The author analyses the implications of tourism activities on economic growth and environmental assets, focusing especially on small island countries. She develops a stylized dynamic economic model in which tourism is the trigger of the incentive mechanism leading to abatement activities and economic growth. The basic idea is that tourists choose the location to visit according to a number of factors (including environmental quality) which are affected by residents' choices. If residents engage in environmental protection activities, it then may be possible for environmentally-based tourism economies to reach a smooth development process. The author shows that the (sustainable) balanced growth path is the only viable equilibrium, and along such a path consumption grows while environmental quality rises. Tourists' preferences crucially affect the long-run outcome, since economic and environmental growth rates increase with the green preference and decrease with the grey preference and crowding aversion parameters. Thus, if tourism specialization is to be the pathway to development, green tourism will need to be promoted.

We analyze the spatio-temporal dynamics of capital and pollution in an economic growth model with purposive environmental protection activities. The production process of a unique homogeneous good generates pollution, thus the increases in output associated with economic growth tend to rise the stock of pollution. Pollution is a negative production externality which thus feeds back on the economy lowering the level of output; in order to compensate for such a negative effect associated with economic development, pollution is reduced by publicly funded abatement activities. We firstly consider a Solow-type framework in which economic and environmental policies are completely exogenous, and then we move to a Ramsey-type context in which they are endogenously determined. We analyze the spatio-temporal dynamics of the model economy through numerical simulations, and we consider two different specifications of the production function (a globally concave and a convex-concave technology) in order to stress the role that eventual poverty traps might play on both economic and environmental outcomes. We show that in the convexconcave technology framework, whenever rich regions are substantially rich diffusion can help poor regions to escape their poverty traps; if however they are not rich enough diffusion might condemn also rich regions to collapse. However, even if rich regions are particularly rich whenever the pollution externality is strong, the whole spatial economy might be doomed to collapse. Forthcoming in Mathematical Social Sciences AbstractWe analyze the spatio-temporal dynamics of capital and pollution in an economic growth model with purposive environmental protection activities. The production process of a unique homogeneous good generates pollution, thus the increases in output associated with economic growth tend to rise the stock of pollution. Pollution is a negative production externality which thus feeds back on the economy lowering the level of output; in order to compensate for such a negative effect associated with economic development, pollution is reduced by publicly funded abatement activities. We firstly consider a Solow-type framework in which economic and environmental policies are completely exogenous, and then we move to a Ramseytype context in which they are endogenously determined. We analyze the spatio-temporal dynamics of the model economy through numerical simulations, and we consider two different specifications of the production function (a globally concave and a convex-concave technology) in order to stress the role that eventual poverty traps might play on both economic and environmental outcomes. We show that in the convex-concave technology framework, whenever rich regions are substantially rich diffusion can help poor regions to escape their poverty traps; if however they are not rich enough diffusion might condemn also rich regions to collapse. However, even if rich regions are particularly rich whenever the pollution externality is strong, the whole spatial economy mi...

We analyze the impact of financial development on economic growth. Differently from previous studies that focus mainly on balanced growth path outcomes, we also analyze the transitional dynamics of our model economy by using a finance‐extended Uzawa–Lucas framework where financial intermediation affects both human and physical capital accumulation. We show that, under certain rather general conditions, economic growth may turn out to be non‐monotonically related to financial development (as suggested by the most recent empirical evidence) and that too much finance may be detrimental to growth. We also show that the degree of financial development may affect the speed of convergence, which suggests that finance may play a crucial role in determining the length of the recovery process associated with exogenous shocks. Moreover, in a special case of the model, we observe that, under a realistic set of parameters, social welfare decreases with financial development, meaning that even when finance positively affects economic growth the short‐term costs associated with financial activities more than compensate their long‐run benefits.

Tourism specialization on the one hand may be a successful tool to achieve fast economic growth, and, on the other hand, may be detrimental for natural resources. Finding the right balance between economic benefits and environmental costs is essential to reach sustainable development, ensuring that tourist numbers do not exceed the carrying capacity of the tourism destination. In this context, the author analyses the determination of the optimal number of visitors in a tourism-based economy and shows that if the tourist number is optimally determined long-run sustainable growth will be possible. He also shows that the optimal number of tourists is strictly smaller than the carrying capacity of the tourism destination, and that such a condition is vital to achieve long-run growth.

Goal programming (GP) is an important class of multi-criteria decision models widely used to analyze and solve applied problems involving conflicting objectives. Originally introduced in the 1950s by Charnes et al. (Manag Sci 2:138-151, 1955) the popularity and applications of GP has increased immensely due to the mathematical simplicity and modeling elegance. Over the recent decades algorithmic developments and computational improvements have greatly contributed to the diverse applications and several variants of GP models. In this paper we present a state of the art literature review on GP applications in three selected (prominent and popular) areas, namely engineering, management and social sciences. Forthcoming in Annals of Operations ResearchAbstract Goal programming (GP) is an important class of multi-criteria decision models widely used to analyze and solve applied problems involving conflicting objectives. Originally introduced in the 1950s by Charnes et al. (1955) the popularity and applications of GP has increased immensely due to the mathematical simplicity and modeling elegance. Over the recent decades algorithmic developments and computational improvements have greatly contributed to the diverse applications and several variants of GP models. In this paper we present a state of the art literature review on GP applications in three selected (prominent and popular) areas, namely engineering, management and social sciences.