Departures from stationarity
A)jeopardize forecasts and inference based on time series regression.
B)occur often in cross-sectional data.
C)can be made to have less severe consequences by using log-log specifications.
D)cannot be fixed.

Question

Quizplus · Accepted Answer

Departures from stationarity can lead to non-stationary data that violate the assumptions of time series regression models, and thereby jeopardize forecasts and inferences based on such models.

Departures from Stationarity