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.

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.

A statistical analysis of spatiotemporal variations and determinant factors of forest carbon storage under China's Natural Forest Protection Program

The Natural Forest Protection Program(NFPP)is one of the key ecological forestry programs in China.It not only facilitates the improvement of forest ecological quality in NFPP areas,but also plays a significant role in increasing the carbon storage of forest ecosystems.The program covers 17 provinces,autonomous regions,and municipalities with correspondingly diverse forest resources and environments,ecological features,engineering measures and forest management regimes,all of which affect regional carbon storage.In this study,volume of timber harvest,tending area,pest-infested forest,firedamaged forest,reforestation,and average annual precipitation,and temperature were evaluated as factors that influence carbon storage.We developed a vector autoregression model for these seven indicators and we studied the dominant factors of carbon storage in the areas covered by NFPP.Timber harvest was the dominant factorinfluencing carbon storage in the Yellow and Yangtze River basins.Reforestation contributed most to carbon storage in the state-owned forest region in Xinjiang.In state-owned forest regions of Heilongjiang and Jilin Provinces,the dominant factors were forest fires and forest cultivation,respectively.For the enhancement of carbon sequestration capacity,a longer rotation period and a smaller timber harvest are recommended for the Yellow and Yangtze River basins.Trees should be planted in stateowned forests in Xinjiang.Forest fires should be prevented in state-owned forests in Heilongjiang,and greater forest tending efforts should be made in the state-owned forests in Jilin.

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.

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.

Stock Market Turnover and China’s Real Estate Market Price: An Empirical Study Based on VAR

Our analysis used the monthly data of the average sales price of commodity houses and stock turnover in the Shenzhen Stock Exchange from January 2016 to December 2020. We selected this data to establish a Vector Autoregression(VAR) model using the Granger causality test to investigate the correlation between the stock market and the real estate market. We found that there is a significant positive correlation between the stock market and the real estate market. We also found that the real estate market price is the one-way Granger cause for the stock market turnover, and that changes in the real estate market price have a significant role in forecasting changes in stock market turnover. Therefore, the linkage between the two markets should be considered in macro regulations, and the impact on one of the markets should be considered when regulating the other.

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.

Implementation of Neural Networks in Time Series to Generate a Portfolio of Investment in Cryptocurrencies

The present work aims to implement two types of neural networks and an analysis of a multivariate time series model of VAR type to predict the price of cryptocurrencies like Bitcoin,Dash,Ethereum,Litecoin,and Ripple.This subject has been popular in recent years due to the rapid price fluctuations and the immense amount of money involved in the cryptocurrencies market.Several technologies have been developed around cryptocurrencies,with Blockchain rising as the most popular.Blockchain has been implementing other information technology projects which have helped to open a wide variety of job positions in some industries.A“New Economy”is emerging and it is important to study its basis in order to establish the pillars that help us to understand its behavior and be ready for a new era.

Factors affecting the pilot trading market of carbon emissions in China

Climate change and carbon emissions are major problems which are attracting worldwide attention. China has had its pilot carbon emission trading markets in seven regions for more than 3 years. What affects carbon emission trading market in China is a big question. More attention is paid to how China promotes the carbon emission trading schemes in the whole country. This paper addresses concerns about the functioning of carbon emission trading schemes in seven pilot regions and takes the weekly data from November 25, 2013, to March 19, 2017. We employ a vector autoregressive model to study how coal price, oil price and stock index have affected the carbon price in China. The results indicate that carbon price is mainly affected by its own historical price; coal price and stock index have negative effects on carbon price, while oil price has a negative effect on carbon price during the first 3 weeks and then has a positive effect on carbon price. More regulatory attention and economic measures are needed to improve market efficiency, and the mechanisms of carbon emission trading schemes should be improved.

Carbon stock and sink economic values of forest ecosystem in the forest industry region of Heilongjiang Province, China

The values of forest carbon stock (CSV) and carbon sink (COV) are important topics in the global carbon cycle. We quantitatively analyzed the factors affecting changes in both for forest ecosystem in 2000−2015. With multiple linear stepwise regression analysis, we obtained the factors that had a significant impact on changes of CSV and COV, and then the impacts of these variables on CSV and COV were used for further quantitative analysis using the vector autoregressive model. Our results indicated that both stand age and afforestation area positively affect CSV and COV;however, the forest enterprise gross output value negatively affects CSV. Stand age has the largest long-term cumulative impact on CSV and COV, reaching 40.4% and 9.8%, respectively. The impact of enterprise gross output value and afforestation area on CSV and COV is the smallest, reaching 4.0% and 0.3%, respectively.

