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The mobilization potential of emergency materials plays an important role for the response to emergency materials under emergencies in China. This paper measures the emergency materials mobilization potential by the final product of the emergency materials after the conversion of raw materials, and establishes the emergency materials mobilization potential evaluation model using system dynamics through analyzing the internal feedback relationship of each sub-module that constitutes the emergency materials mobilization potential. Taking China's petroleum industry chain as the actual background, and the mobilization potential of refined oil as an example, using the idea of "scenario-response", this paper expands the idea of assessing the state value of mobilization potential, quantitatively assesses mobilization potential of refined oil from the aspects of total amount, a certain time point and a certain period of time. The results show that when the demand is at a low level, the reserves of crude oil and refined oil have the greatest contribution to the refined oil mobilization potential. With the increase of demand, the contribution of the company's supernormal production is gradually increasing. In addition, the four factors of the actual production capacity of emergency materials, the amount of crude oil or refined oil reserves and crude oil conversion coefficient have the greatest impact on the refined oil mobilization potential, so it should focus on improving the actual production capacity of emergency materials, the amount of raw materials or final product reserves and the productive efficiency of emergency materials. [ABSTRACT FROM AUTHOR]

Currency mismatch has drawn attention of the scholars in the recent 20 years. Scholars have proposed lots of empirical measures of currency mismatch of bank that only focus on stock currency mismatch, which leads to some limitations in the conclusion. Based on this fact, this paper comes up with a new indicator of flow currency mismatch, which can be used to analyzing the cause of currency mismatch of bank deeply and dynamically. Then this paper gives an empirical analysis of the relationship between the currency mismatch and some economic variables using ADL model. The study shows that the proper depreciation of domestic currencies, appropriately expanding imports to reduce the trade surplus can effectively reduce the currency mismatch in China from the perspective of stock and the promotion of RMB internationalization can effectively reduce the currency mismatch in China from the perspective of flow. [ABSTRACT FROM AUTHOR]

The direct economical losses and the tolls of earthquakes are main impacts of earthquake insurance. This paper collected the loss data of earthquake during the years 1950-2015 in China and modeled the direct economical losses and the tolls of earthquake using Copula-mixed distribution model. First, the truncated Gumble distribution and generalized Pareto distribution are mixed to fit the direct economical losses, and the truncated negative binominal distribution and generalized Pareto distribution are mixed to fit the tolls of earthquake. Second, copulas are used to model the dependence between the direct economical losses and the tolls of earthquake. Finally, Monte Carlo simulation method is used to calculate VaR and ES. The models proposed in the paper may be applied to establish earthquake insurance system in China. [ABSTRACT FROM AUTHOR]

Based on the traditional two-sided market theory and the characteristics of P2P lending platforms, this paper proposes a two-stage game model to analyse different business models, especially profit models of P2P lending platforms. With the purpose of showing the continuous operating condition and developing direction of P2P lending platforms under the financial environment in China, this paper takes China's new policies about P2P into consideration, takes account of impact of policy and finds the following results: 1) under the scenario in which P2P platform charges "subscription fee + transaction fee" or "subscription fee only", network externalities reduces the P2P platforms' profit when lenders are multihoming; 2) adopting the profit model of "subscription fee + transaction fee" makes a higher profit than the profit model of "subscription fee only"; 3) the prohibition in existing policies of P2P lending platforms on principal guaranteed model will protect the interests of lenders. Finally, this paper puts forward policy suggestions of the P2P lending platforms in China. [ABSTRACT FROM AUTHOR]

Using the efficient frontier and capital market model of portfolio theory, this paper calculates the operational efficiency of commercial banks' credit business based on the non-performing loan ratio and NIM (net interest margin) of commercial banks; Using the loss of non-performing loan ratio on commercial banks' credit business income by using panel data of 16 listed commercial banks in China from 2011 to 2016. Through the comparison of the above results, we find that the operational efficiency of commercial banks' credit business based on portfolio theory proposed in this paper can better reveal the relationship between risk and return of commercial banks' credit business. In the future, commercial banks should consider and use portfolio theory in loan business. [ABSTRACT FROM AUTHOR]

