水生态系统服务供需视角下的水网乡村 适应性规划策略——以吴江张鸭荡片区为例

苏南乡村地区一直是中国乡村建设的先行区域，特殊的纵横交错的水网结构构成了一个错综复杂的系统，呈现出其他地区不具有的复杂性和生态特殊性。随着城镇的扩张，乡村的发展建设使其水网空间的平衡发展面临极大的挑战。传统单一静态的规划方法逐渐显示出无法适应经济、社会等发展要求的缺陷。苏南乡村地区以水为核心，从水生态系统服务供需关系的视角下探究水网乡村的适应性规划策略更加适应当前的乡村现状和需求。以传统水网乡村空间形态转译为基础，建立水生态系统供需服务评估体系，在评估水生态系统服务供需能力的基础上，分析供需分异模式及供需矛盾。从构建乡村水域空间生态格局、乡村水域空间功能分区规划，以及乡村水域空间多情景预判3个方面，提出苏南水网乡村的适应性规划策略，并为水网乡村的生态实践提出新思路。     

习近平治水理念研究

[目的]总结习近平治水理念,为指导水利绿色发展提供指南。[方法]以习近平讲话和出版的论述为基础材料,开展系统的综合分析。[结果]习近平治水理念主要包括:水利为民、系统治水、生态优先、科学先行、节水优先、空间均衡、两手发力、久久为功辩证思维和国家安全。[结论]习近平治水理念是立足于中国国情水情富有创新性的水利理论概括和经验总结,是指导新时代中国水利工作的指南,是水利绿色发展的科学世界观和方法论,可为世界水利发展提供中国智慧。     

组织场域视角下水利水电工程BIM技术扩散的影响因素 ——基于TOE框架的分析

在梳理国内外BIM采纳与扩散相关研究的基础上，从新制度主义理论出发，提出了水利水电工程组织场域并分析了其特征；进而运用技术-组织-环境(TOE)框架和匹配理论，分别讨论了水利水电工程组织场域BIM扩散的主要影响因素，形成一个整体的理论分析框架。分析表明，水利水电工程组织场域BIM扩散的影响因素主要包括:相对优势、兼容性和复杂性等技术因素，组织沟通、资源就绪度和高层领导支持等组织因素，以及制度环境、市场环境等环境因素。     

进口贸易视域下国际粮价对国内粮价的传导路径--来自玉米和大豆的证据

基于玉米和大豆等粮食国际、国内价格历史数据,运用协整及误差修正模型、脉冲响应函数等方法,揭示国际粮价对国内粮价的传导作用及影响路径。理论分析表明,国际粮价通过进口直接路径、进口产品成本路径和进口替代路径等三个子路径传导至国内粮价。实证检验发现,国际大豆价格进口直接路径和进口产品成本路径传导均比较充分,即国际大豆价格会影响大豆进口价格,进而影响国内大豆价格,最终影响国内豆油价格;国际玉米价格进口直接路径和进口产品成本路径传导则不充分,国际玉米价格会影响玉米进口价格,但是对国内玉米价格和国内玉米淀粉价格影响程度较低;而在进口替代路径中,玉米和大豆的国际价格传导均不充分。我国应继续推进以提质增效为目标的农业供给侧结构性改革,加大粮食生产科技投入力度,调动农民种粮积极性,集中力量提高粮食供给质量和效率;坚持粮食进口仅为调剂国内供求余缺的方针,把握粮食安全的主动权;建立健全粮食市场的价格调控体系及风险防控体系,规避国际粮食市场剧烈波动对国内粮食市场的影响。     

Analysis of Bitcoin prices using market and sentiment variables

This paper proposes an empirical model for analysing the dynamics of Bitcoin prices. To do this, we consider a vector error correction model over two overlapping periods: 2010–17 and 2010–19. Price discovery is achieved through the Gonzalo–Granger permanent‐transitory decomposition. The pricing factors are endogenous linear combinations of the S&P 500 index, gold price, a Google search variable associated to Bitcoin and a fear index proxied by the FED Financial Stress Index. Our empirical analysis shows that during the first period, a linear combination of four pricing factors describes the efficient Bitcoin price. The S&P 500 index and Google searches have a positive effect whereas gold prices and the fear index have a negative effect. In contrast, during the second period, the efficient price behaves idiosyncratically and can be only rationalised by individuals' search for information on the cryptocurrency. These findings provide empirical evidence on the presence of a correction in Bitcoin prices during the period 2018–19 uncorrelated to market fundamentals. We also show that standard empirical asset pricing models perform poorly for explaining Bitcoin prices.     

