New results for ratios of extremes from distributions with a regularly varying tail are presented. Deriving from independence results for certain functions of order statistics, 'consecutive' ratios of extremes are shown to be independent as well as non-distribution specific. They have tractable...

This paper compares two alternative models for autocorrelated count time series. The first model can be viewed as a 'single source of error' discrete state space model, in which a time-varying parameter is specified as a function of lagged counts, with no additional source of error introduced....

This paper investigates the distributional implication of inflation in Australia. It proposes and applies a method of evaluating the nature and size of the inequality bias of price movements. In the process, the study introduces a new demographic demand model that yields sensible and well...

This study compares the evidence on corruption between alternative data sets. These include the Corruption Perceptions Indices (CPI) that are conventionally used and the micro data sets from the International Crime Victim Surveys (ICVS) and the World Bank Enterprise Surveys (WBES) that have been...

This paper explores the link between crime and corruption, compares their magnitudes, determinants and their effects on growth rates. The study uses a large cross country data set containing individual responses to questions on crime and corruption along with information on the respondents’...

A Kalman filter, suitable for application to a stationary or a non-stationary time series, is proposed. It works on time series with missing values. It can be used on seasonal time series where the associated state space model may not satisfy the traditional observability condition. A new...

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...

The presence of nuisance parameters causes unwanted complications in statistical and econometric inference procedures. A number of modified likelihood and message length functions have been developed for better handling of nuisance parameters but they are not equally efficient. In this paper, we...

The problem of constructing prediction intervals for linear time series (ARIMA) models is examined. The aim is to find prediction intervals which incorporate an allowance for sampling error associated with parameter estimates. The effect of constraints on parameters arising from stationary and...

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.