东北地区装备制造业高端化发展水平及效应评价研究

东北地区有必要大力推进装备制造业的发展,充分利用实体经济的基础性作用,实现东北地区的可持续发展。本文分析东北地区的经济发展是否会受到装备制造业高端化发展的正向影响,同时,从横向和纵向两个维度评价东北地区装备制造业高端化发展水平,与同类研究相比具有一定的创新性。研究结果表明:(1)东北地区的经济水平与装备制造业高端化发展存在互相促进的关系;(2)东北地区装备制造业高端化发展水平总体偏低,同时有逐渐稳定上升的态势。因此,应从装备制造业创新能力、产业集聚、智能化发展、可持续性等方面入手,着力推进东北地区装备制造业高端化发展。

江苏省物流与产业结构适应性研究——基于DEA和VAR的实证分析

在分析江苏省物流业与产业结构发展现状的基础上,通过对江苏省物流业与产业结构的适应性研究,创新性地综合运用DEA和VAR模型定量化方法,探讨了物流业与产业结构的协调关系和动态传导机制,为促进物流资源整合,推动江苏经济转型,促进物流产业健康发展提供政策建议。

货币政策对西北五省省会城市房价的影响

在阐述国内外学者相关研究现状的基础上建立了VAR模型,并利用脉冲响应函数分析了贷款利率和货币供给量变化对"丝绸之路经济带"西北五省城市房价的动态影响。结果表明:在短期内提高贷款利率(即实行紧缩货币政策)会对西北五省省会城市房价产生显著影响;在长期内利率政策变化对西北五省省会城市房价的影响并不显著;不论是短期内还是长期内货币供给量变化对西北五省省会城市房价都会产生显著的正向影响。最后提出了相关政策建议。

铜期货套期保值比率模型的评价

伴随着产业升级和时代变迁,大宗商品的价格变动更加剧烈,相关行业的价格风险也日益凸显。随着金融及其衍生品的飞速发展,套期保值成为相关企业规避风险的重要途径。但是,套期保值的低有效率,一直是制约相关企业运用套期保值规避风险的重要因素。因此,本文对比了目前学术界和商业界常用的几个模型,试图通过实证的方式,找出适合铜期货的套期保值比率最优模型。经过检测,考虑了时间序列间协整关系的ECM模型能够较好地测算套期保值比率。

对外贸易依存度与农业经济增长--基于新疆地州面板数据的实证分析

本文采用1996—2019年的新疆地际面板数据,使用了面板数据误差模型和面板数据向量自回归模型对新疆农业增长速度和新疆对外贸易依存度的长短期和动态关系进行了详细的实证分析,得出了如下结论:新疆农业总产出增长速度和新疆对外贸易依存度之间存在长期协整关系,并且两者的长期均衡关系表现为相互促进;新疆对外贸易依存度有误差修正机制;其短期波动受到农业产出增长速度波动的影响,新疆农业总产出增长速度不存在误差修正机制,其短期波动不受到新疆对外贸易依存度的波动的影响;从长期来分析新疆农业产出增长速度波动被对外贸易依存度的解释力度非常小而且比较稳定,而新疆农业增长速度对新疆对外贸易依存度的解释力度随着时间的推移增加;新疆对外贸易依存度对农业总产出的冲击为正,而相反的冲击效应为负。

Load prediction of grid computing resources based on ARSVR method

Based on the monitoring and discovery service 4 （MDS4） model, a monitoring model for a data grid which supports reliable storage and intrusion tolerance is designed. The load characteristics and indicators of computing resources in the monitoring model are analyzed. Then, a time-series autoregressive prediction model is devised. And an autoregressive support vector regression（ ARSVR） monitoring method is put forward to predict the node load of the data grid. Finally, a model for historical observations sequences is set up using the autoregressive （AR） model and the model order is determined. The support vector regression（SVR） model is trained using historical data and the regression function is obtained. Simulation results show that the ARSVR method can effectively predict the node load.

