Forecasting New Zealand's Real GDP

Aaron Schiff () and Peter C. B. Phillips ()

No 1278, Cowles Foundation Discussion Papers from Cowles Foundation, Yale University

Abstract: Recent time series methods are applied to the problem of forecasting New Zealand's real GDP. Model selection is conducted within autoregressive (AR) and vector autoregressive (VAR) classes, allowing for evolution in the form of the models over time. The selections are performed using the Schwarz (1978) BIC and the Phillips-Ploberger (1996) PIC criteria. The forecasts generated by the data-determined AR models and an international VAR model are found to be competitive with forecasts from fixed format models and forecasts produced by the NZIER. Two illustrations of the methodology in conditional forecasting settings are performed with the VAR models. The first provides conditional predictions of New Zealand's real GDP when there is a future recession in the United States. The second gives conditional predictions of New Zealand's real GDP under a variety of profiles that allow for tightening in monetary conditions by the Reserve Bank.

Keywords: Automated modeling; forecasting; PIC model selection; policy analysis; real GDP (search for similar items in EconPapers)
JEL-codes: C11 C22 C32 C53 (search for similar items in EconPapers)
Date: 2000-10
Note: CFP 1020.
View list of references View citations in EconPapers

Published in New Zealand Economic Papers (2000), 34(2): 159-182

Downloads: (external link)
http://cowles.econ.yale.edu/P/cd/d12b/d1278.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: http://EconPapers.repec.org/RePEc:cwl:cwldpp:1278

Ordering information: This working paper can be ordered from
Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA
The price is None.

Access Statistics for this paper

More papers in Cowles Foundation Discussion Papers from Cowles Foundation, Yale University
Address: Yale University, Box 208281, New Haven, CT 06520-8281 USA
Contact information at EDIRC.
Series data maintained by Glena Ames ().