Relying on University of Michigan data on consumers.in.ation expectations, we establish some stylized facts on the process of in.ation expectation formation across different demographic groups. Percentile time series models are employed to test for rationality and to study learning dynamics...

This paper presents a new approach to portfolio optimisation that we call generalised mean-variance (GMV) analysis. One important case of this approach is based on the stocks m-tile (or quantile): if m = n, where n is the number of stocks, m-tile membership becomes rank. Our analysis is the rank...

This paper provides a novel approach to forecasting time series subject to discrete structural breaks. We propose a Bayesian estimation and prediction procedure that allows for the possibility of new breaks over the forecast horizon, taking account of the size and duration of past breaks (if...

This paper argues that probability forecasts convey information on the uncertainties that surround macroeconomic forecasts in a manner which is straightforward and which is preferable to other alternatives, including the use of confidence intervals. Probability forecasts relating to UK output...

This paper presents the theoretical development of new threshold autoregressive models based on trended time series. The theoretical arguments underlying the models are outlined and a nonlinear economic model is used to derive the specification of the empirical econometric models. Estimation and...

This paper characterizes the asymptotic behaviour, as the number of assets gets arbitrarily large, of the portfolio weights for the class of tangency portfolios belonging to the Markowitz paradigm. It is as- sumed that the joint distribution of asset returns is characterized by a general factor...

Structural VAR and Structural VEC models were estimated for Chile and Colombia, aiming at identifying fiscal policy shocks in both countries between 1990 and 2005. The impulse responses obtained allow the calculation of a pesofor- peso ($/$) effect on output of a shock to public spending and to...

We propose a theoretical framework for assessing whether a forecast model estimated over one period can provide good forecasts over a subsequent period. We formalize this idea by defining a forecast breakdown as a situation in which the out-of-sample performance of the model, judged by some loss...

We evaluate various modelsí relative performance in forecasting future US output growth and inflation on a monthly basis. Our approach takes into account the possibility that the modelsí relative performance can be varying over time. We show that the modelsí relative performance has, in fact,...

This paper develops optimal tests for model selection between two nested models in the presence of underlying parameter instability. These are joint tests for both parameter instability and a null hypothesis on (a subset of) the parameters. They modify the existing tests for parameter...