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Based on comprehensive grain price data, we employ a storage model to estimate consistent interest rates and compare capital market development between Britain and China. Interest rates for Britain were lower than China’s on average by about 3 percentage points from 1770 to 1860. For country pairs with bilateral distance less than 200 kilometers, the regional capital market integration in the Yangzi Delta in China comes close to the British average; but at larger distances, spatial interest rate correlations in Britain are twice those of the Delta and three or more times as high as elsewhere in China. Overall, our results suggest capital market development differences at an early date, so that capital market performance may be important for the Great Divergence that emerged between China and Western countries at this time. (JEL E43, E44, N23, N25, N53, N55, Q11)

PurposeSeasonal fluctuation interference often affects the relational analysis of economic time series. The main purpose of this paper is to propose a new grey relational model for relational analysis of seasonal time series and apply it to identify and eliminate the influence of seasonal fluctuation of retail sales of consumer goods in China.Design/methodology/approachFirst, the whole quarterly time series is divided into four groups by data grouping method. Each group only contains the time series data in the same quarter. Then, the new series of four-quarters are used to establish the grey correlation model and calculate its correlation coefficient. Finally, the correlation degree of factors in each group of data was calculated and sorted to determine its importance.FindingsThe data grouping method can effectively reflect the correlation between time series in different quarters and eliminate the influence of seasonal fluctuation.Practical implicationsIn this paper, the main factors influencing the quarterly fluctuations of retail sales of consumer goods in China are explored by using the grouped grey correlation model. The results show that the main factors are different from quarter to quarter: in the first quarter, the main factors are money supply, tax and per capita disposable income of rural residents. In the second quarter are money supply, fiscal expenditure and tax. In the third quarter are money supply, fiscal expenditure and per capita disposable income of rural residents. In the fourth quarter are money supply, fiscal expenditure and tax.Originality/valueThis paper successfully realizes the application of grey relational model in quarterly time series and extends the applicable scope of grey relational model.

Using U.S. listed firms during the period from 1971 to 2010, this paper investigates the effect of religion on corporate cost behavior. We find that religion mitigates cost stickiness induced by agency or behavioral biases of managers. This result holds for several robustness tests that address endogeneity concerns. The mitigating effect of religion on cost stickiness is through the channel of reducing top managers’ overconfidence and optimistic bias regarding future demand change (risk-aversion mechanism) and promoting managers’ adherence to fiduciary responsibilities and consideration of shareholder benefits (ethic mechanism). Further evidence shows that the reduction in cost stickiness caused by religion increases firm value. Overall, our findings suggest that religion reduces the wedge between a firm’s actual and optimal resource commitments, which helps to improve firm value and resource allocation efficiency.

IntroductionDifferent maintenance strategies have shown efficacy in patients with advanced ovarian cancer, but without drawing any conclusion on which strategy is preferred. Therefore, we will conduct a network meta-analysis and cost-effectiveness analysis to investigate maintenance strategies containing chemotherapy, poly (ADP-ribose) polymerase (PARP) inhibitors and anti-angiogenesis therapy for patients with advanced ovarian cancer.Methods and analysisThe search strategy to identify potentially relevant studies will include hand searches in EMBASE, PubMed, Cochrane library and Web of science. The primary outcome is progression-free survival, defined as the date of randomisation to the date of progression or death. The secondary outcome is overall survival (calculated from the time from randomisation to death from any cause), grade 3–4 haematological and non-haematological toxicities, quality-adjusted life years and incremental cost-effectiveness ratios. Two steps of meta-analysis will be carried out, traditional pair-wise meta-analysis and network meta-analysis. Methodological quality, risk of bias and the strength of evidence from randomised controlled trials (RCTs) will be proposed to assess the quality of RCTs. Heterogeneity, publication bias, subgroup analysis and sensitivity analysis will be explored.Ethics and disseminationThe purpose of our study is to perform a comprehensive efficacy, safety and cost-effectiveness analysis of all maintenance strategies in patients with advanced ovarian cancer. The results will be disseminated through international conference reports and peer-reviewed manuscripts. Ethics approval is not required for network meta-analysis and cost-effectiveness analysis.PROSPERO registration numberCRD42021231814.

Haze has been a severe problem in China for some time, jeopardizing air quality, public health and sustainable growth. This paper examines the direct effect and spatial spillover effect of policy uncertainty on haze pollution with a spatial panel model, using prefecture-level data from 2004 to 2016. This study shows that: (1) policy uncertainty has increased the level of local haze pollution and has a significant spatial spillover effect on surrounding areas, (2) although local policy uncertainty has increased the haze pollution in geographically adjacent cities, it only affects the cities within the province with similar economic distances, and (3) the policy at the central level can effectively alleviate the impact of policy uncertainty at the local level on haze pollution, especially in relation to the spatial spillover effect, but still has limitations in eliminating the direct effect, which is due to the ineradicable nature of policy uncertainty.

