Profiling Tourists for Balanced Utilization of Tourism-Based Resources in Kenya

Kenya is predominantly a nature-based tourism destination with wildlife (concentrated in the southern part of the country) and beaches (along the Indian Ocean) accounting for over 85% of the international tourists visiting the country. Other attractions are based on the physical landscape of the country and the culture of the people. Unfortunately, the full potential of culture-based attractions has not been exploited. The over-concentration of tourism activities in wildlife protected areas and on the coastal zone has had inherent problems that include severe environmental degradation. The less visited attractions stand the risk of neglect and could be eroded from the nation’s heritage with time. There is need to diversify tourism activities and spread them to other parts of the country by putting more emphasis on non-traditional ones such as cultural excursions. This research profiles tourists based on their preferences as assessed from the number of days they spend at different attraction sites. By associating the characteristics of tourists with various attractions, consumer preference profiles were established. Length of stay, presence of children, travel party size and gender are some of the significant factors that determined the profiles. Profiles can be used in encouraging proportionately more tourists with greater affinity for non-traditional attractions. Besides gender, other factors such as socio-economic status and whether one is travelling as a couple or not, turned out to be significant variables in influencing the resulting expenditure levels.Tourist profiles, Attractions, Culture, Expenditure, LISREL, Kenya

A Structural Equation Approach to Spatial Dependence Models

A strong increase in the availability of space-time data has occurred during the past decades. This has led to the development of a substantial literature dealing with the two particular problems inherent to this kind of data, i.e. serial dependence between the observations on each spatial unit over time, and spatial dependence between the observations on the spatial units at each point in time (e.g. Elhorst, 2001, 2003). Typical for spatial panel data models is that the causal direction cannot be based on instantaneous relationships between simultaneously measured variables. Rather the so-called cross-lagged panel design studies compare the effects of variables on each other across time. Although they circumvent the difficult problem of assessing causal direction in cross-sectional research, the cross-lagged panel design studies are usually performed in discrete time (Oud, 2002). Because of different discrete time observation intervals within and between studies, outcomes are often incomparable or appear to be contradictory (Gollob & Reichardt, 1987). This paper will describe the problems of cross-lagged space-time models in discrete time and propose how these problems can be solved through a continuous time approach. In this regard special attention will be paid to structural equation modelling (SEM). In addition, we shall describe how space-time dependence can he handled in a SEM framework

Financing medical specialist services in the Netherlands; welfare implications of imperfect agency

From 1995 onward the financing scheme for specialist care in the Netherlands has moved from a fee-for-service scheme to a lump-sum budget scheme. This paper analyses the economic and welfare effects of this policy change. The paper adopts a model that integrates demand and supply considerations and recognizes the potential roles of moral hazard and supplier-induced demand. The model is fully numerical, being estimated and calibrated upon data for the Dutch health care sector. The paper finds that the shift in financing regime has been welfare-reducing. The policy change induced medical specialists to lower the supply of health services which was already too low from a welfare point of view. This conclusion is robust to significant changes in major parameter values.