Markov-Switching Time-Varying Copula Modeling of Dependence Structure between Oil and GCC Stock Markets

This paper proposes a Markov-switching copula model to examine the presence of regime change in the time-varying dependence structure between oil price changes and stock market returns in six GCC countries. The marginal distributions are assumed to follow a long-memory model while the copula parameters are supposed to evolve according to the Markov-switching process. Furthermore, we estimate the Value-at-Risk (VaR) based on the proposed approach. The empirical results provide evidence of three regime changes, representing precrisis, financial crisis and post-crisis, in the dependence structure between energy and GCC stock markets. In particular, in the pre- and post-crisis regimes, there is no dependence, while in the crisis regime, there is significant tail dependence. For OPEC countries, we find lower tail dependence whereas in non-OPEC countries, we see upper tail dependence. VaR experiments show that the Markov-switching time- varying copula model performs better than the time-varying copula model.

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.

Inflationary effects of oil prices and domestic gasoline prices:Markov-switching-VAR analysis

The purpose of this study is to contribute to the literature by studying the effects of sudden changes both on crude oil import price and domestic gasoline price on inflation for Turkey, an emerging country. Since an inflation targeting regime is being carried out by the Central Bank of Turkey, determination of such effects is becoming more important. Therefore empirical evidence in this paper will serve as guidance for those countries, which have an in- flation targeting regime. Analyses have been done in the period of October 2005-December 2012 by Markovswitching vector autoregressive （MS-VAR） models which are successful in capturing the nonlinear properties of variables. Using MS-VAR analysis, it is found that there are 2 regimes in the analysis period. Furthermore, regime changes can be dated and the turning points of economic cycles can be determined. In addition, it is found that the effect of the changes in crude oil and domestic gasoline prices on consumer prices and core inflation is not the same under different regimes. Moreover, the sudden increase in gasoline price is more important for consumer price infla- tion than crude oil price shocks. Another finding is the presence of a pass-through effect from oil price and ga- soline price to core inflation.

Price linkage between Chinese and international nonferrous metals commodity markets based on VAR-DCC-GARCH models

Using VAR-DCC-GARCH model,the literature on commodity price was extended by exploring the co-movement between Chinese nonferrous metal prices and global nonferrous metal prices represented by the nonferrous metal prices from London Metal Exchange(LME).The results show that LME nonferrous metals prices still have a greater impact on Chinese nonferrous metals prices.However,the impact of Chinese nonferrous metals prices on LME nonferrous metals prices is still weak except for lead price.The co-movement of nonferrous metal prices between LME and China presents hysteretic nature,and it lasts for 7-8trading days.Furthermore,the co-movement between LME nonferrous metals prices and Chinese nonferrous metals prices has the characteristics of time-varying,and the correlation of lead prices between LME and China is the more stable than all other nonferrous metals prices.

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。

金融冲击对劳动市场波动的时变效应——基于TVP-SV-VAR模型的实证研究

本文基于金融市场与劳动市场联动的视角,构建中国金融状况指数,并利用时变参数随机波动向量自回归模型(TVP-SV-VAR)研究金融冲击对劳动市场的影响及时变特征。结果表明,金融冲击显著引发劳动市场的供需失衡。金融状况恶化会提升失业率、降低工资水平并进一步引起宏观经济中的通货紧缩。机制分析表明,企业杠杆对金融冲击的负面影响有放大作用,金融条件紧缩经由企业杠杆的负向调整会进一步导致劳动需求萎缩与失业率上行。对跨境金融冲击和境内金融冲击效果的比较分析揭示,相较于传导渠道,冲击规模是金融冲击对我国劳动市场影响差异的主导因素。据此,本文建议在跨周期调节的同时注意防范化解金融风险,以提升金融支持“稳主体”和“稳就业”的政策效果。

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。

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。

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.

“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。

能源进口与中国绿色金融发展——基于TVP-VAR模型的分析

在当前国际环境不确定性加大的情况下,能源进口波动与国内绿色金融发展的相互影响成为一个应当切实关注的问题。通过建立包含能源进口、能源价格波动、经济政策不确定性和绿色金融发展在内的四变量时变参数向量自回归(TVP-VAR)模型,实证分析2010-2022年主要化石能源进口与绿色金融发展之间的相互影响和脉冲响应关系。结果表明:(1)能源进口的扩张在短期内会对中国绿色金融市场造成波动,长期内会促进中国绿色金融市场的发展;而绿色金融的发展对能源进口具有正向的促进作用,和能源进口呈现良性的循环。(2)能源进口对绿色金融发展的作用随经济政策不确定性和能源价格指数波动的变化而变化,呈现出非线性特征。(3)在国际政治环境不稳定时,石油对于国内经济的影响表现突出,相对重要性高于煤炭和天然气。石油进口波动在长期情况下提高本国经济政策不确定性,但同时也促进绿色金融的发展。研究凸显了深化能源机制体制改革的重要意义,应充分发挥绿色金融市场对能源贸易的激励作用,并通过深化国际交流与合作来降低国际政策不确定性对中国绿色金融发展的影响。

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。

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。

Idealized Experiments for Optimizing Model Parameters Using a 4D-Variational Method in an Intermediate Coupled Model of ENSO

Large biases exist in real-time ENSO prediction, which can be attributed to uncertainties in initial conditions and model parameters. Previously, a 4D variational （4D-Vat） data assimilation system was developed for an intermediate coupled model （ICM） and used to improve ENSO modeling through optimized initial conditions. In this paper, this system is further applied to optimize model parameters. In the ICM used, one important process for ENSO is related to the anomalous temperature of subsurface water entrained into the mixed layer （Te）, which is empirically and explicitly related to sea level （SL） variation. The strength of the thermocline effect on SST （referred to simply as ＂the thermocline effect＂） is represented by an introduced parameter, （l＇Te. A numerical procedure is developed to optimize this model parameter through the 4D-Var assimilation of SST data in a twin experiment context with an idealized setting. Experiments having their initial condition optimized only, and having their initial condition plus this additional model parameter optimized, are compared. It is shown that ENSO evolution can be more effectively recovered by including the additional optimization of this parameter in ENSO modeling. The demonstrated feasibility of optimizing model parameters and initial conditions together through the 4D-Var method provides a modeling platform for ENSO studies. Further applications of the 4D-Vat data assimilation system implemented in the ICM are also discussed.

Incremental 4D-VAR assimilation scheme based on Lorenz model

Four-dimensional variational(4D-VAR) data assimilation method is a perfect data assimilation solution in theory, but the computational issue is quite difficult in operational implementation.The incremental 4D-VAR assimilation scheme is set up in order to reduce the computational cost. It is shown that the accuracy of the observations, the length of the assimilation window and the choice of the first guess have an important influence on the assimilation outcome through the contrast experiment. Compared with the standard 4D-VAR assimilation scheme, the incremental 4D-VAR assimilation scheme shows its advantage in the computation speed through an assimilation experiment.

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。

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。

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.

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.