Disentangling the drivers of renewable energy investments: The role of behavioral factors

The scope of this study is to investigate the main determinants of renewable energy investments in Greece. For this reason, we build an appropriate framework to infer the decision‐making process in the renewable energy sources (RES). The main drivers are then categorized under two groups as economic, and behavioral ones. In the next stage, we rely on binomial (logit and probit) and quantile regression analysis to estimate the impact of these factors on investment decisions towards RES. Our findings indicate that investors who gain better access to knowledge and exhibit a more positive attitude towards the contribution of artificial intelligence (AI) on the RES industry have a higher share of renewables in their portfolio. We argue that these investors are willing to invest a higher amount in the RES industry today. At the same time, quantile regression models illustrate that this relationship is nonmonotonic (i.e., inverted U shaped curve), arguing that positive attitudes towards the contribution of behavioral factors on RES are not adequate to encourage investments after crossing a certain point (threshold). Based on the empirical findings, we argue that the message to policymakers and government officials is to promote a faster penetration of low carbon technologies to achieve sustainable economic and social growth.     

一种基于Radon变换的微表情识别算法

微表情是人们处在一些与平时生活环境不同的高强度环境下试图控制和掩饰的情感表现，也是一种不曾意识到的瞬时脸部表情,持续时间短，强度弱。为了提高其准确率，提出了基于Radon变换的微表情识别算法。首先，对数据库中的视频序列进行灰度归一化、尺寸归一化和二维主成分分析法（Two-dimensional Principal Component Analysis，2DPCA）降维预处理，使用光流法对降维后图像提取运动特征；然后使用Radon变换算法对光流图像进行处理，得到对应微表情的特征值和特征图像；最后使用支持向量机进行微表情分类识别。实验结果表明，使用Radon变换后得到的微表情特征图像得到了较好的识别效果，在微表情数据集CASME和CASMEⅡ上识别率分别为81.48%和82.17%，通过与选取的其他方法对比说明了该方法具有更好的识别性能。     

结合新型模糊支持向量机和证据理论的多传感器水质数据融合

在多传感器水质数据融合领域，证据理论是有效的数据融合方法之一，但基本概率分配一般不易确定，从而使数据融合能力难以有效发挥。支持向量机是统计学习理论之上的高级分类算法，具有普适性和全局优化等特点，但输出的基本概率分配有待进一步提高。提出了一种基于证据理论和新型模糊支持向量机相结合的数据融合方法，通过建立基于分类超平面距离的模糊隶属度，训练模糊支持向量机提高传统支持向量机的基本概率分配，并结合证据理论进行海河水质数据融合。通过证据理论分别结合支持向量机和模糊综合评价法与上述方法进行对比实验，经精度、平均绝对百分误差、均方根误差等指标验证，精度提高10.5%，表明所提方法是一种可靠的多传感器的水质融合方法，较其他方法具有更高的融合精度。     

一种利用机器学习优化MIMO窃听信道天线选择的方法

为保障多输入多输出窃听信道系统中信息传输的保密性，提出了一种基于机器学习的天线选择方案。首先利用机器学习解决分类问题准确率高、处理大数据高效这一优势，设计了基于奇异值分解的特征值提取、基于信干噪比的标签赋值方案，建立了k最近邻分类器和逻辑回归分类器选择最优天线最大化保密性能（可达保密速率和保密中断概率）。与传统天线选择方案相比，所提方案获得了几乎一致的保密性能，并且大幅降低了系统的选择复杂度和误比特率。     

地方政府债务对工业资本配置效率的非线性影响效应——基于动态面板平滑转换回归PSTR模型的检验

经济新常态下,提高工业资本等要素配置效率是实现经济向高质量增长转变的必然要求。本文在政府主导、投资驱动的工业发展模式下,结合地方债务压力和金融发展差异门限变量,在非线性框架下运用动态面板平滑转换回归模型实证检验地方债务规模与工业资本配置效率的渐进演变关系。研究发现,适度的地方债务规模有助于提高资本配置效率,但随着债务压力增加,举债对资本配置的正效应逐步减弱并产生负效应。究其原因,适度举债能补齐工业基础设施短板,压低土地成本,对工业发展产生杠杆效应,从而提高资本配置效率;但过度举债推升财政风险,占用信贷资源并强化企业融资约束,造成资本配置低效率。此外,研究发现,地方信贷规模提升,能缓解举债的融资约束,促进工业行业间的资本流动;而工业金融深化程度提高,能增强市场竞争机制在要素配置中的作用,缓解举债造成投资错配,从而增强资本配置效率。以上分析结果表明,地方政府举债应更理性、适度、规范。     