Data vs. information: Using clustering techniques to enhance stock returns forecasting

This paper explores the use of clustering models of stocks to improve both (a) the prediction of stock prices and (b) the returns of trading algorithms.We cluster stocks using k-means and several alternative distance metrics, using as features quarterly financial ratios, prices and daily returns. Then, for each cluster, we train ARIMA and LSTM forecasting models to predict the daily price of each stock in the cluster. Finally, we employ the clustering-empowered forecasting models to analyze the returns of different trading algorithms.We obtain three key results: (i) LSTM models outperform ARIMA and benchmark models, obtaining positive investment returns in several scenarios; (ii) forecasting is improved by using the additional information provided by the clustering methods, therefore selecting relevant data is an important preprocessing task in the forecasting process; (iii) using information from the whole sample of stocks deteriorates the forecasting ability of LSTM models.These results have been validated using data of 240 companies of the Russell 3000 index spanning 2017 to 2022, training and testing with different subperiods.     

基于经济新常态的长春市水资源开发利用潜力评价

以长春市为研究对象,基于未来经济处于新常态的发展态势,构建包含水资源、社会、经济、生态环境4个子系统的评价指标体系,并确定各指标的评价等级标准;基于模糊数学理论以及层次分析法构建包括目标层、准则层、指标层的3层模糊综合评价模型,以2015年为现状水平年,应用模型对长春市水资源开发利用潜力进行综合评价。结果表明:长春市水资源开发利用程度处于中等偏上水平,各辖区水资源开发利用规模不平衡,可通过产业结构调整提高全市用水效率,为经济持续增长提供保障。     

What determines the long-term correlation between oil prices and exchange rates?

In this study, we obtain the long-term correlation between oil prices and exchange rates by employing the dynamic conditional correlation-mixed data sampling (DCC-MIDAS) model. We then identify the factors that influence the long-term correlation using panel data analysis. We find that the long-run correlations between oil prices and exchange rates are negative for all oil-exchange rate markets except Japan. We also find that both inflation and term spread have negative effects, while the risk-free interest rate has a positive effect on the long-term correlation between oil prices and exchange rates. Importantly, the empirical results show that an increase in inflation will significantly damage the real value of the currency itself.     

Testing vertical price transmission for Vietnam's Robusta coffee

Vietnam has undergone market reforms over the last three decades; and as a consequence, the coffee sector has become increasingly market‐driven. The success of the government's liberalisation policies in terms of market efficiency is investigated by examining the transmission of both positive and negative price changes for Robusta coffee between export and farmgate prices. We used a threshold vector error correction model and high‐frequency daily data. The primary result here is that of a symmetric price transmission between export and farm‐level prices. This result holds when tested with weekly price data, derived from the daily data. Farmgate prices respond faster to decreases than increases in export prices when the long‐run deviation exceeds a certain threshold. These price changes are transmitted within several days. This research also confirms the importance of transaction costs, and other price frictions mostly ignored in prior analyses for coffee.     

水源地突发水污染政府应急预留水量需求预测

近年来,随着工业化和产业化的快速发展,水源地突发水污染事件频发。为应对紧急情况下的水资源非常规需求,保障经济社会稳定发展,政府需要安排一部分应急预留水量。如何合理预测政府应急预留水量的规模是一个值得探讨的课题。提出了一种基于案例推理技术的政府应急预留水量需求预测方法,具体思路是:借助于案例库,利用主成分分析法从众多影响水源地突发水污染事件的因素中提取出两两不相关的因子,以此作为案例的特征属性,基于加权曼哈顿距离测算相似度,依此得到匹配案例,进而测算政府应急预留水量。以太湖流域常州地区水源地为例,进行政府预留水量需求量的预测与分析。该方法可以为政府应急预留水量的配置、储备等提供相关理论知识。