Resource and Energy Economics最新文献

The literature on how price changes affect optimally managed fisheries is mostly concerned with how fish stocks and harvest rates are affected in steady state. There is little published on how prices affect optimal harvest rates at stock levels outside of steady state. Here we show the effect of an unanticipated and permanent price increase. It is shown that in a model of a pure schooling fishery, if the stock is below the steady state, it is optimal to harvest less if the price goes up and vice versa. It is also shown that in a model with stock dependent harvest costs, the optimal response to a price increase is to reduce the harvest rate for low stock levels even if the optimal harvest rate increases close to the steady state. Empirical relevance is demonstrated by illustrating the theoretical results in an estimated model.

Natural resources such as fish, and wildlife have the ability to move across different areas within an ecosystem. Such movements are subject to random changes in environmental conditions (e.g., nutrients, temperature, oxygen). Although empirical evidence suggests that learning about such movements helps improve management, the related economic literature concentrates on scenarios in which the resource population lives in a closed area and cannot migrate. In this paper, we develop a spatial bioeconomic model to examine a renewable resource harvester’s responses to learning about fish movements. Our baseline is the scenario in which the harvester is fully informed about the distribution of fish movements. We find that introducing uncertainty and learning about fish movements critically affects extraction incentives. For instance, we show that uncertainty and learning may increase harvest in a patch and reduce harvest in another patch when the marginal harvesting cost function is constant. In the stock dependent marginal harvesting cost case, we delineate conditions under which uncertainty and learning increase harvest in all patches. We also show how harvest responses to learning change with the distribution of uncertainty.

This paper compares two regimes of tradable emission permits, a regime with international permit trade (IPT) and a regime with domestic permit trade (DPT). We focus on the effects of the distribution of firms between countries. Our model combines intra-industry trade with a monopolistically competitive industry. We find that a more equal distribution of firms between countries results in higher global pollution under the DPT regime, while under the IPT regime the global pollution is invariant with the distribution of firms. We also find that international permit trade can either increase or reduce global pollution, depending on the distribution of firms.

Previous laboratory evidence suggests that people tend to value their decision right beyond its instrumental value. We measure the intrinsic value of decision rights in the context of switching the electricity provider. We focus on customers of an online platform who can either choose a service that reminds them when they are allowed to switch their electricity contract or a service that automatically switches the contract on their behalf whenever possible. Our focus is on the intrinsic value of decision rights as a potential obstacle of this choice automation. Surprisingly, we find that customers who make use of the automation service assign significantly higher intrinsic value to their decision rights, compared to those who opted for the mere reminder. Hence, there appears to be a connection between having a high intrinsic value of decision rights and the level of interest in attributes of the automation service under consideration. The positive correlation suggests that the widespread positive intrinsic value of decision rights and the future adoption of similar automation services and devices do not necessarily contradict each other.

This paper uses a stochastic optimal control model to show how standard loan contracts create incentives for farmers to focus on short-term financial performance at the expense of farms’ long-term natural capital. These incentives are a manifestation of the debt overhang problem. Extending this model shows how sustainability-linked loans can be used to weaken these incentives in a way that potentially benefits farmers and their bankers. The magnitude of the economic benefits generated by these loans depends on farm characteristics. The paper investigates the optimal design of sustainability-linked loans.