Picking on the poor: the contradictions of theory and neo-liberal critique. A response to Stasja Koot's paper on the contradictions of capitalism for Indigenous tourism in the South African Kalahari

The relevance of neo-liberal critique of a community-owned, but commercially managed lodge, is examined with regard to Stasja Koot's paper on “The contradictions of capitalism” published in the Journal of Sustainable Tourism in 2016. Koot focuses on the ≠Khomani Bushmen's relationship with !Xaus Lodge in the Kalahari Desert. His argument locates this small facility as an exemplar of the global contradictions of capitalism in the tourism sector. My response critiques Koot's methodology, theory and conclusions. It provides the missing history of the project discussed, and details the financial evidence that cautions Koot's speculative interpretations. My analysis cautions the relevance and use of Koot's application of David Harvey's Marxist-derived theory of spatial and temporal fixes. This response's assessment is that Koot's conclusions are arrived at without sufficient supporting evidence, and that his theory-led argument conceals a myriad of contextual contradictions that question the unproblematic application of Harvey's theory into a political economic context for which it was not designed. Some comment is offered on researcher positions and responsibilities and on how to interpret responses offered by ≠Khomani sources, whose own playful (and sometimes wilful) exploitation of researchers results in information that must always be triangulated for accuracy.     

Assessing efficiency and investment opportunities in commodities: A time series and portfolio simulations approach

This paper investigates the informational efficiency hypothesis in the short and long term for four major commodity markets (oil, gas, electricity, and coal) from January 1997 to January 2016. Unlike previous studies, we provide a more concise comparative analysis by focusing on different classes of commodities for a large sample, including 5 developed and 3 emerging regions and covering 46 countries. We apply different parametric and non-parametric econometric tests. Our study provides two interesting findings. First, we show that commodity markets are informationally inefficient in the short term. Our portfolio simulations highlight that commodities might provide “good” investment opportunities, but those opportunities vary according to commodity class and regions. Second, we show that most commodity markets become informationally efficient in the long term, thereby reducing investors' interest for the duration. Thus, commodity markets might be used to hedge investor’s portfolios, particularly for speculators and chartists in the short term, while these investments might not be appealing in these markets in the long term.     

Financial Imbalance Index as a New Early Warning Indicator： Methods and Applications in the Chinese Economy

Based on the stylized facts of financial crises and systemic risk accumulation, this paper constructs a new financial imbalance index （FII） from the perspective of endogenous financial cycles and assesses its application in China＇s macro-financial analysis. The results show that the FII is not only an effective index to detect financial imbalances in China＇s economic cycles, but is also more accurate than and plays more of a leading role than conventional indicators, such as the consumer price index, the financial conditions index and the purchasing managers indicator. Empirical analysis shows that the FII can be used as an effective indicator to measure systemic financial risk, and can provide policy-makers and market participants with useful information to make appropriate decisions.     

互联网支付平台跨业经营理财产品的模式和风险——以百度“百发”理财产品为例

互联网支付平台不断渗透金融领域,相继推出各类互联网金融理财产品,引起了互联网金融理财的新趋势.在对比分析常见互联网金融理财产品的基础上,以百度“百发”为案例,总结出互联网支付平台经营金融理财产品的一般模式,探讨互联网金融理财产品运作的风险控制问题以及其对传统金融理财机构的冲击和倒逼作用.     

新形势下加快推进河北省民营经济高质量发展的路径选择--基于俄罗斯中小企业发展的得失分析

当前,大众创业、万众创新已是时代最强音,论文通过对俄罗斯政府推进中小企业发展相关做法的得失进行评析,提出河北发展民营经济的路径和方法,力求为河北省民营企业高质量发展提供有益借鉴。     

Do constraints created by economic growth targets benefit sustainable development? Evidence from China

