Using an extension of general-to-specific modelling, based on the recent developments of impulse-indicator saturation (IIS), we consider selecting significant step indicators from a saturating set to capture location shifts.  The approximate non-centrality of the test is derived for a variety...

We identify anthropogenic contributions to atmospheric CO2 measured at Mauna Loa using a statistical automatic model selection algorithm (Autometrics).  We find that vegetation, temperature and other natural factors alone cannot explain the trend or the variation in CO2 growth.  Industrial...

We demonstrate major flaws in the statistical analysis of Beenstock, Reingewertz and Paldor (2012), discrediting their initial claims as to the different degrees integrability of CO2 and temperature.

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.

We consider model selection for non-linear dynamic equations with more candidate variables than observations, based on a general class of non-linear-in-the-variables functions, addressing possible location shifts by impulse-indicator saturation.  After an automatic search delivers a simplified...

We consider forecasting with factors, variables and both, modeling in-sample using Autometrics so all principal components and variables can be included jointly, while tackling multiple breaks by impulse-indicator saturation.  A forecast-error taxonomy for factor models highlights the impacts...

We consider selecting an econometric model when there is uncertainty over both the choice of variables and the occurrence and timing of multiple location shifts.  The theory of general-to-simple (Gets) selection is outlined and its efficacy demonstrated in a new set of simulation experiments...

Understanding the workings of whole economies is essential for sound policy advice - but not necessarily for accurate forecasts.  Structural models play a major role at most central banks and many other governmental agencies, yet almost none forecast the financial crisis and ensuing...

We evaluate automatically selecting the relevant variables in an econometric model from a large candidate set.  General-to-specific selection is outlined for a constant model in orthogonal variables, where only one decision is required to select, irrespective of the number of regressors (N T)...