Background: Noncommunicable diseases (NCDs) are the leading causes of morbidity and mortality worldwide. Understanding the financing and distribution of diseases can provide a basis for policy formulation and intervention. This study analyses the expenditure of NCDs in China to provide health policy advice.Methods: Data were collected by multi-stage stratified random sampling from 2017-2019. The medical expenses of patients with NCDs were calculated based on “System of Health Accounts 2011”(SHA 2011), Analyze from funding sources, dimensions of institutional flow, and financing scheme. Linear regression analysis was conducted by controlling factors influencing hospitalization expenses. All analyses were performed by STATA 15.0.Results: 408 institutions and 8,104,233 valid items were included in the study. The current curative expenditure (CCE) of NCDs was 14.205 billion China Yuan (CNY) in 2017, 15.914 billion CNY in 2018, and 18.055 billion CNY in 2019. More than 60% came from public financing. The proportion of family health financing continued to decline, reaching 31.16% in 2019. The expenditures were mainly in general hospitals, above 70%. Elderly patients account for the majority. Diseases of the circulatory system, Diseases of the digestive system, and Neoplasms were the main NCDs. Year, age, gender, length of stay, surgery, insurance, and institution level were the factors affecting hospitalization expenses.Conclusions: NCDs are the main economic burden of diseases in China, and their financing and distribution are inequality. To reduce the economic burden of NCDs, the government needs to optimize resource allocation and rationalize institutional flows and functions.

Air quality in China has gradually been improving in recent years; however, the Beijing-Tianjin-Hebei (BTH) region continues to be the most polluted area in China, with the worst air quality index. BTH and its surrounding areas experience high agglomeration of heavy-polluting manufacturers that generate electric power, process petroleum and coal, and carry out smelting and pressing of ferrous metals, raw chemical materials, chemical products, and non-metallic mineral products. This study presents evidence of the air pollution impacts of industrial agglomeration using the Ellison–Glaeser index, Herfindahl–Hirschman index, and spatial autocorrelation analysis. This was based on data from 73,353 enterprises in “2+26” atmospheric pollution transmission channel cities in BTH and its surrounding areas (herein referred to as BTH “2+26” cities). The results showed that Beijing, Yangquan, Puyang, Kaifeng, Taiyuan, and Jinan had the highest Ellison–Glaeser index among the BTH “2+26” cities; this represents the highest enterprise agglomeration. Beijing, Langfang, Tianjin, Baoding, and Tangshan also showed a low Herfindahl–Hirschman index of pollutant emissions, which have a relatively high degree of industrial agglomeration in BTH “2+26” cities. There was an inverted U-shaped relationship between enterprise agglomeration and air quality in the BTH “2+26” cities. This means that air quality improved with increased industrial agglomeration up to a certain level; beyond this point, the air quality begins to deteriorate with a decrease in industrial agglomeration.

Competitive cognition dynamics are widespread in modern society, especially with the rise of information-technology ecosystem. While previous works mainly focus on internal interactions among individuals, the impacts of the external public opinion environment remain unknown. Here, we propose a heuristic model based on co-evolutionary game theory to study the feedback-evolving dynamics of competitive cognitions and the environment. First, we show co-evolutionary trajectories of strategy-environment system under all possible circumstances. Of particular interest, we unveil the detailed dynamical patterns under the existence of an interior saddle point. In this situation, two stable states coexist in the system and both cognitions have a chance to win. We highlight the emergence of bifurcation phenomena, indicating that the final evolutionary outcome is sensitive to initial conditions. Further, the attraction basins of two stable states are not only influenced by the position of the interior saddle point but also affected by the relative speed of environmental feedbacks.

In recent years, the constant advancement of market reform in China improves the market allocation efficiency of production factors and further promotes the rapid growth of economic aggregate output in the country. Additionally, the CO2 emitted in China also constantly increases. Based on panel data pertaining to 30 provinces from 1998 to 2015 in China, the CO2 emission efficiency and marketisation level of China were separately measured using a super Slacks-based measure approach and generalised principal component analysis. On this basis, by utilising a dynamic panel regression model and a panel smooth transition regression model, the influence of market reform on CO2 emission efficiency was explored. The results show that the marketisation level exerts a significantly positive effect on CO2 emission efficiency in both models and the results are robust. On the condition of taking energy price as a threshold variable, the influence of process of marketisation is significantly greater than that when taking technological progress as a threshold variable. It implied that although energy price and technological progress both significantly promote the marginal effect of market reform on CO2 emission efficiency, the energy price shows a greater influence than technological progress. Infrastructure construction and urbanisation can inhibit the improvement of CO2 emission efficiency. Additionally, the proportion of secondary industries can delay the improvement of CO2 emission efficiency.

Solar power has achieved great development in the last decade, and it should continue to play a central role in the face of climate change and sustainable development challenges. This paper builds a real options model that provides a microeconomic analytical framework with the Least Squares Monte Carlo (LSM) method to assess the investment choices of a typical solar panel producer in China facing trade and domestic supply- and demand-side policy uncertainties. It builds a baseline scenario and three policy scenarios with decreasing anti-dumping and countervailing charges, constant feed-in tariff (FIT) level and reduced investment cost. A typical producer will have to make an investment decision on building a new production line in five years based on a decision impact analysis within 20 years. The result shows an immediate investment decision for all scenarios. The producer will have higher return from investment in building a solar power plant with a constant FIT. Export is the optimal choice in other scenarios where investment return is lower. After sensitivity analysis, the paper concludes and can be used as a toolkit for solar panel producers and a reference for policy makers to evaluate the impact of policy uncertainties.

