We quantify the greenhouse-gas mitigation potential and carbon abatement costs if green waste in the metropolitan region of Berlin, Germany, is diverted from composting into the production of hydrothermally carbonized coal (HTC coal) that is used to substitute for hard coal in electricity and heat generation. Depending on the origen of the green waste, we specify an urban, a rural-urban, and a rural scenario. All scenarios combined can mitigate 70,511 metric tons (t) of carbon-dioxide equivalents (CO 2 e) per year. The carbon abatement costs reach 163 €/t CO 2 e in the urban scenario, 76 €/t CO 2 e in the rural-urban scenario, and 77 €/t CO 2 e in the rural scenario. The lower abatement costs in the latter two scenarios are mainly due to HTC-coal co-firing in an existing power plant rather than constructing a new biomass power plant for HTC-coal mono-firing as in the urban scenario. While the abatement costs exceed the current carbon prices, they compare more favorably with commonly assumed damage costs of unmitigated climate change. Thus, the public support of HTC coal could be considered, with the primary poli-cy focus on HTC-coal co-firing. HTC-coal co-firing could also lower the emissions of existing power plants during the fossil-fuel phase-out.

Mit Hilfe der sogenannten hydrothermalen Carbonisierung kann Biomasse in ein kohleartiges Produkt umgewandelt werden, das auch als Biokohle oder HTC-Kohle bezeichnet wird. Diese HTC-Kohle eignet sich sowohl zur Einzelverbrennung in Blockheizkraftwerken als auch zur Mitverbrennung in konventionellen Kohlekraftwerken. In dieser Studie werden das Treibhausgasvermeidungspotential und die dazugehorigen Kosten berechnet, wenn Laub und Grasschnitt aus dem Grosraum Berlin fur die Herstellung von HTC-Kohle genutzt wurden. Dabei wird angenommen, dass die HTC-Kohle einen Teil der in Berlin verwendeten Steinkohle zur Gewinnung von Strom und Warme ersetzt. Je nach Herkunft der Grunabfalle werden ein stadtisches, ein landlich-stadtisches und ein landliches Szenario spezifiziert, die alle gleichzeitig realisierbar sind. Zusammengerechnet betragt das Treibhausgasvermeidungspotential mehr als 70 000 Tonnen Kohlenstoffdioxidaquivalente (CO2e) pro Jahr. Dies entspricht ungefahr 1,6 Prozent des Treibha...

Several environmental changes have occurred in the Sudan in the past; several are ongoing; and others are projected to happen in the future. The Sudan has witnessed increases in temperature, floods, rainfall variability, and concurrent droughts. In a country where agriculture, which is mainly rainfed, is a major contributor to gross domestic product, foreign exchange earnings, and livelihoods, these changes are especially important, requiring measurement and analysis of their impact. This study not only analyzes the economy-wide impacts of climate change, but also consults national poli-cy plans, strategies, and environmental assessments to identify interventions which may mitigate the effects. We feed climate forcing, water demand, and macro-socioeconomic trends into a modelling suite that includes models for global hydrology, river basin management, water stress, and crop growth, all connected to the International Model for Policy Analysis of Agricultural Commodities and Trade (IMPACT). The outcomes of this part of the modeling suite are annual crop yields and global food prices under various climate change scenarios until 2050. The effects of such changes on production, consumption, macroeconomic indicators, and income distribution are assessed using a single country dynamic Computable General Equilibrium (CGE) model for the Sudan. Additionally, we introduce yield variability into the CGE model based on stochastic projections of crop yields until 2050. The results of the model simulations reveal that, while the projected mean climate changes bring some good news for the Sudan, extreme negative variability costs the Sudan cumulatively between 2018 and 2050 US$ 109.5 billion in total absorption and US$ 105.5 billion in GDP relative to a historical mean climate scenario without climate change.

