# If two variables are not cointegrated, can one still cause the other?

For part of a project, I wanted to see if electricity consumption causes GDP in Colorado. I initially intended to follow the approach of Mozumder and Marathe (2007), who use a VECM approach, but that requires cointegration.

I'm not sure what to do now. I tried the Toda-Yamamoto method but my errors seem to be serially correlated...

First, cointegration requires that each series be $$I(1)$$. It is certainly possible for two $$I(0)$$ series to follow a causal relationship (or two $$I(d)$$ variables for that matter).
Second, cointegration implies a long-run equilibrium among the series, which is not required for a causal relationship. A long-run equilibrium between two time series variables $$x$$ and $$y$$ implies that $$y_t-a-bx_t$$ is a stationary process. In other words, if shocks are 'turned off', the values of $$x$$ and $$y$$ will converge such that $$y_t=a+bx_t$$.