Granger Causality Test of Urban-rural Income Gap and Employment of Rural Labor Forces——A Case Study of Shouguang City

Taking Shouguang City in Shandong Province as an example, this article researches the mutual relationship between urban-rural income and employment of rural labor forces, and conducting cointegration test and Granger causality test on the variable sequences using statistical data. The results show that the average annual income of rural labor forces influences the income per capita of rural residents, and there is a Granger causality relationship between the income per capita of rural residents and urban employees' average wage. Engaging in production concerning agriculture, forestry, animal husbandry and fishery makes the total income per capita in rural areas of Shouguang City higher than the average wage of urban residents in Shouguang City, even in Weifang City. The comparative advantage in terms of income causes the city to loose attraction to rural residents in Shouguang City. The comparative advantage drives more rural labor forces in Shouguang City to engage in primary industry, thereby greatly reducing the pressure of employment and transfer of rural labor forces. Finally important following measures are put forward to promote employment and on-the-spot transfer of rural labor forces: vigorously propel agricultural industrialization; increase rural residents' income; improve the living conditions for rural residents.

Correlation analysis and causality test between Ludong-Huanghai block and South Japan

In this paper, we make a comparative analysis and correlation test for the seismic activities in the South Japan and the Ludong-Huanghai block （a secondary tectonic unit in the North China） and approach the relationship between the energy release processes of these two areas by using co-integration analysis and Granger causality test for the time series of random variables. The results show that the seismic activities in these two areas are correlative and synchronous to a certain extent, and their release series of cumulative strain energy are contemporaneously correlative. Both energy series are first-order difference stationary processes and there is secular and steady co-integration between them. We make a positive analysis on the first-order difference energy series through Granger causality test based on vector error correction （VEC） model and find there is unilateral Granger causality and prominent co-integration between the two energy release processes.

Rural Financial Development and Rural Economic Efficiency Improvement Based on Granger Causality Test

Based on the co-integration test theory,Financial Interrelation Ratio(FIR),level of financial efficiency(LFE),level of financial development(LFD) and other indices evaluating the rural financial development are selected by Granger Causality Test.The rural loan balance(RLB),rural deposit balance(RDB),total rural output(TRO),fixed assets investment(FAI),Financial Interrelation Ratio(FIR),economic efficiency(EE),level of financial efficiency(LFE),and level of financial development(LFD) in the years 1979-2007 are collected.Graphical method intuitively reflects the development trend and historical track of relevant indices;and Granger Causality Test verifies the relationship between rural financial development level and rural economic efficiency in the years 1979-2007.Result shows that rural financial development level has significant impact on rural economic growth,but rural economic growth has no significant impact on rural financial development;and rural financial development also has insignificant promotion impact on rural economic efficiency.Thus,conclusions are obtained.Although rural financial development has made certain contribution to the development of rural economy,this kind of contribution is only reflected in total quantity,but not efficiency.Therefore,government should further strengthen the promotion function of financial development for economic efficiency,and gradually establish a virtuous circle system for rural finance and economic development.

基于时变传染网络和分位数Granger因果检验的系统性风险传染研究

基于18个经济体760家金融机构SRISK系统性风险数据,采用时变参数向量自回归模型和广义方差分解法测度全球系统性风险的时变传染网络,进而采用分位数Granger因果检验考察各经济体对中国高分位段系统性风险的影响。研究结果表明,结合SRISK数据和时变传染网络能有效识别重大风险事件的发生;发达和新兴经济体均会产生风险净输出效应,且会通过直接输出或香港地区间接输出风险至中国内地;在全样本与2008年金融危机、欧债危机、中美贸易战和新冠疫情重大风险事件期间,中国皆为风险净溢入国且新冠疫情期间溢入效应达历史最高;美英两国在重大风险事件期间均对中国高分位段系统性风险产生显著影响,新冠疫情期间中国高分位段系统性风险遭受外部冲击的形势最为严峻。