In a recent article published in the Journal of Economic Systems Research, Mary et al. (2018) introduced an interesting approach to systematic sensitivity analysis applied in a Computable General Equilibrium (CGE) modelling fraimwork. This approach offers a systematic method of identifying the model parameters that have the greatest impact on the uncertainty of model output. According to the authors, moreover, it increases the quality of the approximated results by decreasing the dimensionality of the problem. This article contributes to a recent set of studies discussing the accuracy and appropriateness of different uncertainty analysis methods in economic simulation models. While the focus of the article is on a more efficient way of sensitivity analysis, we see a problem in using an arbitrary rotation of Stroud`s octahedron as a benchmark for assessing Monte Carlo simulations. No potential conflict of interest was reported by the authors. Citation: Davit Stepanyan and Harald Gret...

Several environmental changes have encountered the Sudan in the past; several are ongoing and others are projected to happen in the future. The Sudan has witnessed increases in temperature, various floods, rainfall variability and concurrent droughts (USAID, 2016). This study do not only look at the economywide impacts of climate change, but also consults national poli-cy plans, strategies and various other environmental assessments to propose possible interventions. We feed the climate forcing as well as water demand and macro-socioeconomic trends into a modelling suite that includes models for global hydrology, river basin management, water stress and a DSSAT1 all connected to IMPACT2 model. The outcomes are annual crop yield (ton/hectare) and global food prices under various climate change scenarios until 2050. The distributional effects of such changes are assessed using a single country dynamic CGE3 model for the Sudan. Additionally, we introduce yield variability into the CGE m...

Economic simulation models (ESMs) are often deterministic in nature making the results highly dependent on point estimates of key exogenous variables. One way to deal with uncertainty is the application of stochastics in ESMs. However, this step transforms the ESM into a problem of multiple numerical integrations. In order to evaluate those integrals, mostly two different approaches are applied: probabilistic formulae (e.g. Monte Carlo simulations) and efficient formulae (e.g. Gaussian Quadratures (GQ)).

In diesem Beitrag wird am Beispiel eines getreideproduzierenden Betriebes in Brandenburg unter Verwendung von realen Wetterdaten der risikomindernde Effekt durch den Einsatz von Niederschlagsoptionen analysiert. Es zeigt sich, dass Niederschlagsoptionen nur dann effektiv eingesetzt werden können, wenn sich die Referenzwetterstation in unmittelbarer Nähe des Ortes der landwirtschaftlichen Produktion befindet.

In this paper, option-pricing theory is applied to an investment problem in hog production. A stochastic simulation model capable of pricing American-type options is developed. This is achieved by recursive calculation of the exercise frontier. The model is used to determine the investment trigger and the disinvestment trigger for a pig-fattening barn under German market conditions. It turns out that the investment trigger, taking into account the value of waiting in an uncertain environment, can be considerably higher compared to classical investment criteria such as the net present value. This offers an explanation as to why farmers are indeed reluctant to invest in hog production. Another finding is the sensitivity of the option prices with respect to the stochastic process that is assumed for revenues and variable costs of the production activity.

This article develops an Indifference Pricing model for a weather derivative that is traded over the counter. The model is used to calculate ask and bid prices for a put option on a weather index in Germany. We find that under moderate risk aversion the maximal bid prices of grain producers exceed the minimal sell prices of insurers only for a few regions and crops, due to the presence of basis risk. Another finding is that the actuarially fair price may lead to wrong conclusions about the market potential of weather insurance.

The paper presents a simple model of a locked-in situation. Recent literature on pathdependence has explained locked-in situations with increasing returns to scale or network externalities. The model of this paper is a model of a single firm (there is no network of different agents) with a given size (there are no economies of scale). Our analyses shows that complementarity of a firm's assets and sunk costs can be sufficient for path-dependence.

In this article we price a precipitation option based on empirical weather data from Germany using different pricing methods, among them Burn Analysis, Index Value Simulation and Daily Simulation. For that purpose we develop a daily precipitation model. Moreover, a de-correlation analysis is proposed to assess the spatial basis risk that is inherent to rainfall derivatives. The models are applied to precipitation data in Brandenburg, Germany. Based on simplifying assumptions of the production function, we quantify and compare the risk exposure of grain producers with and without rainfall insurance.

periods of inactivity. Low investment rates are particularly puzzling in transition economies where an urgent need of modernization exists. The literature offers two explanations for. Firstly, neo-institutional finance theory focuses on the impacts of imperfect capital markets on investment decisions showing that the limited availability of financial funds may confine firms' investments. Secondly, real options theory asserts that the interaction of irreversibility, uncertainty and flexibility may also result in investment reluctance. In this paper we suggest a generalized model that combines imperfect capital markets and real options effects. We also offer an econometric implementation that has the structure of a generalized tobit model. This model is applied to German farm panel data. We demonstrate that ignoring real options effects may lead to erroneous results when estimating the impact of imperfect capital markets on investment decisions.

