Sequential testing for structural stability in approximate factor models

Testing Structural Stability in Macroeconometric Models

Stability Estimating in Optimal Sequential Hypotheses Testing

We study the stability of the classical optimal sequential probability ratio test based on independent identically distributed observations X1, X2, . . . when testing two simple hypotheses about their common density f : f = f0 versus f = f1. As a functional to be minimized, it is used a weighted sum of the average (under f0) sample number and the two types error probabilities. We prove that the...

TESTING FOR AUTOCORRELATION IN UNEQUALLY REPLICATED FUNCTIONAL MEASUREMENT ERROR MODELS

In the ordinary linear models, regressing the residuals against lagged values has been suggested as an approach to test the hypothesis of zero autocorrelation among residuals. In this paper we extend these results to the both equally and unequally replicated functionally measurement error models. We consider the equally and unequally replicated cases separately, because in the first case the re...

Testing for Structural Change in Conditional Models

In the past decade, we have seen the development of a new set of tests for structural change of unknown timing in regression models, most notably the SupF statistic of Andrews (1993, Econometrica 61, 825}856), the ExpF and AveF statistics of AndrewsPloberger (1994, Econometrica 62, 1383}1414), and the ̧ statistic of Nyblom (1989, Journal of American Statistical Association 84, 223}230). The dis...

A Testing Procedure for Determining the Number of Factors in Approximate Factor Models with Large Datasets

The paradigm of a factor model is very appealing and has been used extensively in economic analyses. Underlying the factor model is the idea that a large number of economic variables can be adequately modelled by a small number of indicator variables. Throughout this extensive research activity on large dimensional factor models a major preoccupation has been the development of tools for determ...