As a kind of capital, intermediate inputs play an important role that cannot be ignored in the process of production. Their coefficient size reflects a country's economic growth mode. Current mainstream economic growth theories only consider the value added production function, rather than gross output production function, thus ignoring the role of intermediate inputs in the production process and the evaluation of economic efficiency. This paper is based on the statistical characteristics, basic model and empirical test of the basic paradigm. From the perspective of statistical characteristics, China's intermediate inputs coefficients are significantly higher than that of U.S. and Japan and other developed countries. The energy consumption per unit GDP is far over the world average level, which shows that the characteristic of China's economic growth is of extensive growth mode. By using theoretical derivation and numerical simulation, this paper has drawn the conclusion that a country's economic growth mode is related to the intermediate inputs elasticity of substitution, value added rate (VAR), technical level, and some other parameters. Firstly, there exists substitution rather than complementary linkage between primary investment and intermediate inputs. Secondly, economic growth rate shows negative correlation with the size of the elasticity of substitution of intermediate inputs, and the greater, the slower, and vice versa. Thirdly, inverted U shape shows that with the increase of intermediate inputs rate, the equilibrium output increases first and then decreased. In other words, there exists an optimal VAR. In the empirical analysis by using data of China, U.S., Japan and Brazil, the paper proves that there are obvious differences in the elasticity of substitution of intermediate inputs among different countries at their different stages during development. On the one hand, there is a different elasticity of substitution at different stage for a country with a certain independence, and the elasticity of substitution of U.S. is much higher than that of China. On the other hand, there is deviation between the actual VAR and the optimal VAR among these countries, and the deviation of China and Brazil is much larger than that of U.S. and Japan. [ABSTRACT FROM AUTHOR]

Based on five original sentiment indicators in Hong Kong stock market, including the closed-end fund discount rate, the average first-day returns of initial public offering (IPO), the number of IPO, the market trading volume and turnover, this paper uses the principal component analysis method to calculate a comprehensive investor sentiment index. After excluding the trend and seasonal factors from the comprehensive investor sentiment index and Hong Kong Hang Seng Index by autoregressive moving average-generalized autoregressive conditional heteroskedasticity (ARMA-GARCH) family models, this paper makes correlation analysis and Granger causality test on the residuals of ARMA-GARCH model. The study shows that ARMA-GARCH models can effectively process the autocorrelation and heteroscedasticity of investor sentiment index and Hong Kong Hang Seng Index. Also, it indicates that the Hang Seng index return is the Granger cause of investor sentiment in short terms while not in long terms. That is to say investor sentiment would be more optimistic in short terms when the Hong Kong stock market goes up, and vice versa. [ABSTRACT FROM AUTHOR]

This paper reviews the work of financial system engineering in China from 2010 to 2014, and further concludes future development strategies. Firstly, the research object and method are defined. Through literature documentation process with both China and abroad papers, statistics of Journals, research institutions, research team, and supported fund are obtained. Through Bradford and Lotka test, we conclude the current research status of financial system engineering development in China. Further, all research are classified into 9 main research questions, which are the key research questions during the past 5 years. Finally, we proposed development strategies for future development of financial system engineering research. [ABSTRACT FROM AUTHOR]

The water level control plan is an important problem of getting more benefits of cascade reservoirs. Especially to reservoirs with large regulating capacity, the rationality and effectiveness of water level control plan under jointly operation determine the comprehensive benefits of cascade reservoirs. In this paper, the cascade reservoirs in lower reach of Yalong River are taken as a case study. Optimal operation model of the cascade reservoirs is built and a new approach named double progressive method (DPM) is proposed and applied. The impoundment starting time and minimum water level are two key problems of water level control plan. By solving the two problems and taking the results as foundation, the optimal water level control plan of Yalong River lower reach cascade reservoirs under different runoff frequency is concluded. The conclusion and water level control plan of this paper can be references for real operation of cascade reservoirs in lower reach of Yalong River. [ABSTRACT FROM AUTHOR]

