Determinants of Long-term Economic Development: An Empirical Cross-country Study Involving Rough Sets Theory and Rule Induction

Empirical findings on determinants of long-term economic growth are numerous, sometimes inconsistent, highly exciting and still incomplete. The empirical analysis was almost exclusively carried out by standard econometrics. This study compares results gained by cross-country regressions as reported in the literature with those gained by the rough sets theory and rule induction. The main advantages of using rough sets are being able to classify classes and to discretize. Thus, we do not have to deal with distributional, independence, (log-)linearity, and many other assumptions, but can keep the data as they are. The main difference between regression results and rough sets is that most education and human capital indicators can be labeled as robust attributes. In addition, we find that political indicators enter in a non-linear fashion with respect to growth.Economic growth, Rough sets, Rule induction

Assessing the land resource-food price nexus of the Sustainable Development Goals

Agraïments: We acknowledge support from EU Seventh Framework Programme, theme ICT-2013.5.4: ICT for Governance and Policy Modelling under contract no. 611688; the United Nations Environment Programme, IRP, sub-programme Resource Efficiency (61P1) under contract no. 2105-CPL-5068-3639-1161-1161; the Beijing Natural Science Foundation (grant 8151002); and the National Science and Technology Major Project (2015ZX07203-005).The 17 Sustainable Development Goals (SDGs) call for a comprehensive new approach to development rooted in planetary boundaries, equity, and inclusivity. The wide scope of the SDGs will necessitate unprecedented integration of siloed policy portfolios to work at international, regional, and national levels toward multiple goals and mitigate the conflicts that arise from competing resource demands. In this analysis, we adopt a comprehensive modeling approach to understand how coherent policy combinations can manage trade-offs among environmental conservation initiatives and food prices. Our scenario results indicate that SDG strategies constructed around Sustainable Consumption and Production policies can minimize problem-shifting, which has long placed global development and conservation agendas at odds. We conclude that Sustainable Consumption and Production policies (goal 12) are most effective at minimizing trade-offs and argue for their centrality to the formulation of coherent SDG strategies. We also find that alternative socioeconomic futures - mainly, population and economic growth pathways - generate smaller impacts on the eventual achievement of land resource -related SDGs than do resource-use and management policies. We expect that this and future systems analyses will allow policymakers to negotiate trade-offs and exploit synergies as they assemble sustainable development strategies equal in scope to the ambition of the SDGs

Social Cost of Carbon: What Do the Numbers Really Mean?

Social cost of carbon (SCC) is estimated by integrated assessment models (IAM) and is widely used by government agencies to value climate policy impacts. While there is an ongoing debate about obtained numerical estimates and related uncertainties, little attention has been paid so far to the SCC calculation method itself. This work attempts to fill the gap by providing theoretical background and economic interpretation of the SCC calculation approach implemented in the open-source IAM DICE (Dynamic Integrated model of Climate and the Economy). Our analysis indicates that the present calculation method provides an approximation that might work pretty well in some cases, while in the other cases the estimated value substantially (by the factor of four) deviates from the "true" value. This deviation stems from the inability of the present calculation method to catch the linkages between two key IAM's components -- complex interconnected systems -- climate and economy, both influenced by emission abatement policies. Within the modeling framework of DICE, the presently estimated SCC valuates policy-uncontrolled emissions against economically unjustified consumption, which makes it irrelevant for application in climate-economic policies and, therefore, calls for a replacement by a more appropriate indicator. An apparent SCC alternative, which can be employed for policy formulation is the direct output of the DICE model -- the socially optimal marginal abatement cost (SMAC), which corresponds to technological possibilities at optimal level of carbon emissions abatement. In policy making, because of the previously employed implicit approximation, great attention needs to be paid to the use of SCC estimates obtained earlier

Systemic trade-risk of critical resources

In the wake of the 2008 financial crisis the role of strongly interconnected markets in fostering systemic instability has been increasingly acknowledged. Trade networks of commodities are susceptible to deleterious cascades of supply shocks that increase systemic trade-risks and pose a threat to geopolitical stability. On a global and a regional level we show that supply risk, scarcity, and price volatility of non-fuel mineral resources are intricately connected with the structure of the world-trade network of or spanned by these resources. On the global level we demonstrate that the scarcity of a resource, as measured by its trade volume compared to extractable reserves, is closely related to the susceptibility of the trade network with respect to cascading shocks. On the regional level we find that to some extent the region-specific price volatility and supply risk can be understood by centrality measures that capture systemic trade-risk. The resources associated with the highest systemic trade-risk indicators are often those that are produced as byproducts of major metals. We identify significant shortcomings in the management of systemic trade-risk, in particular in the EU