京津冀协同发展下房价互动关系研究

本文通过构建向量自回归模型,利用脉冲响应函数分析了京津冀地区房价的互动关系。结果表明:北京和天津房价相互间的影响作用较大,但两地房价均不受河北省房价变动的影响,且这两个地区的房价具有较强的“外部溢出效应”;北京和天津房价的波动主要是受自身内部原因影响较大,即存在较大的“内部积累效应”;河北省房价受京津房价冲击较大。

Influence factors of international gold futures price volatility

Based on the commodity property and finance property of gold in the international gold futures market,the influence factors of international gold futures price volatility are analyzed from the perspectives of supply and demand factors,financial factors and speculation factors.The structural vector autoregression(SVAR)model is applied to investigating the direction and strength of the effects of influence factors on the international gold futures prices and the variance decomposition approach(VDA)is used to compare the contributions of these factors.The results show that the supply and demand factors still play a fundamental role in the international gold futures price volatility and the role of“China’s gold demand”is exaggerated.The financial factors and speculation factors have significant impacts on the international gold futures price volatility,which reflects that the financial property of gold becomes increasingly important.Governments and investors should pay close attention to the financial property of gold futures.

Impact of Inflation, Dollar Exchange Rate and Interest Rate on Red Meat Production in Turkey： Vector Autoregressive （VAR） Analysis

In this study, impact of inflation （WPI--Wholesale Price Index）, exchange rate, and interest rate on the production of red meat in Turkey was examined using the vector autoregressive （VAR） model. The model consisting of variables of dollar exchange rate, inflation rate, interest rate, beef, buffalo meat, mutton, and goat meat production amounts has been estimated for the period from 1981 to 2014. It has been detected that there is a tie among the dollar exchange rate, inflation rate, interest rate, and the amount of red meat production in Turkey. In order to determine the direction of this relation, Granger causality test was conducted. A one-way causal relation has been observed between： the goat meat production and dollar exchange rate; the buffalo meat production and the mutton production; and the beef production and the mutton production. To interpret VAR model, the impulse response function and variance decomposition analysis was used. As a result of variance decomposition, it has been detected that explanatory power of changes in the variance of dollar exchange rate, inflation rate, and interest rate in goat meat production amount is more than explanatory power of changes in the variances of mutton, beef, and buffalo meat variables.

Vector Autoregressive （VAR） Modeling and Projection of DSE

In this paper, vector autoregressive （VAR） models have been recognized for the selected indicators of Dhaka stock exchange （DSE）. Bangladesh uses the micro economic variables, such as stock trade, invested stock capital, stock volume, current market value, and DSE general indexes which have the direct impact on DSE prices. The data were collected for the period from June 2004 to July 2013 as the basis on daily scale. But to get the maximum explorative information and reduction of volatility, the data have been transformed to the monthly scale. The outliers and extreme values of the study variables are detected through box and whisker plot. To detect the unit root property of the study variables, various unit root tests have been applied. The forecast performance of the different VAR models is compared to have the minimum residual. Moreover, the dynamics of this financial market is analyzed through Granger causality and impulse response analysis.

Analysis of the Bovespa Futures and Spot Indexes With High Frequency Data

Data from the World Federation of Exchanges show that Brazil＇s Sao Paulo stock exchange is one of the largest worldwide in terms of market value. Thus, the objective of this study is to obtain univariate and bivariate forecasting models based on intraday data from the futures and spot markets of the BOVESPA index. The interest is to verify if there exist arbitrage opportunities in Brazilian financial market. To this end, three econometric forecasting models were built： ARFIMA, vector autoregressive （VAR）, and vector error correction （VEC）. Furthermore, it presents the results of a Granger causality test for the aforementioned series. This type of study shows that it is important to identify arbitrage opportunities in financial markets and, in particular, in the application of these models on data of this nature. In terms of the forecasts made with these models, VEC showed better results. The causality test shows that futures BOVESPA index Granger causes spot BOVESPA index. This result may indicate arbitrage opportunities in Brazil.

Monetary Model of Exchange Rate Determination： Evidence From the Czech Republic, Hungary, and Poland

Using a monetary model of exchange rate determination that suggests a strong link between the nominal exchange rate and a set of monetary fundamentals, exchange rate dynamics for the Czech Republic, Hungary, and Poland is studied. As the cointegration relationship among exchange rate, output, and the monetary fundamentals （money supply and interest rate） is found, vector autoregressions （VAR）/vector error-correction （VEC） and two-stage least squares （2SLS） error-correction models are used in this context, since both approaches allow estimating short-run correlations between exchange rates and fundamentals while taking into account the existent long-run exchange rate constraints. Based on the quarterly data for the period of 1998-2012, it is found that for all countries, an increase in the money supply, domestic output slowdown, or stronger growth abroad are factors behind a nominal exchange rate depreciation, just as predicted by the monetary model of exchange rate. However, the effects of domestic-foreign interest rate differential are quite heterogeneous, being in line with theoretical predictions of a standard monetary model for Poland only. According to the decomposition of variance, money supply and interest rates account for 30%-46% of the exchange rate variation in the Czech Republic, from 10% to 14% in Hungary, and from 23% to 42% in Poland.

