We show that the CUSUM and LM tests for structural change in the volatility process enjoy monotonic power. The framework is general including many recently proposed non-stationary GARCH-type models. The result is in contrast to the well-known issue of non-monotonic power for the CUSUM-based...

We propose a test for the evaluation of statistical acceptability of a functional constraint which is imposed on parameters in the mixed data sampling regressions. The asymptotic behavior of the test statistic is characterized and a few other extensions are discussed.

This article tests the linearity assumption underlying the popular heterogeneous autoregressive model for realized volatility (HAR-RV). We implement a consistent model specification test that is robust to both distributional and model misspecification. We find that, using a nonparametric HAR-RV...

In this paper, we consider a cointegrated panel data model with non-stationary common factors, which, because of its appeal in many economic applications, has received much attention in the recent literature. By deriving a Granger-type representation theorem, we obtain several equivalent model...

We propose an adaptive truncated product method that facilitates the selection of the truncation point among a set of candidates. To efficiently estimate the distribution of the proposed method when the p-values are correlated, we develop a single-layer bootstrap procedure.

In an influential paper, Pesaran [Pesaran, M.H. (2006). Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica 74, 967–1012] proposes a very simple estimator of factor-augmented regressions that has since then become very popular. In this note...

This paper proposes a cumulative sum (CUSUM) based statistic to test if there is a common variance change-point in panel data models. Asymptotic distribution is derived under the null hypothesis and the consistency of the test is proven under the alternative hypothesis. Monte Carlo experiment is...

In this note, we provide the application of HCCME-type refinements to nonlinear GMM models with Bayesian interpretations.

In this note, we argue that tests of overidentifying restrictions give little information on the validity of the moment conditions implied by the underlying economic model, and therefore are mute about the possibility of identifying the parameters of interest.

This note proposes a class of estimators for estimating the asymptotic covariance matrix of the generalized method of moments (GMM) estimator in the stationary time series models. The proposed estimator is general enough to include the traditional heteroskedasticity and autocorrelation...