A multivariate distance nonlinear causality test based on partial distance correlation: a machine learning application to energy futures

This paper proposes a multivariate distance nonlinear causality test (MDNC) using the partial distance correlation in a time series framework. Partial distance correlation as an extension of the Brownian distance correlation calculates the distance correlation between random vectors X and Y controlling for a random vector Z. Our test can detect nonlinear lagged relationships between time series, and when integrated with machine learning methods it can improve the forecasting power. We apply our method as a feature selection procedure and combine it with the support vector machine and random forests algorithms to study the forecast of the main energy financial time series (oil, coal, and natural gas futures). It shows substantial improvement in forecasting the fuel energy time series in comparison to the classical Granger causality method in time series.     

Limitations of portfolio diversification through fat tails of the return Distributions: Some empirical evidence

This study investigates the level of risk due to fat tails of the return distribution and the changes of tail fatness (TF) through portfolio diversification. TF is not eliminated through portfolio diversification, and, interestingly, the positive tail has declining fatness until a certain level is reached, while the negative tail has rising fatness. This indicates that fat tails are highly relevant to common factors on systematic risk and that the relevance of common factors is higher for the negative tail compared to the positive tail. In the portfolio diversification effect, the declining fatness of the positive tail further reduces risk, but the rising fatness of the negative tail does not contribute to this effect. The asymmetry between the fatness of the positive and negative tails in the return distribution corresponds to the asymmetry of the trade-off relationship between loss avoidance and profit sacrifice that is expected as a consequence of portfolio diversification. Investors use portfolio diversification to reduce their risk of suffering high losses, but following this strategy means sacrificing high-profit potential. Our study provides empirical confirmation for the practical limitation of portfolio diversification and explains why investors with diversified portfolios suffer high losses from market crashes. An examination of the Northeast Asian stock markets of China, Japan, Korea, and Taiwan show identical results.     

Land use and land cover scenarios: An interdisciplinary approach integrating local conditions and the global shared socioeconomic pathways

Land Use and Land Cover (LULC) changes have profound impacts on the functioning of (agro)ecosystems and have potential to mitigate global climate change. However, we still lack interdisciplinary methods to project future LULC scenarios at spatial scales that are relevant for local decision making and future environmental assessments. Here we apply an interdisciplinary approach to develop spatially explicit projections of LULC at a resolution of 30 × 30 m informed by historic relationships between LULC and their key drivers, within the context of the four qualitative scenarios of global shared socioeconomic pathways. We apply this methodology to a case study in the Zona da Mata, Brazil, which has a history of major LULC changes. The analysis of LULC changes from 1986 to 2015 indicates that pasture area decreased from 76 to 58 % of total area, while forest areas increased from 18 to 24 %, and coffee from 3 to 11 %. Environmental protection legislation, rural credit for smallholder farmers, and demand for agricultural and raw products were identified as main drivers of LULC changes. Projected LULC for 2045 strongly depends on the global socioeconomic pathway scenarios, and forest and coffee areas may increase substantially under strong government measures in the environmentally conscious Green Road scenario or decrease in the high consumption Rocky Road scenario. Our study shows that under the set of drivers during the past three decades reforestation can go hand in hand with increase of agricultural production, but that major and contrasting changes in LULC can be expected depending on the socioeconomic pathway that will be followed in the future. To guide this process, LULC scenarios at the local scale can inform the planning of local and regional development and forest conservation.     

Policy lessons from spatiotemporal enrollment patterns of payment for ecosystem service programs in Argentina

Payment for ecosystem services schemes (PES) are lauded as a market-based solution to curtail deforestation and restore degraded ecosystems. However, PES programs often fail to conserve sites under strong long-term deforestation pressures. Underperformance, in part, is likely due to adverse selection. Spatial adverse selection occurs when landowners are more likely to enroll parcels with low deforestation pressure than parcels with high deforestation pressure. Temporal adverse selection arises when parcels are enrolled for short time periods. In both cases, financial resources are allocated without having a sizeable impact on long-term land use change. Improving program performance to overcome these shortcomings requires understanding attributes of landowners and their parcels across large scales to identify spatial and temporal enrollment patterns that drive adverse selection. In this paper, we examine these patterns in Argentina’s PES program in Chaco forest, a global deforestation hotspot. Our study area covers 252,319 km². Results from multinomial logistic regression models showed that large parcels of enrolled land and parcels owned by absentee landowners exhibit greater evidence of spatiotemporal adverse selection than smaller parcels or parcels owned by local landowners. Furthermore, parcels managed under land use plans for conservation and restoration are more likely to be associated with adverse selection than parcels managed for financial returns such as harvest of non-timber forest products, silviculture, and silvopasture. However, prior to recommending that PES programs focus on land uses with higher potential earnings, a greater understanding is needed of the degree to which these land uses meet ecological and biodiversity goals of PES programs. We suggest that increased spatial targeting of enrollment, along with enrollment of local landowners and further incentives for land uses that support conservation and restoration, could promote long-term conservation of forest lands.     