Using recent survey panel data from 1000 Chinese rural households from 2005-2011, this paper attempted to estimate the extent of consumer credit constraints as well as its impact on the net income and consumption expenditure of rural households. Our results revealed that 83.7% of Chinese rural households were rationed in the credit markets. Of these, 55.2% were completely rationed and 24.2% were partially rationed. Furthermore, this consumer credit rationing caused a 13.7% loss in net income and a 25.6% loss in consumption expenditure for these rural households in China. Finally this paper proposes some policy suggestions based on the empirical results. [ABSTRACT FROM AUTHOR]

The economics literature contains many theoretical analyses of imitation and differentiation strategies but relatively few empirical studies of these topics due to the limitation of data and methods. This paper conducts empirical research on competitive behavior among three dominant Chinese satellite TVs. It indicates that: 1) Program selection decisions of dominant satellite TVs primarily depend on their previous decision, showing decision inertia, which is verified by the fact that shock of each satellite TV's previous decisions best explains its current decision. Meanwhile, there is strategic dynamic interaction between each other, in the form of a mixed strategy with both imitation and differentiation. 2) Degree of imitation depends on satellite TVs' competitive positions. Leaders tend to differentiate, while pursuers incline to imitate. 3) Satellite TVs' decision patterns show heterogeneity related to program types. A satellite TV's decisions on its representative and advantageous programs are less affected by its competitors, while decisions on other programs suffer greater impacts. And heterogeneity is more obvious in pursuers. Impacts of market structure and degree of imitation on program ratings are further studied. Results indicate that: 1) Competitive pressure has negative crowd-out effect on leaders' program ratings, while it has positive spillover effect on pursuers. This finding is consistent with the fact that rating gap between first-class dominant satellite TVs and second-class dominant ones has narrowed. 2) Imitation leads to higher program ratings, indicating possible presence of herd behavior among Chinese audience. [ABSTRACT FROM AUTHOR]

Since the Ministry of Environmental Protection of China began testing the PM2.5 index in 2013, the impact of air quality on the national economy has received increasing attention. The haze has spread to all parts of the country. Does it affect real estate prices? This paper uses spatial econometric model to empirically examine the impact of haze on urban house prices, and make heterogeneity analysis at different regions and different periods, based on the data of 280 prefecture-level cities in China from 2002 to 2016. The main conclusions include: The spatial aggregation effect of house price and PM2.5 concentration distribution across the country. From a national perspective, PM2.5 concentration will have a negative effect on house prices. For every 1 unit increase in PM2.5 concentration, house prices fell by 0.37%. Air quality has an impact on house prices at different time periods, but when macroeconomic regulation is strengthened, the effect of air quality will be weakened. From a regional perspective, the difference in economic development level will affect the effect of air quality on house prices. The more economically developed regions, the stronger the impact of air quality on house prices. [ABSTRACT FROM AUTHOR]

Based on the combination of input-output model and social network analysis methods, in this paper, we decompose the R&D investment model driven by different types of demands in China's manufacturing, and discuss the intermediary role of network characteristics in terms of the relationship between the R&D investment and the innovation output. The results show that the R&D input of technology-intensive manufacturing industry is driven by both domestic final demand and intermediate demand, while the R&D input structure of capital-intensive manufacturing industry is dominated by intermediate demand. The R&D investments source from different types of demands significantly promote China's manufacturing innovation output, and the contributions from high to low are foreign final demands, domestic final demands and intermediate demands. Therefore, the final demand is the main force to drive R&D input and then achieve innovation output. As for R&D promoting the innovation output, production network characteristic variables exert significant intermediary effects. The centrality degree and various R&D investments mutually promote the growth of the innovation output. The upstream degree limits the contribution of R&D input driven by intermediate demand to innovation output. [ABSTRACT FROM AUTHOR]

