Serena Ng

TL;DR: In this paper, a modified information criterion (MIC) with a penalty factor that is sample dependent was proposed to select appropriate truncation lag values for unit root tests with a moving-average root close to -1.

TL;DR: In this article, the convergence rate for the factor estimates that will allow for consistent estimation of the number of factors is established, and some panel criteria are proposed to obtain the convergence rates.

TL;DR: In this paper, the authors developed some econometric theory for factor models of large dimensions and proposed some panel C(p) criteria and showed that the number of factors can be consistently estimated using the criteria.

Abstract: Abstract We analyze the choice of the truncation lag in the context of the Said-Dickey test for the presence of a unit root in a general autoregressive moving average model. It is shown that a deterministic relationship between the truncation lag and the sample size is dominated by data-dependent rules that take sample information into account. In particular, we study data-dependent rules that are not constrained to satisfy the lower bound condition imposed by Said-Dickey. Akaike's information criterion falls into this category. The analytical properties of the truncation lag selected according to a class of information criteria are compared to those based on sequential testing for the significance of coefficients on additional lags. The asymptotic properties of the unit root test under various methods for selecting the truncation lag are analyzed, and simulations are used to show their distinctive behavior in finite samples. Our results favor methods based on sequential tests over those based on informat...

TL;DR: It is shown that a deterministic relationship between the truncation lag and the sample size is dominated by data-dependent rules that take sample information into account, and methods based on sequential tests over those based on informat...