We derive expressions for the first-order bias of the MLE for a Poisson regression model and show how these can be used to adjust the estimator and reduce bias without increasing MSE. The analytic results are supported by Monte Carlo simulations and three illustrative empirical applications.

Extreme Value Theory (EVT) measures the behaviour of extreme observations on a random variable. EVT in risk management, an approach to modelling and measuring risks under rare events, has taken on a prominent role in recent years. This article contributes to the literature in two respects by...

In this article, we compare the forecasting performances of the Self-Exciting Threshold Autoregressive (SETAR) model and a fuzzy clustering regression model. The series used in this study are high-frequency financial data in the form of seven major stock prices in the US stock markets; the stock...

In this study we suggest a Bayesian approach to fuzzy clustering analysis – the Bayesian fuzzy regression. Bayesian Posterior Odds analysis is employed to select the correct number of clusters for the fuzzy regression analysis. In this study, we use a natural conjugate prior for the...

With $4.5 trillion in total assets, the People’s Bank of China now surpasses the U.S. Federal Reserve as the world’s biggest central bank. The Rise of the People’s Bank of China investigates how this increasingly authoritative institution grew from a Leninist party-state that once...

In this paper we investigate the impact of data revisions on forecasting and model selection procedures. A linear ARMA model and nonlinear SETAR model are considered in this study. Two Canadian macroeconomic time series have been analyzed: the real-time monetary aggregate M3 (1977-2000), and...

There is now an extensive empirical literature relating to tests for various forms of convergence between the real per capita outputs of different countries. The evidence from these tests is mixed, and depends upon the type of data used, the countries in question, and the sample period in...

In this study we suggest a Bayesian approach to fuzzy clustering analysis – the Bayesian fuzzy regression. Bayesian Posterior Odds analysis is employed to select the correct number of clusters for the fuzzy regression analysis. In this study, we use a natural conjugate prior for the...

In this paper we investigate the forecasting performance of the non-linear time series SETAR model by using Canadian GDP data from 1965 to 2000. Besides the with-in-sample fit, the forecasting performance of a standard linear ARIMA model for the same sample has also been generated for...