Capital intensity is an important indicator for reflecting the relative changes of production factors of an industry. The facilitating effect of capital deepening, i.e., the positive impact of the augment of capital intensity, towards the structural transformation of the industry is definite. Therefore, the accurate prediction of capital intensity of the new energy industry is of great significance in facilitating the structural transformation and upgrading of the industry. Based on the Cobb-Douglas production function, an industry-level capital-labour ratio (KLR) model is established to describe the dynamic characteristics of the capital intensity. Then, by combining the estimation and prediction method of the nonlinear grey Bernoulli model (NGBM(1, 1)) with the KLR model, a new hybrid grey model, i.e., NGBM(1, 1)-KLR model is proposed. In this way, the economic meaning of the KLR and the advantage of the NGBM(1, 1) model in solving small-sample and nonlinear problems are complemented with each other, which enables one to more favourably predict the capital intensity of the industry. To verify the effectiveness and superiority of the proposed model, the NGBM (1, 1)-KLR model is used to predict the capital intensity of the new energy industry in China, and the model is compared with the GM(1, 1) and the NGBM(1, 1) models in the prediction performance. The empirical results show that the NGBM(1, 1)-KLR model can more accurately predict the capital intensity of the industry in China than the GM(1, 1) and the NGBM(1, 1) models. Moreover, the new hybrid grey model is used to carry out the out-of-sample prediction for the capital intensity of the new energy industry in China in the period of 2017–2020. The predicted results demonstrate that the structure of the industry in China will further transform and upgrade towards the capital deepening.

Asymmetry is omnipresent in human society and nature and the reasons causing asymmetry are multiple. To think about the impact of asymmetries on the cooperation systems, we focus on a typical model of great asymmetric traits---the boxed pigs game---and extended the one-to-one interaction to the interaction in population. We consider the asymmetry of payoff and the spatial structure of the two populations in space. Our results have shown that the almost equal abundance and strength of two populations kills cooperative behavior. The single increase of either strength-asymmetry or abundance-asymmetry promotes cooperation. But high levels of both asymmetries would inhibit cooperative behavior, making the powerful mechanism of cooperation broken.

In emerging markets, the externality of political environment is an important factor affecting the design of agent contracts. However, few studies have studied political determinants of incentives in CEO compensation. This study utilizes an exogenous political shock in China (i.e., the investigations of the Central Commission for Discipline Inspection) to identify the causal effect of anti-corruption on CEO compensation by using firm-level data during 2000–2016 from China through a difference-in-differences method. By considering the reduction in corruption arising from the shock, we find that CEO compensation substantially increases. Channel analysis reveals that the anti-corruption campaign reduces the negative externalities of corruption and increases incentive efficiency in non-state-owned enterprises. In addition, the effect of the anti-corruption campaign on CEO compensation is particularly pronounced with firms exposing to high corrupt environment, inspection groups having high ability, and CEOs without political connections.

Background China's health financing system has changed from the government-led mode under the planned economy to the diversified mode under the market economy. Equity in health financing has been a national health priority. This study aimed to predict changes in total health expenditure (THE), government health expenditure (GHE), social health expenditure (SHE) and out-of-pocket health expenditure (OOP) in China from 2018 to 2022, and to provide a theoretical basis for health policy adjustment. Methods Based on health expenditure date of time series from 1978-2017, R3.5.1 software was used to construct the Autoregressive Integrated Moving Average (ARIMA) model. Results The model of THE, GHE, SHE and OOP are ARIMA (3.3.0), ARIMA (1.3.1), ARIMA (2.4.0), ARIMA (2.2.2). According to the simulation results, in 2022, China's THE is expected to reach 8473.00 billion Yuan, and the constituent ratios in GHE, SHE and OOP will be 25.49%, 51.25% and 23.26%, respectively. The proportion of THE to GDP will continuously increase from 2018-2022 at a reasonable pace, while THE itself will increase rapidly. Conclusions China should take effective measures to control the excessive growth of THE, keep decreasing the OOP percentage, and improve the efficiency and fairness of the use of health funds.

Carbon leakage is one of the most critical environmental issues considered in China during the process of enacting mitigation policies. This study analyzes potential carbon leakage risk within and outside an emissions trading scheme (ETS). Results show that within ETS, six and eight four-digit subsectors are considered at risk of carbon leakage under a regulated and liberalized electricity market, respectively. Accordingly, the appropriate proportion of free allowances required for compensation varies between 15.8% and 17.0%. For non-ETS subsectors, four scenarios are designed for in-depth analysis. The results show that carbon leakage occurs in most scenarios. With carbon tax and a regulated market, the risk that carbon leakage will most likely occur in non-ETS sectors in China are insignificant if the average auctioning factor of ETS is lower than 60%. This result suggests that carbon leakage in non-ETS sectors is an insignificant concern in the near term. However, it can be serious if the auctioning factor increases or if the electricity market is liberalized in the future. Meanwhile, the sensitivity analysis implies that ETS expansion will help prevent non-ETS sectors from carbon leakage risk and will make the implementation of the auction mechanism for allocating initial allowances attractive and acceptable. Therefore, this study highlights that the design of carbon tax and its complementary measures should be regarded seriously to assure synergy, particularly with the process of the electricity market.

Bitcoin’s emergence has the potential to pave the way for a technological revolution in financial markets. What determines its valuation is an important open question with far-reaching business and...

