dc.contributor.author |
Balcilar, Mehmet
|
|
dc.contributor.author |
Gupta, Rangan
|
|
dc.contributor.author |
Jooste, Charl
|
|
dc.date.accessioned |
2016-08-18T07:39:14Z |
|
dc.date.issued |
2017 |
|
dc.description.abstract |
We compare inflation forecasts of a vector fractionally integrated autoregressive
moving average (VARFIMA) model against standard forecasting models. U.S.
inflation forecasts improve when controlling for persistence and economic policy
uncertainty (EPU). Importantly, the VARFIMA model, comprising of inflation and
EPU, outperforms commonly used inflation forecast models. |
en_ZA |
dc.description.department |
Economics |
en_ZA |
dc.description.embargo |
2018-02-28 |
|
dc.description.librarian |
hb2016 |
en_ZA |
dc.description.uri |
http://www.tandfonline.com/loi/raec20 |
en_ZA |
dc.identifier.citation |
Mehmet Balcilar, Rangan Gupta & Charl Jooste (2017) Long memory,
economic policy uncertainty and forecasting US inflation: a Bayesian VARFIMA approach, Applied
Economics, 49:11, 1047-1054, DOI:
10.1080/00036846.2016.1210777. |
en_ZA |
dc.identifier.issn |
0003-6846 (print) |
|
dc.identifier.issn |
1466-4283 (online) |
|
dc.identifier.other |
10.1080/00036846.2016.1210777 |
|
dc.identifier.uri |
http://hdl.handle.net/2263/56394 |
|
dc.language.iso |
en |
en_ZA |
dc.publisher |
Routledge |
en_ZA |
dc.rights |
© 2016 Informa UK Limited, trading as Taylor & Francis Group. This is an electronic version of an article published in Applied Economics, vol. 49, no. 11, pp. 1047-1054, 2017. doi : 10.1080/00036846.2016.1210777. Applied Economics is available online at : http://www.tandfonline.comloi/raec20. |
en_ZA |
dc.subject |
Inflation |
en_ZA |
dc.subject |
Long-range dependency |
en_ZA |
dc.subject |
Vector fractionally integrated autoregressive moving average (VARFIMA) |
en_ZA |
dc.subject |
Economic policy uncertainty (EPU) |
en_ZA |
dc.title |
Long memory, economic policy uncertainty and forecasting US inflation : a Bayesian VARFIMA approach |
en_ZA |
dc.type |
Postprint Article |
en_ZA |