Climate Change and Future Analysis: Is Stationarity Dying?

Economists often do risk analysis in support of management decisions. Commonly, such anal-yses are based on probability distributions aris-ing from historical data where the distribu-tions developed are based on at least a partial assumption of stationarity. For example, in water-based risk analysis one typically assumes the distribution is stationary, and uses the 100 year drought. In yield-related analyses ana-lysts typically assume the mean is changing with time (proxying for technological progress along with monetary inflation) but that the variance is stationary. Climate change may alter distribution sta-tionarity (as asserted in a water setting by Milly et al. 2008). Evidence exists that climate change will shift the mean and variance of crop yields, challenging the stationarity assumption. If so, risk analysis would need to use distri-butions with nonstationary means and vari-ances along with possibly shifting higher order moments. Here we examine stationarity and crop yields, statistically examining historical crop yield stationarity variability allowing both mean and variance to be affected. Finally, we evaluate stationarity under projected climate change scenarios. Background on Climate Change and Yields The influence of climate change on agricul-tural crop yields has been widely studied, as reviewed in documents such as the In-