In this paper, we study maximum likelihood estimation and Lagrange multiplier testing of a one-way error components regression model suitable for incomplete panel and including parametrically specified variance functions for both individual-specific and general error disturbances.

This paper proposes a range of parametric and nonparametric corrections to the GPH estimator of the differencing parameter in a fractionally integrated process. It is argued that the GPH estimator can suffer from an identification problem at the very low frequencies in the spectrum in small samples.

This paper proposes alternative methods for constructing estimators from accept-reject samples by incorporating the variables rejected by the algorithm.

This paper synthesises a global approach to both Bayesian and likelihood treatments of the estimation of the parameters of a hidden Markov model for the cases of normal and Poisson underlying distribution.

This paper puts forth a concept of Adptivety Rational Equilibrium (A.R.E) where agents base decisions upon predictions of future values of endogenous variables whose actual values are determined by equilibrium equations.

The estimation of quadratic functions of a multivariate normal mean is an inferential problem which, while being simple to state and often encountered in practice, leads to surprising complications both from frequentist and Bayesian points of view. The drawbacks of Bayesian inference using the...

In this paper we compare via Monte Carlo experiments some methods to estimate the parameter of long-range dependence. We then apply these procedures to a financial time series to investigate its long-memory properties. The evidence of smooth long-range dependence makes the usual Efficiency...

We consider truncated processes, both in discrete and continuous time, and study their dynamic properties. When the underlying process is a diffusion process, we derive the infinitesimal generator of its truncated counterpart. This result is the basis for the estimation of the drift and...

Brief summaries and user instruction are presented for the programs TRAMO ("Time Series regression with ARIMA Noise, Missing Observations and Outlers") and SEATS ("Signal Extraction in ARIMA Time Series").