Government spending plays an important role in determining economic performances in China. Its macroeconomic effects are analyzed in this paper. We show that government spending in China (i) Granger-causes output, consumption and investment booms as well as inflation and (ii) has a multiplier larger than 1. The large multiplier effects are found not only in aggregate time-series data but also in panel data at the provincial level. We also provide a theoretical model and Monte Carlo analysis to rationalize our empirical findings. Our theoretical and Monte Carlo analyses support the large multiplier found in China but also suggests that government spending is not necessarily a free lunch in spite of the large multiplier effects.

According to industrial organization theory, market structure is a crucial factor to market performance. Based on the VAR model and the data from 1994 to 2014, we revealed the dynamic response route of the market structure to these factors and the change process of contribution rate of these factors to the market structure. It shows that market structure is inertial adjustment; technology advance and industry policy have continuous effects on improvement of market concentration ratio; market size and production scale have sustained negative effects on market concentration ratio; fixed capital has barrier effect, which is mainly the entry barrier effect at the beginning, and then the exit barrier effect continues to play a leading role. Therefore, the government has no need to introduce special policies to encourage merger or expansion on the capacity as enterprises would do it spontaneously; it is necessary to make market access system stricter, to improve exit compensation mechanism and to promote technological innovation; all these policies need dynamic adjustment based on the stages of economic cycle.

The extant choice literature has proposed different non-compensatory rules as a more realistic description of consumers’ choice than a standard compensatory model. Some research has further suggested a two-stage sequential decision process of non-compensatory consideration and then compensatory choice, where the determinants of each stage may differ. Some aspects of non-compensatory choice modeling are under-studied. In this article, we hope to advance the understanding of non-compensatory choice models with the following aims: (a) providing an overview of existing representations for non-compensatory choice decisions, (b) discussing how such choice decisions can manifest from the economic search theoretical perspective, (c) exploring the empirical identification of non-compensatory decisions using different data, and (d) presenting applications of non-compensatory choice models in novel domains.

Carbon market becomes increasingly popular as a cost-effective instrument to mitigate CO 2 emissions. However, its construction is a learning-by-doing process, and needs consistent regulatory updates in order to deliver optimal effects. This paper uses the event study method to assess the impacts of different policy adjustments on the EUA returns in the European Union Emissions Trading Scheme (EU ETS) since 2005. Comparing to existing studies that focus on the impact of a single policy, this paper provides a complementary reference on if and to what extent policy adjustments can impact the carbon prices by classifying all regulatory update events into six categories. Its key findings are as follows. First, aggregate impacts of total 50 events studied are low while impacts of events having underlying negative impacts are higher than those having underlying positive impacts. Second, 24 events have significant impacts on EUA returns and are coherent to their theoretical impacts (except one event). Third, events having negligible impact on EUA returns are those that are announced not for the first time or those having no impact on CO 2 quotas supply and demand. Finally, there are different impact patterns: some events have different impacts on short-end and long-end carbon prices.

We study the impacts of a priori knowledge of spot markets for excess capacity on stochastic service network design problems. We do this by investigating whether it is beneficial to take spot markets into account at the design stage when building a transportation plan facing uncertain demands. We show that in most situations, taking spot markets into account at design level reduces the total costs, not just from the benefit of selling excess capacity, but also from changes in the design of the service network itself. We also show that when deterministic models are used to produce solutions for stochastic service network design problems, introducing spot markets at the design stage has undetermined effects. This is important since in most real cases, only the deterministic models can actually be solved. We only study cases where it would not be profitable for our vehicles to operate solely in the spot market as the income per capacity unit is much lower than our costs per capacity unit; the spot market is a means to obtain some income from excess capacity, but it is not our primary market.

The Braess's paradox is the phenomenon that increasing the resources leads to the reduction of the overall welfare, originally proposed in the field of transportation. An evolutionary game model is proposed to explicitly depict the process of individual learning in this phenomenon. It can shows clearly how the individual rationality leads to collective irrationality. A proper charging scheme is provided which can not only solve the Braess's paradox, but also maximize social welfare. This work provides inspiration for the policy to guide the self-interested individuals to achieve social welfare maximization.

With growing popularity of Big Data Analysis, Predicting the Support-Resistance Levels of stock prices is important problem, due to an investor in stock market ideally should get maximum returns on the investment made and for that should know how importance of Support-Resistance Levels. In this paper, we analysis the significance of price Support-Resistance Levels of Chinese Stock Market based on the proposed information granulation and FCM fuzzy clustering algorithm. The Proposed stock information granulation method considers the observed historical closing price of day K-line and 15-Minutes K-line. The research data set that has been used in this study is from Chinese Stock Market. Through analysis of experimental study, we found that the effectiveness of Support-Resistance Levels is nearly about Two-thirds.

