This paper studies some seemingly anomalous results that arise in possibly misspecified and unidentified linear asset-pricing models estimated by maximum likelihood and one-step generalized method of moments (GMM). Strikingly, when useless factors (that is, factors that are independent of the...

Two of the most important stylized facts well-known in finance relate to the non-Gaussian distribution and to the volatility clustering of stock returns. In this paper, we show that a new class of stochastic processes – called Multifractional Processes with Random Exponent (MPRE) – can...

This article addresses unit root testing on regulated series through the variance ratio (VR) statistic of Nielsen (2009). The asymptotic distribution of the regulated VR statistic is developed with and without OLS detrending. Results of Cavaliere and Xu (2011) are extended by also developing the...

This paper considers integer-valued autoregressive processes where the autoregression parameter is close to unity. We consider the asymptotics of this 'near unit root' situation. The local asymptotic structure of the likelihood ratios of the model is obtained, showing that the limit experiment...

One important question in the DSGE literature is whether we should detrend data when estimating the parameters of a DSGE model using the moment method. It has been common in the literature to detrend data in the same way the model is detrended. Doing so works relatively well with linear models,...

We propose two new parametric tests for an unknown threshold in models with endogenous regressors. They are both based on unconventional 2SLS estimators that use additional information about the linearity of the first stage. This information leads to more accurate residuals and therefore tests...

Using 2SLS estimation, we propose two tests for a threshold in models with endogenous regressors: a sup LR test and a sup Wald test. Here, the 2SLS estimation is not conventional because it uses additional information about the first-stage being linear or not. Because of this additional...