Evaluation of forestland use in mining operation activities in Turkey in terms of sustainable natural resources

Mining has been necessary for human activities and is conducted in line with this need. The location of mines must sometimes be where land use overlaps with other activities because the location of the mined substance cannot be changed. In Turkey, forestland are the most common of these overlapping areas. Therefore, mining has frequently occurred on forestland in Turkey—and worldwide. After the mining operation activities are conducted, the forestland are rehabilitated and returned to the forest administration. The examination of used and returned areas provides an opportunity to create an optimal situation between “mining for sustainable development” and “protection of forestland.”Accordingly, several questions, such as mining production amounts, degrees of social and economic development of the cities in which enterprises are conducting mining, the quantity of the areas they used for mining activities in forestland, the areas which were returned to the forest administration, operating license areas and operation permit areas, and the life of mining operation, were asked to the mining enterprises in Turkey through the “Survey Monkey” program in 2018. Thus, according to mineral groups, different land use rates were compared with the operating license areas, and the land uses for each mineral group were analyzed by considering the operation activity periods. The results indicate that the sustainability of the use of forestry in mining activities in Turkey has changed in a positive direction, particularly because of changes in mining and environmental legislation in Turkey over the last decade.     

Relationships between absenteeism,conservation group membership,and land management among family forest owners

Absentee landowners, or those who do not live on their forestland, own approximately 117 million acres of private forestland in the U.S. Thus, their land management decisions and activities influence the flow of forest-based goods and services. We explore the question of whether absentee family forest owners are less active land managers than resident landowners and whether membership in conservation organizations is associated with higher levels of land management activity by absentee owners. To examine these questions, we administered a mail survey to randomly-selected family forest landowners in Indiana. While we found some support for the contention that absentee owners are less active forestland managers than resident owners, we also found they are not necessarily inactive landowners. We found absentee owners were less likely to have: inspected their forestland for invasive plants, pulled or cut invasive plants, used herbicides to kill invasive plants, reduced fire hazard, or grazed livestock than resident owners. Absentee owners were more likely to be enrolled in the Indiana Classified Forest and Wildlands Program, a preferential forest property tax program. Absentee owners who are members of a conservation organization were more likely than absentee non-member owners to have undertaken a variety of land management activities, including: undertaking wildlife habitat improvement projects, inspecting their forestland for invasive plants, pulling or cutting invasive plants, enrolling in the Indiana Classified Forest and Wildlands program, and obtaining a management plan.     

The difference of expert opinion on the forest-based ecotourism development in developed countries and Iran

Ecotourism development in a forest area includes many positive and negative aspects and requires a comprehensive study that can consider all simultaneously. Because of the inner and outer dependence or feedback links between the criteria in this research, the Analytical Network Process (ANP) based on the BOCR Model was used. Decision making and planning for the development of ecotourism is influenced by the attitude of experts towards development impacts. The question of this research was whether due to different environmental conditions in Iran, is it appropriate to follow ecotourism development patterns of developed countries? Given the different forest conditions in Iran, the weights of decision-making criteria for ecotourism development was significantly different for experts from Iran and developed countries. Weight difference for five sub-criteria, ECB2, ECB3, SOB4, ENC4 and, ENR2 were not significant, but for the rest of the sub-criteria were significant at 1% level. The results of comparing the mean weight values of the alternatives with an independent t-test indicated the difference was significant at 1% level. According to experts of the developed countries, ecotourism development with a weight of 0.927 and according to experts of Iran with a weight of 0.531 was prioritized.     

Predicting bank insolvencies using machine learning techniques

Proactively monitoring and assessing the economic health of financial institutions has always been the cornerstone of supervisory authorities. In this work, we employ a series of modeling techniques to predict bank insolvencies on a sample of US-based financial institutions. Our empirical results indicate that the method of Random Forests (RF) has a superior out-of-sample and out-of-time predictive performance, with Neural Networks also performing almost equally well as RF in out-of-time samples. These conclusions are drawn not only by comparison with broadly used bank failure models, such as Logistic, but also by comparison with other advanced machine learning techniques. Furthermore, our results illustrate that in the CAMELS evaluation framework, metrics related to earnings and capital constitute the factors with higher marginal contribution to the prediction of bank failures. Finally, we assess the generalization of our model by providing a case study to a sample of major European banks.     

On the existence of the ex post symmetric random entry model

This paper studies symmetry among countably infinitely many agents who randomly enter into a stochastic process, one for each period. Upon entry, they observe only the current period signal and try to draw inference about the underlying state governing the stochastic process. We show that there exist random entry models under which agents are ex post symmetric. That is, all agents have identical posterior belief about the underlying states, although they are not ex ante symmetric. The form of the posterior belief is uniquely pinned down by ex post symmetry and a stationarity condition. Our results provide a common prior foundation for the model studied in Liu and Skrzypacz (2014).     

Ex-post incentive compatible and individually rational assignments in housing markets with interdependent values

This paper presents a model for housing markets with interdependent values. We introduce private information on the quality of a house (i.e., high or low), which is known only to the initial owner. Interdependency means that the ex-post preference of an agent depends on the private information of the other agents with regard to the quality of houses. We prove that on a domain satisfying a richness condition, the no-trade rule is the only rule that satisfies ex-post incentive compatibility and ex-post individual rationality.