Background Unfavorable psychosocial working conditions have been associated with cognitive decline and chronic diseases, both of which may subsequently accelerate functional dependence. This study aimed to investigate the association between job demand–control–support combinations and trajectories of disability in later life and to further explore the role of cognitive decline and the co-occurrence of chronic diseases in mediating this association. Methods and findings In this cohort study, 2,937 community dwellers aged 60+ years (mean age 73 ± 10.6; 62.9% female) residing in the Kungsholmen District of Stockholm, Sweden, participated in the baseline survey (2001–2004) and were followed up to 12 years. Lifelong occupational history was obtained through a standardized interview; job demands, job control, and social support at work in the longest-held occupation were graded with a psychosocial job–exposure matrix. Job control, demands, and social support were dichotomized using the median values from the matrix, respectively, to further generate demand–control–support combinations. Disability was measured by summing the number of impaired basic and instrumental activities of daily living. Global cognitive function was assessed by Mini-Mental State Examination. Chronic conditions were ascertained by clinical examinations, medical history, and patient clinical records; the total number of chronic diseases was summed. Data were analyzed using linear mixed-effects models and mediation analysis. Age, sex, education, alcohol consumption, smoking, leisure activity engagement, early-life socioeconomic status, occupational characteristic and physical demands, and baseline cognitive function and number of chronic diseases were adjusted for in the analyses. Compared with active jobs (high control/high demands; n = 1,807), high strain (low control/high demands; n = 328), low strain (high control/low demands; n = 495), and passive jobs (low control/low demands; n = 307) were all associated with a faster rate of disability progression (β = 0.07, 95% CI 0.02–0.13, p = 0.01; β = 0.10, 95% CI 0.06–0.15, p < 0.001; β = 0.11, 95% CI 0.05–0.18, p < 0.001). The association between high strain and disability progression was only shown in people with low social support at work (β = 0.13, 95% CI 0.07–0.19, p < 0.001), but not in those with high social support (β = 0.004, 95% CI −0.09 to 0.10, p = 0.93). Moreover, we estimated that the association between demand–control status and disability trajectories was mediated 38.5% by cognitive decline and 18.4% by accumulation of chronic diseases during the follow-up period. The limitations of this study include unmeasured confounding, self-reported work experience, and the reliance on a psychosocial job–exposure matrix that does not consider variabilities in individuals’ perception on working conditions or job characteristics within occupations. Conclusions Our findings suggest that negative psychosocial working conditions during working life may accelerate disability progression in later life. Notably, social support at work may buffer the detrimental effect of high strain on disability progression. Cognitive decline and chronic-disease accumulation, and especially the former, partially mediate the association of psychosocial working conditions with trajectories of disability. Further studies are required to explore more mechanisms that underlie the association between psychosocial working conditions and disability trajectories., Kuan-Yu Pan and colleagues reveal potential protective effects of psychosocial support at work against cognitive decline and disability., Author summary Why was this study done? Work is one of the activities that take up a considerable amount of time in our adult lives, thus potentially making it an important determinant of health, even in later life. Inability to independently carry out daily tasks (defined as disability) can affect older people’s quality of life and pose a burden on caregivers and societies. A better understanding of the pathway between midlife working conditions and late-life disability may help the development of preventive strategies. What did the researchers do and find? We studied the association of psychosocial working conditions with the rate of disability progression over 12 years in a cohort of 2,937 individuals aged 60 years and older. We found that unfavorable psychosocial working conditions, including high-strain, low-strain, and passive jobs, were related to a faster rate of disability progression. The association of high-strain jobs with accelerated disability accumulation was only present among people with low social support at work. The decrement in cognitive function and increase in chronic-disease burden, and especially the former, partially explained the relationship between unfavorable working conditions and disability progression in later life. What do these findings mean? Unfavorable psychosocial working conditions during working life are related to the progression of disability in later life. Public health authorities, employers, and employees should all be aware of that. Social support at work is especially important in a high-strain work environment given its capacity to attenuate the impact of high-strain jobs on disability accumulation. Monitoring cognitive function and medical conditions of people with unfavorable working conditions is endorsed by the role of both dimensions, and especially of cognitive dysfunction, in accelerating disability progression in older age.

Purpose – Since the construction of China-ASEAN Free Trade Area (CAFTA) launched in 2002, the bilateral trade increased rapidly. The purpose of this paper is to test the competition and cooperation in trade relationships between China and the main trading partners (Singapore, Malaysia and Thailand (SMT)) from ASEAN in international trade under CAFTA. Design/methodology/approach – Grey Lotka-Volterra competition models are established for testing the trade relationships between China and SMT, respectively, based on the data of import and export from 2003 to 2014. To improve modeling accuracy, the interpolated coefficients for dynamic background value are introduced into the grey Lotka-Volterra model. The optimal parameters are solved through minimizing the mean absolute percentage error and the constraint of parameter relationships. Besides, eigenvalues of the Jacobian matrix are adopted to carry out the stability of equilibrium points of the trade relationships. Findings – As the beneficiary party, China has mutual benefit and win-win trade relationship with Singapore, while it has predator-prey trade relationships with Malaysia and Thailand. The future exports from SMT to China will stabilize at 462.31, 598.13 and 447.03 billion dollars, respectively. The future exports from China to SMT will stabilize at 637.16, 943.71 and 827.52 billion dollars, respectively. Practical implications – This study can be regarded as an important reference for China and its trading partners from ASEAN. The modeling results can help the decision makers to formulate appropriate international trade strategies to gain and maintain competitive advantages. Originality/value – A new approach to testing the trade relationships is proposed based on grey Lotka-Volterra competition model. The study also proposed a dynamic optimization method for the background value of grey Lotka-Volterra model.

