辽吉黑农产品供应链大数据平台构建研究

[目的]通过构建辽吉黑农产品供应链大数据平台,以期实现东北地区经济持续发展,整合辽吉黑农产品种植、生产、运输等分散主体,有效协调政府部门监管、企业加工和运输、消费者等之间的利益提供借鉴。[方法]文章分析辽吉黑农产品发展现状及以零散农户为中心、以中间商为中心、以龙头企业为中心、以农民合作社为中心的4种农产品供应链模式,剖析辽吉黑农产品供应链存在生产信息化水平落后、农产品物流技术滞后、农产品信息服务平台缺失等问题,构建辽吉黑农产品供应链大数据平台。[结果]辽吉黑农产品供应链大数据平台可实现4个功能:(1)通过建立省级或者大区域农产品信息平台,有助于实现农产品资源跨区域整合和流通,实现资源优化配置,有利于各参与者统筹规划,实现农产品资源互联互通和农产品信息共享;(2)突破传统单一的某个环节监管、某一链条监管,实现从田间到餐桌全链条监管;(3)从传统的提供数据供应、需求向整条链条上农产品供给数量、需求数量、加工企业、分销网络等数据信息归纳、处理和分析,从提供信息向提供决策服务转变;(4)从事后处理向事前预警、风险防控转变,极大提升了政府各职能部门的监管效率和监管力度。[结论]采用"互联网+"思路构建的农产品供应链大数据平台,可促进农产品的协调和增值效应,确保农产品供应链健康、安全、可持续发展。     

代际差异视角下流动人口生活满意度影响因素分析

目的 探讨新一代与老一代流动人口生活满意度的影响因素,为制定流动人口管理和农民工市民化政策提供参考。方法 文章基于珠三角地区流动人口的问卷调查数据,构建OLS回归模型和分位数回归模型分析两代流动人口生活满意度。结果 （1）住房面积、社会保险、个人收入、对所在城市印象以及城市医疗影响两代流动人口生活满意度,但是在不同生活满意度分位数水平下,影响因素存在差异;（2）在低生活满意度水平下,务工年限、个人收入显著地影响老一代流动人口生活满意度,而住房面积、社会保险及对所在城市的印象显著地影响新老两代流动人口生活满意度;（3）在高生活满意度水平下,社会保险、对所在城市印象显著地影响老一代流动人口生活满意度,而务工年限显著地影响新一代流动人口生活满意度。结论 新一代流动人口的生活满意度高于老一代流动人口,在不同生活满意度分位数水平下,两代流动人口影响因素存在差异。因此,制定流动人口生活满意度政策需要考虑代际差异,还需要考虑不同分位数水平下的差异。     

Multivariate geometric expectiles

A generalization of expectiles for d-dimensional multivariate distribution functions is introduced. The resulting geometric expectiles are unique solutions to a convex risk minimization problem and are given by d-dimensional vectors. They are well behaved under common data transformations and the corresponding sample version is shown to be a consistent estimator. We exemplify their usage as risk measures in a number of multivariate settings, highlighting the influence of varying margins and dependence structures.     

High-frequency monitoring of growth at risk

Monitoring changes in financial conditions provides valuable information on the contribution of financial risks to future economic growth. For that purpose, central banks need real-time indicators to promptly adjust their policy stance. In this paper, we extend the quarterly growth-at-risk (GaR) approach of Adrian et al. (2019) by accounting for the high-frequency nature of financial conditions indicators. Specifically, we use Bayesian mixed-data sampling (MIDAS) quantile regressions to exploit the information content of both a financial stress index and a financial conditions index, leading to real-time high-frequency GaR measures for the euro area. We show that our daily GaR indicator (i) displays good GDP nowcasting properties, (ii) can provide an early signal of GDP downturns, and (iii) allows day-to-day assessment of the effects of monetary policies. During the first six months of the Covid-19 pandemic period, it has provided a timely measure of the tail risks to euro-area GDP.     

