This paper investigates the finite sample distribution of the least squares estimator of the autoregressive parameter in a first-order autoregressive model. Uniform asymptotic expansion for the distribution applicable to both stationary and nonstationary cases is obtained. Accuracy of the...

The finite sample behaviour is analysed of particular least squares (LS) and method of moments (MM) estimators in panel data models with individual effects and both a lagged dependent variable regressor and another explanatory variable which may be affected by lagged feedbacks from the dependent...

We introduce a novel weighted least squares approach to estimate daily realized covariation and microstructure noise variance using high-frequency data. We provide an asymptotic theory and conduct a comprehensive Monte Carlo simulation to demonstrate the desirable statistical properties of the...

When using a model for prediction, or for representing the data, the percentage error may be more important than the absolute error. We therefore present the method of least squares regression based on percentage errors. Exact expressions are derived for the coefficients, and we show how models...