The problem considered in this paper is how to find reliable prediction intervals with simple exponential smoothing and trend corrected exponential smoothing. Methods for constructing prediction intervals based on linear approximation and bootstrapping are proposed.

It is well known that the usual techniques for estimating random and fixed effects panel data models are inconsistent in the dynamic setting. As a consequence, numerous consistent estimators have been proposed in the literature. However, all such estimators rely on certain well defined...

This paper is concerned with model selection based on penalized maximized log likelihood function. Its main emphasis is on how these penalities might be chosen in small samples to give good statistical properties.

A Bayesian approach is presented for nonparametric estimation of an additive regression model with autocorrelated errors.

The main objective of this study is to investigate the rebustness of the popular Durbin-Watson (DW), Langrage multiplier (LM), Box-Pierce (BP) and Ljung-Box (LB) tests and their corrected versions against autoregressive distrurbances in the presence of dynamic heteroscedastic disturbances with...

In this paper two new estimators are offred (one each for the fixed random effects specifications), and small sample performance compared with that of all the existing estimators.

The analysis of economic time series assumes specific economic behaviour of a representative agent. The data used in analysis is generated by aggregating observations of all individuals in a population. This is valid only if all members of a population have the same data generating process, but...

Using vector autoregressive (VAR) models and Monte-Carlo simulation methods we investigate the potential gains for forecasting accuracy and estimation uncertainty of two commonly used restrictions arising from economic relationships. The first reduces parameter space by imposing long-term...

We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We consider model selection criteria which have data-dependent penalties for a...