In this paper we confront sensitivity analysis with diagnostic testing.Every model is misspecified, but a model is useful if the parameters of interest (the focus) are not sensitive to small perturbations in the underlying assumptions. The study of the e ect of these violations on the focus is...

This paper discusses and documents the algorithms of SsfPack 2.2. SsfPack is a suite of C routines for carrying out computations involving the statistical analysis of univariate and multivariate models in state space form. The emphasis is on documenting the link we have made to the Ox computing...

The binary-choice regression models such as probit and logit are used to describe the effect of explanatory variables on a binary response vari- able. Typically estimated by the maximum likelihood method, estimates are very sensitive to deviations from a model, such as heteroscedastic- ity and...

This paper looks at unobserved components models and examines the implied weighting pat- terns for signal extraction. There are three main themes. The first is the implications of correlated disturbances driving the components, especially those cases in which the correlation is perfect. The...

We propose a class of distribution-free rank-based tests for the null hypothesis of a unit root. This class is indexed by the choice of a reference density g, which needs not coincide with the unknown actual innovation density f. The validity of these tests, in terms of exact finite sample size,...

This paper introduces a new class of robust regression estimators. The proposed twostep least weighted squares (2S-LWS) estimator employs data-adaptive weights determined from the empirical distribution, quantile, or density functions of regression residuals obtained from an initial robust fit....

Abstract This paper considers optimal unit root tests for a Gaussian cross-sectionally independent heterogeneous panel with incidental intercepts and heterogeneous alternatives generated by random perturbations. We derive the (asymptotic and local) power envelope for two models: an auxiliary...

The reaction coefficients of expected inflations and output gaps in the forecast-based monetary policy reaction function may be merely weakly …identified when the smoothing coefficient is close to unity and the nominal interest rates are highly persistent. In this paper we modify the method...

In this paper we estimate the yield curve of U.S. government bonds using a Markov switching latent variable model. We show how measures such as the level, slope, and curvature of the yield curve are a¤ected by business cycle conditions. We present a switching latent model which not only seem to...