This paper introduces a novel approach for dealing with the 'curse of dimensionality' in the case of large linear dynamic systems. Restrictions on the coefficients of an unrestricted VAR are proposed that are binding only in a limit as the number of endogenous variables tends to infinity. It is...

We study how the use of judgement or “add-factors” in macroeconomic forecasting may disturb the set of equilibrium outcomes when agents learn using recursive methods. We isolate conditions under which new phenomena, which we call exuberance equilibria, can exist in standard macroeconomic...

In this paper we revisit the literature on the economic consequences from inefficiency in public services provision. Following Dupuit (1844) and Pigou (1947) we argue that it is important to take the financing side explicitly into account. The fact that public expenditure financing must rely on...

We show that, when private sector expectations are determined in line with adaptive learning, optimal policy responds persistently to cost-push shocks. The optimal response is stronger and more persistent, the higher is the initial level of perceived inflation persistence by the private sector....

In the paper, we provide a critical and selective survey of arguments relevant for the assessment of the case for price level path stability (PLPS). Using a standard hybrid new Keynesian model we argue that price level stability provides a natural framework for monetary policy under commitment....

The move to monetary union in Europe led to convergence of interest rates among the participating countries. This was associated with notable cross-country differences in the behaviour of key macroeconomic aggregates. Compared to the low interest rate countries, former high interest rate...

Bayesian inference in a time series model provides exact, out-of-sample predictive distributions that fully and coherently incorporate parameter uncertainty. This study compares and evaluates Bayesian predictive distributions from alternative models, using as an illustration five alternative...

A prediction model is any statement of a probability distribution for an outcome not yet observed. This study considers the properties of weighted linear combinations of n prediction models, or linear pools, evaluated using the conventional log predictive scoring rule. The log score is a concave...

This paper introduces the concepts of time-specific weak and strong cross section dependence. A double- indexed process is said to be cross sectionally weakly dependent at a given point in time, t, if its weighted average along the cross section dimension (N) converges to its expectation in...