Two stage model of ecological and economic decisions

Imperfection of ecological and economic decisions should be corrected by certain programs of public-private partnership. It is important to suggest and substantiate incentives for participation in such programs. The two-stage approach for making strategic and adaptive ecological and economic decisions is proposed

Induced Discounting and Risk Management

The goal of this paper is to specify and summarize assumptions and proofs for new approaches to discounting proposed inour catastrophic risk management studies. The main issue is concerned with justification of investments, which may turn into benefits over long and uncertain time horizon. For example, how can we justify mitigation efforts for expected 300-year flood that can occur also next year. The discounting is supposed to impose time preferences to resolve this issue, but this view may be dramatically misleading. We show that any discounted infinite horizon sum of values can be equivalently replaced by undiscounted sum of the same values with random finite time horizon. The expected duration of this stopping time horizon for standard discount rates obtained from capital markets does not exceed a few decades and therefore such rates may significantly underestimate the net benefits of long-term decisions. The alternative undiscounted random stopping time criterion allows to induce social stopping time discounting focusing on arrival times of potential extreme events rather then horizons of market interests. In general, induced discount rates are conditional on the degree of social commitment to mitigate risk. Random extreme events affect these rates, which alter the optimal mitigation efforts that, in turn, change events This endogeneity of the induced discounting restricts exact evaluations necessary for using traditional deterministic methods and it calls for stochastic optimisation methods. The paper provides insights in the nature of discounting that are critically important for developing robust long-term risk management strategies

Discounting and catastrophic risk management

The risk management of complex coupled human-environmental systems essentially relies on discounting future losses and gains to their present values. These evaluations are used to justify catastrophic risks management decisions which may turn into benefits over long and uncertain time horizons. The misperception of proper discounting rates critically affects evaluations and may be rather misleading. Catastrophes are not properly treated within conventional economic theory. The lack of proper evaluations dramatically contributes to increasing the vulnerability of our society to human-made and natural disasters. Underestimation of rare low probability - high consequences potentially catastrophic scenarios (events) have led to the growth of buildings and industrial land and sizable value accumulation in flood (and other disaster) prone areas without paying proper attention to flood mitigations. A challenge is that an extreme event, say a once-in-300-year flood which occurs on average only once in 300 years, may have never occurred before in a given region. Therefore, purely adaptive policies relying on historical observations provide no awareness of the risk although, a 300-year flood may occur next year. For example, floods in Austria, Germany and the Czech Republic in 2002 were classified as 1000-, 500-, 250-, and 100-year events. Chernobyl nuclear disaster was evaluated as 106-year event. Yet common practice is to ignore these types of events as improbable events during a human lifetime. This paper analyzes the implications of potentially catastrophic events on the choice of discounting for long-term catastrophic risk management. It is shown that arbitrary discounting can be linked to "stopping time" events, which define the discount-related random horizon ("end of the world") of valuations. In other words, any discounting compares potential gains and losses only within a finite random discount-related stopping time horizon. The expected duration of this horizon for standard discount rates obtained from capital markets does not exceed a few decades and, as such, these rates cannot properly evaluate impacts of 1000-, 500-, 250-, 100- year catastrophes. The paper demonstrates that the correct discounting can be induced by the concept of stopping time, i.e. by explicit modelling of arrival time scenarios of potential catastrophes. In general, catastrophic events affect the induced discount rates, which alter the optimal mitigation efforts that, in turn, change events. The paper shows that stopping-time related discounting calls for the use of stochastic optimisation methods. Combined with explicit spatio-temporal catastrophe modelling, this induces the discounting which allows to properly focus risk management solutions on arrival times of potential catastrophic events rather then horizons of capital markets

The Optimal Technological Development Path to Reduce Pollution and Restructure Iron and Steel Industry for Sustainable Transition