农业生产性服务业与新型农业经营主体耦合协调关系的实证研究--以吉林省为例

在乡村振兴和农村产业融合大背景下,正确认识和处理农业生产性服务业和新型农业经营主体之间的协调发展关系具有重要意义。为明确农业生产性服务业与新型农业经营主体两系统的耦合协调关系,基于吉林省2010-2022年农业生产性服务业与新型农业经营主体的时间序列数据,运用协整分析、Granger因果检验和耦合协调模型分析农业生产性服务业与新型农业经营主体间的互动关系和动态耦合发展趋势。结果表明:吉林省农业生产性服务业与新型农业经营主体发展水平持续攀升,分别由0.284 9提升至0.837 9、0.100 1提升至0.994 1;农业生产性服务业与新型农业经营主体两系统存在着显著正相关的长期均衡关系,且互为格兰杰原因,即农业生产性服务业是有效促进新型农业主体发展的重要原因,新型农业经营主体是推动推动农业生产性服务业提升的重要动力;2010-2022年,吉林省农业生产性服务业与新型农业经营主体之间的耦合协调关系上升趋势明显,先后经历拮抗阶段(0.410 9)、勉强协调(0.517 9~0.572 0)、初级协调(0.637 4)、中级协调(0.735 8~0.773 8)、高度协调(0.843 1~0.870 9~0.916 6~0.914 7~0.914 8~0.915 3~0.915 7)的变化过程,目前两系统处于关系稳定的高水平耦合阶段。未来应通过促进农业生产性服务业与新型农业经营主体协调发展推进现代农业进程。

Analysis of services trade and employment in China by co-integration and causality

This article describes a study by co-integration test and Granger causality test on the relationships between China's services trades and employment using the data of services trade from the WTO website and the employment data from China Statistic Yearbook for the years from 1982 to 2003. Co-integration test showed that 1% increase in export value and import value of services created respectively 0.205% and 0.068 7% more job opportunities in the service sector. Both export and import of services impacted positively on employment in service industry, and export did more than import. However, in the short run, the impacts of services export and import on employment in service industry were both very small, though positive; and the impacts of employment in service industry on both export and import of services were very big, but not stable. Granger causality test indicated that employment in service industry was a Granger cause of services export. The findings highlight the importance of facilitating services import and reducing import barriers, and suggest that the competitiveness of China's labor- intensive services trade can be exploited to boost services export and help employment in service sector, and that the structure of services trade should be optimized by shifting from labor-intensive to knowledge-and technology-intensive services thus to enhance China's competitiveness of services export.

中国金融-房地产系统的风险溢出效应研究

本研究提出了风险级联传染网络模型,证明了当传染轮数趋于无穷时,节点风险增量收敛的充分必要条件是风险传染强度矩阵特征值的模值小于1。在实证研究方面,本研究基于公开的股票市场数据,构建了中国的房地产-金融系统风险传染网络。结果表明:(1)从2010年到2022年,总体风险传染强度在波动中不断上升,房地产业是最大的系统性风险源头(2)房地产业对银行业的溢出风险存在类别与空间异质性。(3)节点重要性分数服从幂律分布。

欧洲七国入境中国旅游与进出口贸易的关系——1985-2009年的协整分析和Granger因果关系检验

选取1985～2009年欧洲七国入境中国客流量与进出口贸易统计数据,运用协整分析和Granger因果检验方法,构建各国入境中国客流量与进口贸易、出口贸易的协整方程和修正模型,分别对欧洲七国入境中国客流量与进出口贸易额之间的关系进行分析和研究。结果表明:欧洲七国入境中国客流量与其对中国进出口贸易额存在长期均衡关系,各国入境客流量对进口和出口贸易额的长期弹性远大于短期弹性;Granger因果关系检验显示,欧洲七国入境中国客流量与进口贸易额存在显著的单向因果关系,英国、德国和瑞典入境中国客流量与出口贸易额的单向因果关系显著,瑞士进口贸易额、意大利出口贸易额与其入境中国客流量的单向因果关系显著,其差异性与各国入境中国客流量的大小、贸易依存度、贸易顺逆差情况和双边关系的对称性差异密切相关。

