We describe and examine a consistent test for the correct specification of a regression function with dependent data. The test is based on the supremum of the difference between the parametric and nonparametric estimates of the regression model. Rather surprisingly, the behaviour of the test...

This article proposes a class of goodness-of-fit tests for the autocorrelation function of a time series process, including those exhibiting long-range dependence. Test statistics for composite hypotheses are functionals of a (approximated) martingale transformation of the Bartlett's Tp-process...

The purpose of this paper is to introduce and examine two alternative, although similar, approaches to the Moving Blocks and subsampling Bootstraps to bootstrapping the estimator of the parameters for time series regression models. More specifically, the first bootstrap is based on resampling...

Order selection based on criteria by Akaike (1974), AIC, Schwarz (1978), BIC or Hannan and Quinn (1979) HIC is often applied in empirical examples. They have been used in the context of order selection of weakly dependent ARMA models, AR models with unit or explosive roots and in the context of...

Model selection and estimation are important topics in econometric analysis which can become considerably complicated in high dimensional settings, where the set of possible regressors can become larger than the set of available observations. For large scale problems the penalized regression...

This paper introduces and analyses a setting with general heterogeneity in regression modelling. It shows that regression models with fixed or time-varying parameters can be estimated by OLS or time-varying OLS methods, respectively, for a very wide class of regressors and noises, not covered by...

We establish asymptotic normality of weighted sums of stationary linear processes with general triangular array weights and when the innovations in the linear process are martingale differences. The results are obtained under minimal conditions on the weights and as long as the process of...

This paper explores a semiparametric version of a time-varying regression, where a subset of the regressors have a fixed coefficient and the rest a time-varying one. We provide an estimation method and establish associated theoretical properties of the estimates and standard errors in extended...