利用频移动态特征的辐射源目标盲分选

利用辐射源目标的频移动态特征进行盲分选时，针对已有的分选方法不能很好解决非合作接收数据非周期、间断、交叠的问题，提出了一种改进的逻辑回归分选算法,将信号分选转化为轨迹分类的问题来处理。首先，借鉴多目标航迹起始模型中的M/N逻辑法的框架，设计新的数据关联门限，以建立目标起始曲线；其次，采用最小二乘拟合方法替代卡尔曼滤波，设计新的外推规则，建立载频变化预测曲线；分析新的接收数据与预测曲线的关联性，不断迭代回归或形成新的分支，最后获得目标分选结果。仿真与实测试验表明，利用逻辑回归分选算法，对不同运动目标搭载的同频辐射源可进行自动分选，4个仿真目标与2个真实目标的分选正确率达到100%。同时，该方法拓展了辐射源目标盲分选中的动态频移特征应用，为辐射源个体识别提供了新的支持。     

Does oligopsony power matter in price support policy design? Empirical evidence from the Thai Jasmine rice market

In the oligopsony market, farmers may receive low prices and policy analysis assuming perfect competition can yield serious bias results. In this paper, we estimate oligopsony power between processors and farmers and evaluate the welfare impact of the paddy pledging program (PPP), a generous price support program in the Thai Jasmine rice market, with an imperfect competition model. We develop a model that consists of rice supply equation and derived demand equation. We then simultaneously estimate these equations using system estimation methods to recover oligopsony power parameters. Finally, we use these parameters to assess the welfare impact of the price support program. Using annual panel data running from crop marketing year 2001/2002–2015/2016 and exploiting the institutional feature of the PPP, we find strong evidence of some oligopsony power, a moderate level of oligopsony price distortion, and a negative relationship between price support and oligopsony power. We also find that the PPP is inefficient but effective in income redistribution. Moreover, the program benefits both farmers and consumers. With better policymaking decisions, the PPP can be efficient by setting a suitable support price. Therefore, our results show that in the case of the Thai Jasmine rice market, the generally accepted “wisdom” about agricultural price support policy does not necessarily hold, and price support can be designed to improve the efficiency of the market.     

Theoretical analysis and model design of search for ecological conservation redlines based on the sensitivity assessment of ecosystem services

Most small-scale social economies are characterised by their deficiency, lack, and/or difficulty in matching natural data. Against this backdrop, this paper builds a relatively uniform theoretical framework and designs a more economical and objective method for demarcating ecological conservation redlines (ECR) based on sensitivity assessment of ecosystem services. The results show that the sensitivity assessment model designed in this study can identify sensitive zones effectively, and that the ECR in Hubei Province are well within the sensitive zones so identified. The delimited areas based on the sensitive assessment of ecosystem services have great similarities (95%) with the actual ECR areas in Hubei Province. The most ecologically important functional zones (EIFZ) can also be identified using the regional ecological sensitivity coefficient. When the threshold of EIFZ is set higher, the probability that it falls within the ecologically sensitive areas is greater and the ECR delimited by the method proposed in this study will be more reliable. Theoretically, the delimitation of ECR can be inserted at any evaluation level with a grid resolution higher than that of the land use data, which can be used as a supplement to the ECR delimitation method in ecology or geography.     

Dependent relationships between Chinese commodity markets and the international financial market: Evidence from quantile time-frequency analysis

In this article, the quantile time–frequency method is utilized to study the dependence of Chinese commodities on the international financial market. The impacts of risk management and diversification benefits of different portfolios are examined by calculating the reduction in downside risk. Moreover, we estimate and compare Sharpe Ratios (SRs) and Generalized Sharpe Ratios (GSRs) based on the frequencies of the investigated portfolios. Our empirical results reveal a strong asymmetric response from Chinese commodity markets. Specifically, we find that gold is a safe-haven asset, and due to negative correlations found at lower quantiles in medium and long term, an increase in the USD index damages bull commodity markets but boosts bear conditions under long-term investments, and negative (positive) tail correlations with interest rates (IRs) in bull (bear) markets are observed. It is proven that WTI can decrease short-run risks while USD and GOLD are more efficient in the diversification of downside risk. Adding international commodities may not improve the returns of Chinese commodities at given risk levels in the short and medium term through SRs and GSRs. In brief, investors should consider these dependence structures and modes of risk management in terms of time and frequency.     

Time-varying beta in functional factor models: Evidence from China

In this paper, we introduce a functional method to investigate how betas change over time in factor models. Based on the China A-share data, we drop the constant beta assumption in the CAPM and multi-factor models to estimate the time-varying betas directly from the functional data regression. The empirical results show that exposures to all risk factors have certain time-varying patterns in the Chinese A-share stock market.