We consider time series models in which the conditional mean of the response variable given thepast depends on latent covariates. We assume that the covariates can be estimated consistentlyand use an iterative nonparametric kernel smoothing procedure for estimating the conditional meanfunction....

This paper develops a new test of orthogonality based on a zero restriction on the covariance between the dependent variable and the predictor. The test provides a useful alternative to regression-based tests when conditioning variables have roots close or equal to unity. In this case standard...

This paper proposes a test for linearity against exponential smooth transition models with endogenous right-hand-side variables: to the very best of our knowledge, this class of models is new to the literature. By Monte Carlo analysis the test is shown to have good finite sample properties

This paper explores the power of two tests for nonlinearity against spurious nonlinear regression. Results show that while the BDS test is susceptible to spuriousness, an approach introduced by Pena and Rodriguez (2005) is powerful, regardless of sample size

This study addresses some modeling questions related to the possibility of structural change in models with non-stationary variables. Focusing on cointegration issues, some methodological aspects ere discussed, attempting to integrate coherently the several steps of the modelling strategy. These...

Phillips (1986) provides asymptotic theory for regressions that relate nonstationary time series including those integrated of order 1, I(1). A practical implication of related literature on spurious regression is that one cannot trust the usual confidence intervals. Therefore it is recommended...

This paper introduces a representation of an integrated vector time series in which the coefficient of multiple correlation computed from the long-run covariance matrix of the innovation sequences is a primitive parameter of the model. Based on this representation, a notion of near cointegration...

Semiparametric partially linear models are advantageous to use in empirical studies of various economic problems due to a special feature such that both the parametric and nonparametric components can simultaneously exist in the model. However, a systematic estimation procedure and method have...

Local asymptotic power advantages are available for testing the null hypothesis that the slope coefficient is zero in regressions of y(t+k)-y(t) on x(t) for k 1 where the x(t) and the change in y(t) are I(0) series. The advantages of these long-horizon regression tests accrue in a linear...

This paper studies the asymptotic properties of a nonstationary partially linear regression model. In particular, we allow for covariates to enter the unit root (or near unit root) model in a nonparametric fashion, so that our model is an extension of the semiparametric model analyzed in...