Fisheries Management under Irreversible Investment: Does Stochasticity Matter?

We present a continuous, nonlinear, stochastic and dynamic model for capital investment in the exploitation of a renewable resource. Both the resource stock and capital stock are treated as state variables. The resource owner controls fishing effort and the investment rate in an optimal way. Biological stock growth and capital depreciation rate are stochastic in the model. We find that the stochastic resource should be managed conservatively. The capital utilization rate is found to be a non-increasing function of stochasticity. Investment could be either higher or lower depending on the interaction between the capital and the resource stocks. In general a stochastic capital depreciation rate has only weak influence on optimal management. In the long run, the steady state harvest for a stochastic resource becomes lower than the deterministic level.Physical capital; irreversible investment; stochastic growth; long-term sustainable optimal

Forage fish interactions: A symposium on creating the tools for ecosystem-based management of marine resources

Forage fish (FF) have a unique position within marine foodwebs and the development of sustainable harvest strategies for FF will be a critical step in advancing and implementing the broader, ecosystem-based management of marine systems. In all, 70 scientists from 16 nations gathered for a symposium on 12–14 November 2012 that was designed to address three key questions regarding the effective management of FF and their ecosystems: (i) how do environmental factors and predator–prey interactions drive the productivity and distribution of FF stocks across ecosystems worldwide, (ii) what are the economic and ecological costs and benefits of different FF management strategies, and (iii) do commonalities exist across ecosystems in terms of the effective management of FF exploitation

Concerns among local government facility managers

Purpose: To investigate which concerns are most important for local government facility managers in Norway. Design: We analyze a survey dataset covering about 2/3 of all Norwegian local governments, using descriptive statistics techniques. Findings: The facility managers are most worried about weak fiscal conditions and lack of political priority of facility management. Almost all facility managers report concerns about these issues, and the responses do not vary much across local governments with different characteristics. There is also widespread concern, albeit less serious, about organizational structure and recuitment problems. Local governments with a decentralized facility management are more concerned about the organizational structure than those with a centralized structure, and low-population local governments are more concerned about recruitment problems than those with a high population. Finally, local governments that report that their public buildings are in good condition generally have fewer and less serious concerns, in line with what one could expect. Originality/value: The paper offers insights into which concerns that are most important among local government facility managers

Building conditions in Norwegian local governments : trends and determinants

In light of evidence of low levels of maintenance of public buildings, we investigate trends and determinants of public building conditions in Norwegian local governments. On average, the condition of Norwegian local public facilities have improved slightly in the period 2004 - 2016. Survey data suggest substantial fluctuations in building conditions and a negative relationship between building conditions in 2004 and 2016. A driver behind this result is high investments in local governments with poor building conditions in 2004. Further, we find no systematic relationship between the conditions in 2004 and maintenance expenditures in subsequent years. We conclude that if maintenance levels are too low, investment levels may be too high. Generally, our results hint at an unhealthy balance between maintenance spending and public spending. Finally, we find that both political and fiscal factors are important in explaining building conditions

Harvesting in a Fishery with Stochastic Growth and a Mean-Reverting Price

We analyze a continuous, nonlinear bioeconomic model to demonstrate how stochasticity in the growth of fish stocks affects the optimal exploitation policy when prices are stochastic, mean-reverting and possibly harvest dependent. Optimal exploitation has nonlinear responses to the price signal and should be conservative at low levels of biological stochasticity and aggressive at high levels. Price stochasticity induces conservative exploitation with little or no biological uncertainty, but has no strong effect when the biological uncertainty is larger. We further observe that resource exploitation should be conservative when the price reverts slowly to the mean. Simulations show that, in the long run, both the stock level and the exploitation rate are lower than in the deterministic solution. With a harvest-dependent price, the long-run price is higher in the stochastic system. The price mean reversion rate has no influence on the long-run solutions. Key words Feedback policy, fisheries management, Hamilton-Jacobi-Bellman approach, mean-reversion, stochastic optimization.acceptedVersio

An analysis of maintenance schedules for public facilities

We present a flexible, formal framework for maintenance scheduling for public facilities. Key features of the model include an accelerating deterioration scheme, a general utility measure, and real estate market effects in the salvage function. The model is rich enough to capture a range of stylistic scenarios pertaining to public facilities while remaining simple enough to allow formal analysis of the optimal maintenance schedule. Based on our analysis, we draw a phase diagram that classifies the generic behavior of the optimal solution. We illustrate our analysis in numerical examples that highlight essential trade-offs and the time dependence of the facility maintenance problem. Under simplifying assumptions, we also derive the basics of an exact solution.publishedVersio

Greed is good: from super-harvest to recovery in a stochastic predator-prey system

This paper demonstrates a predator-prey system of cod and capelin that confronts a possible scenario of prey extinction under the first-best policy in a stochastic world. We discover a novel ‘super-harvest’ phenomenon that the optimal harvest of the predator is even higher than the myopic policy, or the ‘greedy solution’, on part of the state space. This intrinsic attempt to harvest more predator to protect the prey is a critical evidence supporting the idea behind ‘greed is good’. We ban prey harvest and increase predator harvest in a designated state space area based on the optimal policy. Three heuristic recovery plans are generated following this principle. We employ stochastic simulations to analyse the probability of prey recovery and evaluate corresponding costs in terms of value loss percentage. We find that the alternative policies enhance prey recovery rates mostly around the area of 50% recovery probability under the optimal policy. When we scale up the predator harvest by 1.5, the prey recovery rate escalates for as much as 28% at a cost of 5% value loss. We establish two strategies: modest deviation from the optimal on a large area or intense measure on a small area. It seems more cost-effective to target the stock space with accuracy than to simply boost predator harvest when the aim is to achieve remarkable improvement of prey recovery probability

A bridge between continuous and discrete-time bioeconomic models: Seasonality in fisheries

We develop a discretization method for continuous-time bioeconomic models. Based on this method, we develop a discrete-time bioeconomic model to analyze seasonality in fisheries. The discretization method consists of three steps: first, we estimate a proper growth function for the continuous-time model with the ensemble Kalman Filter. Second, we use the Runge-Kutta method to discretize the growth function. Third, we use the Bellman approach to analyze optimal management of seasonal fisheries in a discrete-time setting. We analyze both the case of quarterly harvest and the case of monthly harvest, and we compare these cases with the case of annual harvest. We find that seasonal harvesting is a win-win optimal solution with higher harvest, higher optimal steady state equilibrium, and higher economic value than obtained in the case of annual harvesting. We also demonstrate that the discretization method overcomes the errors and preserves the strengths of both continuous and discrete-time bioeconomic models

A bridge between continuous and discrete-time bioeconomic models: Seasonality in fisheries

We develop a discretization method to construct a discrete finite-time bioeconomic model, corresponding to bioeconomic models with continuous-time growth function, but allowing the analysis of seasonality in fisheries. The discretization method consists of three steps: first, we estimate a proper growth function for the continuous-time model with the Ensemble Kalman Filter. Second, we use the Runge-Kutta method to discretize the growth function. Third, we use the Bellman approach to analyze the optimal management of seasonal fisheries in a discrete-time setting. We analyze both the case of quarterly harvest and the case of monthly harvest, and we compare these cases with the case of annual harvest. We find that seasonal harvesting is a win–win optimal solution that provides higher harvest, higher optimal steady state equilibrium, and higher economic value than annual harvesting. We also demonstrate that the discretization method overcomes the errors and preserves the strengths of both continuous and discrete-time bioeconomic models.submittedVersio