Effects of Low-cost Offsets on Energy Investment -New Perspectives on REDD-

Tropical deforestation is one of the major sources of carbon emissions, but the Kyoto Protocol presently excludes avoiding these specific emissions to fulfill stabilization targets. Since the 13th Conference of the Parties (COP) to the UNFCCC in 2007, where the need for policy incentives for the reduction of emissions from deforestation and degradation (REDD) was first officially recognized, the focus of this debate has shifted to issues of implementation and methodology. One question is how REDD would be financed, which could be solved by integrating REDD credits into existing carbon markets. However, concern has been voiced regarding the effects that the availability of cheap REDD credits might have on energy investments and the development of clean technology. On the other hand, investors and producers are also worried that emissions trading schemes like the one installed in Europe might deter investment into new technologies and harm profits of existing plants due to fluctuations in the price of emissions permits. This paper seeks to contribute to this discussion by developing a real options model, where there is an option to invest in less carbon-intensive energy technology and an option to purchase credits on REDD, which you will exercise or not depending on the future evolution of CO2 prices. In this way, unresolved questions can still be addressed at a later stage, while producers and investors hold REDD options to maintain flexibility for later decisions. We find that investment in cleaner technology is not significantly affected if REDD options are priced as a derivative of CO2 permits. Indeed, the availability of REDD options helps to smooth out price fluctuations that might arise from permit trading and thus decreases risk for the producer - thereby being a complement to permit trading rather than an obstacle undermining cap-and-trade.Real Options, Energy Investment, Cap-And-Trade, REDD

Predicting the Deforestation–Trend Under Different Carbon–Prices

Background: Global carbon stocks in forest biomass are decreasing by 1.1 Gt of carbon annually, owing to continued deforestation and forest degradation. Deforestation emissions are partly offset by forest expansion and increases in growing stock primarily in the extra-tropical north. Innovative financial mechanisms would be required to help reducing deforestation. Using a spatially explicit integrated biophysical and socio-economic land use model we estimated the impact of carbon price incentive schemes and payment modalities on deforestation. One payment modality is adding costs for carbon emission, the other is to pay incentives for keeping the forest carbon stock intact. Results, Baseline scenario calculations show that close to 200mil ha or around 5% of today’s forest area will be lost between 2006 and 2025, resulting in a release of additional 17.5 GtC. Today’s forest cover will shrink by around 500 million hectares, which is 1/8 of the current forest cover, within the next 100 years. The accumulated carbon release during the next 100 years amounts to 45 GtC, which is 15% of the total carbon stored in forests today. Incentives of 6 US$/tC for the standing biomass paid every 5 years will bring deforestation down by 50$/year. On the other hand a carbon tax of 12$/tC harvested forest biomass will also cut deforestation by half. The tax income will decrease from 6 billion US$ in 2005 to 4.3 billion US$in 2025 and 0.7 billion US$ in 2100 due to decreasing deforestation speed. Conclusions, Avoiding deforestation requires financial mechanisms that make retention of forests economically competitive with the currently often preferred option to seek profits from other land uses. Incentive payments need to be at a very high level to be effective against deforestation. Taxes on the other hand will generate budgetary revenues by the regions which are already poor. A combination of incentives and taxes could turn out to be a viable solution for this dilemma. Increasing the value of forest land and thereby make it less easily prone to deforestation would act as a strong incentive to increase productivity of agricultural and fuelwood production, which could be supported by revenues generated by the deforestation tax.Deforestation, Carbon Prices

Efficiency and Economies of Scale in Academic Knowledge Production

This paper investigates the properties of knowledge production in academic research using a panel of 17 OECD countries reaching from 1989 to 1996. The production process is modelled using capital and labour as inputs and the number of published international journal articles and/or the number of graduates as outputs. First, we test for the existence of economies of scale in academic research. Our results give indication for decreasing returns to scale in the production of new academic knowledge. This empirical result might contribute to the recent controversy on the properties of the innovation technology used in endogenous growth models. Second, we determine efficiency scores for each individual country. For the estimation of efficiencies we apply parametric and non-parametric methods. Although results differ slightly with the method used, a stable efficiency ranking is found.Academic Research, Education, Knowledge Production, Efficiency, Endogenous Growth

Agricultural adaptation to climate policies under technical change

This study uses a partial equilibrium model of the US agricultural sector to examine how technical progress and carbon price levels affect land management adaptation. We find that the climate policy range, over which a more extensive agriculture is preferred, decreases as crop yields increase. Second, technical progress with traditional crops offers less mitigation benefits than progress with mitigation options themselves. Third, while agricultural producers benefit from technical progress on energy crops, they fare worse if technical progress improves traditional crops and low carbon prices.Technical Change, Producer Adaptation, Agricultural Sector Model, Carbon Sequestration, Mathematical Programming, Climate Policy Simulation

The risks of multiple breadbasket failures in the 21st century: a science research agenda

Thomson ReutersThis report stems from an international, interdisciplinary workshop organized by Knowledge Systems for Sustainability and hosted by the Frederick S. Pardee Center for the Study of the Longer-Range Future, with support from Thomson Reuters, in November 2014.Written by an interdisciplinary team of leading researchers, this report describes a science research agenda toward improved probabilistic modeling and prediction of multiple breadbasket failures and the potential consequences for global food systems. The authors highlight gaps in the existing empirical foundation and analytical capabilities and offer general approaches to address these gaps. They also suggest the need to fuse diverse data sources, recent observations, and new suites of dynamic models capable of connecting agricultural outcomes to elements of the global food system. The goal of these efforts is to provide better information concerning potential systemic risks to breadbaskets in various regions of the world to inform policies and decisions that have the potential for global impacts