We consider issues related to the order of an autoregression selected using information criteria. We study the sensitivity of the estimated order to (i) whether the effective number of observations is held fixed when estimating models of different order, (ii) whether the estimate of the variance...

This paper studies two refinements to the method of factor forecasting. First, we consider the method of quadratic principal components that allows the link function between the predictors and the factors to be non-linear. Second, the factors used in the forecasting equation are estimated in a...

This paper studies estimation of panel cointegration models with cross-sectional dependence generated by unobserved global stochastic trends. The standard least squares estimator is, in general, inconsistent owing to the spuriousness induced by the unobservable I(1) trends. We propose two...

Much is written about the use of factors estimated by the method of principal components from large panels in linear regression models. In this paper, we provide an analysis for non-linear estimation and establish the conditions under which the estimated factors can be treated as though they...

In a recent paper, Engel, C. (1999) presents monte-carlo evidence to suggest that unit root tests cannot detect a non-stationary component in the real exchange rate even when this component accounts for almost half of its longhorizon forecast error variance. This hidden non-stationary component...

This paper considers a moments based non-linear estimator that is root-T consistent and uniformly asymptotically normal irrespective of the degree of persistence of the forcing process. These properties hold for linear autoregressive models, linear predictive regressions, as well as certain...