China is the world’s largest iron and steel producer and Jing-Jin-Ji (Beijing-Tianjin-Hebei) region accounts for nearly 1/3 of the national iron and steel production, while it is facing serious air pollution. Among the top 10 worst polluted cities in China, seven were located in Hebei province in 2014. Recent years Jing-Jin-Ji region has been promoted iron & steel industry with green clean technology for accelerating sustainable economic transition. This paper tries to response the basic questions: How can we reduce pollution and restructure the iron and steel industry for sustainable economic transition in Jing-Jin-Ji? How can the iron-steel industry achieve its 13th five year plan targets? How does its outlook look like in the next 10 years? For the analysis, we develop a dynamic optimization model to explore the optimal technological development path of iron and steel industry under the environment (CO2, SO2, NOx, and PM2.5) in combing with overcapacity reduction targets over the next 10 years. The results show that increasing capacity of scrap-EAF and DRI-EAF technologies can significantly co-decrease CO2, SO2, NOx and PM2.5 by 50%, 60%, 57%, and 62% respectively. The optimal technological portfolio indicates that the production share of EAF technology will increase with the potential increase trends of scrap volumes. The paper indicates that in China, iron and steel production shift from BOF to EAF technology is an optimal way for lower energy/CO2 and air pollutants emissions, and for iron and steel industry transition to green and sustainable development. The paper argues that reducing iron and steel production volume does not mean stopping iron and steel industry development, but low-carbon and green development in the iron & steel industry, it can achieve the goal for sustainable transition in the region

Optimizing Regional Food and Energy Production under Limited Water Availability through Integrated Modeling

Across the world, human activity is approaching planetary boundaries. In northwest China, in particular, the coal industry and agriculture are competing for key limited inputs of land and water. In this situation, the traditional approach to planning the development of each sector independently fails to deliver sustainable solutions, as solutions made in sectorial ‘silos’ are often suboptimal for the entire economy. We propose a spatially detailed cost-minimizing model for coal and agricultural production in a region under constraints on land and water availability. We apply the model to the case study of Shanxi province, China. We show how such an integrated optimization, which takes maximum advantage of the spatial heterogeneity in resource abundance, could help resolve the conflicts around the water–food–energy (WFE) nexus and assist in its management. We quantify the production-possibility frontiers under different water-availability scenarios and demonstrate that in water-scarce regions, like Shanxi, the production capacity and corresponding production solutions are highly sensitive to water constraints. The shadow prices estimated in the model could be the basis for intelligent differentiated water pricing, not only to enable the water-resource transfer between agriculture and the coal industry, and across regions, but also to achieve cost-effective WFE management

Design of Flood-loss Sharing Programs in the Upper Tisza Region, Hungary: A dynamic multi-agent adaptive Monte Carlo approach

Losses from human-made and natural catastrophes are rapidly increasing. The main reason for this is the clustering of people and capital in hazard-prone areas as well as the creation of new hazard-prone areas, a phenomenon that may be aggravated by a lack of knowledge of the risks. This alarming human-induced tendency calls for new integrated approaches to catastrophic risk management. This paper demonstrates how flood catastrophe model and adaptive Monte Carlo optimization can be linked into an integrated Catastrophe Management Model to give insights on the feasibility of a flood management program and to assist in designing a robust program. As a part of integrated flood risk management, the proposed model takes into account the specifics of the catastrophic risk management: highly mutually dependent losses, the lack of information, the need for long-term perspectives and geographically explicit models, the involvement of various agents such as individuals, governments, insurers, reinsurers, and investors. Therefore, the integrated catastrophe management model turns out to be an important mitigation measure in comprehending catastrophes. As a concrete case we consider a pilot region of the Upper Tisza river, Hungary. Specifically, we analyze the demand of the region in a multipillar flood-loss sharing program involving a partial compensation by the central government, a voluntary private property insurance, a voluntary private risk-based insurance GIS-based catastrophe models and specific stochastic optimization methods are used to guide policy analysis with respect to location-specific risk exposures. To analyze the stability of the program, we use economically sound risk indicators