Uncertainty,cost-effectiveness and environmental safety of robust carbon trading: integrated approach

Carbon markets, like other commodity markets, are volatile. They react to stochastic “disequilibrium” spot prices, which may be affected by inadequate policies, speculations and bubbles. The market-based emission trading, therefore, does not necessarily minimize abatement costs and achieve emission reduction goals. We introduce a basic stochastic model integrating emissions reduction, monitoring and trading costs allowing us to analyze the robustness of emission and uncertainty reduction policies under environmental safety constraints asymmetric information and other multiple anthropogenic and natural uncertainties. Explicit treatment of uncertainties provides incentives for reducing them before trading. We illustrate functioning of the robust market with numerical results involving such countries as the US, Australia, Canada, Japan, EU27, Russia, Ukraine. In particular, we analyze if the knowledge about uncertainties may affect portfolios of technological and trade policies or structure of the market and how uncertainty characteristics may affect market prices and change the market structure.     

Carbon emission trading and carbon taxes under uncertainties

The idea of market-based carbon emission trading and carbon taxes is gaining in popularity as a global climate change policy instrument. However, these mechanisms might not necessarily have a positive outcome unless their value reflects socioeconomic and environmental impacts and regulations. Moreover, the fact that they have various inherent exogenous and endogenous uncertainties raises serious concerns about their ability to reduce emissions in a cost-effective way. This paper aims to introduce a simple stochastic model that allows the robustness of economic mechanisms for emission reduction under multiple natural and human-related uncertainties to be analyzed. Unlike standard equilibrium state analysis, the model shows that the explicit introduction of uncertainties regarding emissions, abatement costs, and equilibrium states makes it almost impossible for existing market-based trading and carbon taxes to be environmentally safe and cost-effective. Here we propose a computerized multi-agent trading model. This can be viewed as a prototype to simulate an emission trading market that is regulated in a decentralized way. We argue that a market of this type is better equipped to deal with long-term emission reductions, their direct regulation, irreversibility, and “lock-in” equilibria.     

Risk-adjusted approaches for planning sustainable agricultural development

In this paper we show that explicit treatment of risks and uncertainties in agricultural production planning may considerably alter strategies for achieving robust outcomes with regard to sustainable agricultural developments. We discuss production planning models under uncertainties and risks that may assist in planning location-specific production expansion within environmental and health risk indicators and constraints. The proposed approaches are illustrated with the example of spatially explicit livestock production allocation in China to 2030.