The aim of this study is to assess whether combining econometric models with different explanatory variables can contribute better tourism demand forecasts. Inbound the UK from seven leading markets forecast, respectively, based on quarterly data using both individual and combination models. Causal that serve as constituents in take two specifications which are identified influencing factors. e...

BACKGROUND Developing countries have witnessed economic growth as their GDP keeps increasing steadily over the years. The growth led to higher energy consumption which eventually leads to increase in air pollutions that pose a danger to human health. People's healthcare demand, in turn, increase due to the changes in the socioeconomic life and improvement in the health technology. This study is...

We consider the problem of model selection for geospatial data. Spatial correlation is often ignored in the selection of explanatory variables, and this can influence model selection results. For example, the importance of particular explanatory variables may not be apparent when spatial correlation is ignored. To address this problem, we consider the Akaike Information Criterion (AIC) as appli...

This chapter gives an account of the recent literature on estimating models for panel count data. Specifically, the treatment of unobserved individual heterogeneity that is correlated with the explanatory variables and the presence of explanatory variables that are not strictly exogenous are central. Moment conditions are discussed for these type of problems that enable estimation of the parame...

This paper investigates the impact of the introduction of transactional Internet banking on performance and risk profile of major credit unions in Australia. Performance was measured using linear programming technique of data envelopment analysis and regressed on relevant explanatory variables using censored normal regression. Accounting data were used to measure risk profile and regressed on r...

The weighted likelihood approach is used to perform robust inference on the parameters in a generalized linear models. We distinguish the case of replicated observations of the dependent variable for each combination of the explanatory variables, common in the design of experiment framework, and the case of one observation for each combination of the explanatory variables, very common in observ...

SUMMARY Cook, Gold, and Li (2007, Biometrics 63, 540-549) extended the Kulldorff (1997, Communications in Statistics 26, 1481-1496) scan statistic for spatial cluster detection to survival-type observations. Their approach was based on the score statistic and they proposed a permutation distribution for the maximum of score tests. The score statistic makes it possible to apply the scan statisti...