The relationship between international crude oil prices and China＇s refined oil prices based on a structural VAR model

With the frequent fluctuations of international crude oil prices and China＇s increasing dependence on foreign oil in recent years, the volatility of international oil prices has significantly influenced China domestic refined oil price. This paper aims to investigate the transmission and feedback mechanism between international crude oil prices and China＇s refined oil prices for the time span from January 2011 to November 2015 by using the Granger causality test, vector autoregression model, impulse response function and variance decomposition methods. It is demonstrated that variation of international crude oil prices can cause China domestic refined oil price to change with a weak feedback effect. Moreover, international crude oil prices and China domestic refined oil prices are affected by their lag terms in positive and negative directions in different degrees. Besides, an international crude oil price shock has a signif- icant positive impact on domestic refined oil prices while the impulse response of the international crude oil price variable to the domestic refined oil price shock is negatively insignificant. Furthermore, international crude oil prices and domestic refined oil prices have strong historical inheri- tance. According to the variance decomposition analysis, the international crude oil price is significantly affected by its own disturbance influence, and a domestic refined oil price shock has a slight impact on international crude oil price changes. The domestic refined oil price variance is mainly caused by international crude oil price disturbance, while the domestic refined oil price is slightly affected by its own disturbance. Generally, domestic refined oil prices do not immediately respond to an international crude oil price change, that is, there is a time lag.

An Empirical Study of the Relationship among Population Mobility Industrial Structure Upgrading, and Economic Growth-Based on the SPVAR Model

Based on the inter-provincial panel data for 31 provinces in China from 2000 to 2019,and incorporating geospatial factors,a spatial panel vector autoregressive(SPVAR)model consisting of population mobility,industrial structure upgrading,and economic growth is constructed.The space-time impulse response function is used to analyze the space-time conduction of exogenous variables on the impact of three endogenous variables.The study found that first,the population influx barely benefited the industrial structure upgrading and economic growth.Second,the upgrading of the industrial structure would aggravate the population mobility in the province,causing low-level laborers to leave the province in shortterm,but in long-term,there would be influx of talents.Third,the economic growth in developed regions plays a significant role in promoting the industrial development of their province and population-rich provinces,but it has less impact on provinces with high-level industrial structure.Finally,policy recommendations are provided in regard to the benign interaction among population mobility,industrial structure upgrading,and economic growth in addition to clarifying the idea of economic development,implementing correct population policies,and promoting the coordinated regional development.

Structural Monetary Policy, Bank Credit and Bank Liquidity—An Empirical Analysis Based on VAR Model

After the outbreak of the international financial crisis,the People’s Bank of China,based on traditional monetary policy tools,launched a series of structural monetary policy tools such as standing lending facility(SLF),medium-term lending facility(MLF),and pledged supplementary lending(PSL)and targeted at liquidity via the commercial banking system.In order to test the credit transmission effect of structured monetary policy,this paper empirically analyzes the relationship between structured monetary policy,bank liquidity and bank credit based on the VAR model.The research shows that the implementation of structured monetary policy reduces the liquidity of commercial banks in the short term and increases in loans to small or micro enterprises and agriculture-related loans,these policies have produced significant short-term effects on credit transmission in steady of long-term effects.Thus,a series of supporting measures are needed to fully exert the effects of structural monetary policy.

The Structural Relationship between Chinese Money Supply and Inflation Based on VAR Model

With the development of economy, more and more attention is paid to the relationship between money supply and inflation in the economic field. This paper chooses consumer price index (CPI) as an important index to measure the level of inflation, by choosing between January 2008 and March 2019 money in circulation M0, narrow measure M1, broad measure M2, consumer price index CPI monthly data as sample, building a vector autoregressive (VAR) model and using econometric methods of impulse response function and variance decomposition, and finally characterizes money in circulation M0, narrow measure M1, broad measure M2 and the relationship between consumer price index CPI and different sizes of the impact of inflation in the money supply relationship.

Empirical Analysis of Gross Domestic Product and Coal Import Based on VAR Model

The speed of China’s economic development is gradually accelerating, and the demand for energy is also constantly increasing, especially the demand for coal. In order to reveal whether the coal imports have an impact on China’s economic development, this paper constructs the VAR(6) model by selecting the quarterly data of coal imports (CIV) and gross domestic product (GDP) from 2002 to 2017, performing ADF (Augmented Dickey-Fuller) stationarity test and Johansen cointegration test. It shows that there is a long-term stable equilibrium relationship between coal imports and GDP. Then the impulse response function is used to obtain the relationship between coal imports and GDP. It is found that the impact of coal imports on GDP is greater than the impact of GDP on coal imports.

