Warum und wie die Liberalisierung des Cannabismarktes in Deutschland erfolgen sollte

Wirtschaftsdienst - Der vorliegende Beitrag fasst die Argumente für eine Legalisierung von Cannabis zusammen und macht Vorschläge zur Ausgestaltung des Regulierungsrahmens. Hauptargument...     

Integrated bio-economic models as tools to support land-use decision making: a review of potential and limitations

Bio-economic modelling has become a useful tool for anticipating the outcomes of policies and technologies before their implementation. Advances in mathematical programming have made it possible to build more comprehensive models. In an overview of recent studies about bio-economic models applied to land-use problems in agriculture and forestry, we evaluated how aspects such as uncertainty, multiple objective functions, system dynamics and time have been incorporated into models. We found that single objective models were more frequently applied at the farm level, while multiple objective modelling has been applied to meet concerns at the landscape level. Among the objectives, social aspects are seldom represented in all models, when being compared to economic and environmental aspects. The integration of uncertainty is occasionally a topic, while stochastic approaches are more frequently applied than non-stochastic robust methods. Most multiple-objective models do not integrate uncertainty or sequential decision making. Static approaches continue to be more recurrent than truly dynamic models. Even though integrating multiple aspects may enhance our understanding of a system; it involves a tradeoff between complexity and robustness of the results obtained. Land-use models have to address this balance between complexity and robustness in order to evolve towards robust multiple-objective spatial optimization as a prerequisite to achieve sustainability goals.     

Cost-effective compensation to avoid carbon emissions from forest loss: An approach to consider price-quantity effects and risk-aversion

Analyses were carried out on financial compensation to avoid loss of tropical forests and related carbon (C) emissions when marginal financial yield declined for land-use options with extended areas, and when a risk-averting perspective (modeled according to financial theory around the capital asset pricing model) is assumed. The approach in this study was to consider natural forest, forest plantation, pasture, and cropland simultaneously to investigate how an optimized land-use distribution may reduce the amount of compensation necessary to avoid C emissions from forest loss.The financial compensations derived were as high as US$ 176 per hectare per year when comparing natural forests only with the most profitable alternative (croplands). However, compensation decreased to US$ 124 for risk-neutral decision-makers, who would strive for optimized land-use allocation, and to only US$ 47 per hectare per year for risk-avoiders, who would look to maximize the reward-to-variability ratio. Sensitivity analyses indicated that the compensation under risk-aversion increased much less than under risk-ignoring when increased productivity of agricultural land-use or growing demand for agricultural products was simulated. It was concluded that considering appropriate diversification strategies and the well documented human behavior to avoid risks is an important step in developing cost-effective compensation policies.     

Political Partisanship:

A bstract Analysis of the bases of political party choice in the United States reveals that social structural factors are more important than economic factors in determining patterns of partisanship. Among economic factors, moreover, differentiation in the realms of credit and consumption is more important than differences in relation to economic production. The absence of traditional class-conflict politics, however, does not lead to a state of political consensus, because new modes of economic differentiation have emerged, cleavages based on earlier economic cleavages have persisted after the basic economic issues have been resolved, and non-economic cleavages, particularly along racial lines, still await resolution.     

Optimizing the shares of native tree species in forest plantations with biased financial parameters

Addressing uncertainty is a key requirement to follow the principle of precaution in sustainable ecosystem management. The maximization of worst-case outcomes according to the “maximin” decision rule, based on the two parameters mean and variance of a financial indicator, is a prominent approach to integrate uncertainty in decision-making. In forestry, the problem of selecting the optimum tree species combination for a forest plantation investment can be seen as a problem of optimal portfolio selection, to be solved according to the “maximin” decision rule. Yet, it is well known that portfolios computed from expected means and variances are highly sensitive to changes in the estimated parameters. The financial results may be poor if we rely too much on the historical data. This paper tests an extended worst-case model that considers a lower bound for the expected mean net present value (NPV) of a tree species portfolio and an upper bound for its variance. Biased expected mean NPVs, variances and correlations for the tree species Picea abies [L.] Karst. (Spruce) and Fagus sylvatica L. (Beech) were used to test the variability of the resulting tree species portfolios (27 scenarios). A comprehensive simulated data set, which was adopted from an existing study and defined as the independent reference, served to evaluate the financial performance of the tree species portfolios obtained from optimization with the biased data. Compared with the results of classical worst-case optimization instances, it was feasible to reduce the variability of tree species shares effectively when the optimization was carried out with the extended worst-case approach. Furthermore, the financial performance of this approach was better when tested with the independent data. The worst-case forest NPVs achieved with the extended approach were on average 10% (statistical confidence 0.95) or 147% (statistical confidence 0.99) greater in comparison to the results of the classical approach. The influence of the uncertainty parameter selection was tested and the results were discussed against the controversial viewpoints on the usefulness of the “information-gap decision theory”. Finally, the significance of our results for sustainable ecosystem management is pointed out.     

Integrating neighbourhood effects in the calculation of optimal final tree diameters

Modern silvicultural treatments are based on single trees whereas classic forest economics look at the stand level. To accompany each other it is necessary to transfer the established economic models to the single tree level. This paper is an approach to use the Faustmann model and the corresponding marginal rate of return (Pressler percent) to derive value increment rates of single trees taking into account neighbourhood effects due to competition between individual trees. Furthermore, optimal rotation periods and optimal final diameters for future trees will be calculated.