This paper uses Baker et al. (2016) to construct China's economic policy uncertainty index (EPU) and China's economic policy uncertainty index based on Chinese newspaper text keyword search (CEPU). Using monthly import data of about 5000 kinds of products in China from January 2010 to April 2016, we estimate the impact of EPU and CEPU on these products' import and find that economic policy uncertainty has different effects on imports of different products, both negative and positive. Further, we use BEC classification, differentiated products and homogeneous products, the number and concentration of countries in global trade, and the elasticity of import demand to characterize the heterogeneity of products and explain the differences in the impact of economic uncertainty on different products. We find that when the uncertainties of China's economic policy increase, capital goods and transport equipment are more negatively affected by imports than intermediate inputs and differentiated products are homogeneous products; the smaller the elasticity of demand substitution, the more countries imported globally, the lower the concentration of global importing countries, and the higher the concentration of global exporting countries, the negative reaction of product imports the bigger. In addition, we compare the performance of EPU and CEPU indices. CEPU index is more reasonable than the EPU index. [ABSTRACT FROM AUTHOR]

Structural changes often occur in air passengers due to some external factors such as airport expansion, policy orientation and economic development; model uncertainty is a common long-standing issue in forecasting. To address these issues, a novel time-varying Jackknife model averaging method (TVJMA) (Sun et al, 2020, 2012) is employed to predict air passengers of the Top 5 airports in China. Based on nonparametric estimation, the optimal time-varying weights for various candidate models with time-varying parameters in candidate models are obtained by minimizing the local Jackknife criterion at every time point t. TVJMA method allows the weights and parameters to change over time. Empirical results show that the TVJMA method used in this paper is significantly superior to other benchmark models, including Hansen and Racine's (2012) Jackknife model averaging method (JMA), autoregression model (AR), autoregression integrated moving average model (ARIMA), seasonal autoregression integrated moving average model (SARIMA), and time-varying parameter model (TVP). Furthermore, the predictive effect of TVJMA is robust to different test sets and prediction steps. Overall, TVJMA method effectively reduces the predictive risk caused by structural changes and model uncertainty, and thus produces accurate and stable forecasts of air passengers. [ABSTRACT FROM AUTHOR]

To develop an outstanding Renminbi exchange rate forecasting model based on the background of Renminbi internationalization and the increased two-way volatility becomes much more important. The forecasting ability of a parameter model depends not only on whether it is correctly specified, but also on one hand the efficiency of whether it can detect the structure changes and using the effective observations to estimate the parameters, and on the other hand on the ability of selecting the proper covariates that can be used in forecasting. In order to solve these required problems, this paper has developed the penalized adaptive method which can adaptively select the covariates and detect the structure changes. The developed model can outperform the local adaptive method and other economic fundamental methods in exchange rate predictions. In the USD against RMB exchange rate regime, we find out that the newly developed methods can manage of significantly increasing the forecasting accuracy compared with the second-best model. After the 811-exchange-rate-reform, the economic fundamentals have been significantly improved in determining the exchange rate expectation. Moreover, after the 811-exchange-rate-reform, the exchange rate of USD against RMB itself does not decide alone by the USD. It is also decided heavily by the other fundermental differences between China and the other developed countries such as UK, Euro Zone and Japan. The manageable floating exchange rate system is also crucial in preventing the exchange rate risk in China. [ABSTRACT FROM AUTHOR]

The traditional evaluation methods of earthquake disaster loss does not have a unified index to make a comprehensive assessment of the loss of earthquake disaster, which will cause some difficulties in the application. In order to comprehensively evaluate the loss of earthquake disaster and carry out multiple models comparison research, this paper presents multi-model methods for evaluating the loss of earthquake disaster based on lifeyears. Through the improvement of the lifeyears loss theory and the analysis of the value of the method parameters, the calculation scheme was determined. A comparative study was conducted on the lifeyears loss of earthquake in China grouped by years and regions. The relationship between the total lifeyears loss and its influence factors, such as the affected population, the epicentral intensity, the earthquake magnitude and recovery time was studied. The results showed that four influencing factors were all positively correlated with the total lifeyears loss. The affected population has the greatest correlation and the correlation of the other three factors is decreasing in turn. The linear regression model, the neural network quantile regression model and the nonlinear model of gene expression programming were established on the basis of the analysis of the influencing factors and the comparative analysis was carried out. Earthquake disaster loss was evaluated and predicted by using the evaluation model, which reduced data dependence and simplified the assessment process. [ABSTRACT FROM AUTHOR]

