Multi-agent contracting with countervailing incentives and limited liability

We consider a principal who deals with a privately informed agent protected by limited liability in a correlated information setting. The agent's technology is such that the fixed cost declines with the marginal cost (the type), so that countervailing incentives may arise. We show that, with high liability, the first-best outcome can be effected for any type if (1) the fixed cost is non-concave in type, under the contract that yields the smallest feasible loss to the agent; (2) the fixed cost is not very concave in type, under the contract that yields the maximum sustainable loss to the agent. We further show that, with low liability, the first-best outcome is still implemented for a non-degenerate range of types if the fixed cost is less concave in type than some given threshold, which tightens as the liability reduces. The optimal contract entails pooling otherwise.

Baysian Model Averaging, Learning and Model Selection

Agents have two forecasting models, one consistent with the unique rational expectations equilibrium, another that assumes a time-varying parameter structure. When agents use Bayesian updating to choose between models in a self-referential system, we find that learning dynamics lead to selection of one of the two models. However, there are parameter regions for which the non-rational forecasting model is selected in the long-run. A key structural parameter governing outcomes measures the degree of expectations feedback in Muth's model of price determination.

Local consumption and territorial based accounting for CO2 Emissions

We examine the complications involved in attributing emissions at a sub-regional or local level. Speci cally, we look at how functional specialisation embedded within the metropolitan area can, via trade between sub-regions, create intra-metropolitan emissions interdependencies; and how this complicates environmental policy implementation in an analogous manner to international trade at the national level. For this purpose we use a 3-region emissions extended input-output model of the Glasgow metropolitan area (2 regions: city and surrounding suburban area) and the rest of Scotland. The model utilises data on commuter flows and household consumption to capture income and consumption flows across sub-regions. This enables a carbon attribution analysis at the sub-regional level, allowing us to shed light on the signi cant emissions interdependencies that can exist within metropolitan areas.