Stochastic Search Variable Selection in Vector Error Correction Models with an Application to a Model of the UK Macroeconomy

This paper develops methods for Stochastic Search Variable Selection (currently popular with regression and Vector Autoregressive models) for Vector Error Correction models where there are many possible restrictions on the cointegration space. We show how this allows the researcher to begin with a single unrestricted model and either do model selection or model averaging in an automatic and computationally efficient manner. We apply our methods to a large UK macroeconomic model.

Future of the Clean Development Mechanism in Tackling Climate Change

Using a theoretical framework, we explain the impact of the Clean Development Mechanism (CDM) on emissions in Annex I and non-Annex I countries. We show that on one hand, emissions in the non-Annex I country decline because of abatement sponsored by the Annex I country under the CDM; on the other hand, emissions may increase because (i) the Annex I country increases emissions in its own country, and (ii) the non-Annex I country crowds out the bene ts from the CDM projects by increasing its domestic emissions. For the CDM to be e¤ective in reducing global emissions, we show that partial Certi ed Emissions Reduction credits should be given to the Annex I country that sponsors CDM projects in the non-Annex I country. We also suggest that the CDM Executive Board should not allow the CDM projects to be hosted by non-Annex I countries that are too conscious about their emission levels.