This paper uses the mixture innovation time-varying parameter vector autoregressive models with stochastic volatility model (MI-TVP-SV-VAR) to construct the China financial status index (MFCI) to measure China's financial situation. Based on the multifractal asymmetric detrended cross-correlation analysis (MF-ADCCA) algorithm, the MFCI is used to predict the development of the real economy. In the empirical study, the research sample selects the monthly data of China from 2000 to 2017. The empirical results show that the weights of various financial status variables have flexible time-varying, and the stock price, bond price and real estate price have greater weight in MFCI. During the sample period, MFCI is able to maintain a consistency trend with the development of the real economy (EC) and is ahead of changes in the real economy. The asymmetric correlation test based on MF-ADCCA algorithm shows that MFCI has a persistent cross-correlation with EC. The decline of MFCI will lead to the decline of EC, and the rise of MFCI will lead to the rise of EC. The cross-effect of MFCI on EC changes the asymmetric influence of the individual sequence itself, indicating that the impact of China's financial situation on the development of the real economy exists, and MFCI has a predictive effect on the development of the real economy. The intertemporal correlation test shows that the predictive effect of MFCI on the real economy is more effective within 6 months. [ABSTRACT FROM AUTHOR]

A key problem in prediction theory is to improve adaptiveness to data characteristics. This paper proposed a novel method called buffered adaptive grey rolling model or BARGM model, which combines the buffer operator and grey rolling model. First, the new model decomposes original sequence into continuous data slices, and uses feedback input to adjust modeling data by buffer operator with variable weight on each data slice, then a extended grey forecasting model is utilized to model the adjusted data slices stepwisely and generate the extrapolation values. With comparison to GM(1. 1). BARGM lias two obvious features: Changing the monotonicity of traditional time response function and strong expansibility. The case study uses the BARGM and benchmark models to analyze China's greenhouse gas emission data, and the results demonstrate that the accuracy of fitting and prediction improve obviously, and prove the new model's effectiveness. [ABSTRACT FROM AUTHOR]

Local volatility model is widely used in the fields of risk management, options pricing, etc. The model can not only describe the "smile" and the term structure of volatility, but can also ensure the completeness of the market. The core goal of local volatility research is to calculate the implied volatility. In this paper, the implied volatility surfaces arc built with both parametric and non-parametric methods to obtain smoother volatility surfaces. Parametric method can ensure the absence of arbitrage. Meanwhile, a closed form of solving the local volatility model with non-parametric method is proposed, which can eliminate the approximation error. In addition, the pricing of Shanghai 50ETF option in China based on the local volatility model is studied by comparing effects of the models from aspects of in-the-sample, out-of-the sample and hedging pricing errors. The empirical results show that the non-parametric method is better than the parametric method for errors in-the-samplc; the parametric method has better results for out-of-sample and hedging effects. Particularly, both the options pricing and hedging effects of the implied volatility modeling methods are better than nn-modeled method in the aspects that the pricing errors can be decreased by more than half and the mean square error can be reduced by 1~2 orders of magnitude. [ABSTRACT FROM AUTHOR]

The generally slow growth rates in the aftermath of the global financial crisis have prompted many nations to pursue the political and economic policies that lead the wave of "anti-globalization". To reflect on the phenomenon of "anti-globalization", we need to have a better understanding of the benefits of globalization and its "hidden" costs. In view that there is no literature to explore the impact of export expansion on health theoretically, this paper made the first attempt to examine the relationship between export expansion and health based on China's powerful context. We consider a framework where workers bargain with their employer, and the firm chooses the optimal capital, labor, and materials based on the maximization of profit function. Each worker chooses the optimal effort level by equalizing the marginal benefit of efibrt, determined through bargaining, with the marginal cost of effort. Based on an extended Grossman health demand model, we systematically examine the channels through which export expansion affects health, i.e.. work intensity, wage rate, income inequality, the provision level of public service, and environmental quality. Finally, we give the corresponding policy implications based on our conclusion. [ABSTRACT FROM AUTHOR]

