On the robustness of stylised business cycle facts for contemporary New Zealand

We assess the robustness of stylised business cycle facts for contemporary New Zealand, traditionally computed from HP1600 trend-filtered data. The merits of these HP1600 estimates are considered, relative to those computed from two loess (local regression) trend filtering methods, one (loess11) cho...

Full description

Saved in:
Bibliographic Details
Published in:New Zealand economic papers 2017-09, Vol.51 (3), p.193-216
Main Authors: Hall, Viv B., Thomson, Peter, McKelvie, Stuart
Format: Article
Language:English
Subjects:
Analysis
Business cycles
growth cycle analysis
Growth factors
New Zealand
Stylised business cycle facts
time-varying estimates
trend robustness
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We assess the robustness of stylised business cycle facts for contemporary New Zealand, traditionally computed from HP1600 trend-filtered data. The merits of these HP1600 estimates are considered, relative to those computed from two loess (local regression) trend filtering methods, one (loess11) chosen to exhibit greater fidelity and the other (loess47) to show more pronounced smoothness. The robustness of our key business cycle facts is further evaluated in terms of simple robust standard error estimates of measures of time-invariant volatility and correlation. Time-varying estimates of these quantities are also investigated. Statistically significant bivariate correlations are established for key real expenditure variables, labour market, fiscal and monetary policy, and some inflation variables, with almost all loess47 absolute magnitudes being somewhat greater than HP1600 magnitudes. Their pro- or counter-cyclicality and their lead/lag relationships are robust across HP1600 and loess47 trend filtering, though not for CPI and non-tradables price level variables.
ISSN:0077-9954
1943-4863
DOI:10.1080/00779954.2016.1189956