Outside the box: using synthetic control methods as a forecasting technique

Stefan Klößner and Gregor Pfeifer

Applied Economics Letters, 2018, vol. 25, issue 9, 615-618

Abstract: We introduce synthetic control methods (SCM) as a forecasting technique. Using (i) as economic predictors solely the outcome itself, i.e. lagged values of the dependent variable, and (ii) lagged time series of the outcome to build the donor pool, we let SCM choose and weight appropriate values in order to come up with a sensible forecast of the US GDP growth. This procedure performs competitively viable compared with alternative forecasting methods.

Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://hdl.handle.net/10.1080/13504851.2017.1352071 (text/html)
Access to full text is restricted to subscribers.

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:taf:apeclt:v:25:y:2018:i:9:p:615-618

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEL20

DOI: 10.1080/13504851.2017.1352071

Access Statistics for this article

Applied Economics Letters is currently edited by Anita Phillips

More articles in Applied Economics Letters from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().