EconPapers    
Economics at your fingertips  
 

Bayesian Estimation of Fractionally Integrated Vector Autoregressions and an Application to Identified Technology Shocks

Ross Doppelt and Keith O'Hara
Additional contact information
Ross Doppelt: Penn State
Keith O'Hara: New York University

No 1212, 2018 Meeting Papers from Society for Economic Dynamics

Abstract: We introduce a new method for Bayesian estimation of fractionally integrated vector autoregressions (FIVARs). The FIVAR, which nests a standard VAR as a special case, allows each series to exhibit long memory, meaning that low frequencies can play a dominant role — a salient feature of many macroeconomic and financial time series. Although the parameter space is typically high-dimensional, our inferential procedure is computationally tractable and relatively easy to implement. We apply our methodology to the identification of technology shocks, an empirical problem in which business-cycle predictions depend on carefully accounting for low-frequency fluctuations.

New Economics Papers: this item is included in nep-ecm, nep-ets and nep-mac
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
https://economicdynamics.org/meetpapers/2018/paper_1212.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:red:sed018:1212

Access Statistics for this paper

More papers in 2018 Meeting Papers from Society for Economic Dynamics Society for Economic Dynamics Marina Azzimonti Department of Economics Stonybrook University 10 Nicolls Road Stonybrook NY 11790 USA. Contact information at EDIRC.
Bibliographic data for series maintained by Christian Zimmermann ().

 
Page updated 2019-01-31
Handle: RePEc:red:sed018:1212