The effect of data transformation on common cycle, cointegration, and unit root tests: Monte Carlo results and a simple test

Valentina Corradi, Norman R. Swanson

Research output: Contribution to journalArticlepeer-review

Abstract

Cointegration, common cycle, and related tests statistics are often constructed using logged data, even without clear reason why logs should be used rather than levels. Unfortunately, it is also the case that standard data transformation tests, such as those based on Box-Cox transformations, cannot be shown to be consistent unless assumptions concerning whether variables I ( 0 ) or I ( 1 ) are made. In this paper, we propose a simple randomized procedure for choosing between levels and log-levels specifications in the (possible) presence of deterministic and/or stochastic trends, and discuss the impact of incorrect data transformation on common cycle, cointegration and unit root tests.

Original languageEnglish (US)
Pages (from-to)195-229
Number of pages35
JournalJournal of Econometrics
Volume132
Issue number1
DOIs
StatePublished - May 2006

Keywords

  • Common cycles
  • Common trends
  • Nonlinear transformation
  • Nonstationarity
  • Randomized procedure

ASJC Scopus subject areas

  • Economics and Econometrics

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