Template-type: ReDif-Paper 1.0
Author-Name: Götz, T.B.
Author-workplace-name: Quantitative Economics
Author-Name: Hecq, A.W.
Author-workplace-name: Quantitative Economics
Author-Name: Urbain, J.R.Y.J.
Author-workplace-name: Quantitative Economics
Title: Testing for common cycles in non-stationary VARs with varied frecquency data
Abstract: This paper proposes a new way for detecting the presence of common cyclical features<br/>when several time series are observed/sampled at different frequencies, hence generalizing<br/>the common-frequency approach introduced by Engle and Kozicki (1993) and Vahid and<br/>Engle (1993). We start with the mixed-frequency VAR representation investigated in Ghysels<br/>(2012) for stationary time series. For non-stationary time series in levels, we show<br/>that one has to account for the presence of two sets of long-run relationships. The First set<br/>is implied by identities stemming from the fact that the differences of the high-frequency<br/>I(1) regressors are stationary. The second set comes from possible additional long-run relationships<br/>between one of the high-frequency series and the low-frequency variables. Our<br/>transformed VECM representations extend the results of Ghysels (2012) and are very important<br/>for determining the correct set of variables to be used in a subsequent common<br/>cycle investigation. This has some empirical implications both for the behavior of the test<br/>statistics as well as for forecasting. Empirical analyses with the quarterly real GNP and<br/>monthly industrial production indices for, respectively, the U.S. and Germany illustrate our<br/>new approach. This is also investigated in a Monte Carlo study, where we compare our proposed<br/>mixed-frequency models with models stemming from classical temporal aggregation<br/>methods.
Series: GSBE Research Memoranda
Creation-Date: 20130101
Number: 002
File-URL: https://cris.maastrichtuniversity.nl/ws/files/874213/guid-f631c3c7-e8bd-4c28-bb20-ab282fc8f02c-ASSET1.0.pdf
File-Format: application/pdf
File-Size: 713004
Handle: Repec:unm:umagsb:2013002
DOI: 10.26481/umagsb.2013002