An interregional input-output analysis of the pollution content of trade flows and environmental trade balances between five states in the US Mid-West

In this paper we attempt an empirical application of the multi-region input-output (MRIO) method in order to enumerate the pollution content of interregional trade flows between five Mid-West regions/states in the US –Illinois, Indiana, Iowa, Michigan and Wisconsin – and the rest of the US. This allows us to analyse some very important issues in terms of the nature and significance of interregional environmental spillovers within the US Mid-West and the existence of pollution ‘trade balances’ between states. Our results raise questions in terms of the extent to which authorities at State level can control local emissions where they are limited in the way some emissions can be controlled, particularly with respect to changes in demand elsewhere in the Mid-West and US. This implies a need for policy co-ordination between national and state level authorities in the US to meet emissions reductions targets. The existence of an environmental trade balances between states also raises issues in terms of net losses/gains in terms of pollutants as a result of interregional trade within the US and whether, if certain activities can be carried out using less polluting technology in one region relative to others, it is better for the US as a whole if this type of relationship exists.

Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables

Macroeconomists working with multivariate models typically face uncertainty over which (if any) of their variables have long run steady states which are subject to breaks. Furthermore, the nature of the break process is often unknown. In this paper, we draw on methods from the Bayesian clustering literature to develop an econometric methodology which: i) finds groups of variables which have the same number of breaks; and ii) determines the nature of the break process within each group. We present an application involving a five-variate steady-state VAR.