In this paper, fractal analysis methods are used to study the complexity characteristics of multivariate cross-correlations between the metal futures and spot markets in China. Firstly, the widely used multifractal detrended cross-correlation analysis (MF-DCCA) is extended to multivariate case, and the multivariate multifractal detrended cross-correlation analysis (MV-MFDCCA) is proposed. Then, the daily returns series of the futures and spot markets for China's basic metal copper, aluminum and zinc are regarded as two systems, and the multifractal analysis methods including the MV-MFDCCA are used to empirically investigate the multivariate cross-correlation between the two systems from the perspective of system theory. The results show that there are long-range power law cross-correlations and multifractal characteristics within and between the two systems, and the multifractal strengths of autocorrelations and cross-correlations for the spot system and its components are greater than those of the futures system and its corresponding components. In addition, in the situation of large fluctuations, the cross-correlation between the futures and spot systems is mainly influenced by the relationship between the futures copper and spot copper, while in the small fluctuation situation, mainly influenced by the relationship between the futures zinc and spot zinc. [ABSTRACT FROM AUTHOR]

This paper studies the impact of urban basic public service differences on the housing market. We focus on the role of urban basic public service in the housing market and the underlining mechanism. We employ the public service data of 29 large and medium-sized cities in China from 2006 to 2014 and use the entropy method to calculate the basic public service index of different cities in each year. By employing panel regression models, we investigate the impact of urban basic public services on housing prices. We find that the impact of medical resources on housing market is very significant. This is especially true for first-tier cities. The concentration of medical resources is an important factor that drives up the housing prices in first-tier cities. The policy implications of this study are that rationally coordinating resources such as medical care and education, and promoting the equalization of regional basic public services will help promote the healthy development of housing market in China and help build a long-term regulation mechanism for the housing market. At the same time, coordinating urban public services and formulating housing control policies should be tailored to local conditions and urban policies. [ABSTRACT FROM AUTHOR]

Developing scientific and effective air quality early warning system has important scientific and practical significance for protecting people's physical health and promoting social harmony and stability. Therefore, the isolation forest (iForest) algorithm is employed to analyze the outlier data in original air quality index (AQI) data, and then an effective air quality early warning system is developed in this paper. The system is consists of four modules:data preprocessing module, optimization module, forecasting module and correction module, which combines time varying filtering based empirical mode decomposition (TVF-EMD), modified butterfly optimization algorithm (MBOA), outlier robust extreme learning machine (ORELM), and nonlinear correction strategy, and successfully achieves effective early warning for air quality. In order to verify the effectiveness of the developed air quality early warning system, five cities with different air pollution level in China are employed for empirical research. The results show that:1) Compared with empirical mode decomposition (EMD), TVF-EMD can be more effective to reduce the nonlinear and non-stationary features of the original data; 2) The developed MBOA-based error nonlinear correction strategy is superior to other error correction strategies, which can significantly improve the performance of the early warning system; 3) The performance of the developed system is superior to other compared methods, which can provide effective early warning for cities with different air pollution level. [ABSTRACT FROM AUTHOR]

In order to promote the transformation of China's energy consumption and reduce CO2 emissions, this paper first uses the club convergence test method to conduct a detailed empirical study of the differences in the inter-provincial evolution of different types of fossil energy consumption. Then, based on the results of convergence clustering, a hierarchical (group) forecasting method is used to predict short-term CO2 emissions at different levels. The results show that due to the different dependence of economic development on coal consumption, coal consumption of various provinces converges to three levels. Driven by the energy intensity and structural effects, the province's oil and natural gas consumption have generally converged upward. The forecasts indicate that CO2 emissions from fossil fuels will be dominated by coal, which is dominated by the 13 provinces in clubs2. Meanwhile, oil consumption will increase CO2 emissions, natural gas will reduce total emissions, and provincial CO2 emissions and its growth rates will still have large differences. These findings have important implications for the establishment of specific regional energy consumption and emission policies:clubs2's provinces are key areas for controlling coal consumption and reducing CO2 emissions; strictly controlling oil consumption in high-income and heavy-industry provinces will further reduce total CO2 emissions. [ABSTRACT FROM AUTHOR]