Research on the Relationship Between Environmental and Economic Coupling Systems in Bohai Bay Area Based on a Vector Autoregression(VAR)Model

This study analyzed the impact of land-based contaminants and tertiary industrial structure on economic development in the selected Bohai Bay area,China.Based on panel data spanning 2011-2020,a vector autoregressive(VAR)model is used to analyze and forecast the short-run and long-run relationships between three industrial structures,pollutant discharge,and economic development.The results showed that the environmental index had a long-term cointegration relationship with the industrial structure economic index.Per capital chemical oxygen demand(PCOD)and per capita ammonia nitrogen(PNH_(3)N)had a positive impact on delta per capita GDP(dPGDP),while per capita solid waste(PSW),the secondary industry rate(SIR)and delta tertiary industry(dTIR)had a negative impact on dPGDP.The VAR model under this coupling system had stability and credibility.The impulse response results showed that the short-term effect of the coupling system on dPGDP was basically consistent with the Granger causality test results.In addition,variance decomposition was used in this study to predict the long-term impact of the coupling system in the next ten periods(i.e.,ten years).It was found that dTIR had a great impact on dPGDP,with a contribution rate as high as 74.35%in the tenth period,followed by the contribution rate of PCOD up to 3.94%,while the long-term contribution rates of PSW,SIR and PNH3N were all less than 1%.The results show that the government should support the development of the tertiary industry to maintain the vitality of economic development and prevent environmental deterioration.

Should Low-Frequency-High-Consumption Enterprises Add Online-to-Offline Platforms?An Empirical Study Using the VAR Model

This study investigates the impact of online-to-offline(O2O)platforms,such as Ele.me and Meituan,on offline sales in low-frequency-high-consumption industries,specifically a mid-to-highend liquor distribution chain.Using data from 77 offline stores in Beijing collected during 2019-2022,the study employs a VAR model to analyze the relationship between offline sales and the use of O2O platforms.The results reveal a long-term equilibrium between the two,with most indicators showing a positive impact of O2O platforms on offline sales.The research provides valuable insights for lowfrequency-high-consumption enterprises in making multi-channel decisions and quantifies the impact of O2O platforms on offline sales.

基于VAR模型的生猪产业链价格波动影响因素分析

生猪产业链价格剧烈波动不仅关系消费者的切身利益,也对生猪产业长远发展具有重要影响。基于2009—2022年161个月度样本数据,文章采用VAR模型,从生猪产业链主要产品价格以及上游环节、中下游环节2个层面出发,探究生猪产业链价格波动的影响因素。结果显示:生猪产业链价格波动受自身主要产品价格的影响最大,前10期生猪产业链主要产品价格对当月生猪产业链价格波动仍具有61.835 8%的影响。从产业链上游环节观察,稻糠价格、大豆价格和小麦麸价格均能够对生猪产业链价格波动产生显著影响,前10期稻糠价格对当月生猪产业链价格波动的影响达到39.783 8%。从产业链中下游环节观察,通货膨胀水平和养殖场规模对生猪产业链价格波动的影响程度较大。研究表明,生猪产业链价格波动容易受到自身主要产品价格、稻糠价格、大豆价格、小麦麸价格、通货膨胀水平、养殖场规模等因素影响,应从完善价格波动预警机制和加强流通运行环节调控两方面着手推动生猪市场稳定发展。

财政政策、货币政策与高质量就业——基于TVP-SV-VAR模型的动态分析

更加充分、更高质量的就业是实现经济高质量发展的应有之义。文章采用中国2000—2021年的季度时间序列数据,基于时变参数向量自回归(TVP-SV-VAR)模型,实证检验财政政策与货币政策对就业质量的时变及动态影响。研究发现:落实减税降费政策、优化财政支出结构在短期和中长期均有效地促进了高质量就业。面对国际金融危机冲击时,财政政策在短期内实现了对就业质量的保障,而在长期内政策效果受到削弱,这说明高质量就业的实现并非“斯须之作”。数量型货币政策对就业质量的调节作用较为平稳,其影响具有滞后性,而价格型工具更能有效熨平外部冲击对就业质量的影响。相较货币政策,财政政策对就业质量的调控具有更强的拉动作用与抗冲击能力。

我国牛肉价格波动影响因素研究——基于VAR模型的实证分析

为保证牛肉价格合理稳定、推动牛肉市场持续健康发展,文章基于2011年12月—2022年12月中国畜牧业月度数据,以内部传导和外部冲击为视角,选取玉米价格、生产者预期、犊牛价格、国家政策构建VAR模型,实证检验我国牛肉价格波动影响因素及程度。结果显示,玉米价格、生产者预期、犊牛价格、国家政策均可对牛肉价格造成影响。其中,玉米价格可通过内部传导机制对我国牛肉价格波动产生显著影响,且稳定贡献率在8%左右;国家政策可通过外部冲击机制对我国牛肉价格波动形成显著影响,贡献率为15%;前期牛肉价格可显著影响后期牛肉市场价格。因此,文章提出降低肉牛产业饲料成本、加大肉牛产业政府财政支持力度、完善牛肉价格波动市场监管体系的建议,以期为稳定牛肉价格、促进畜牧产业可持续发展提供参考。

