DescriptionIn the 21th-century environmental sciences have embraced the idea of change. The effects of climate variability, technological change, and societal change combine to create a more dynamical world. Central in that world is a need to quantify the effects of those changes on the environment in ways that allow a combination of environmental and economic analysis.
In this context statistical analysis of environmental and economic data is still a powerful tool, but its techniques may need to adapt to new circumstances. One example of this is change point analysis. While this is understood in a manufacturing or financial context where long time series are available, it is now also applied to relatively short time series of environmental extremes. For those applications effects due to the finite length of the time series and quantification of the uncertainty of the location of the change are of great interest. For this reason, it was decided to examine and compare the behavior of classical change point analysis tools, a Bayesian method, and a method based on confidence sets.
|Period||19 Dec 2018|
|Event title||CE2_2018: 2nd Conference on Econometrics for Environment|