Answer-first summary for fast verification
Answer: not be covariance stationary and the regression coefficients will not be consistent.
## Explanation When two time series each have a unit root (are non-stationary) but are **not cointegrated**, this means there is no long-run equilibrium relationship between them. **Key implications:** - The error term in the regression will inherit the non-stationarity from the original series - Non-stationary error terms violate the assumptions of classical linear regression - This leads to **spurious regression** where the regression appears significant but is actually meaningless - The regression coefficients will **not be consistent** (they don't converge to the true population values) - The error term will **not be covariance stationary** Therefore, both the error term non-stationarity and inconsistent coefficients occur when non-stationary series are not cointegrated.
Author: LeetQuiz Editorial Team
Ultimate access to all questions.
An analyst regresses changes in an exchange rate over time on the two countries' inflation rate differential. While each of the two time series has a unit root, the time series are not cointegrated. This implies that the error term in the linear regression will:
A
be covariance stationary and the regression coefficients will be consistent.
B
be covariance stationary but the regression coefficients will not be consistent.
C
not be covariance stationary and the regression coefficients will not be consistent.
No comments yet.