To capture location shifts in the context of model selection, we propose selecting significant step indicators from a saturating set added to the union of all of the candidate variables. The null retention frequency and approximate non-centrality of a selection test are derived using a...

This timely Handbook reviews many key issues in the economics of energy and climate change, raising new questions and offering solutions that might help to minimize the threat of energy-induced climate change.

To capture location shifts in the context of model selection, we propose selecting significant step indicators from a saturating set added to the union of all of the candidate variables. The null retention frequency and approximate non-centrality of a selection test are derived using a...

To capture location shifts in the context of model selection, we propose selecting significant step indicators from a saturating set added to the union of all of the candidate variables. The null retention frequency and approximate non-centrality of a selection test are derived using a...

Quantifying the uncertainty around structural breaks is crucial to attribute breaks to potential causes. Step-Indicator saturation (SIS, see Castle et al 2015) allows for the detection of structural breaks using model selection, however, little is known about the uncertainty around the timing of...