Closed-end country funds are interesting in that they have two sets of prices for the same underlying assets—the net asset value (NAV) of the fund holdings as measured using the underlying firms’ stock prices in their home markets and the fund price at which the fund trades on a U.S. stock exchange. Utilizing the theoretical framework of information asymmetry in two separate markets for an identical asset, we find that the difference between the fund’s NAV and its trading price (i.e., the fund discount) is positively associated with the earnings opacity of the underlying companies. Such a positive association is consistent with the notion that U.S. investors face higher information acquisition and processing costs when compared with local investors, and therefore earnings opacity exacerbates the information disadvantage of U.S. investors, leading to a larger fund discount. We further show that the positive relation varies predictably with U.S. investors’ information acquisition and processing costs and with the extent to which host stock markets are segmented from the U.S. market. Specifically, we find that the positive relation between earnings opacity and fund discounts is weaker for those funds with more U.S. cross-listings in fund holdings, with underlying companies following financial reporting standards similar to U.S. standards, and with less segmented local markets.

This paper analyzes the bullwhip effect in multi-echelon supply chains under a general class of nonlinear ordering policies. A describing-function approach from control theory is used to derive closed-form formulas to predict amplification of order fluctuations along the supply chain. It is proven that with consideration of nonlinearity in the ordering policy, the magnitude of the bullwhip effect will eventually become bounded after growing through the first few stages of the supply chain. It is also proven that the average customer demand as well as the demand fluctuation frequency would directly affect the bounded magnitude, while the suppliers’ demand forecasting method has no effect at all. For illustration, analytical results for a class of order-up-to policies are derived and verified by numerical simulations. The proposed modeling framework holds the promise to not only explain empirical observations, but also serve as the basis for developing counteracting strategies against the bullwhip effect.

Coal, oil and gas, and clean energy consumptions were considered to be three competitive populations in a closed system and their dynamic competitive relationships were investigated using a Lotka-Volterra model. The parameters of this model were identified through non-linear least squares estimation method; on this basis, this study analysed the equilibrium of the system and predicted its future development trend. Results show that both coal, and oil and gas, consumptions positively promoted clean energy consumption, while oil and gas exerted a greater influence than coal; moreover, clean energy consumption helps to promote oil and gas consumption, and this phenomenon forms competition for coal consumption. The energy consumption system of China is unstable and her energy supply structure still needs further adjustment in the short-term. Although future energy consumption is still dominated by coal, its market share presents a downward trend, and clean energy is expected to become more popular.

Based on panel data from 2007 to 2016, this paper investigates the carbon abatement effect of China’s pilot Emission Trading Scheme (ETS) and the influencing paths of the policy at both national and regional level by using Difference in Differences model and parallel multiple mediator model. The results reveal that the policy has reduced the total carbon emission reduction by 13.39%, with an upward abatement trend annually. Secondly, a systematic framework containing technique effect, composition effect and allocation effect is proposed to further investigate the influencing mechanisms of the achieved emission curbing effect. It reflects that the policy has not yet promoted the low-carbon innovation completely, only innovation of high-quality played an effective mediating role. Meantime, two other influencing channels of industrial upgrading and optimized resource allocation are verified. Thirdly, policy’s heterogeneous impacts are detected by classifying China into three representative regions according to economic and geographical differences, where western China experiences the strongest emission abatement by 21.57%, whereas central China and eastern China is 9.83% and 6.65% respectively. Fourthly, assessments of the regional influencing mechanisms show that the mediating role of high-quality low-carbon technology innovation is only significant in the western region, while the other two regions tend to have rebound effect. Besides, the promotion of industrial upgrading is positively related to the development levels of regions, with the improvement of 18.01% in the eastern region, followed by 17.34% and 12.46% in the central and western region. Finally, the optimization of the resource allocation has not been promoted regardless of the regions. In general, although the current policy has a significant carbon reduction effect, there is still much space for potential abatement to be developed.

This paper evaluates a well-known approach from the economic history literature that uses grain prices to shed light on interest rates. Although this method has been applied in influential work starting with McCloskey and Nash (Am Econ Rev 74:174–187, 1984) and has potentially wide applicability in situations where interest rates are not available, this paper provides the first analysis of how well the storage cost approach captures actual capital market performance on a number of different dimensions. Using matched data on bank interest rates and grain prices for early 19th century U.S. regions, we find that the storage cost approach is useful for quantifying the performance of capital markets. The storage cost approach captures well regional differences in market performance implied by bank rates data, in terms of both the average interest rates and capital market integration. Moreover, the results are stronger than interest rate figures derived from the bills of exchange rates. The paper also assesses the storage cost approach’s robustness to measurement error, incomplete information, outliers, and other factors.

Summary Explaining biodiversity in nature is a fundamental problem in ecology. An outstanding challenge is embodied in the so-called Competitive Exclusion Principle: two species competing for one limiting resource cannot coexist at constant population densities, or more generally, the number of consumer species in steady coexistence cannot exceed that of resources. The fact that competitive exclusion is rarely observed in natural ecosystems has not been fully understood. Here we show that, by forming chasing pairs and chasing triplets among the consumers and resources in the consumption process, the Competitive Exclusion Principle can be naturally violated. The modeling framework developed here is broadly applicable and can be used to explain the biodiversity of many consumer-resource ecosystems and hence deepens our understanding of biodiversity in nature., Graphical Abstract, Highlights • Foraging with only chasing pairs cannot break the Competitive Exclusion Principle (CEP) • A population dynamics model involving both chasing pairs and triplets can break CEP • Redundant foraging within the chasing triplets facilitates species coexistence • The theoretical framework is testable in ecosystems involving pack hunting, Microbiology; Evolutionary Ecology; In Silico Biology

