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.

Characterizing Behavioral Decisions with Choice Datas

A number of different models with behavioral economics have a reduced form representation where potentially boundedly rational decision-makers do not necessarily internalize all the consequences of their actions on payoff relevant features (which we label as psychological states) of the choice environment. This paper studies the restrictions that such behavioral models impose on choice data and the implications they have for welfare analysis. First, we propose a welfare benchmark that is justified using standard axioms of rational choice and can be applied to a number of existing seminal behavioral economics models. Second, we show that Sen's axioms and fully characterize choice data consistent with behavioral decision-makers. Third, we show how choice data to infer information about the normative signi.cance of psychological states and establish the possibility of identifying welfare dominated choices.

Partial Knowledge Restrictions on theTwo-Stage Threshold Model of Choice

In the context of the two-stage threshold model of decision making, with the agent’s choices determined by the interaction Of three “structural variables,” we study the restrictions on behavior that arise when one or more variables are xogenously known. Our results supply necessary and sufficient conditions for consistency with the model for all possible states of partial Knowledge, and for both single- and multivalued choice functions.

The Optimal Degree of Monetary-Discretion in a New Keynesian Model with Private Information

This paper considers the optimal degree of discretion in monetary policy when the central bank conducts policy based on its private information about the state of the economy and is unable to commit. Society seeks to maximize social welfare by imposing restrictions on the central bank's actions over time, and the central bank takes these restrictions and the New Keynesian Phillips curve as constraints. By solving a dynamic mechanism design problem we find that it is optimal to grant "constrained discretion" to the central bank by imposing both upper and lower bounds on permissible inflation, and that these bounds must be set in a history-dependent way. The optimal degree of discretion varies over time with the severity of the time-inconsistency problem, and, although no discretion is optimal when the time-inconsistency problem is very severe, our numerical experiment suggests that no-discretion is a transient phenomenon, and that some discretion is granted eventually.