“双支柱”政策调控与企业金融资产配置时变关系研究:基于TVP-SV-VAR模型的实证检验

金融科技发展和市场制度变革给传统金融体系带来的巨大冲击,使得“双支柱”政策调控的有效性面临严峻考验。借助TVP-SV-VAR模型,实证检验“双支柱”政策调控对企业金融资产配置的动态脉冲效应。研究表明,货币政策和宏观审慎政策的调控效果呈现出阶段性的演化特征,二者的协同效应能够有效抑制企业金融资产的过度配置。相比制度环境冲击,“双支柱”政策调控在面对金融环境冲击时表现出更强的作用效果和力度。进一步研究发现,“双支柱”政策通过资本流动管理、资产价格稳定和金融风险缓释途径影响企业金融资产配置,且对流动性与非流动性金融资产配置的作用效果存在显著差异。研究结论为理解实体企业金融化和完善金融市场制度提供了新的理论视角,也为政府相关部门依据金融环境和制度环境进行“双支柱”政策调控的动态调整提供决策依据。

服务业进出口、OFDI和全要素生产率的动态关系研究——基于VAR模型的实证分析

研究服务业贸易、投资与服务业之间的影响关系,对提升我国服务行业国际竞争力、促进其高质量发展具有重要意义。论文使用我国2000—2021年数据,构建VAR模型对服务业进出口、服务业对外直接投资(OFDI)和全要素生产率的动态交互关系进行实证分析。研究结果显示,服务业进出口对服务业对外直接投资具有正相关关系,且长期支持效果明显;服务业进出口对OFDI、全要素生产率提升具有促进作用;在短期内,全要素生产率与OFDI之间存在双向促进作用,从长期来看则存在一定负向影响。基于实证研究结论,文中提出制定政策鼓励服务企业参与国际化竞争、发挥服务业进出口对OFDI的促进效应、提升服务企业自主创新能力等相关对策建议。

基于VAR模型的专业市场与跨境电商融合发展研究

专业市场如何应对电子商务冲击,是近二十年来各界普遍关注的现实问题。跨境电商和市场采购两种新业态新模式已成为我国外贸高质量发展的新引擎,专业市场与跨境电商的关系从冲击应对走向融合发展。浙江省义乌市是专业市场和跨境电商的改革前沿阵地。利用义乌市2008—2022年的时间序列数据,建立向量自回归模型,定量分析专业市场与跨境电商的融合发展关系。结果表明:专业市场生态体系有利于跨境电商“嵌入式”发展,专业市场的持续改革有效应对了跨境电商冲击,但两者融合发展仍缺乏互动效应和长效机制。为进一步促进两者融合发展,应搭建专业市场跨境电商平台、叠加商流和信息流带动产业转型升级、融通跨境电商进口贸易供应链和配套政策。

官方新闻对人民币汇率变动的影响——基于TVP-VAR模型的研究

以中国官方发布的汇率新闻为对象的研究,从文本措辞角度对2010年至2023年中国央行和外汇局的官方网站新闻进行分类,构建“汇率升贬”、“汇率弹性”、“汇率制度”、“人民币国际化”和“美元相关”五种新闻措辞指数,进而利用TVP-VAR模型研究官方新闻对人民币汇率的影响。研究表明,官方新闻对人民币汇率存在明显时变特征,产生的冲击效应在短期尤为明显,长期趋近于零;官方新闻中不同措辞类型对人民币汇率的影响存在异质性;在进一步研究中发现,官方新闻指数对人民币汇率有升值影响,对汇率波动有增强效果,且离岸市场受到的影响更大。

新疆乡村生态旅游与区域经济发展的动态关系研究——基于VAR模型

乡村旅游产业已成为一种具有重大意义的新兴产业,不仅可以加强城乡融合,还可以激发农村经济的活力,实现工业升级,成为当地实现乡村振兴的重要支撑。研究以2000—2020年新疆乡村生态旅游数据为基础,构建了以森林覆盖率、果园面积、年接待游客人数、农村人均家庭经营净收入、地区生产总值为变量的VAR模型,采用协整检验、格兰杰因果检验、脉冲响应和方差分解等分析手段,探讨新疆地区乡村生态旅游与地区经济发展之间的动态关联。结果表明:新疆乡村生态旅游与区域经济发展具有长期稳定共同发展的趋势;新疆地区生产总值GDP与森林覆盖率和每年接待游客人数具有单向因果关系;地区生产总值对森林覆盖率和每年接待游客人数的波动影响较大。