开放式基金赎回问题研究——基于Panel-Data的Granger因果检验

本文应用新近发展的Panel-Data Granger因果检验方法,检验开放式基金的赎回率和基金单位净值(NAPS)增长率以及基金累计净值(ACCNAV)增长率之间的因果关系。通过对2002年12月31日以前成立的17支基金的14个季度数据的研究发现:(1)基金单位净值增长率和基金累计净值增长率并不是基金赎回率的Granger原因,一直困扰着开放式基金的"赎回困惑"不过是一个"假象";(2)基金赎回率是基金单位净值增长率和基金累计净值增长率的Granger原因,高的基金赎回率大大的降低了基金单位净值增长率和基金累计净值增长率。

Panel-Data下Granger因果检验的理论和应用发展综述

Panel-Data下Granger因果检验的相关理论是最近几年才发展起来的,现有的研究提出了关于Panel-Data下Granger因果检验的四个基本假设:同质无因果关系假设(HNCH)、同质因果关系假设(HCH)、异质因果关系假设(HECH)以及异质无因果关系假设(HENCH),根据检验参数的特点给出三种类型的检验模型:固定系数模型、随机系数模型和混合固定随机系数模型。目前,还只有固定系数模型的相关理论较为完善,另外两种模型的检验还都存在一定的难度。因此,只有从理论研究和实际应用两个方面对该理论进行阐述,并对现有的理论进行简要的评述,才可指出其存在的不足及可能的改进方向。

基于MI-Granger-NARX融合模型的铁路网规模测算方法

铁路网的建设进程应与经济社会发展保持适度匹配,其路网规模受人口资源、经济社会、交通政策和运营组织等因素影响,具有动态、时滞、非线性的复杂特征。首先,在不依赖先验信息的情况下,运用互信息法对人均GDP、全社会货运量、旅客周转量等12项影响铁路网规模的指标进行互信息计算。接着,运用Granger因果检验对初选指标进一步筛选,获得7项最具解释力的指标。然后,利用NARX良好的学习记忆与延迟反馈功能构建测算模型,以筛选所得7项指标作为自变量输入、铁路网里程序列作为因变量自回归输入测算铁路网里程。最后,将本模型与传统BP、NAR和单一NARX等神经网络模型的测算结果进行验证、对比。结果表明本模型解释能力更强、泛化能力更好和结果精度更高。

区域物流发展水平与进出口贸易关系的实证研究——基于河南省1978-2010年数据的协整分析和Granger因果检验

从供给和需求两个视角选取物流业发展水平的评价指标,对河南省物流业发展水平与进出口贸易增长关系进行了计量分析。通过Johansen协整检验得出:河南省物流业的供给和需求水平与进出口贸易之间存在长期稳定的协整关系;通过Granger因果检验得出:河南省物流业需求水平对进出口贸易有显著的影响,而物流业供给水平对进出口贸易影响不显著,物流业总体发展水平与进出口贸易之间未呈现良性互动态势。

农业财政支出与农业GDP波动(1978-2001)——一个Granger因果检验

中国农业财政支出与农业GDP增长都呈循环波动形式。为表明农业财政支出波动受农业GDP波动影响,利用一个非参数检验法识别出两者的非随机波动之后,基于两者波动的协整关系,建立误差修正模型,检验两者波动的Granger因果关系。

工资上升、国际油价上涨对中国出口绩效的动态冲击效应研究——基于非线性Granger检验和TVR-VAR模型的考察

基于非线性Granger因果检验方法检验了各因素与出口绩效之间的互动关联,在此基础采用TVP-VAR模型考察不同时间点、不同提前期各变量对出口绩效的动态演变特征。最终得出以下主要结论:工资上升在短期内会促进出口增长,但并没有形成工资上升冲击对出口的"惯性效应",而中、长期冲击影响为负;国际油价的上涨冲击在短期内对出口额没有显著影响,在中、长期会通过出口价格上涨而抑制出口;此外,由于出口产品附加值低、出口需求弹性较大,使得实际有效汇率指数上升对出口产生了较为显著的抑制作用;"外需疲软、内需增强"的状况使得经济增长驱动型出口正效应逐渐减弱;中国经济已与世界经济具有很强的协同性,国际经济形势与中国出口显著正相关。

