1. Partial Identification of Heteroskedastic Structural VARs: Theory and Bayesian Inference
- Author
-
Lütkepohl, Helmut, Shang, Fei, Uzeda, Luis, and Woźniak, Tomasz
- Subjects
Economics - Econometrics ,Statistics - Applications - Abstract
We consider structural vector autoregressions identified through stochastic volatility. Our focus is on whether a particular structural shock is identified by heteroskedasticity without the need to impose any sign or exclusion restrictions. Three contributions emerge from our exercise: (i) a set of conditions under which the matrix containing structural parameters is partially or globally unique; (ii) a statistical procedure to assess the validity of the conditions mentioned above; and (iii) a shrinkage prior distribution for conditional variances centred on a hypothesis of homoskedasticity. Such a prior ensures that the evidence for identifying a structural shock comes only from the data and is not favoured by the prior. We illustrate our new methods using a U.S. fiscal structural model.
- Published
- 2024