An economic growth target is a declaration by policy authorities of commitment to that target and the corresponding allocation of resources. The constraints created by economic growth target are an important economic management method in China, which has helped China's economy to achieve remarkable achievements. However, it has also brought about serious environmental problems, threatening China's sustainable development. Using the data about economic growth targets in the work reports of 30 Chinese provincial governments from 2006 to 2017, this paper constructs several spatial measurement methods, such as the spatial Durbin model, to examine the constraints created by economic growth target's impacts on air pollution. The main conclusions are as follows. First, a significant “U-shaped” relationship exists between the constraints created by economic growth targets and air pollution. Second, the spatial Durbin model analysis revealed that PM_2.5 across China's provinces display significant positive spatial spillover effects and spatial agglomeration characteristics. Third, the direct, indirect, and total effects of constraints created by economic growth targets on air pollution are all statistically significant and depict a “U shape.” Finally, the constraints created by economic growth targets have an apparent threshold effect on air pollution, and the inhibiting effects increase with human capital and industrial restructuring. However, with the increase in foreign direct investments, constraints created by economic growth targets may increase air pollution. The conclusions of this paper are of great significance for improving the management of local government economic growth targets and sustainable development.     

The role of financial development on the underground economy in regards to Europe’s 2020 strategy

This paper attempts to investigate the relationships between development in the financial sector and the size of the underground economy in European Union countries. Our aim is to investigate the role of financial sector development when it comes to the size of the underground economy, as well as how financial development aids in meeting the growth objectives of the ‘Europe 2020 Strategy’. Panel data analysis will be conducted for the period 2004–2017 in order to examine the effects of financial sector development on the size of the underground economy. The main findings of this paper suggest that financial development has a significantly reducing effect on the size of the underground economy. In conclusion, development within the financial sector significantly lessens underground economic activity in the European Union. With further development of the financial sector, underground economies will not be an obstacle for the fulfilment of the cohesion and growth objectives of the Europe 2020 strategy.     

The “Six Ws” of sustainable development risks

Risk management in an organization represents a decisive function in seizing opportunities and managing the risks that can affect a business's reputation, prosperity, growth, value creation, stakeholder engagement, long-term survival, and a firm's contribution to sustainable development. For this paper, we conduct a systematic literature review of 148 indexed studies and uses the “Six Ws” (what, who, why, where, when, and how) approach to understand the linkages between sustainability and risk management. This study's findings reveal that the management of environmental, social, and governance (ESG) concerns plays a mitigation's function on business risks.     

Extreme risk spillovers between crude palm oil prices and exchange rates

This study is the first attempt to examine the extreme risk spillovers between Malaysian crude palm oil (CPO) and foreign exchange currencies of the three largest CPO importers: India, the European Union and China throughout the global financial crisis. Using daily data of three currencies, CPO spot and futures from 2000 to 2018, our results show: First, before the crisis, the unexpected change in foreign exchange rates is the primary driver of risk spillover to the CPO market. Second, during the crisis, the extreme movement of CPO spot returns is dominant in the Malaysian exchange rates relative to the euro. Third, after the crisis, the spillover flows from the CPO market to the foreign exchange market. Overall, our findings show the importance of CPO pricing dynamics in mitigating foreign exchange risk over the crisis period. This paper contributes to the extant literature by recognizing the effect of risk spillover on the targeted foreign exchange rate for portfolio allocation.     

Performance assessment of ensemble learning systems in financial data classification

Financial data classification plays an important role in investment and banking industry with the purpose to control default risk, improve cash and select the best customers. Ensemble learning and classification systems are becoming gradually more applied to classify financial data where outputs from different classification systems are combined. The objective of this research is to assess the relative performance of existing state‐of‐the‐art ensemble learning and classification systems with applications to corporate bankruptcy prediction and credit scoring. The considered ensemble systems include AdaBoost, LogitBoost, RUSBoost, subspace, and bagging ensemble system. The experimental results from three datasets: one is composed of quantitative attributes, one encompasses qualitative data, and another one combines both quantitative and qualitative attributes. By using ten‐fold cross‐validation method, the experimental results show that AdaBoost is effective in terms of low classification error, limited complexity, and short time processing of the data. In addition, the experimental results show that ensemble classification systems outperform existing models that were recently validated on the same databases. Therefore, ensemble classification system can be employed to increase the reliability and consistency of financial data classification task.