Climate Change and Future Analysis: Is Stationarity Dying?
- Additional Document Info
- View All
Evidence exists that climate change will shift the mean and variance of crop yields, challenging the stationarity assumption. The primary reason is that the Fixed Effects model allows researchers to estimate a unit-specific effect for each state in the model. In addition, the Fixed Effects model does not require the restrictive assumption that the state-specific effect is independent of the included covariates as the Random Effects model does. State dummies are included in the regression to capture state-specific effects that are invariant over time. The pattern is somewhat different for corn in the North Plains, where the corresponding changes are 29% and 61%for changes in average climate conditions, and 24% and 76% when higher temperature variability occurs. The regression results show that stationarity does not hold as we find that both the mean and the variance of key climate variables evolved over time.
author list (cited authors)
McCarl, B. A., Villavicencio, X., & Wu, X.