Hog prices fluctuate dramatically has always been a major risk issue for any country live hog industry. This study aimed to reveal the spatial characteristics and the effects hog price volatility taking China as an example. This article introduced the monthly volatility of hog prices: P=∣(Pt 1-Pt)∣/Pt*100%, to measure the fluctuation degree of hog price, using the Global Moran I Index to indicate the correlation degree of economic variables adjacent or close to each other in space and using Local Moran I Index to analyze the local spatial difference of economic variables. On this basis, we calculated the effect of spillover using the SAR model. It was found that there was a significant spatial spillover effect in hog prices in China. With the comprehensive comparisons of the direct effects and indirect effects of each explanatory variable, it was present that the hog price fluctuation of a region was affected not only by the changes in the explanatory variables in the region, but also by that of the neighboring regions. We suggest that livestock farmers in the production decision-making, not only need to control production cost, but also to pay close attention to the current situation of pig price fluctuations in neighboring areas and the measures taken by stakeholders.

There has been growing interest in making predictions from business survival data. Survival models could be used to predict the time-to-next-purchase in marketing, model churn or attrition rates in...

Based on an analysis of the congestion effect and changes in the speed of vehicle flow during morning and evening peaks in a large- or medium-sized city, the piecewise function is used to capture the rules of the time-varying speed of vehicles, which are very important in modelling their fuel consumption and CO2 emission. A joint optimization model of the green vehicle scheduling and routing problem with time-varying speeds is presented in this study. Extra wages during nonworking periods and soft time-window constraints are considered. A heuristic algorithm based on the adaptive large neighborhood search algorithm is also presented. Finally, a numerical simulation example is provided to illustrate the optimization model and its algorithm. Results show that, (1) the shortest route is not necessarily the route that consumes the least energy, (2) the departure time influences the vehicle fuel consumption and CO2 emissions and the optimal departure time saves on fuel consumption and reduces CO2 emissions by up to 5.4%, and (3) extra driver wages have significant effects on routing and departure time slot decisions.

Using a perception-based crime deterrence approach, we present evidence that corporate insiders located closer to the Securities and Exchange Commission regional offices trade less frequently on their own company's stocks, while they earn higher abnormal returns from such insider transactions. These results are robust to several additional tests. Our further analysis indicates that such differences in trading profitability are mitigated during the periods of a high level of legal jeopardy such as the periods around earnings announcements and mergers and acquisitions. These findings are consistent with the view that Securities and Exchange Commission oversight has an impact on insiders' trading behavior by influencing their perceptions of sanctions risk. Copyright © 2015 John Wiley & Sons, Ltd.

In 2013, China launched its domestic pilot emissions trading scheme (ETS) as a cost-effective strategy to reduce CO2 emissions. Theoretically, the ETS can interact with the feed-in tariffs (FITs) applied to renewable energies (REN). This article presents a simple method to demonstrate how FITs can be adjusted based on the evolution of ETS carbon prices in order to provide a cost-effective climate policy package in China. First, by using provincial data and wind and solar power as examples, it calculates the implicit carbon prices that FITs generate in different Chinese provinces and finds that they are much higher than current carbon prices in the pilot ETS. This shows the necessity of using both instruments to guarantee current level incentives to develop REN for climate change purposes, at least in the short and medium terms. Second, by keeping the annual total carbon price level stable (the sum of the implicit FIT carbon price and the ETS carbon price), and taking into account the cost evolution of REN...

To accurately predict the consumption of clean energy in China, a grey dynamic model is constructed by taking economic growth and environmental regulation as exogenous variables. The Nash equilibrium idea-based optimization method is proposed to solve the parameters of the model so as to obtain better modeling effects than that of the traditional model. The empirical results show that: (1) a spontaneous increasing mechanism of the clean energy consumption has not yet formed in China; (2) both GDP and effluent charge play a positive role in accelerating clean energy consumption in China, but effluent charge has a stronger effect than GDP; (3) clean energy consumption in China is expected to stably increase at an annual rate of 5.73 % averagely in 2012---2020. By 2020, clean energy consumption in China is expected to reach 454.55 million tons of standard coal. The study also provides some policy suggestions of promoting clean energy consumption based on the empirical analysis conclusions.

We examine the challenges and opportunities to introduce emissions trading (ETS) in China’s electricity sector, in which the interaction between ETS and electricity market reform plays a major role. China’s electricity sector is currently in a slow progress towards a more competitive and market-based system. Both equal share dispatching policy and regulated wholesale and retail pricing policies pose significant challenges for implementation of ETS in China’s electricity sector. One of the important points of ETS is to give a price for carbon emissions and establish a cost pass-through mechanism (reminded that the essential of carbon pricing is to put a price on carbon emissions that is equal to discounted value of the external damages). It should be regarded as a part of broader policy package for energy and resources price reform. This will require that any low-carbon power policy should be considered as a part of whole policy package aiming at further liberalizing the electricity sector in China. Three policy options are identified to incorporate ETS with electricity reform under different circumstances. A combination of those three options is also proposed to break the lock and reinforce the positive interaction between ETS and the transition towards a competitive electricity system, in link with current pilot ETS designs. A roadmap to introduce ETS in a stepwise manner is suggested.

