Restricted VARs?
Principal Investigator(s): View help for Principal Investigator(s) Christian K. Wolf, MIT
Version: View help for Version V1
| Name | File Type | Size | Last Modified |
|---|---|---|---|
| aeapp_replication | 03/22/2022 10:56:AM |
Project Citation:
Wolf, Christian K. Data and Code for: What Can We Learn From Sign-Restricted VARs? Nashville, TN: American Economic Association [publisher], 2022. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2022-05-17. https://doi.org/10.3886/E165722V1
Project Description
Summary:
View help for Summary
I use a simple business-cycle model to illustrate the workings and limitations of sign restrictions in Structural Vector Autoregressions. Three lessons emerge. First, such sign-based identification is vulnerable to ``shock masquerading'': linear combinations of other shocks may be mis-identified as the shock of interest. Second, since the popular Haar prior automatically over-weights more volatile shocks, the implied posterior is decisively shaped by relative shock volatilities – a feature of shocks that has nothing to do with their dynamic causal effects. Third, sign restrictions on structural elasticities – rather than just the usual restrictions on impulse responses – can be highly informative.
Scope of Project
Subject Terms:
View help for Subject Terms
sign restrictions;
Haar prior;
zero restrictions;
monetary policy
JEL Classification:
View help for JEL Classification
C32 Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
E32 Business Fluctuations; Cycles
C32 Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
E32 Business Fluctuations; Cycles
Related Publications
Published Versions
Report a Problem
Found a serious problem with the data, such as disclosure risk or copyrighted content? Let us know.
This material is distributed exactly as it arrived from the data depositor. ICPSR has not checked or processed this material. Users should consult the investigator(s) if further information is desired.