我国碳市场与化石能源市场溢出效应研究——基于VAR-GARCH-BEKK模型的分析

碳市场的建立是实现“双碳”目标的重要保障,分析碳市场与化石能源市场间的溢出效应有助于提升市场流动性、规避碳金融风险,从而更好地推动国家气候战略目标。本文运用主成分分析方法将我国8个碳试点价格集成,明确试点阶段我国碳市场的整体发展规律,并通过VAR-GARCH-BEKK模型,进一步探究了全国统一碳市场建立前后碳市场与化石能源市场之间溢出效应的变化情况。结果表明,试点阶段碳市场与各类化石能源市场之间均存在显著的单向均值溢出效应。然而,在全国碳排放权交易市场建立初期,仅有部分发电行业参与交易,这在一定程度上削弱了碳市场与化石能源市场之间的联动关系,造成了二者之间均值溢出效应的下降。此外,全国统一碳市场的建立吸引了更多的投资者,加剧了碳市场和化石能源市场间的风险传染,需要进一步完善监管政策体系,保障碳市场平稳健康运行。

基于贝叶斯模型与VAR模型的蔬菜销量与定价预测

对商超蔬菜日销售数据进行数据透视筛选,利用同期平均法处理异常值和缺失值,生成年度日销售新数据.对单品蔬菜销量进行Shapiro-Wilks检验,发现不服从正态分布,但经相关性分析发现同类别不同蔬菜单品销量间存在显著相关性.构建同类蔬菜销量Bayesian模型,定量化表达单品间销量的关系,建立单品蔬菜销量的Bayesian模型刻画销量的主要影响因素,两个模型分析和预测结果与实际相符.构建VAR(2)模型,完成未来一周补货设计.以收益最大化为目标,在满足市场需求与销售空间限制下,建立优化模型,完成未来一天的补货量及定价设计,为商超蔬菜销售提供合理化建议.

基于VAR模型的我国肉羊育肥饲料价格波动实证研究

文章利用2012年1月-2022年12月的132个肉羊育肥饲料价格月度数据,从内部传导和外部冲击2个视角出发,选取豆粕价格、小麦麸价格、羊肉价格以及自然灾害风险指数作为解释变量,对我国肉羊育肥饲料价格波动的影响因素展开分析。结果表明:豆粕价格通过内部传导机制对肉羊育肥饲料产生显著影响;自然灾害事件通过外部冲击机制对肉羊育肥饲料价格波动产生明显影响;前期肉羊育肥饲料价格对后期肉羊育肥饲料价格具有显著影响。研究表明,文章结论可为维护肉羊育肥饲料价格长期稳定提供参考。

跨周期调节视域下货币政策对市场信心的影响研究——基于TVP-VAR模型的动态分析

搞好跨周期政策设计,提高逆周期调节能力,需要做好“稳预期”工作,本文对代表预期核心指标的信心展开研究。首先通过动态因子模型构建了包含各类经济主体心理预期指标的信心周期综合指数,接着在新凯恩斯模型的框架下理论分析信心在宏观经济运行以及货币政策传导中的重要作用。实证部分结合信心周期综合指数,运用TVP-VAR模型考察了信心对宏观经济运行影响效应的时变特征以及不同货币政策调控对信心的时变影响。研究结论和启示如下:(1)信心与经济周期之间具有正向相互驱动效应,央行在政策框架的设计上需要考虑信心体系的稳定;(2)通货膨胀会对信心带来负向冲击,从而使得价格周期与信心周期背离,信心不是驱动价格周期波动的格兰杰原因;(3)在货币政策调控方面,宽松的数量型调控政策提振信心的效果更直接,价格型政策调控在“稳预期”工作上还亟待提高。

基于VAR模型的石家庄市PM_(2.5)的影响因素研究

根据石家庄市2013年12月2日至2021年2月1日的空气污染物PM_(2.5)、PM_(10)、SO_(2)、CO、NO_(2)和O_(3)浓度数据,以及日平均气温、日平均气压、日平均相对湿度、2 min平均风速和10 min平均风速气象数据,利用向量自回归模型(Vector autoregression,VAR),从各空气污染物变量和气象变量中选取对时间序列影响较大的重要变量,研究PM_(2.5)与重要变量之间的动态关系及它们对PM_(2.5)浓度的影响。结果表明:SO_(2)浓度、NO_(2)浓度、O_(3)浓度、日平均气温、日平均气压、2 min平均风速相较其他变量对PM_(2.5)浓度有显著影响;从长期关系来看,SO_(2)浓度和日平均气压变量对PM_(2.5)浓度有正向影响,NO_(2)浓度、O_(3)浓度、日平均气温,以及2 min平均风速变量对PM_(2.5)浓度的增加有抑制作用。