Spillover Effect in the RMB Foreign Exchange Market:Based on VAR and DCC-MVGARCH Models

This paper analyzes the stability and marketization of the RMB exchange rate after China introduced the foreign exchange rate reform by linking the RMB exchange rate with the offshore and onshore markets on August 11,2015(“8/11”).Under the framework of dynamic analysis,through Granger causality test,VAR model and DCC-MVGARCH model,the empirical analysis is conducted about the three market exchange rate linkages of CNY,NDF and CNH from May 2012 to December 2018.Then,the direction and degree of the linkage between the RMB’s offshore and onshore exchange rates before and after the“8/11”exchange rate reform are compared.The research results show that:(1)since the“8/11”exchange rate reform,the RMB exchange rate has become more flexible;(2)the price-determining power of the RMB exchange rate may be weakened,and policy adjustment should take effect;and(3)the prerequisites,under which the offshore market can play a role,are the development of the market itself.This paper proposes that:(1)the onshore and offshore markets should develop in a collaborative manner to further increase exchange rate elasticity and flexibility;(2)close attention should be paid to the relationship between the offshore and onshore markets,and policy determination and flexibility should be maintained;and(3)the offshore market should be improved and play a due role.

Dynamic Relation between Rural Human Capital and Farmers'Income in Henan Province

We use relevant economic and labor force data from 1990 to 2009 of Henan Province to analyze the dynamic relation between stock of rural human capital and farmers' income.Results indicate that a certain causal relationship and long-run equilibrium relation exist between rural human capital and farmers' income,but their interaction shows some lagging characteristic.Increase of farmers' income in Henan Province increases the stock of rural human capital in this province for a short term.However,in the long run,this accumulation effect will decline along with renewal and aging of knowledge.The positive promotion action of rural human capital on farmers' income will appear after a long lag time.Therefore,the policy of strengthening rural human capital input should be long-term and continuous.

Demonstration Analysis of Relationship Between R&D Investment and GDP

To reveal the quantitative relationship between research and development (R&D) investment and gross domestic product (GDP) in China, we have demonstrated and analyzed the relationship between R&D investment and science and technology (S&T) progress, and based on a mount of S&T statistical data, have proceeded demonstration research of the relationship between R&D investment and GDP in China with Solow and vector auto regression (VAR) models. Cubic curve fitting and cross-correlation analysis of them with SPSS have shown that there is a strong synchronic relationship between R&D investment and GDP.

Low Carbon Beijing:Research on the Influencing Factors of Carbon Emission Trading Price

The international community has taken extensive actions to achieve carbon neutrality and sustainable development with the intensification of global warming and climate change.China has also carried out a long-term layout,setting the goal of achieving a carbon peak by 2030 and carbon neutrality by 2060.In 2021,with the official launch of a unified national carbon emissions trading market,China’s nationwide carbon emissions trading kicked off.Carbon emission trading is an important policy tool for China’s carbon peak and carbon-neutral action and an essential part of the country’s promotion of a comprehensive green transformation of the economy and society.This study uses a VAR(Vector Autoregressive)model to analyze the influencing factors of the Beijing carbon emissions trading price from January 2014 to December 2019.The study found that coal prices have the most significant impact on Beijing’s carbon emissions trading prices.Oil prices,industrial development indexes,and AQI(Air Quality Index)impacted Beijing’s carbon emissions trading prices.In contrast,natural gas prices and economic indexes have the most negligible impact.These findings will help decision-makers determine a reasonable price for carbon emissions trading and contribute to the market’s healthy development.

The Impact of Macroeconomic Fluctuations on Stock Exchange Markets： A Comparative Analysis on CEECs

Stock exchange market responses to macroeconomic fluctuations show deviations between countries in terms of direction, magnitude and duration due to the idiosyncratic characteristics of the countries. The paper empirically searches for the identification of these variations for CEECs, namely Czech Republic, Hungary, Poland, Slovak Republic and also Turkey for the period of December, 1999 to December, 2009. The empirical analyses demonstrate that for each CEEC, stock exchange market responds positively to industrial production and to appreciation of local currency. Czech Republic and Hungary display negative and the rest display positive response to M1, whereas the response of stock market to CB policy rate shows mixed results for each country. Besides, foreign exchange market returns are found to be the variable with the highest significance in explaining the stock exchange market returns. These findings point out to arbitrage opportunities for investors and give insight to Monetary Policy Authorities about the Monetary Transmission Mechanisms of the countries.

The relationship between rural surplus labor transfer,urbanization and income gap

Based on the time series data of Shandong province from 2001 to 2018,a VAR model consisting of three variables,namely,rural surplus labor transfer,urbanization and urban-rural income gap,was constructed,and the interaction among the three variables and their characteristics were empirically analyzed.The results show that urbanization and rural surplus labor transfer are Granger causation to each other,and there is a positive correlation between urban-rural income gap and rural surplus labor force in long-term equilibrium,while there is a negative correlation between urban-rural income gap and rural surplus labor force transfer.Therefore,it is necessary to fully recognize the relationship between the transfer of rural surplus labor,urbanization and urban-rural income gap,accelerate the urbanization construction,promote the rural surplus labor to gather in cities,and gradually narrow the urban-rural income gap.

A Study of the Setting of Margin Levels in Futures Market

Margin rules are very important rules in futures market. This paper provides a new Value-at-Risk （VaR） approach which uses GARCH model to set margin levels. The new approach overcomes the limitation of the hypothesis of normal distribution in traditional methods and improves the estimation precision. We use the data of metal futures in China＇s Shanghai Futures Exchange （SHFE） to have an empirical study.