CEEMD双层分解和Granger因果变量选择风电功率预测

针对风电功率时间序列具有高度随机波动性而无法精准预测的问题,提出一种基于完备集成经验模态分解(CEEMD)、Granger因果关系检验和长短时记忆网络的新型混合预测方法用于预测风电功率。首先,为研究风电功率和风速的隐性相关性,通过CEEMD算法对风电功率和风速时间序列分别进行序列分解,实现双层分解。其次,通过Granger因果关系方法对各风速分量与各风电功率分量进行因果关系检验,分析风电功率分量与各风速分量间的相关性,以此实现各风电功率分量的输入变量选择。最后,采用长短时记忆网络对各风电功率分量进行预测,并集成得到最终的风电功率预测结果。通过风电厂的实际数据进行了试验,并与多个应用广泛的经典模型进行对比,结果表明该方法的预测精度取得了大幅度提高,能够对风电功率实现精准预测。

中国玉米淀粉期货市场有效性研究--基于VAR模型

玉米淀粉在日常生活中应用广泛,但近年来它在我国价格波动剧烈,这样的状况不利于我国玉米淀粉产业的健康发展。因此,选取2017年1月2日至2021年4月30日我国玉米淀粉期现货每日交易价格数据,运用E-G两步法协整检验,格兰杰因果检验、方差分解等方法验证我国玉米淀粉期货市场能否有效发挥价格发现功能。研究表明:中国玉米淀粉期现货市场之间维持长期均衡关系,且现货市场受到期货市场的显著影响,期货市场初步具有价格发现功能。

Abnormal behavior detection by causality analysis and sparse reconstruction

A new approach for abnormal behavior detection was proposed using causality analysis and sparse reconstruction. To effectively represent multiple-object behavior, low level visual features and causality features were adopted. The low level visual features, which included trajectory shape descriptor, speeded up robust features and histograms of optical flow, were used to describe properties of individual behavior, and causality features obtained by causality analysis were introduced to depict the interaction information among a set of objects. In order to cope with feature noisy and uncertainty, a method for multiple-object anomaly detection was presented via a sparse reconstruction. The abnormality of the testing sample was decided by the sparse reconstruction cost from an atomically learned dictionary. Experiment results show the effectiveness of the proposed method in comparison with other state-of-the-art methods on the public databases for abnormal behavior detection.

ICA Based Identification of Time-Varying Linear Causal Model

Recently, several approaches have been proposed to discover the causality of the time-independent or fixed causal model. However, in many realistic applications, especially in economics and neuroscience, causality among variables might be time-varying. A time-varying linear causal model with non-Gaussian noise is considered and the estimation of the causal model from observational data is focused. Firstly, an independent component analysis(ICA) based two stage method is proposed to estimate the time-varying causal coefficients. It shows that, under appropriate assumptions, the time varying coefficients in the proposed model can be estimated by the proposed approach, and results of experiment on artificial data show the effectiveness of the proposed approach. And then, the granger causality test is used to ascertain the causal direction among the variables. Finally, the new approach is applied to the real stock data to identify the causality among three stock indices and the result is consistent with common sense.

基于Attention-ConvLSTM的出租车需求预测研究

准确合理的出租车需求预测能平衡乘客出行需要且缓解城市交通拥堵,但出租车需求是动态的,它会随着时间的周期性和空间的相关性变化而变化。使用神经网络的出租车需求预测模型广受关注,但目前大部分模型对需求数据的时空间特征提取有效性不足,缺乏筛选数据特征的能力,使得预测结果不够贴合现实情况。对此,本文提出AttConvLSTM预测模型。首先通过k-means聚类和Granger因果关系检验寻找与检验时空相关性,再结合影响需求的气候和节假日等外部因素,运用卷积长短期记忆网络(ConvLSTM)融合注意力机制捕获及评估时空间特征,对特征进行选择性注意,从而提高预测结果的精度与可靠性。最终选取纽约市出租车需求数据进行实验,结果表明该模型相比多种知名基线模型表现出更高的准确度和稳定性。