Quantitative Analysis of Influence Force of Shanghai Expo on GGDP

Quantitative study of the impact of Shanghai World Expo on green GDP （GGDP） is significant for deploying sustainable development policy in China. The formula of GGDP is： GGDP = GDP--the loss of natural resources environment relegation cost ＋ comprehensive utilized value of waste. Based on this, the study employed vector autoregressive （VAR） model to predict the value of GGDP and other economic variables on condition that there was no Shanghai World Expo. Then Influence of Expo is defined as the rate of increase of GGDP. The result demonstrated that Shanghai World Expo had accelerated the growth rate of GGDP vastly with the elimination of effect of Beijing Olympics. Additionally, the quantitative analysis between GGDP and other economic variables suggested GGDP would replace GDP to evaluate the development of economy. Finally, the paper proposed that incidents like World Expo can enhance the level of influence for a country and that post-impact of Shanghai Expo should continue to be used to promote GGDP and that GGDP should serve as one of the indicators in assessment of political achievement.

Is proximity to oil refinery a big factor in explaining differences in gas prices？

According to the Energy Information Administration, average retail gasoline prices tend to typically be higher in certain states than in others. Aside from taxes, the factors shown to contribute to regional and even local differences in gasoline prices include proximity of supply, supply disruptions, competition in the local market and environmental programs. Of interest in this paper is proximity of supply. It has been hypothesized that areas farthest from the Gulf Coast （the source of nearly half of the gasoline produced in the United States and, thus, a major supplier to the rest of the country） tend to have higher prices. To test this hypothesis, the paper assembles state level monthly retail gasoline data for the period 1983 to 2007 for five states with oil refineries （Alabama, Georgia, Texas, Mississippi and Louisiana） and five states without refineries （Arkansas, Tennessee, North Carolina, South Carolina and Florida）. The analysis employs dynamic correlation, regression, cointegration and vector autoregressive methods. Overall, the results show that retail gas prices in states with refineries and those without refineries tend to move in the same direction over time. The small differences observed over time may suggest that price shocks take a short time to be felt nationwide.

The Influence of Exchange Rate on the Volume of Japanese Manufacturing Export

This paper investigates the influence of exchange rate volatility on the volume of Japanese manufacturing export. The volatility in yen is shown by conditional variance from EGARCH （Exponential Generalized Autoregressive Conditional Heteroscedasticity） model, allowing for asymmetric effects that a shock of an appreciation of the yen is different from that of a depreciation of the yen. The export action model including exchange rate volatility is constructed based on VAR （Vector Auto Regressive） model to examine the relationship between exchange rate uncertainty and the volume of export. Tests are performed for typical eight kinds of industry in Japan. Few empirical studies focus on each Japanese industry export. Results indicate significant negative effects of exchange rate volatility on most manufacturing exports. In addition, this paper analyzes the each industry, featurc of the influence of exchange rate on the volume of Japanese export. The authors find that equipment industries occupying 60% or more of total Japanese exports especially tend to receive negative influence of exchange.

Non-performing Loans in Turkish Banking Sector and Balance Sheets Effects

In the 21st century, while the scope of banking activities has been expanding every day, collecting deposits and providing credit remain as their main and most important functions. They transfer the collected funds thanks to the market confidence they create back to the market in terms of the credits they give. For the organizations operating in the banking sector, crediting is the highest revenue earning source. However, uncollected loans may disrupt the activities of banks and may reduce their effectiveness. Therefore, the control of bank credits has a particular importance in the bank balance sheets. In this study, the relationship between bank balance sheets and non-performing loans （NPL） will be analyzed using Granger causality test and vector autoregressive （VAR） method. This study aims to discuss the impact of NPL on balance sheets and contribute to making correct credit decisions. It also intends to assist to reduce the NPL ratios of banks and minimize the level of negativity in their financial statements.

