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This study provides a case example, referred to the county of Valdeorras (Galicia, Spain), to analyse different alternatives of public investment for sustainable mobility in rural areas. First, we develop a transport model based on gravity models to obtain commuting-to-work patterns, means of transport and routes, calibrating the results with the patterns observed according to different sources. Then, we make our own projections ten years ahead on population growth, geographical distribution, and employment rates, to obtain two scenarios on future trends. In a third step, we analyse different alternatives for public policy targets on sustainable mobility using a multi-criteria approach. The costs of implementing the mobility actions are compared against two potential benefits: 1. a higher integration among the villages that conform the dynamic axis of the area, and of these with their rural hinterland; 2. reducing the environmental impact –in terms of fuel consumption levels. The mobility alternatives are compared following a simple Analytic Hierarchy Process. The analysis helps to identify the potential benefits of exploiting a currently underutilised railroad facility in the area of study. [ABSTRACT FROM AUTHOR]

We examine the interaction between a firm that uses either a dirty or a clean technology to produce a product over two periods, 1 and 2, and an environmentally conscious regulator that chooses the environmental tax/subsidy policy. The regulator ignores with which technology the firm manufactures the product and only has a prior belief about it. In this context, if the regulator can credibly commit to the policy for both periods, social welfare is generally higher than if it cannot commit, because distortions in firm's production at period 1 for signalling purposes strongly reduces the optimality of an environmental policy of short duration. A period-by-period policy in which the regulator does not commit to the policy terms for period 2 (which will be contingent to information provided by the firm in period 1) is only optimal when clean technology is very expensive to produce with it and the regulator's environmental concern is not very high. The results highlight the importance of taking into account the time horizon in policymaking, as well as the limitations of regulatory policies that seek to elicit information about the type of technology used by firms. [ABSTRACT FROM AUTHOR]