The medium-term power load forecasting is often disturbed by a variety of external factors (such as temperature, holidays and wind power) and uncertainties. Also, the factors affecting the medium-term power load forecasting are complex and changeable, and it is difficult to predict accurately. In the big data environment, how to obtain valuable information quickly in a variety of large number of influence factors has become the key to the power load forecasting problems. A method of density forecasting based on LASSO quantile regression was proposed in this paper. First, the important influence factors were selected from the various external factors affecting the power load forecasting, and the LASSO quantile regression model was established. Then, by using the triangular kernel function, LASSO quantile regression was combined with the method of kernel density estimation for the medium-term power load probability density forecasting. Taking the historical load and external influence factors (including temperature, holidays and wind power) of a sub-provincial city in eastern China as an example, the probability density prediction of medium-term power load was carried out. The average absolute error obtained was respectively 3.53% and 3.69% in the median and the mode, which was better than the results without considering the external factors and without variable selection. In order to further verify the superiority of the method, the method was compared with the nonlinear quantile regression (NLQR) and the quantile regression neural network based on triangle kernel (QRNNT) probability density forecasting methods. The results illustrate that this method can better solve the high-dimensional data problem in power load forecasting, and obtain more accurate results of power load forecasting. [ABSTRACT FROM AUTHOR]

Hesitant fuzzy linguistic term set (HFLTS) is defined as an ordered and consecutive subset of the linguistic term set for a linguistic variable. This paper carries out some states of the art review over the development of HFLTS theory. Firstly, we introduce the definition and originality of the HFLTS, and then conduct the review from four aspects, which are the hesitant fuzzy linguistic fusion theory, the hesitant fuzzy linguistic measurement theory, the hesitant fuzzy linguistic preference relation theory and the hesitant fuzzy linguistic decision making methodologies. Finally, we outline the future research directions on qualitative decision making with hesitant fuzzy linguistic information. [ABSTRACT FROM AUTHOR]

After the initiation of carbon trading pilots in seven provinces and cities in China, issues of their effectiveness and impact on economy, environment and export are of great significance to policy makers, managers and experts of environmental science. To respond to these issues, we first define the concepts of carbon emission reduction, energy saving and low-carbon economy and discuss policy measures and economic instruments related to carbon emission reduction. Focusing on "quantity control" and "price control", we analyze in detail their implementation process and actual effectiveness in both theoretical and practical points. Also, we present in this paper the mechanism and pathways of carbon emission reduction and their inspiration to China from macro, micro and technical perspectives. We then review the related literature and comment how these academic results can be used to help China to achieve its carbon reduction target at optimal economic costs. Finally, we point out the deficiencies and possible theoretical gaps in the previous studies and present some important issues that need further academic exploration. [ABSTRACT FROM AUTHOR]

Energy and environmental issues associated with the automotive industry constraints gradually expanded, with the continuous development of new energy vehicles and vehicle types constantly updated, the future of Chinese auto energy saving and environmental benefit analysis has yet to be analyzed. Firstly, this paper cited competition mechanism based on biological populations Lotka-Volterra model, using MATLAB modeling, simulation electric vehicles, conventional cars and natural gas vehicles in the next 40 years to maintain the amount of curve; combined with energy consumption and emissions in the process of car use and fuel production, car ownership of three models, quantitative analysed the energy conservation and emissions reduction benefits of automobile type change in the future. The results showed that: the future of conventional cars and natural gas car ownership will show the first increase after a decrease of parabolic trends, electric car ownership is "S" trend continues to grow; future total energy consumption and carbon emissions from vehicles show increased and then decreased of parabolic trend. [ABSTRACT FROM AUTHOR]

In this paper, we first use a simple mathematic model to infer the role of buy-side analysts in correcting the optimistic stock recommendation and earning forecast of sell-side analysts, and then investigating the relationship between investor sentiment and optimistic stock recommendation and earning forecast in those two types of analysts. The results show that, when the market sentiment is higher, the stock recommendation and earning forecast are more optimistic for sell-side analysts, whereas the stock recommendation and earning forecast are more conservative for buy-side analysts. Further evidence confirm that the relationship between in market sentiment and stock recommendation and earning forecast are significantly different between buy-side analysts and sell-side analysts. Our findings have import implications for stock market development in China. [ABSTRACT FROM AUTHOR]