Conditional density forecast of China’s energy demand via QRNN model

We propose a new method for conditional density forecast of China’s energy demand through quantile regression neural network (QRNN). This method has at least two advantages. First, it is flexible to explore the true nonlinearity in the energy demand system via neural network structure. Second, it is able to describe the whole conditional distribution of energy demand via quantile regression. In the empirical study on China’s energy demand, QRNN outperforms several classical methods in terms of forecast accuracy both in-sample and out-of-sample. Considering China’s economic and social environment, we set a scenario for predictors and forecast the conditional density of China’s energy demand from 2015 to 2020. The empirical results show that the conditional density curve moves to right and its dispersion increases over time, which indicates that the energy demand in China will keep growing with an average annual rate of 9.672% and its uncertainty is enlarged with 42.210%.     

Gender diversity and firm performance: evidence from India and Singapore

ABSTRACT

This study investigates if gender diversity on boards is an effective driver of financial performance. For this purpose, this study choses two countries, one of which has the soft law approach (Singapore) while the other has mandatory requirements (India) on corporate boards gender diversity. By doing so, it examines if there is a comparability between the listed firms of the two countries. Our results suggest that the gender diversity has a positive and significant effect on the financial performance of the firms of both the countries. Although, the gender diversity of the two countries does not seem to affect the growth opportunities of both the countries. Further, our results indicate that the board characteristics affect the performance positively and significantly when the sample is divided into five quantiles for the firms in these two countries. These findings have implications to the managerial decision making and relevance to stewardship theory and resource dependency theory.     

工会的“收入溢价”效应研究——基于中国流动人口动态监测数据的分析

基于中国流动人口动态监测数据（2014）,实证分析流动人口工会的“收入溢价”效应。研究发现：工会能显著提升流动人口的收入,但工会的“收入溢价”效应具有异质性,城城流动人口高于乡城流动人口、签订合同者高于未签订合同者,个体私营企业的表现要优于国有集体企业和外资企业;分位数回归结果显示,随着分位数水平的上升,流动人口工会的收入效应呈倒“U”型,对中等收入者的作用最大,其次是低收入者,对高收入者的作用最小;采用倾向得分匹配法解决自选择问题,发现我国流动人口仍存在明显的工会“收入溢价”效应。     

Data visualization and forecast combination for probabilistic load forecasting in GEFCom2017 final match

This paper describes the methods used by Team Cassandra, a joint effort between IBM Research Australia and the University of Melbourne, in the GEFCom2017 load forecasting competition. An important first phase in the forecasting effort involved a deep exploration of the underlying dataset. Several data visualisation techniques were applied to help us better understand the nature and size of gaps, outliers, the relationships between different entities in the dataset, and the relevance of custom date ranges. Improved, cleaned data were then used to train multiple probabilistic forecasting models. These included a number of standard and well-known approaches, as well as a neural-network based quantile forecast model that was developed specifically for this dataset. Finally, model selection and forecast combination were used to choose a custom forecasting model for every entity in the dataset.     

财政投入和金融支持对农民农业增收贡献的比较

基于2000～2013年省级面板数据,运用固定效应模型和分位数回归模型考察了财政投入和金融支持对提升农民农业收入的影响,并采用因素分解法比较两者对农民农业增收的贡献大小,继而通过两步固定效应回归、分组回归和替换变量回归三种方式检验结果的稳健性,均得出一致结果,即财政投入和金融支持均促进农业增收,其中财政投入贡献更大,此外大规模的土地投入和完善的基础设施建设也有利于农业收入提高.     

Asymmetric Fluctuating Behavior of China's Housing Prices

The present study explains the reasons for the imbalanced development of the Chinese housing market. Using the quantile autoregression unit‐root test, we examine housing prices in China's five major cities. The results show that the rising and falling of housing prices in these cities exhibits asymmetric reversion. When housing prices fall, market capital is highly sensitive to housing prices, and housing prices resist the pressure to fall further. However, when housing prices rise, the housing market becomes imbalanced, with housing prices tending to overreact in an upturn. The results of this study indicate that when housing prices rise irrationally, the government should intervene in the housing market promptly to prevent housing bubbles.