We use a dynamic CGE model (SICGE) to assess the economic and climate impacts of emissions trading system (ETS) in China with a carbon price of 100 Yuan/ton CO2. A particular focus is given to the regulated electricity price regime, which is a major concern of electricity sector’s cost-effective participation in ETS in China. We found: (1) Carbon pricing is an effective policy for China to reduce CO2 emissions. Total CO2 emissions reduction ranges from 6.8% to 11.2% in short-term. (2) Rigid electricity price entails lower CO2 emissions reduction but can be considered as a feasible starting point to introduce carbon pricing policies in short-term as long as governmental subsidies are given to electricity production. (3) In mid- and long-term, the efficient policy is to earmark carbon revenue with competitive electricity price. We propose to use carbon revenue to reduce consumption tax in the first year of the introduction of carbon price and to use the carbon revenue to reduce production tax in following years.

Economic development is one of the targets of the whole human society. In macroeconomic theory, the developments of the economy are largely driven by consumption, investment, government purchases. In economic theory, we usually use to describe the development of economy, GDP and GDP will be affected by the price level. To measure the price level, we generally use the consumer price index, commodity retail price index to describe; Investment is usually measured with fixed asset investment and gross value of industrial output. In this article, through nearly 20 years in China's gross domestic product (GDP) and gross domestic product (GDP) of some important indicators, such as the residents' consumption level, the fiscal expenditure, gross value of industrial output and commodity retail price index, the consumer price index, urban residents' income, rural residents income, such as the total energy consumption data, using SPSS software to provide the descriptive analysis, factor analysis, regression analysis and other methods of data carried on the thorough analysis, and analysis the problems reflected by some targeted Suggestions are given.

China is undergoing rapid urbanization accompanied by rapid urban development and migration of rural populations to the cities. Because local governments are selling land to compensate for an unbalanced tax system that provides them with insufficient budgets, urban expansion is booming around the country. However, this form of land finance has grown out of control, in some cases producing uninhabited “ghost towns”, without any feedback from institutions that would limit the problem. Simultaneously, social problems have arisen from a failure to compensate the land's former residents for loss of their land and future livelihood, thereby jeopardizing China's social stability. This under-recognized contradiction created by urbanization is endangering China's environment and its socioeconomic development, and will endanger other developing countries seeking to emulate China's urbanization model.

The electricity sector accounts for a large share of China’s carbon dioxide emissions and of the economy-wide abatement potential. China’s planned national emissions trading scheme would include electricity generation, as nearly all emissions trading schemes do. The critical difference is that in most existing carbon pricing systems the power sector operates with competitive markets and cost-based pricing, while the Chinese power industry still uses a highly regulated dispatch and pricing system. Together these limitations mean that the effect of a carbon price on China is limited in terms of the impact on operational decisions for existing power stations and in terms of the effects on investment decisions. We explore the channels of interaction between electricity market reform and carbon pricing in China, and provide quantitative estimates of the effects and interactions on electricity sector emissions. A probabilistic discrete choice model is used to simulate the behavior of investors in the power sector. The analysis indicates that market reform can help reduce emissions intensity, but to meet China’s 2030 targets for non-fossil fuel generation a low to moderate carbon price is also necessary; conversely, a carbon price will only be effective with market reform that provides flexibility in dispatch. Using our simplified quantitative analysis, the carbon price required for the same share of non-fossil fuel generation would be about twice as high without market reform. Combining market reform and a carbon price could achieve significant rates of decarbonization and is likely to be the most effective and most feasibly policy package to cut emissions from China’s power sector.

The aim of the present work is to examine whether the price volatility of nonferrous metal futures can be used to predict the aggregate stock market returns in China. During a sample period from January of 2004 to December of 2011, empirical results show that the price volatility of basic nonferrous metals is a good predictor of value-weighted stock portfolio at various horizons in both in-sample and out-of-sample regressions. The predictive power of metal copper volatility is greater than that of aluminum. The results are robust to alternative measurements of variables and econometric approaches. After controlling several well-known macro pricing variables, the predictive power of copper volatility declines but remains statistically significant. Since the predictability exists only during our sample period, we conjecture that the stock market predictability by metal price volatility is partly driven by commodity financialization.

In 2013, China launched its domestic pilot Emission Trading Scheme (ETS) as a cost-effective strategy for reducing carbon dioxide emissions. ETS generates carbon prices that interact with the Feed-in Tariff (FIT) policy applied to renewable energies (REN). This paper discusses whether ETS and FIT policies should be mutually exclusive or integrated packages for achieving China's carbon and renewable energy targets, using wind and solar energy as examples. We use equivalent CO 2 price as an indicator to assess whether ETS could replace FIT policy at the provincial level. The results show that ETS alone is unlikely to provide sufficient incentive for REN development in China. ETS and FIT policy should be integrated but with coordination to avoid cost-ineffectiveness. Our model predicts that FIT levels should decrease by 3.04–4.63 percent (for wind) and 7.84–8.87 percent (for solar) from 2015 to 2020 if a national ETS commences in 2018.

This paper aims at improving industrial production level so as to promote economic growth in Maoming. By using econometric model, estimation, analysis and forecast, data from 1999 to 2012 are analyzed. The relationship between Maoming industries and local economic growth is also analyzed. The results can be found that industrial products and stable growth has prompted the economic growth rate in Maoming city. It can be concluded that Maoming industries play a great role in promoting economic growth.