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Foreign direct investment has been extensively recognised as an important resource of economic growth. Governments have been playing an active role in encouraging this type of investment. Despite efforts by governments, only a few countries have been successful in attracting investment for their tourism industry. The purpose of this paper is to detect meaningful relationships between government policies and investment.

This study utilizes statistical and machine learning techniques. A predictive model has been constructed and evaluated using a set of countries, which differ from those putatively used for model generation. Good governance indicators, together with data about investments in the tourism industry, are the main instruments used in the model.

The findings suggest that the formulation and implementation of sound policies, together with regulations, promotes the development of a private sector; and the private sector has a significant role in attracting tourism investment.

The study contributes to research in the tourism industry by using intelligent data analysis techniques.

The availability of comprehensive datasets and a very limited set of empirical studies, related to investment in the tourism industry, has stimulated this research to focus on integrating quantitative resources and assessing the significance of government policies.

This paper aims to present a multi-period dynamic power project financing model to produce pragmatic estimates of benchmark wholesale power prices based on the principles of normal profit. This, in turn, can guide policymakers as to whether price spikes or bidding above marginal cost in wholesale electricity markets warrants any investigation at all. One of the seemingly complex areas associated with energy-only wholesale electricity pools is at what point market power abuse is present on the supply side. It should not be this way. If a theoretically robust measure of normal profit exists, identification of potential market power abuse is straightforward. Such a definition readily exists and can be traced back to the ground-breaking work of financial economists in the 1960s.

Using a multi-period dynamic power project model, the authors produce pragmatic and theoretically robust measures of normal profit for project financed plant and plant financed on balance sheet. These model results are then integrated into a static partial equilibrium model of a power system. The model results are in turn used to guide policymaking on generator bidding in energy-only power markets.

Under conditions of perfect plant availability and divisibility with no transmission constraints, energy-only markets result in clearing prices which are not economically viable in the long run. Bidding must, therefore, deviate from strict short-run marginal cost at some stage. To distinguish between quasi-contributions to substantial sunk costs and market power abuse, a pragmatic and robust measure of normal profit is required.

This article finds policymakers can be guided by an ex-post analysis of base energy prices against pragmatic estimates for the long-run marginal cost of the base plant, and an ex-ante analysis of call option prices along the forward curve against pragmatic estimates of the carrying cost of the peaking plant.