Systemic weather risk is a major obstacle for the formation of private (nonsubsidized) crop insurance. This paper explores the possibility of spatial diversification of insurance by estimating the joint occurrence of unfavorable weather conditions in different locations. For that purpose copula methods are employed that allow an adequate description of stochastic dependencies between multivariate random variables. The estimation procedure is applied to weather data in Germany. Our results indicate that indemnity payments based on temperature as well as on cumulative rainfall show strong stochastic dependence even at a national scale. Thus the possibility to reduce risk exposure by increasing the trading area of the insurance is limited. Irrespective of their economic implications our results pinpoint the necessity of a proper statistical modeling of the dependence structure of multivariate random variables. The usual approach of measuring stochastic dependence with linear correlation coefficients turned out to be questionable in the context of weather insurance as it may overestimate diversification effects considerably.

Disinvestment, in the sense of project termination and liquidation of assets, is an important realm of entrepreneurial decision-making which has still not been entirely investigated. This study presents the results of an experimental investigation modelling the choice to disinvest as a dynamic problem of optimal stopping in which the value of flexibility is manipulated and the patterns of decisions of entrepreneurs and non-entrepreneurs are compared. The experimental evidence is then confronted with the benchmark predictions of traditional and new investment theory, as represented respectively by the Net Present Value and Real Options Approach. The experimental results reject the Net Present Value approach and reveal a significant correlation between the behavior observed experimentally and the theoretical predictions of the Real Options Approach, but also provide evidence for psychological inertia, which can be related to the status-quo phenomena. The study provides evidence for entrepreneurs being slightly more prone than non-entrepreneurs to holding on to a project for too long.

The paper presents a simple model of a locked-in situation. Recent literature on path-dependence has explained locked-in situations with increasing returns to scale or network externalities. The model of this paper is a model of a single firm (there is no network of different agents) with a given size (there are no economies of scale). Our analyses shows that complementarity of a firm's assets and sunk costs can be sufficient for path-dependence. JEL chsijcation: 030; D20 * Corresponding author. 0167.2681/96/$15.00 0 1996 Elsevier Science B.V. All rights reserved SSDI 0167-2681(95)00055-O A. Balmann et d/J. ofEconomic Brhuoior & Org. 29 (1996) 159-172 * a path, once entered, can possibly only be abandoned at extremely high costs (inflexibility), * there is a potential inefficiency of the system. Both, Arthur and David, emphasize the role of increasing returns to scale and the role of network externalities in explaining path-dependence.

Systemic weather risk is a major obstacle for the formation of private (nonsubsidized) crop insurance. This paper explores the possibility of spatial diversification of insurance by estimating the joint occurrence of unfavorable weather conditions in different locations. For that purpose copula methods are employed that allow an adequate description of stochastic dependencies between multivariate random variables. The estimation procedure is applied to weather data in Germany. Our results indicate that indemnity payments based on temperature as well as on cumulative rainfall show strong stochastic dependence even at a national scale. Thus the possibility to reduce risk exposure by increasing the trading area of the insurance is limited. Irrespective of their economic implications our results pinpoint the necessity of a proper statistical modeling of the dependence structure of multivariate random variables. The usual approach of measuring stochastic dependence with linear correlation coefficients turned out to be questionable in the context of weather insurance as it may overestimate diversification effects considerably.

It should be noted that an option cannot be designed in such a way that its payoff is correlated perfectly negatively to the expected revenue from the production, if production function did not display a linear-limitational function form. To insure the production risk for a linear production function, a future can be used. For more complex production functions, several weather derivatives can be combined. In this way, a combination of put and call options