When the ARMA-GARCH model errors lack a finite fourth moment, the asymptotic distribution of the quasi-maximum likelihood estimator may not be Normal. In such a scenario the conventional bootstrap turns out inconsistent. Surprisingly, simulations show that the conventional bootstrap, despite its...

Measurement error causes a downward bias when estimating a panel data linear regression model. The panel data context offers various opportunities to derive moment conditions that result in consistent GMM estimators. We consider three sources of moment conditions: (i) restrictions on the...

We propose a new identification strategy for the quadratic regression model with classical measurement error, based on higher-order moment conditions. Our novel approach contributes to the literature in two ways: by not requiring any side information (such as a known measurement-error variance,...

The rich dependency structure of panel data can be exploited to generate moment conditions that can be used to identify linear regression models in the presence of measurement error. This paper adds to a small body of literature on this topic by showing how heteroskedasticity and nonlinear...

Measurement error causes a downward bias when estimating a panel data linear regression model. The panel data context offers various opportunities to derive moment conditions that result in consistent GMM estimators. We consider three sources of moment conditions: (i) restrictions on the...

Measurement error causes a downward bias when estimating a panel data linear regression model. The panel data context offers various opportunities to derive moment conditions that result in consistent GMM estimators. We consider three sources of moment conditions: (i) restrictions on the...