Title
Could we use the panel regression to examine the relationship between a stationary series and a non-stationary series?
Authors
Abstract
While many studies report correlations between a stationary time series Yt and a non-stationary time series Xt, Wong and Pham (2025) hypothesized that
applying standard regression-based correlation tests in this context may yield spurious or non-informative results and conjectured that standard correlation statistics are not suitable for evaluating such relationships. Thereafter, through simulation studies, they find the spurious nature of the correlation and the inadequacy of standard tests in this setting. Thereafter, they developed the estimation and testing theory for the correlation between a stationary Yt and a non-stationary Xt and proved that the standard correlation statistic cannot be used in this setting and that the resulting test statistic differs from the one used to test the correlation between two random series Yt and Xt, concluding that the traditional correlation test cannot be used to test for the correlation between a stationary time series Yt and a non-stationary time series Xt. Nevertheless,
as far as we know, no study in the literature has investigated whether a correlation exists between panel data with a non-stationary variable and a
stationary variable. This paper investigates the issue.
Keywords
Cointegration, stationarity, non-stationarity, correlation, time series analysis
JEL Classi cation
C01, C15, C22, C58, C60
How to Cite
Wong, W.-K., & Pham, M. T. (2026). Could we use correlation to examine panel data with I(0) and I(1) variables? The International Journal of Finance, 38, forthcoming.