Impact of Rising Oil Prices on the Living Cost in Burkina Faso

Fluctuations of the world oil prices affect economic performance. Outside the impact on the sector of energy production, the rising oil price has consequences on inflationary pressures and a deteriorating fiscal position of Burkina Faso. In this context, studying the impact of rising oil prices on the economy, especially the cost of living of its population has a great interest because although many studies have attempted to link 〈〈oil prices〉~ and 〈〈cost of living~, very few have focused on the specific case of Burkina Faso. This allows us to make our contribution to this construction literature. This contribution will consist to highlight the relation between changes in oil prices and the cost of living in Burkina Faso. Also to be reached, we will find the best indicator to reflect the cost of living in Burkina Faso, identify the suitable econometric model for estimating the correlation and verify the existence of the relation between oil prices and the cost of living. For a better approach to this study, we used a VAR （Vector Auto-Regressive） model. Also, we will use documentary research that will make an assessment on the existing in terms of theoretical debates around the theme descriptive statistics that will help to introduce and describe the variables used in the study, and econometric analysis will analyze and estimate the parameters of our objective function using Eviews.

中国旅游业高质量发展与共同富裕的互动关系

【目的】旅游业高质量发展与共同富裕息息相关,厘清二者的互动关系对于促进中国旅游业转型升级,助推共同富裕目标实现具有重要意义。【方法】首先,利用改进后的熵值法分别测算旅游业高质量发展与共同富裕水平;其次,分析旅游业高质量发展与共同富裕耦合协调状态;最后,借助PVAR模型探析旅游业高质量发展与共同富裕的互动响应关系。【结果】研究表明:(1)2010—2019年,中国旅游业高质量发展与共同富裕水平呈现出稳步上升态势,但增速较缓且存在显著的空间差异性。(2)中国旅游业高质量发展与共同富裕的耦合协调度由基本协调向中度协调跃升,在空间上表现出“东部>中部>西部”的分布格局。(3)中国旅游业高质量发展与共同富裕交互影响,从短期影响来看,二者的交互效应较大;从长期影响来看,二者受自身发展的影响较大。【结论】中国旅游业高质量发展与共同富裕总体上均处于上升状态,但各地区间的发展仍存在一定差距,应根据地区的发展特点采取针对性的措施进行改善。

IS TECHNICAL ANALYSIS INFORMATIVE IN UK STOCK MARKET? EVIDENCE FROM DECOMPOSITION-BASED VECTOR AUTOREGRESSIVE(DVAR) MODEL

The paper proposes a new approach -- The decomposition-based vector autoregressive （DVAR） model to scrutinize the predictability of the UK stock market. Empirical studies performed on the monthly British FTSE100 index over 1984-2012 confirm that the DVAR model does provide informative forecasts for both in-sample and out-of-sample forecasts. Trading strategies based on the DVAR forecasts can Significantly beat the simple buy-and-hold, which demonstrates the valuable information provided by technical analysis in the UK stock market.

Synergic Relationship between the Grain for Green Program and the Agricultural Eco-economic System in Ansai County based on the VAR model

Understanding the synergic relationship between the Grain for Green Program(GGP)and the agricultural eco-economic system is important for designing an optimized agricultural eco-economic system and developing a highly efficient structure of an agricultural industry chain and a resource chain.This study used Ansai County time series data from 1995 to 2014,applied vector autoregressive(VAR)models and used tools such as Granger causality,impulse response analysis and variance decomposition,to explore the synergy between the GGP and the agricultural eco-economic system.The results revealed a synergic and reciprocal relationship between the GGP and the agroeconomic system.The contribution of the GGP to the agroecosystem reached 34%,which was significantly higher than either its largest contribution to the agroeconomic system(20.8%)or its peak contribution to the agrosocial system(26.7%).The agroeconomic system had the most prominent influence on the GGP,with a year-round stable contribution of up to 55.3%.These results were consistent with reality.However,the impact of the GGP on the agricultural eco-economic system was weaker than the effect of the agricultural eco-economic system on the GGP.The lag of variable stationarity after the shock was relatively short,indicating that optimal coupling had not formed between the GGP and the agricultural eco-economic system.On the basis of enhancing the ecological functions,we should construct the agricultural industry-resource chain such that it focuses on promoting the effective utilization of resources in the region.In addition,the development of a carbon sink industry can be used to manifest the ecological values of ecological functions.